From 8eeddea7e9eccd940ca564b02aabc4c7e8a0a8f3 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 10:17:11 -0500
Subject: [PATCH 01/56] update project metadata and deps

---
 pyproject.toml |  17 ++-
 uv.lock        | 362 ++++++++++++++++++++++++++++++++++++++++++++-----
 2 files changed, 342 insertions(+), 37 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index d059b8763..7e01894ec 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [project]
 name = "multidimio"
-version = "0.9.2"
+version = "1.0.0-alpha.1"
 description = "Cloud-native, scalable, and user-friendly multi dimensional energy data!"
 authors = [{ name = "Altay Sansal", email = "altay.sansal@tgs.com" }]
 requires-python = ">=3.11,<3.14"
@@ -27,10 +27,14 @@ dependencies = [
     "click-params (>=0.5.0,<0.6.0)",
     "dask (>=2024.12.0)",
     "fsspec (>=2024.10.0)",
+    "pint>=0.24.3,<0.25",
     "psutil (>=6.1.0,<7.0.0)",
+    "pydantic (>=2.8.2,<3.0.0)",
+    "pydantic-settings (>=2.4.0,<3.0.0)",
     "rich (>=13.9.4,<14.0.0)",
     "segy (>=0.4.0,<0.5.0)",
     "tqdm (>=4.67.0,<5.0.0)",
+    "xarray>=2025.3.1",
     "zarr (>=3.0.8,<4.0.0)",
 ]
 
@@ -180,11 +184,16 @@ pretty = true
 show_column_numbers = true
 show_error_codes = true
 show_error_context = true
-disallow_untyped_defs = true # for strict mypy: (this is the tricky one)
-plugins = ["numpy.typing.mypy_plugin"]
+disallow_untyped_defs = true  # for strict mypy: (this is the tricky one)
+plugins = ["pydantic.mypy", "numpy.typing.mypy_plugin"]
+
+[tool.pydantic-mypy]
+init_forbid_extra = true
+init_typed = true
+warn_required_dynamic_aliases = true
 
 [tool.bumpversion]
-current_version = "0.9.2"
+current_version = "1.0.0-alpha.1"
 allow_dirty = true
 commit = false
 tag = false
diff --git a/uv.lock b/uv.lock
index fa5bd21f5..2e73c4199 100644
--- a/uv.lock
+++ b/uv.lock
@@ -276,6 +276,21 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/b7/b8/3fe70c75fe32afc4bb507f75563d39bc5642255d1d94f1f23604725780bf/babel-2.17.0-py3-none-any.whl", hash = "sha256:4d0b53093fdfb4b21c92b5213dba5a1b23885afa8383709427046b21c366e5f2", size = 10182537 },
 ]
 
+[[package]]
+name = "bandit"
+version = "1.8.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+    { name = "pyyaml" },
+    { name = "rich" },
+    { name = "stevedore" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/1a/a5/144a45f8e67df9d66c3bc3f7e69a39537db8bff1189ab7cff4e9459215da/bandit-1.8.3.tar.gz", hash = "sha256:f5847beb654d309422985c36644649924e0ea4425c76dec2e89110b87506193a", size = 4232005 }
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+]
+
 [[package]]
 name = "beautifulsoup4"
 version = "4.13.3"
@@ -289,6 +304,34 @@ wheels = [
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+    { name = "mypy-extensions" },
+    { name = "packaging" },
+    { name = "pathspec" },
+    { name = "platformdirs" },
+]
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 name = "bokeh"
 version = "3.7.2"
@@ -697,6 +740,15 @@ wheels = [
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 name = "dask"
 version = "2025.3.0"
@@ -853,6 +905,97 @@ wheels = [
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 version = "0.4.2"
@@ -1644,17 +1805,21 @@ wheels = [
 
 [[package]]
 name = "multidimio"
-version = "0.9.1"
+version = "1.0.0a1"
 source = { editable = "." }
 dependencies = [
     { name = "click" },
     { name = "click-params" },
     { name = "dask" },
     { name = "fsspec" },
+    { name = "pint" },
     { name = "psutil" },
+    { name = "pydantic" },
+    { name = "pydantic-settings" },
     { name = "rich" },
     { name = "segy" },
     { name = "tqdm" },
+    { name = "xarray" },
     { name = "zarr" },
 ]
 
@@ -1674,14 +1839,23 @@ lossy = [
 
 [package.dev-dependencies]
 dev = [
+    { name = "black" },
     { name = "coverage", extra = ["toml"] },
+    { name = "darglint" },
+    { name = "flake8" },
+    { name = "flake8-bandit" },
+    { name = "flake8-bugbear" },
+    { name = "flake8-docstrings" },
+    { name = "flake8-rst-docstrings" },
+    { name = "isort" },
     { name = "mypy" },
+    { name = "pep8-naming" },
     { name = "pre-commit" },
     { name = "pre-commit-hooks" },
     { name = "pygments" },
     { name = "pytest" },
     { name = "pytest-dependency" },
-    { name = "ruff" },
+    { name = "pyupgrade" },
     { name = "safety" },
     { name = "typeguard" },
     { name = "xdoctest", extra = ["colors"] },
@@ -1707,26 +1881,39 @@ requires-dist = [
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     { name = "fsspec", specifier = ">=2024.10.0" },
     { name = "gcsfs", marker = "extra == 'cloud'", specifier = ">=2024.10.0" },
+    { name = "pint", specifier = ">=0.24.3,<0.25" },
     { name = "psutil", specifier = ">=6.1.0,<7.0.0" },
+    { name = "pydantic", specifier = ">=2.8.2,<3.0.0" },
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     { name = "rich", specifier = ">=13.9.4,<14.0.0" },
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     { name = "tqdm", specifier = ">=4.67.0,<5.0.0" },
-    { name = "zarr", specifier = ">=3.0.8,<4.0.0" },
+    { name = "xarray", specifier = ">=2025.3.1" },
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     { name = "coverage", extras = ["toml"], specifier = ">=7.6.7,<8" },
+    { name = "darglint", specifier = ">=1.8.1,<2" },
+    { name = "flake8", specifier = ">=7.1.0,<8" },
+    { name = "flake8-bandit", specifier = ">=4.1.1,<5" },
+    { name = "flake8-bugbear", specifier = ">=24.4.26,<25" },
+    { name = "flake8-docstrings", specifier = ">=1.7.0,<2" },
+    { name = "flake8-rst-docstrings", specifier = ">=0.3.0,<0.4" },
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     { name = "typeguard", specifier = ">=4.4.1,<5" },
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-    { url = "https://files.pythonhosted.org/packages/de/7e/fff70b02e57852fda17bd43f99dda37b9bcf3e1af3d97c5834ff48d04715/ruff-0.11.8-py3-none-win32.whl", hash = "sha256:5b18caa297a786465cc511d7f8be19226acf9c0a1127e06e736cd4e1878c3ea2", size = 10451102 },
-    { url = "https://files.pythonhosted.org/packages/7b/a9/eaa571eb70648c9bde3120a1d5892597de57766e376b831b06e7c1e43945/ruff-0.11.8-py3-none-win_amd64.whl", hash = "sha256:6e70d11043bef637c5617297bdedec9632af15d53ac1e1ba29c448da9341b0c4", size = 11597410 },
-    { url = "https://files.pythonhosted.org/packages/cd/be/f6b790d6ae98f1f32c645f8540d5c96248b72343b0a56fab3a07f2941897/ruff-0.11.8-py3-none-win_arm64.whl", hash = "sha256:304432e4c4a792e3da85b7699feb3426a0908ab98bf29df22a31b0cdd098fac2", size = 10713129 },
-]
-
 [[package]]
 name = "s3fs"
 version = "2024.12.0"
@@ -3310,6 +3571,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/a0/4b/528ccf7a982216885a1ff4908e886b8fb5f19862d1962f56a3fce2435a70/starlette-0.46.1-py3-none-any.whl", hash = "sha256:77c74ed9d2720138b25875133f3a2dae6d854af2ec37dceb56aef370c1d8a227", size = 71995 },
 ]
 
+[[package]]
+name = "stevedore"
+version = "5.4.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pbr" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/28/3f/13cacea96900bbd31bb05c6b74135f85d15564fc583802be56976c940470/stevedore-5.4.1.tar.gz", hash = "sha256:3135b5ae50fe12816ef291baff420acb727fcd356106e3e9cbfa9e5985cd6f4b", size = 513858 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f7/45/8c4ebc0c460e6ec38e62ab245ad3c7fc10b210116cea7c16d61602aa9558/stevedore-5.4.1-py3-none-any.whl", hash = "sha256:d10a31c7b86cba16c1f6e8d15416955fc797052351a56af15e608ad20811fcfe", size = 49533 },
+]
+
 [[package]]
 name = "tabulate"
 version = "0.9.0"
@@ -3328,6 +3601,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/27/44/aa5c8b10b2cce7a053018e0d132bd58e27527a0243c4985383d5b6fd93e9/tblib-3.1.0-py3-none-any.whl", hash = "sha256:670bb4582578134b3d81a84afa1b016128b429f3d48e6cbbaecc9d15675e984e", size = 12552 },
 ]
 
+[[package]]
+name = "tokenize-rt"
+version = "6.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/6b/0a/5854d8ced8c1e00193d1353d13db82d7f813f99bd5dcb776ce3e2a4c0d19/tokenize_rt-6.1.0.tar.gz", hash = "sha256:e8ee836616c0877ab7c7b54776d2fefcc3bde714449a206762425ae114b53c86", size = 5506 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/87/ba/576aac29b10dfa49a6ce650001d1bb31f81e734660555eaf144bfe5b8995/tokenize_rt-6.1.0-py2.py3-none-any.whl", hash = "sha256:d706141cdec4aa5f358945abe36b911b8cbdc844545da99e811250c0cee9b6fc", size = 6015 },
+]
+
 [[package]]
 name = "tomli"
 version = "2.2.1"
@@ -3667,6 +3949,20 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2d/82/f56956041adef78f849db6b289b282e72b55ab8045a75abad81898c28d19/wrapt-1.17.2-py3-none-any.whl", hash = "sha256:b18f2d1533a71f069c7f82d524a52599053d4c7166e9dd374ae2136b7f40f7c8", size = 23594 },
 ]
 
+[[package]]
+name = "xarray"
+version = "2025.3.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "numpy" },
+    { name = "packaging" },
+    { name = "pandas" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/7c/c4/6931c37cd418658d596e78794bdd1bcb67efec0aac3cdb720e37e03c1ea1/xarray-2025.3.1.tar.gz", hash = "sha256:0252c96a73528b29d1ed7f0ab28d928d2ec00ad809e47369803b184dece1e447", size = 3300778 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/91/fd/973deafd9f87085136a58573600646b408ae7af47859f35151f0d83d5090/xarray-2025.3.1-py3-none-any.whl", hash = "sha256:3404e313930c226db70a945377441ea3c957225d8ba2d429e764c099bb91a546", size = 1279327 },
+]
+
 [[package]]
 name = "xdoctest"
 version = "1.2.0"
@@ -3755,7 +4051,7 @@ wheels = [
 
 [[package]]
 name = "zarr"
-version = "3.0.8"
+version = "3.0.6"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "donfig" },
@@ -3764,9 +4060,9 @@ dependencies = [
     { name = "packaging" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/52/60/9652fd0536fbaca8d08cbc1a5572c52e0ce01773297df75da8bb47e45907/zarr-3.0.8.tar.gz", hash = "sha256:88505d095af899a88ae8ac4db02f4650ef0801d2ff6f65b6d1f0a45dcf760a6d", size = 256825 }
+sdist = { url = "https://files.pythonhosted.org/packages/6f/bf/2820e8ad5f086ea5cd4c4d65eb5e0113f98145ddf5810cec1c75fb10fb98/zarr-3.0.6.tar.gz", hash = "sha256:6ef23c740e34917a2a1099471361537732942e49f0cabe95c9b7124cd0d6d84f", size = 240812 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/3b/e20bdf84088c11f2c396d034506cbffadd53e024111c1aa4585c2aba1523/zarr-3.0.8-py3-none-any.whl", hash = "sha256:7f81e7aec086437d98882aa432209107114bd7f3a9f4958b2af9c6b5928a70a7", size = 205364 },
+    { url = "https://files.pythonhosted.org/packages/fb/38/56a1c129577d20dc975a934ccc3f7f16276eab04ff0ffbe02ea348407a37/zarr-3.0.6-py3-none-any.whl", hash = "sha256:dba078726b6e4defb0ae6a852b7e7035ce163d89d485961681ece49191dcce82", size = 196357 },
 ]
 
 [[package]]

From 293a7144a60833794437c6173bb8cccddbde8fe8 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 10:17:33 -0500
Subject: [PATCH 02/56] update project metadata and deps

---
 noxfile.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/noxfile.py b/noxfile.py
index d78994a09..281ec5258 100644
--- a/noxfile.py
+++ b/noxfile.py
@@ -257,6 +257,7 @@ def docs_build(session: Session) -> None:
     session_install_uv_package(
         session,
         [
+            "autodoc-pydantic",
             "sphinx",
             "sphinx-click",
             "sphinx-copybutton",
@@ -282,6 +283,7 @@ def docs(session: Session) -> None:
     session_install_uv_package(
         session,
         [
+            "autodoc-pydantic",
             "sphinx",
             "sphinx-autobuild",
             "sphinx-click",

From faacbaa86a66d17fc430de4e17282fc17807c6d6 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 14:42:57 -0500
Subject: [PATCH 03/56] add schemas

---
 src/mdio/schemas/__init__.py    |  18 ++++
 src/mdio/schemas/base.py        |  43 +++++++++
 src/mdio/schemas/builder.py     | 156 +++++++++++++++++++++++++++++++
 src/mdio/schemas/chunk_grid.py  |  44 +++++++++
 src/mdio/schemas/compressors.py | 159 ++++++++++++++++++++++++++++++++
 src/mdio/schemas/core.py        |  49 ++++++++++
 src/mdio/schemas/dimension.py   |  12 +++
 src/mdio/schemas/dtype.py       |  55 +++++++++++
 src/mdio/schemas/metadata.py    |  31 +++++++
 src/mdio/schemas/units.py       |  51 ++++++++++
 src/mdio/schemas/v0/__init__.py |   6 ++
 src/mdio/schemas/v0/dataset.py  |  88 ++++++++++++++++++
 src/mdio/schemas/v1/__init__.py |   6 ++
 src/mdio/schemas/v1/dataset.py  |  49 ++++++++++
 src/mdio/schemas/v1/stats.py    |  72 +++++++++++++++
 src/mdio/schemas/v1/units.py    | 126 +++++++++++++++++++++++++
 src/mdio/schemas/v1/variable.py |  55 +++++++++++
 17 files changed, 1020 insertions(+)
 create mode 100644 src/mdio/schemas/__init__.py
 create mode 100644 src/mdio/schemas/base.py
 create mode 100644 src/mdio/schemas/builder.py
 create mode 100644 src/mdio/schemas/chunk_grid.py
 create mode 100644 src/mdio/schemas/compressors.py
 create mode 100644 src/mdio/schemas/core.py
 create mode 100644 src/mdio/schemas/dimension.py
 create mode 100644 src/mdio/schemas/dtype.py
 create mode 100644 src/mdio/schemas/metadata.py
 create mode 100644 src/mdio/schemas/units.py
 create mode 100644 src/mdio/schemas/v0/__init__.py
 create mode 100644 src/mdio/schemas/v0/dataset.py
 create mode 100644 src/mdio/schemas/v1/__init__.py
 create mode 100644 src/mdio/schemas/v1/dataset.py
 create mode 100644 src/mdio/schemas/v1/stats.py
 create mode 100644 src/mdio/schemas/v1/units.py
 create mode 100644 src/mdio/schemas/v1/variable.py

diff --git a/src/mdio/schemas/__init__.py b/src/mdio/schemas/__init__.py
new file mode 100644
index 000000000..17ae4dd3f
--- /dev/null
+++ b/src/mdio/schemas/__init__.py
@@ -0,0 +1,18 @@
+"""MDIO schemas for different data types."""
+
+from mdio.schemas.compressors import ZFP
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+
+
+__all__ = [
+    "Blosc",
+    "ZFP",
+    "NamedDimension",
+    "ScalarType",
+    "StructuredField",
+    "StructuredType",
+]
diff --git a/src/mdio/schemas/base.py b/src/mdio/schemas/base.py
new file mode 100644
index 000000000..d4bdfd480
--- /dev/null
+++ b/src/mdio/schemas/base.py
@@ -0,0 +1,43 @@
+"""Base models to subclass from."""
+
+from pydantic import ConfigDict
+from pydantic import Field
+from pydantic.json_schema import GenerateJsonSchema
+
+from mdio.schemas.compressors import ZFP
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.core import CamelCaseStrictModel
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import DataTypeModel
+
+
+JSON_SCHEMA_DIALECT = GenerateJsonSchema.schema_dialect
+
+
+class BaseDataset(CamelCaseStrictModel):
+    """A base class for MDIO datasets.
+
+    We add schema dialect to extend the config of `StrictCamelBaseModel`.
+    We use the default Pydantic schema generator `GenerateJsonSchema` to
+    define the JSON schema dialect accurately.
+    """
+
+    model_config = ConfigDict(json_schema_extra={"$schema": JSON_SCHEMA_DIALECT})
+
+
+class BaseArray(DataTypeModel, CamelCaseStrictModel):
+    """A base array schema."""
+
+    dimensions: list[NamedDimension] | list[str] = Field(
+        ..., description="List of Dimension collection or reference to dimension names."
+    )
+    compressor: Blosc | ZFP | None = Field(
+        default=None, description="Compression settings."
+    )
+
+
+class NamedArray(BaseArray):
+    """An array with a name."""
+
+    name: str = Field(..., description="Name of the array.")
+    long_name: str | None = Field(default=None, description="Fully descriptive name.")
diff --git a/src/mdio/schemas/builder.py b/src/mdio/schemas/builder.py
new file mode 100644
index 000000000..9a0e6cbbb
--- /dev/null
+++ b/src/mdio/schemas/builder.py
@@ -0,0 +1,156 @@
+"""Schema builders."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from mdio.schemas import NamedDimension
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset import DatasetMetadata
+from mdio.schemas.v1.variable import Variable
+from mdio.schemas.v1.variable import VariableMetadata
+
+
+class VariableBuilder:
+    """Dataset builder."""
+
+    def __init__(self) -> None:
+        """Initialize the builder."""
+        self.name = None
+        self.long_name = None
+        self.dtype = None
+        self.chunks = None
+        self.dims = None
+        self.coords = None
+        self.compressor = None
+        self.meta_dict = None
+
+    def set_name(self, name: str) -> VariableBuilder:
+        """Set variable name."""
+        self.name = name
+        return self
+
+    def set_long_name(self, long_name: str) -> VariableBuilder:
+        """Add long, descriptive name to the variable."""
+        self.long_name = long_name
+        return self
+
+    def set_compressor(self, compressor: dict[str, Any]) -> VariableBuilder:
+        """Add long, descriptive name to the variable."""
+        self.compressor = compressor
+        return self
+
+    def add_dimension(self, *dimensions: str | dict[str, int]) -> VariableBuilder:
+        """Add a dimension to the dataset."""
+        if self.dims is None:
+            self.dims = []
+
+        if isinstance(dimensions[0], str):
+            dims = list(dimensions)
+        elif isinstance(dimensions[0], dict):
+            dims = [
+                NamedDimension(name=name, size=size)
+                for dim in dimensions
+                for name, size in dim.items()
+            ]
+        else:
+            raise NotImplementedError
+
+        self.dims.extend(dims)
+        return self
+
+    def add_coordinate(self, *names: str) -> VariableBuilder:
+        """Add a coordinate to the variable."""
+        if self.coords is None:
+            self.coords = []
+
+        self.coords.extend(names)
+        return self
+
+    def set_format(self, format_: str | dict[str, str]) -> VariableBuilder:
+        """Set variable format."""
+        if isinstance(format_, dict):
+            fields = [{"name": n, "format": f} for n, f in format_.items()]
+            format_ = {"fields": fields}
+
+        self.dtype = format_
+        return self
+
+    def set_chunks(self, chunks: list[int]) -> VariableBuilder:
+        """Set variable chunks."""
+        if self.meta_dict is None:
+            self.meta_dict = {}
+
+        self.meta_dict["chunkGrid"] = {"configuration": {"chunkShape": chunks}}
+        return self
+
+    def set_units(self, units: dict[str, str]) -> VariableBuilder:
+        """Set variable units."""
+        if self.meta_dict is None:
+            self.meta_dict = {}
+
+        self.meta_dict["unitsV1"] = units
+        return self
+
+    def add_attribute(self, key: str, value: Any) -> VariableBuilder:  # noqa: ANN401
+        """Add a user attribute to the variable metadata."""
+        if self.meta_dict is None:
+            self.meta_dict = {}
+
+        self.meta_dict["attributes"] = {key: value}
+        return self
+
+    def build(self) -> Variable:
+        """Build the dataset model."""
+        if self.chunks is not None and len(self.chunks) != len(self.dims):
+            msg = "Variable chunks must have same number of dimensions."
+            raise ValueError(msg)
+
+        var_kwargs = {}
+
+        if self.meta_dict is not None:
+            var_kwargs["metadata"] = VariableMetadata.model_validate(self.meta_dict)
+
+        return Variable(
+            name=self.name,
+            long_name=self.long_name,
+            data_type=self.dtype,
+            dimensions=self.dims,
+            coordinates=self.coords,
+            compressor=self.compressor,
+            **var_kwargs,
+        )
+
+
+class DatasetBuilder:
+    """Dataset builder."""
+
+    def __init__(self) -> None:
+        """Initialize the builder."""
+        self.variables = []
+        self.name = None
+        self.metadata = None
+
+    def set_name(self, name: str) -> DatasetBuilder:
+        """Set dataset name."""
+        self.name = name
+        return self
+
+    def add_variable(self, variable: Variable) -> DatasetBuilder:
+        """Add a variable to the dataset."""
+        self.variables.append(variable)
+        return self
+
+    def add_variables(self, variables: list[Variable]) -> DatasetBuilder:
+        """Add multiple variables to the dataset."""
+        [self.add_variable(variable) for variable in variables]
+        return self
+
+    def set_metadata(self, metadata: DatasetMetadata) -> DatasetBuilder:
+        """Add a metadata to the dataset."""
+        self.metadata = metadata
+        return self
+
+    def build(self) -> Dataset:
+        """Build the dataset model."""
+        return Dataset(variables=self.variables, metadata=self.metadata)
diff --git a/src/mdio/schemas/chunk_grid.py b/src/mdio/schemas/chunk_grid.py
new file mode 100644
index 000000000..478f11cb7
--- /dev/null
+++ b/src/mdio/schemas/chunk_grid.py
@@ -0,0 +1,44 @@
+"""This module contains data models for Zarr's chunk grid."""
+
+from __future__ import annotations
+
+from pydantic import Field
+
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+class RegularChunkShape(CamelCaseStrictModel):
+    """Represents regular chunk sizes along each dimension."""
+
+    chunk_shape: list[int] = Field(
+        ..., description="Lengths of the chunk along each dimension of the array."
+    )
+
+
+class RectilinearChunkShape(CamelCaseStrictModel):
+    """Represents irregular chunk sizes along each dimension."""
+
+    chunk_shape: list[list[int]] = Field(
+        ...,
+        description="Lengths of the chunk along each dimension of the array.",
+    )
+
+
+class RegularChunkGrid(CamelCaseStrictModel):
+    """Represents a rectangular and regularly spaced chunk grid."""
+
+    name: str = Field(default="regular", description="The name of the chunk grid.")
+
+    configuration: RegularChunkShape = Field(
+        ..., description="Configuration of the regular chunk grid."
+    )
+
+
+class RectilinearChunkGrid(CamelCaseStrictModel):
+    """Represents a rectangular and irregularly spaced chunk grid."""
+
+    name: str = Field(default="rectilinear", description="The name of the chunk grid.")
+
+    configuration: RectilinearChunkShape = Field(
+        ..., description="Configuration of the irregular chunk grid."
+    )
diff --git a/src/mdio/schemas/compressors.py b/src/mdio/schemas/compressors.py
new file mode 100644
index 000000000..b550b98dd
--- /dev/null
+++ b/src/mdio/schemas/compressors.py
@@ -0,0 +1,159 @@
+"""This module contains a Pydantic model to parameterize compressors.
+
+Important Objects:
+    - Blosc: A Pydantic model that represents a Blosc compression setup.
+    - ZFP: Class that represents the ZFP compression model.
+"""
+
+from __future__ import annotations
+
+from enum import IntEnum
+from enum import StrEnum
+
+from pydantic import Field
+from pydantic import model_validator
+
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+class BloscAlgorithm(StrEnum):
+    """Enum for Blosc algorithm options."""
+
+    BLOSCLZ = "blosclz"
+    LZ4 = "lz4"
+    LZ4HC = "lz4hc"
+    ZLIB = "zlib"
+    ZSTD = "zstd"
+
+
+class BloscShuffle(IntEnum):
+    """Enum for Blosc shuffle options."""
+
+    NOSHUFFLE = 0
+    SHUFFLE = 1
+    BITSHUFFLE = 2
+    AUTOSHUFFLE = -1
+
+
+class Blosc(CamelCaseStrictModel):
+    """Data Model for Blosc options."""
+
+    name: str = Field(default="blosc", description="Name of the compressor.")
+    algorithm: BloscAlgorithm = Field(
+        default=BloscAlgorithm.LZ4,
+        description="The Blosc compression algorithm to be used.",
+    )
+    level: int = Field(default=5, ge=0, le=9, description="The compression level.")
+    shuffle: BloscShuffle = Field(
+        default=BloscShuffle.SHUFFLE,
+        description="The shuffle strategy to be applied before compression.",
+    )
+    blocksize: int = Field(
+        default=0,
+        description="The size of the block to be used for compression.",
+    )
+
+    def make_instance(self):  # noqa: ANN201
+        """Translate parameters to compressor kwargs.."""
+        from zarr.codecs import Blosc as _Blosc
+
+        return _Blosc(
+            cname=self.algorithm,
+            clevel=self.level,
+            shuffle=self.shuffle,
+            blocksize=self.blocksize,
+        )
+
+
+zfp_mode_map = {
+    "fixed_rate": 2,
+    "fixed_precision": 3,
+    "fixed_accuracy": 4,
+    "reversible": 5,
+}
+
+
+class ZFPMode(StrEnum):
+    """Enum for ZFP algorithm modes."""
+
+    FIXED_RATE = "fixed_rate"
+    FIXED_PRECISION = "fixed_precision"
+    FIXED_ACCURACY = "fixed_accuracy"
+    REVERSIBLE = "reversible"
+
+    @property
+    def int_code(self) -> int:
+        """Return the integer code of ZFP mode."""
+        return zfp_mode_map[self.value]
+
+
+class ZFP(CamelCaseStrictModel):
+    """Data Model for ZFP options."""
+
+    name: str = Field(default="zfp", description="Name of the compressor.")
+    mode: ZFPMode = Field()
+
+    tolerance: float | None = Field(
+        default=None,
+        description="Fixed accuracy in terms of absolute error tolerance.",
+    )
+
+    rate: float | None = Field(
+        default=None,
+        description="Fixed rate in terms of number of compressed bits per value.",
+    )
+
+    precision: int | None = Field(
+        default=None,
+        description="Fixed precision in terms of number of uncompressed bits per value.",
+    )
+
+    write_header: bool = Field(
+        default=True,
+        description="Encode array shape, scalar type, and compression parameters.",
+    )
+
+    @model_validator(mode="after")
+    def check_requirements(self) -> ZFP:
+        """Check if ZFP parameters make sense."""
+        mode = self.mode
+
+        # Check if reversible mode is provided without other parameters.
+        if mode == ZFPMode.REVERSIBLE and any(
+            getattr(self, key) is not None for key in ["tolerance", "rate", "precision"]
+        ):
+            msg = "Other fields must be None in REVERSIBLE mode"
+            raise ValueError(msg)
+
+        if mode == ZFPMode.FIXED_ACCURACY and self.tolerance is None:
+            msg = "Tolerance required for FIXED_ACCURACY mode"
+            raise ValueError(msg)
+
+        if mode == ZFPMode.FIXED_RATE and self.rate is None:
+            msg = "Rate required for FIXED_RATE mode"
+            raise ValueError(msg)
+
+        if mode == ZFPMode.FIXED_PRECISION and self.precision is None:
+            msg = "Precision required for FIXED_PRECISION mode"
+            raise ValueError(msg)
+
+        return self
+
+    def make_instance(self):  # noqa: ANN201
+        """Translate parameters to compressor kwargs.."""
+        from zarr.codecs import ZFPY as _ZFPY
+
+        return _ZFPY(
+            mode=self.mode.int_code,
+            tolerance=self.tolerance,
+            rate=self.rate,
+            precision=self.precision,
+        )
+
+
+class CompressorModel(CamelCaseStrictModel):
+    """Model representing compressor configuration."""
+
+    compressor: Blosc | ZFP | None = Field(
+        default=None, description="Compression settings."
+    )
diff --git a/src/mdio/schemas/core.py b/src/mdio/schemas/core.py
new file mode 100644
index 000000000..34a09066a
--- /dev/null
+++ b/src/mdio/schemas/core.py
@@ -0,0 +1,49 @@
+"""This module implements the core components of the MDIO schemas."""
+
+from __future__ import annotations
+
+from typing import Any
+from typing import get_type_hints
+
+from pydantic import BaseModel
+from pydantic import ConfigDict
+from pydantic.alias_generators import to_camel
+
+
+def model_fields(model: type[BaseModel]) -> dict[str, tuple[Any, Any]]:
+    """Extract Pydantic BaseModel fields.
+
+    Args:
+        model: (Type) The model object for which the fields will be extracted.
+
+    Returns:
+        A dictionary containing the fields of the model along with
+        their corresponding types and default values.
+
+    Example:
+        >>> class MyModel(BaseModel):
+        ...     name: str
+        ...     age: int = 0
+        ...
+        >>> model_fields(MyModel)
+        {'name': (str, <default_value>), 'age': (int, 0)}
+    """
+    annotations = get_type_hints(model)
+
+    fields = {}
+    for field_name, field in model.model_fields.items():
+        fields[field_name] = (annotations[field_name], field)
+
+    return fields
+
+
+class StrictModel(BaseModel):
+    """A model with forbidden extras."""
+
+    model_config = ConfigDict(extra="forbid", populate_by_name=True)
+
+
+class CamelCaseStrictModel(StrictModel):
+    """A model with forbidden extras and camel case aliases."""
+
+    model_config = ConfigDict(alias_generator=to_camel)
diff --git a/src/mdio/schemas/dimension.py b/src/mdio/schemas/dimension.py
new file mode 100644
index 000000000..62185a395
--- /dev/null
+++ b/src/mdio/schemas/dimension.py
@@ -0,0 +1,12 @@
+"""Dimension schema."""
+
+from pydantic import Field
+
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+class NamedDimension(CamelCaseStrictModel):
+    """Represents a single dimension with a name and size."""
+
+    name: str = Field(..., description="Unique identifier for the dimension.")
+    size: int = Field(..., gt=0, description="Total size of the dimension.")
diff --git a/src/mdio/schemas/dtype.py b/src/mdio/schemas/dtype.py
new file mode 100644
index 000000000..5c2427b00
--- /dev/null
+++ b/src/mdio/schemas/dtype.py
@@ -0,0 +1,55 @@
+"""Schemas for scalar types.
+
+We take booleans, unsigned and signed integers, floats, and
+complex numbers from numpy data types and allow those.
+"""
+
+from __future__ import annotations
+
+from enum import StrEnum
+
+from pydantic import Field
+
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+class ScalarType(StrEnum):
+    """Scalar array data type."""
+
+    BOOL = "bool"
+    INT8 = "int8"
+    INT16 = "int16"
+    INT32 = "int32"
+    INT64 = "int64"
+    UINT8 = "uint8"
+    UINT16 = "uint16"
+    UINT32 = "uint32"
+    UINT64 = "uint64"
+    FLOAT16 = "float16"
+    FLOAT32 = "float32"
+    FLOAT64 = "float64"
+    FLOAT128 = "float128"
+    COMPLEX64 = "complex64"
+    COMPLEX128 = "complex128"
+    COMPLEX256 = "complex256"
+
+
+class StructuredField(CamelCaseStrictModel):
+    """Structured array field with name, format."""
+
+    format: ScalarType = Field(...)
+    name: str = Field(...)
+
+
+class StructuredType(CamelCaseStrictModel):
+    """Structured array type with packed fields."""
+
+    fields: list[StructuredField] = Field()
+
+
+class DataTypeModel(CamelCaseStrictModel):
+    """Structured array type with fields and total item size."""
+
+    data_type: ScalarType | StructuredType = Field(
+        ..., description="Type of the array."
+    )
diff --git a/src/mdio/schemas/metadata.py b/src/mdio/schemas/metadata.py
new file mode 100644
index 000000000..dc2d66767
--- /dev/null
+++ b/src/mdio/schemas/metadata.py
@@ -0,0 +1,31 @@
+"""Metadata schemas and conventions."""
+
+from typing import Any
+
+from pydantic import Field
+
+from mdio.schemas.chunk_grid import RectilinearChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+class ChunkGridMetadata(CamelCaseStrictModel):
+    """Definition of chunk grid."""
+
+    chunk_grid: RegularChunkGrid | RectilinearChunkGrid | None = Field(
+        default=None,
+        description="Chunk grid specification for the array.",
+    )
+
+
+class VersionedMetadataConvention(CamelCaseStrictModel):
+    """Data model for versioned metadata convention."""
+
+
+class UserAttributes(CamelCaseStrictModel):
+    """User defined attributes as key/value pairs."""
+
+    attributes: dict[str, Any] | None = Field(
+        default=None,
+        description="User defined attributes as key/value pairs.",
+    )
diff --git a/src/mdio/schemas/units.py b/src/mdio/schemas/units.py
new file mode 100644
index 000000000..6844b4330
--- /dev/null
+++ b/src/mdio/schemas/units.py
@@ -0,0 +1,51 @@
+"""Common units for resource assessment data."""
+
+from __future__ import annotations
+
+from enum import Enum
+from enum import unique
+
+from pydantic import Field
+from pydantic import create_model
+
+from mdio.schemas.core import CamelCaseStrictModel
+
+
+@unique
+class UnitEnum(str, Enum):
+    """An Enum representing units as strings, from pint."""
+
+
+def create_unit_model(
+    unit_enum: type[UnitEnum],
+    model_name: str,
+    quantity: str,
+    module: str,
+) -> type[CamelCaseStrictModel]:
+    """Dynamically creates a pydantic model from a unit Enum.
+
+    Args:
+        unit_enum: UnitEnum representing the units for a specific quantity.
+        model_name: The name of the model to be created.
+        quantity: String representing the quantity for which the unit model is created.
+        module: Name of the module in which the model is to be created.
+            This should be the `__name__` attribute of the module.
+
+    Returns:
+        A Pydantic Model representing the unit model derived from the BaseModel.
+
+    Example:
+        unit_enum = UnitEnum
+        model_name = "LengthUnitModel"
+        quantity = "length"
+        create_unit_model(unit_enum, model_name, quantity)
+    """
+    fields = {quantity: (unit_enum, Field(..., description=f"Unit of {quantity}."))}
+
+    return create_model(
+        model_name,
+        **fields,
+        __base__=CamelCaseStrictModel,
+        __doc__=f"Model representing units of {quantity}.",
+        __module__=module,
+    )
diff --git a/src/mdio/schemas/v0/__init__.py b/src/mdio/schemas/v0/__init__.py
new file mode 100644
index 000000000..e74f484f1
--- /dev/null
+++ b/src/mdio/schemas/v0/__init__.py
@@ -0,0 +1,6 @@
+"""Schema specific to MDIO v0."""
+
+from mdio.schemas.v0.dataset import DatasetModelV0
+
+
+__all__ = ["DatasetModelV0"]
diff --git a/src/mdio/schemas/v0/dataset.py b/src/mdio/schemas/v0/dataset.py
new file mode 100644
index 000000000..58c3ae72b
--- /dev/null
+++ b/src/mdio/schemas/v0/dataset.py
@@ -0,0 +1,88 @@
+"""Dataset model for MDIO V0."""
+
+from __future__ import annotations
+
+from pydantic import AwareDatetime
+from pydantic import Field
+
+from mdio.schemas.base import BaseArray
+from mdio.schemas.base import BaseDataset
+from mdio.schemas.core import CamelCaseStrictModel
+from mdio.schemas.core import StrictModel
+
+
+class DimensionModelV0(CamelCaseStrictModel):
+    """Represents dimension schema for MDIO v0."""
+
+    name: str = Field(..., description="Name of the dimension.")
+    coords: list[int] = Field(..., description="Coordinate labels (ticks).")
+
+
+class DatasetMetadataModelV0(StrictModel):
+    """Represents dataset attributes schema for MDIO v0."""
+
+    api_version: str = Field(
+        ...,
+        description="MDIO version.",
+    )
+
+    created: AwareDatetime = Field(
+        ...,
+        description="Creation time with TZ info.",
+    )
+
+    dimension: list[DimensionModelV0] = Field(
+        ...,
+        description="Dimensions.",
+    )
+
+    mean: float | None = Field(
+        default=None,
+        description="Mean value of the samples.",
+    )
+
+    # Statistical information
+    std: float | None = Field(
+        default=None, description="Standard deviation of the samples."
+    )
+
+    rms: float | None = Field(
+        default=None, description="Root mean squared value of the samples."
+    )
+
+    min: float | None = Field(
+        default=None,
+        description="Minimum value of the samples.",
+    )
+
+    max: float | None = Field(
+        default=None,
+        description="Maximum value of the samples.",
+    )
+
+    trace_count: int | None = Field(
+        default=None, description="Number of traces in the SEG-Y file."
+    )
+
+
+class VariableModelV0(BaseArray):
+    """Represents an MDIO v0 variable schema."""
+
+
+class DatasetModelV0(BaseDataset):
+    """Represents an MDIO v0 dataset schema."""
+
+    seismic: list[VariableModelV0] = Field(
+        ...,
+        description="Variable containing seismic.",
+    )
+
+    headers: list[VariableModelV0] = Field(
+        ...,
+        description="Variable containing headers.",
+    )
+
+    metadata: DatasetMetadataModelV0 = Field(
+        ...,
+        description="Dataset metadata.",
+    )
diff --git a/src/mdio/schemas/v1/__init__.py b/src/mdio/schemas/v1/__init__.py
new file mode 100644
index 000000000..4f9bcdf36
--- /dev/null
+++ b/src/mdio/schemas/v1/__init__.py
@@ -0,0 +1,6 @@
+"""Schema specific to MDIO v1."""
+
+from mdio.schemas.v1.dataset import Dataset
+
+
+__all__ = ["Dataset"]
diff --git a/src/mdio/schemas/v1/dataset.py b/src/mdio/schemas/v1/dataset.py
new file mode 100644
index 000000000..f101093bb
--- /dev/null
+++ b/src/mdio/schemas/v1/dataset.py
@@ -0,0 +1,49 @@
+"""Dataset model for MDIO V1."""
+
+from pydantic import AwareDatetime
+from pydantic import Field
+from pydantic import create_model
+
+from mdio.schemas.base import BaseDataset
+from mdio.schemas.core import CamelCaseStrictModel
+from mdio.schemas.core import model_fields
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.variable import Variable
+
+
+class DatasetInfo(CamelCaseStrictModel):
+    """Contains information about a dataset."""
+
+    name: str = Field(..., description="Name or identifier for the dataset.")
+
+    api_version: str = Field(
+        ...,
+        description="The version of the MDIO API that the dataset complies with.",
+    )
+
+    created_on: AwareDatetime = Field(
+        ...,
+        description=(
+            "The timestamp indicating when the dataset was first created, "
+            "including timezone information. Expressed in ISO 8601 format."
+        ),
+    )
+
+
+DatasetMetadata = create_model(
+    "DatasetMetadata",
+    **model_fields(DatasetInfo),
+    **model_fields(UserAttributes),
+    __base__=CamelCaseStrictModel,
+)
+DatasetMetadata.__doc__ = "The metadata about the dataset."
+
+
+class Dataset(BaseDataset):
+    """Represents an MDIO v1 dataset.
+
+    A dataset consists of variables and metadata.
+    """
+
+    variables: list[Variable] = Field(..., description="Variables in MDIO dataset")
+    metadata: DatasetMetadata = Field(..., description="Dataset metadata.")
diff --git a/src/mdio/schemas/v1/stats.py b/src/mdio/schemas/v1/stats.py
new file mode 100644
index 000000000..a8a319c02
--- /dev/null
+++ b/src/mdio/schemas/v1/stats.py
@@ -0,0 +1,72 @@
+"""Statistics schema for MDIO v1 arrays.
+
+This module provides two Histogram classes (CenteredBinHistogram and
+EdgeDefinedHistogram),a summary statistics class, and a summary statistics
+metadata class.
+
+SummaryStatistics: a class that represents the minimum summary statistics
+of an array consisting of count, sum, sum of squares, min, max, and a histogram.
+
+SummaryStatisticsMetadata: represents metadata for statistics, with a field
+for v1 of the stats.
+
+CenteredBinHistogram takes the center points of each bin in a histogram,
+while EdgeDefinedHistogram takes the left edges and widths of each bin.
+Both classes extend from the base class BaseHistogram, which represents
+a histogram with count of each bin.
+"""
+
+from __future__ import annotations
+
+from typing import TypeAlias
+
+from pydantic import Field
+
+from mdio.schemas.core import CamelCaseStrictModel
+from mdio.schemas.metadata import VersionedMetadataConvention
+
+
+class BaseHistogram(CamelCaseStrictModel):
+    """Represents a histogram with bin counts."""
+
+    counts: list[int] = Field(..., description="Count of each each bin.")
+
+
+class CenteredBinHistogram(BaseHistogram):
+    """Class representing a center bin histogram."""
+
+    bin_centers: list[float | int] = Field(..., description="List of bin centers.")
+
+
+class EdgeDefinedHistogram(BaseHistogram):
+    """A class representing an edge-defined histogram."""
+
+    bin_edges: list[float | int] = Field(
+        ..., description="The left edges of the histogram bins."
+    )
+    bin_widths: list[float | int] = Field(
+        ..., description="The widths of the histogram bins."
+    )
+
+
+Histogram: TypeAlias = CenteredBinHistogram | EdgeDefinedHistogram
+
+
+class SummaryStatistics(CamelCaseStrictModel):
+    """Data model for some statistics in MDIO v1 arrays."""
+
+    count: int = Field(..., description="The number of data points.")
+    sum: float = Field(..., description="The total of all data values.")
+    sum_squares: float = Field(..., description="The total of all data values squared.")
+    min: float = Field(..., description="The smallest value in the variable.")
+    max: float = Field(..., description="The largest value in the variable.")
+    histogram: Histogram = Field(..., description="Binned frequency distribution.")
+
+
+class StatisticsMetadata(VersionedMetadataConvention):
+    """Data Model representing metadata for statistics."""
+
+    stats_v1: SummaryStatistics | list[SummaryStatistics] | None = Field(
+        default=None,
+        description="Minimal summary statistics.",
+    )
diff --git a/src/mdio/schemas/v1/units.py b/src/mdio/schemas/v1/units.py
new file mode 100644
index 000000000..dd46296c0
--- /dev/null
+++ b/src/mdio/schemas/v1/units.py
@@ -0,0 +1,126 @@
+"""Unit schemas specific to MDIO v1."""
+
+from __future__ import annotations
+
+from typing import TypeAlias
+
+from pint import UnitRegistry
+from pydantic import Field
+
+from mdio.schemas.metadata import VersionedMetadataConvention
+from mdio.schemas.units import UnitEnum
+from mdio.schemas.units import create_unit_model
+
+
+ureg = UnitRegistry()
+ureg.default_format = "~C"  # compact, abbreviated (symbol).
+
+
+class LengthUnitEnum(UnitEnum):
+    """Enum class representing metric units of length."""
+
+    MILLIMETER = ureg.millimeter
+    CENTIMETER = ureg.centimeter
+    METER = ureg.meter
+    KILOMETER = ureg.kilometer
+
+    INCH = ureg.inch
+    FOOT = ureg.foot
+    YARD = ureg.yard
+    MILE = ureg.mile
+
+
+LengthUnitModel = create_unit_model(
+    LengthUnitEnum, "LengthUnitModel", "length", __name__
+)
+
+
+class TimeUnitEnum(UnitEnum):
+    """Enum class representing units of time."""
+
+    NANOSECOND = ureg.nanosecond
+    MICROSECOND = ureg.microsecond
+    MILLISECOND = ureg.millisecond
+    SECOND = ureg.second
+    MINUTE = ureg.minute
+    HOUR = ureg.hour
+    DAY = ureg.day
+
+
+TimeUnitModel = create_unit_model(TimeUnitEnum, "TimeUnitModel", "time", __name__)
+
+
+class DensityUnitEnum(UnitEnum):
+    """Enum class representing units of density."""
+
+    GRAMS_PER_CC = ureg.gram / ureg.centimeter**3
+    KILOGRAMS_PER_M3 = ureg.kilogram / ureg.meter**3
+    POUNDS_PER_GAL = ureg.pounds / ureg.gallon
+
+
+DensityUnitModel = create_unit_model(
+    DensityUnitEnum, "DensityUnitModel", "density", __name__
+)
+
+
+class SpeedUnitEnum(UnitEnum):
+    """Enum class representing units of speed."""
+
+    METER_PER_SECOND = ureg.meter / ureg.second
+    FEET_PER_SECOND = ureg.feet / ureg.second
+
+
+SpeedUnitModel = create_unit_model(SpeedUnitEnum, "SpeedUnitModel", "speed", __name__)
+
+
+class AngleUnitEnum(UnitEnum):
+    """Enum class representing units of angle."""
+
+    DEGREES = ureg.degree
+    RADIANS = ureg.radian
+
+
+AngleUnitModel = create_unit_model(AngleUnitEnum, "AngleUnitModel", "angle", __name__)
+
+
+class FrequencyUnitEnum(UnitEnum):
+    """Enum class representing units of frequency."""
+
+    HERTZ = ureg.hertz
+
+
+FrequencyUnitModel = create_unit_model(
+    FrequencyUnitEnum, "FrequencyUnitModel", "frequency", __name__
+)
+
+
+class VoltageUnitEnum(UnitEnum):
+    """Enum class representing units of voltage."""
+
+    MICROVOLT = ureg.microvolt
+    MILLIVOLT = ureg.millivolt
+    VOLT = ureg.volt
+
+
+VoltageUnitModel = create_unit_model(
+    VoltageUnitEnum, "VoltageUnitModel", "voltage", __name__
+)
+
+
+# Composite model types
+AllUnitModel: TypeAlias = (
+    LengthUnitModel
+    | TimeUnitModel
+    | AngleUnitModel
+    | DensityUnitModel
+    | SpeedUnitModel
+    | FrequencyUnitModel
+    | VoltageUnitModel
+)
+
+
+# Versioned metadata conventions for units
+class AllUnits(VersionedMetadataConvention):
+    """All Units."""
+
+    units_v1: AllUnitModel | list[AllUnitModel] | None = Field(default=None)
diff --git a/src/mdio/schemas/v1/variable.py b/src/mdio/schemas/v1/variable.py
new file mode 100644
index 000000000..22ad0bf33
--- /dev/null
+++ b/src/mdio/schemas/v1/variable.py
@@ -0,0 +1,55 @@
+"""This module defines `LabeledArray`, `Coordinate`, and `Variable`.
+
+`LabeledArray` is a basic array unit which includes basic properties like
+name, dimension, data type, compressor etc.
+
+`Coordinate` extends the `LabeledArray` class, it represents the Coordinate
+array in the MDIO format. It has dimensions which are fully defined and can hold
+additional metadata.
+
+`Variable` is another class that extends the `LabeledArray`. It represents a
+variable in MDIO format. It can have coordinates and can also hold metadata.
+"""
+
+from pydantic import Field
+from pydantic import create_model
+
+from mdio.schemas.base import NamedArray
+from mdio.schemas.core import CamelCaseStrictModel
+from mdio.schemas.core import model_fields
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.units import AllUnits
+
+
+class Coordinate(NamedArray):
+    """An MDIO coordinate array with metadata."""
+
+    data_type: ScalarType = Field(..., description="Data type of coordinate.")
+    metadata: list[AllUnits | UserAttributes] | None = Field(
+        default=None, description="Coordinate metadata."
+    )
+
+
+VariableMetadata = create_model(
+    "VariableMetadata",
+    **model_fields(ChunkGridMetadata),
+    **model_fields(AllUnits),
+    **model_fields(StatisticsMetadata),
+    **model_fields(UserAttributes),
+    __base__=CamelCaseStrictModel,
+)
+
+
+class Variable(NamedArray):
+    """An MDIO variable that has coordinates and metadata."""
+
+    coordinates: list[Coordinate] | list[str] | None = Field(
+        default=None,
+        description="Coordinates of the MDIO variable dimensions.",
+    )
+    metadata: VariableMetadata | None = Field(
+        default=None, description="Variable metadata."
+    )

From 1a1e7436b96041df944b058c976da7b753f1db73 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 14:43:21 -0500
Subject: [PATCH 04/56] Relocate quickstart notebook to tutorials directory

---
 docs/tutorials/creation.ipynb | 1225 ++++++++++++++++++++++-----------
 1 file changed, 838 insertions(+), 387 deletions(-)

diff --git a/docs/tutorials/creation.ipynb b/docs/tutorials/creation.ipynb
index af4d3b65d..d154c63f8 100644
--- a/docs/tutorials/creation.ipynb
+++ b/docs/tutorials/creation.ipynb
@@ -1,396 +1,847 @@
 {
  "cells": [
   {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "# Create an Empty MDIO\n",
-    "\n",
-    "```{article-info}\n",
-    ":author: Altay Sansal\n",
-    ":date: \"{sub-ref}`today`\"\n",
-    ":read-time: \"{sub-ref}`wordcount-minutes` min read\"\n",
-    ":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\n",
-    "```\n",
-    "\n",
-    "Here we will create an empty MDIO file and populate its fields.\n",
-    "\n",
-    "```{warning}\n",
-    "For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\n",
-    "`pip install matplotlib` or `conda install matplotlib`.\n",
-    "```\n",
-    "\n",
-    "We first need to import the configuration classes and create function to be able to create the empty MDIO."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:04.371422Z",
-     "start_time": "2025-04-16T14:50:04.368107Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "from mdio import Dimension\n",
-    "from mdio import Grid\n",
-    "from mdio import MDIOCreateConfig\n",
-    "from mdio import MDIOReader\n",
-    "from mdio import MDIOVariableConfig\n",
-    "from mdio import MDIOWriter\n",
-    "from mdio import create_empty\n",
-    "from mdio.converters.segy import get_compressor\n",
-    "from mdio.segy.compat import mdio_segy_spec"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "## Setting Up Grid Dimensions and Variable(s)\n",
-    "\n",
-    "Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\n",
-    "dimensions. This is exactly like a 3D Post-Stack dataset.\n",
-    "\n",
-    "We will use the standard `chunked_012` access pattern. All variable names must start\n",
-    "with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\n",
-    "\n",
-    "We will also use an MDIO private utility function to get the compressor easily. The\n",
-    "compressor is fully customizable, but this function gives us ones available in SEG-Y\n",
-    "ingestion.\n",
-    "\n",
-    "If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\n",
-    "we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\n",
-    "\n",
-    "At the end we create empty MDIO on local disk or cloud, based on the path string."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:06.121450Z",
-     "start_time": "2025-04-16T14:50:06.002634Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "grid = Grid(\n",
-    "    dims=[\n",
-    "        Dimension(name=\"inline\", coords=range(100, 300, 1)),  # 100-300 with step 1\n",
-    "        Dimension(name=\"crossline\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\n",
-    "        Dimension(name=\"sample\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "compressor = get_compressor(lossless=True)\n",
-    "header_dtype = mdio_segy_spec().trace.header.dtype\n",
-    "variable = MDIOVariableConfig(\n",
-    "    name=\"chunked_012\",\n",
-    "    dtype=\"float32\",\n",
-    "    chunks=(128, 128, 128),\n",
-    "    compressors=compressor,\n",
-    "    header_dtype=header_dtype,\n",
-    ")\n",
-    "\n",
-    "create_conf = MDIOCreateConfig(path=\"demo.mdio\", grid=grid, variables=[variable])\n",
-    "create_empty(config=create_conf);"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Populating the MDIO\n",
-    "\n",
-    "Once empty MDIO is created, you can populate it with sample data, header data,\n",
-    "metadata, and statistics. The `live_mask` is automatically flipped to 1 after\n",
-    "every write. However, the consistency of the `live_mask` is up to the user. If\n",
-    "not populated correctly, at read time, traces may be skipped.\n",
-    "\n",
-    "We will read the usual stats and as you can see they're all empty. Text header\n",
-    "and binary header are only required if we are going to export this back to SEG-Y,\n",
-    "and can be modified. We can edit these if necessary using the writer."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:09.974442Z",
-     "start_time": "2025-04-16T14:50:09.951257Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(['C00                                                                             ',\n",
-       "  'C01                                                                             ',\n",
-       "  'C02                                                                             ',\n",
-       "  'C03                                                                             ',\n",
-       "  'C04                                                                             '],\n",
-       " {},\n",
-       " {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "writer = MDIOWriter(create_conf.path)\n",
-    "\n",
-    "# Truncate text header for display\n",
-    "writer.text_header[:5], writer.binary_header, writer.stats"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Updating File and Checking with `MDIOReader`.\n",
-    "\n",
-    "We write traces here, the headers are still empty. If you need the headers\n",
-    "populated, this is where they would be written to file as well.\n",
-    "\n",
-    "All the extra metadata we are writing is so that we can export back to SEG-Y\n",
-    "in the future. If that's not a requirement most of the metadata can be\n",
-    "omitted.\n",
-    "\n",
-    "If you already have an MDIO prior to this, all the metadata can be copied\n",
-    "over from the previous version."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:12.498287Z",
-     "start_time": "2025-04-16T14:50:11.670230Z"
-    },
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "({'data_sample_format': 1,\n",
-       "  'sample_interval': 4,\n",
-       "  'samples_per_trace': 750,\n",
-       "  'segy_revision_major': 1,\n",
-       "  'segy_revision_minor': 0},\n",
-       " {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sample_dim = writer.grid.select_dim(\"sample\")\n",
-    "sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\n",
-    "num_samples = sample_dim.size\n",
-    "writer.binary_header = {\n",
-    "    \"data_sample_format\": 1,\n",
-    "    \"sample_interval\": sample_interval,\n",
-    "    \"samples_per_trace\": num_samples,\n",
-    "    \"segy_revision_major\": 1,\n",
-    "    \"segy_revision_minor\": 0,\n",
-    "}\n",
-    "\n",
-    "# Write some values to the file\n",
-    "writer[:5] = 1\n",
-    "writer[5:10] = 2\n",
-    "writer[50:100] = 3\n",
-    "writer[150:175] = -1\n",
-    "\n",
-    "# Write some made up stats\n",
-    "writer.stats = {\"mean\": 12, \"std\": 5, \"rms\": 3, \"min\": -4, \"max\": 4}\n",
-    "\n",
-    "reader = MDIOReader(create_conf.path)\n",
-    "reader.binary_header, reader.stats"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": "Plot some of the data we populated:"
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:14.256953Z",
-     "start_time": "2025-04-16T14:50:14.036094Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(1, 2, sharex=\"all\")\n",
-    "ax[0].imshow(writer.live_mask[:].T, aspect=\"auto\")\n",
-    "ax[1].imshow(reader[:, 150].T, aspect=\"auto\")\n",
-    "\n",
-    "ax[0].set_xlabel(\"inline\")\n",
-    "ax[0].set_ylabel(\"crossline\")\n",
-    "ax[1].set_xlabel(\"inline\")\n",
-    "ax[1].set_ylabel(\"sample\")\n",
-    "ax[0].set_title(\"Live Mask\")\n",
-    "ax[1].set_title(\"Middle Crossline\")\n",
-    "fig.tight_layout();"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Write to SEG-Y\n",
-    "\n",
-    "Because we populated all the fields necessary for SEG-Y output, we can call the\n",
-    "MDIO to SEGY converter and get a file out."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:15.788812Z",
-     "start_time": "2025-04-16T14:50:15.009889Z"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\n",
-      "Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\n",
-      "[[1. 1. 1. ... 1. 1. 1.]\n",
-      " [1. 1. 1. ... 1. 1. 1.]\n",
-      " [1. 1. 1. ... 1. 1. 1.]\n",
-      " ...\n",
-      " [1. 1. 1. ... 1. 1. 1.]\n",
-      " [1. 1. 1. ... 1. 1. 1.]\n",
-      " [1. 1. 1. ... 1. 1. 1.]]\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "from segy import SegyFile\n",
-    "\n",
-    "from mdio import mdio_to_segy\n",
-    "\n",
-    "mdio_to_segy(\"demo.mdio\", \"demo.segy\")\n",
-    "segy = SegyFile(\"demo.segy\")\n",
-    "print(segy.binary_header)\n",
-    "print(segy.sample[:100])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
    "metadata": {},
+   "cell_type": "raw",
    "source": [
-    "## Copying an Existing MDIO without Data and Headers\n",
-    "\n",
-    "We also provide a `create_empty_like` function which allows us to create an MDIO file\n",
-    "with the same structure and basic metadata as an existing one.\n",
-    "\n",
-    "This will carry over:\n",
-    "* All access patterns in source MDIO\n",
-    "* Grid (shape, coordinates, dimensions, etc)\n",
-    "* Text Header\n",
-    "* Binary Header\n",
-    "\n",
-    "It will **NOT** carry over:\n",
-    "* Trace data\n",
-    "* Header data\n",
-    "* Statistics\n",
-    "* Live Mask"
+    "{\n",
+    " \"cells\": [\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%% md\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"source\": [\n",
+    "    \"# Create an Empty MDIO\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"```{article-info}\\n\",\n",
+    "    \":author: Altay Sansal\\n\",\n",
+    "    \":date: \\\"{sub-ref}`today`\\\"\\n\",\n",
+    "    \":read-time: \\\"{sub-ref}`wordcount-minutes` min read\\\"\\n\",\n",
+    "    \":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\n\",\n",
+    "    \"```\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"Here we will create an empty MDIO file and populate its fields.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"```{warning}\\n\",\n",
+    "    \"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\n\",\n",
+    "    \"`pip install matplotlib` or `conda install matplotlib`.\\n\",\n",
+    "    \"```\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We first need to import the configuration classes and create function to be able to create the empty MDIO.\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 2,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:04.371422Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:04.368107Z\"\n",
+    "    },\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%%\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [],\n",
+    "   \"source\": [\n",
+    "    \"import matplotlib.pyplot as plt\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"from mdio import Dimension\\n\",\n",
+    "    \"from mdio import Grid\\n\",\n",
+    "    \"from mdio import MDIOCreateConfig\\n\",\n",
+    "    \"from mdio import MDIOReader\\n\",\n",
+    "    \"from mdio import MDIOVariableConfig\\n\",\n",
+    "    \"from mdio import MDIOWriter\\n\",\n",
+    "    \"from mdio import create_empty\\n\",\n",
+    "    \"from mdio.converters.segy import get_compressor\\n\",\n",
+    "    \"from mdio.segy.compat import mdio_segy_spec\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%% md\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"source\": [\n",
+    "    \"## Setting Up Grid Dimensions and Variable(s)\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\n\",\n",
+    "    \"dimensions. This is exactly like a 3D Post-Stack dataset.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We will use the standard `chunked_012` access pattern. All variable names must start\\n\",\n",
+    "    \"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We will also use an MDIO private utility function to get the compressor easily. The\\n\",\n",
+    "    \"compressor is fully customizable, but this function gives us ones available in SEG-Y\\n\",\n",
+    "    \"ingestion.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\n\",\n",
+    "    \"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"At the end we create empty MDIO on local disk or cloud, based on the path string.\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 3,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:06.121450Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:06.002634Z\"\n",
+    "    },\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%%\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [],\n",
+    "   \"source\": [\n",
+    "    \"grid = Grid(\\n\",\n",
+    "    \"    dims=[\\n\",\n",
+    "    \"        Dimension(name=\\\"inline\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\n\",\n",
+    "    \"        Dimension(name=\\\"crossline\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\n\",\n",
+    "    \"        Dimension(name=\\\"sample\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\n\",\n",
+    "    \"    ]\\n\",\n",
+    "    \")\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"compressor = get_compressor(lossless=True)\\n\",\n",
+    "    \"header_dtype = mdio_segy_spec().trace.header.dtype\\n\",\n",
+    "    \"variable = MDIOVariableConfig(\\n\",\n",
+    "    \"    name=\\\"chunked_012\\\",\\n\",\n",
+    "    \"    dtype=\\\"float32\\\",\\n\",\n",
+    "    \"    chunks=(128, 128, 128),\\n\",\n",
+    "    \"    compressors=compressor,\\n\",\n",
+    "    \"    header_dtype=header_dtype,\\n\",\n",
+    "    \")\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"create_conf = MDIOCreateConfig(path=\\\"demo.mdio\\\", grid=grid, variables=[variable])\\n\",\n",
+    "    \"create_empty(config=create_conf);\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {},\n",
+    "   \"source\": [\n",
+    "    \"## Populating the MDIO\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"Once empty MDIO is created, you can populate it with sample data, header data,\\n\",\n",
+    "    \"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\n\",\n",
+    "    \"every write. However, the consistency of the `live_mask` is up to the user. If\\n\",\n",
+    "    \"not populated correctly, at read time, traces may be skipped.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We will read the usual stats and as you can see they're all empty. Text header\\n\",\n",
+    "    \"and binary header are only required if we are going to export this back to SEG-Y,\\n\",\n",
+    "    \"and can be modified. We can edit these if necessary using the writer.\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 4,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:09.974442Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:09.951257Z\"\n",
+    "    },\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%%\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [\n",
+    "    {\n",
+    "     \"data\": {\n",
+    "      \"text/plain\": [\n",
+    "       \"(['C00                                                                             ',\\n\",\n",
+    "       \"  'C01                                                                             ',\\n\",\n",
+    "       \"  'C02                                                                             ',\\n\",\n",
+    "       \"  'C03                                                                             ',\\n\",\n",
+    "       \"  'C04                                                                             '],\\n\",\n",
+    "       \" {},\\n\",\n",
+    "       \" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\"\n",
+    "      ]\n",
+    "     },\n",
+    "     \"execution_count\": 4,\n",
+    "     \"metadata\": {},\n",
+    "     \"output_type\": \"execute_result\"\n",
+    "    }\n",
+    "   ],\n",
+    "   \"source\": [\n",
+    "    \"writer = MDIOWriter(create_conf.path)\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"# Truncate text header for display\\n\",\n",
+    "    \"writer.text_header[:5], writer.binary_header, writer.stats\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {},\n",
+    "   \"source\": [\n",
+    "    \"## Updating File and Checking with `MDIOReader`.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We write traces here, the headers are still empty. If you need the headers\\n\",\n",
+    "    \"populated, this is where they would be written to file as well.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"All the extra metadata we are writing is so that we can export back to SEG-Y\\n\",\n",
+    "    \"in the future. If that's not a requirement most of the metadata can be\\n\",\n",
+    "    \"omitted.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"If you already have an MDIO prior to this, all the metadata can be copied\\n\",\n",
+    "    \"over from the previous version.\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 5,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:12.498287Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:11.670230Z\"\n",
+    "    },\n",
+    "    \"pycharm\": {\n",
+    "     \"name\": \"#%%\\n\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [\n",
+    "    {\n",
+    "     \"data\": {\n",
+    "      \"text/plain\": [\n",
+    "       \"({'data_sample_format': 1,\\n\",\n",
+    "       \"  'sample_interval': 4,\\n\",\n",
+    "       \"  'samples_per_trace': 750,\\n\",\n",
+    "       \"  'segy_revision_major': 1,\\n\",\n",
+    "       \"  'segy_revision_minor': 0},\\n\",\n",
+    "       \" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\"\n",
+    "      ]\n",
+    "     },\n",
+    "     \"execution_count\": 5,\n",
+    "     \"metadata\": {},\n",
+    "     \"output_type\": \"execute_result\"\n",
+    "    }\n",
+    "   ],\n",
+    "   \"source\": [\n",
+    "    \"sample_dim = writer.grid.select_dim(\\\"sample\\\")\\n\",\n",
+    "    \"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\n\",\n",
+    "    \"num_samples = sample_dim.size\\n\",\n",
+    "    \"writer.binary_header = {\\n\",\n",
+    "    \"    \\\"data_sample_format\\\": 1,\\n\",\n",
+    "    \"    \\\"sample_interval\\\": sample_interval,\\n\",\n",
+    "    \"    \\\"samples_per_trace\\\": num_samples,\\n\",\n",
+    "    \"    \\\"segy_revision_major\\\": 1,\\n\",\n",
+    "    \"    \\\"segy_revision_minor\\\": 0,\\n\",\n",
+    "    \"}\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"# Write some values to the file\\n\",\n",
+    "    \"writer[:5] = 1\\n\",\n",
+    "    \"writer[5:10] = 2\\n\",\n",
+    "    \"writer[50:100] = 3\\n\",\n",
+    "    \"writer[150:175] = -1\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"# Write some made up stats\\n\",\n",
+    "    \"writer.stats = {\\\"mean\\\": 12, \\\"std\\\": 5, \\\"rms\\\": 3, \\\"min\\\": -4, \\\"max\\\": 4}\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"reader = MDIOReader(create_conf.path)\\n\",\n",
+    "    \"reader.binary_header, reader.stats\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {},\n",
+    "   \"source\": \"Plot some of the data we populated:\"\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 6,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:14.256953Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:14.036094Z\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [\n",
+    "    {\n",
+    "     \"data\": {\n",
+    "      \"image/png\": 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\",\n",
+    "      \"text/plain\": [\n",
+    "       \"<Figure size 640x480 with 2 Axes>\"\n",
+    "      ]\n",
+    "     },\n",
+    "     \"metadata\": {},\n",
+    "     \"output_type\": \"display_data\"\n",
+    "    }\n",
+    "   ],\n",
+    "   \"source\": [\n",
+    "    \"fig, ax = plt.subplots(1, 2, sharex=\\\"all\\\")\\n\",\n",
+    "    \"ax[0].imshow(writer.live_mask[:].T, aspect=\\\"auto\\\")\\n\",\n",
+    "    \"ax[1].imshow(reader[:, 150].T, aspect=\\\"auto\\\")\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"ax[0].set_xlabel(\\\"inline\\\")\\n\",\n",
+    "    \"ax[0].set_ylabel(\\\"crossline\\\")\\n\",\n",
+    "    \"ax[1].set_xlabel(\\\"inline\\\")\\n\",\n",
+    "    \"ax[1].set_ylabel(\\\"sample\\\")\\n\",\n",
+    "    \"ax[0].set_title(\\\"Live Mask\\\")\\n\",\n",
+    "    \"ax[1].set_title(\\\"Middle Crossline\\\")\\n\",\n",
+    "    \"fig.tight_layout();\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {},\n",
+    "   \"source\": [\n",
+    "    \"## Write to SEG-Y\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"Because we populated all the fields necessary for SEG-Y output, we can call the\\n\",\n",
+    "    \"MDIO to SEGY converter and get a file out.\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 7,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:15.788812Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:15.009889Z\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [\n",
+    "    {\n",
+    "     \"name\": \"stderr\",\n",
+    "     \"output_type\": \"stream\",\n",
+    "     \"text\": [\n",
+    "      \"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\n\",\n",
+    "      \"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\"\n",
+    "     ]\n",
+    "    },\n",
+    "    {\n",
+    "     \"name\": \"stdout\",\n",
+    "     \"output_type\": \"stream\",\n",
+    "     \"text\": [\n",
+    "      \"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\n\",\n",
+    "      \"[[1. 1. 1. ... 1. 1. 1.]\\n\",\n",
+    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
+    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
+    "      \" ...\\n\",\n",
+    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
+    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
+    "      \" [1. 1. 1. ... 1. 1. 1.]]\\n\"\n",
+    "     ]\n",
+    "    },\n",
+    "    {\n",
+    "     \"name\": \"stderr\",\n",
+    "     \"output_type\": \"stream\",\n",
+    "     \"text\": [\n",
+    "      \"\\n\"\n",
+    "     ]\n",
+    "    }\n",
+    "   ],\n",
+    "   \"source\": [\n",
+    "    \"from segy import SegyFile\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"from mdio import mdio_to_segy\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"mdio_to_segy(\\\"demo.mdio\\\", \\\"demo.segy\\\")\\n\",\n",
+    "    \"segy = SegyFile(\\\"demo.segy\\\")\\n\",\n",
+    "    \"print(segy.binary_header)\\n\",\n",
+    "    \"print(segy.sample[:100])\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"markdown\",\n",
+    "   \"metadata\": {},\n",
+    "   \"source\": [\n",
+    "    \"## Copying an Existing MDIO without Data and Headers\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"We also provide a `create_empty_like` function which allows us to create an MDIO file\\n\",\n",
+    "    \"with the same structure and basic metadata as an existing one.\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"This will carry over:\\n\",\n",
+    "    \"* All access patterns in source MDIO\\n\",\n",
+    "    \"* Grid (shape, coordinates, dimensions, etc)\\n\",\n",
+    "    \"* Text Header\\n\",\n",
+    "    \"* Binary Header\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"It will **NOT** carry over:\\n\",\n",
+    "    \"* Trace data\\n\",\n",
+    "    \"* Header data\\n\",\n",
+    "    \"* Statistics\\n\",\n",
+    "    \"* Live Mask\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": 8,\n",
+    "   \"metadata\": {\n",
+    "    \"ExecuteTime\": {\n",
+    "     \"end_time\": \"2025-04-16T14:50:17.246513Z\",\n",
+    "     \"start_time\": \"2025-04-16T14:50:17.111779Z\"\n",
+    "    }\n",
+    "   },\n",
+    "   \"outputs\": [],\n",
+    "   \"source\": [\n",
+    "    \"from mdio import create_empty_like\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"copy_path = \\\"copy_of_existing.mdio\\\"\\n\",\n",
+    "    \"create_empty_like(create_conf.path, copy_path)\\n\",\n",
+    "    \"\\n\",\n",
+    "    \"copy_reader = MDIOReader(copy_path)\\n\",\n",
+    "    \"assert copy_reader.shape == reader.shape\\n\",\n",
+    "    \"assert copy_reader.binary_header == reader.binary_header\\n\",\n",
+    "    \"assert copy_reader.stats != reader.stats\"\n",
+    "   ]\n",
+    "  },\n",
+    "  {\n",
+    "   \"cell_type\": \"code\",\n",
+    "   \"execution_count\": null,\n",
+    "   \"metadata\": {},\n",
+    "   \"outputs\": [],\n",
+    "   \"source\": []\n",
+    "  }\n",
+    " ],\n",
+    " \"metadata\": {\n",
+    "  \"kernelspec\": {\n",
+    "   \"display_name\": \"Python 3 (ipykernel)\",\n",
+    "   \"language\": \"python\",\n",
+    "   \"name\": \"python3\"\n",
+    "  },\n",
+    "  \"language_info\": {\n",
+    "   \"codemirror_mode\": {\n",
+    "    \"name\": \"ipython\",\n",
+    "    \"version\": 3\n",
+    "   },\n",
+    "   \"file_extension\": \".py\",\n",
+    "   \"mimetype\": \"text/x-python\",\n",
+    "   \"name\": \"python\",\n",
+    "   \"nbconvert_exporter\": \"python\",\n",
+    "   \"pygments_lexer\": \"ipython3\",\n",
+    "   \"version\": \"3.12.3\"\n",
+    "  },\n",
+    "  \"widgets\": {\n",
+    "   \"application/vnd.jupyter.widget-state+json\": {\n",
+    "    \"state\": {\n",
+    "     \"104c0d4e90244ebc959e51a58794dcf4\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/base\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"LayoutModel\",\n",
+    "      \"state\": {\n",
+    "       \"display\": \"inline-flex\",\n",
+    "       \"flex_flow\": \"row wrap\",\n",
+    "       \"width\": \"100%\"\n",
+    "      }\n",
+    "     },\n",
+    "     \"1c0f5b458ee1401eaa8de63c65802073\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"HTMLStyleModel\",\n",
+    "      \"state\": {\n",
+    "       \"description_width\": \"\",\n",
+    "       \"font_size\": null,\n",
+    "       \"text_color\": null\n",
+    "      }\n",
+    "     },\n",
+    "     \"21b25dd6080d42368afc06770d5e1755\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"HTMLModel\",\n",
+    "      \"state\": {\n",
+    "       \"layout\": \"IPY_MODEL_35fb49026dac479eba87217c2f6bcb9a\",\n",
+    "       \"style\": \"IPY_MODEL_3ab3e27c83aa423d9ecdac94e576f0fe\",\n",
+    "       \"value\": \"Ingesting SEG-Y in 6 chunks: 100%\"\n",
+    "      }\n",
+    "     },\n",
+    "     \"2693aae410f04e7587f0400b5eef1079\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
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+    "       \"description_width\": \"\"\n",
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+    "       \"description_width\": \"\"\n",
+    "      }\n",
+    "     },\n",
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+    "      \"model_name\": \"LayoutModel\",\n",
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+    "       \"layout\": \"IPY_MODEL_9fe5348964cd4f7880bcd33204bbc7a2\",\n",
+    "       \"style\": \"IPY_MODEL_4df685a95de542ffab6f265df89b8949\",\n",
+    "       \"value\": \"Step 2 / 2 Concat Blocks: \"\n",
+    "      }\n",
+    "     },\n",
+    "     \"e66368cda8124001b16459a0634029e2\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"HTMLStyleModel\",\n",
+    "      \"state\": {\n",
+    "       \"description_width\": \"\",\n",
+    "       \"font_size\": null,\n",
+    "       \"text_color\": null\n",
+    "      }\n",
+    "     },\n",
+    "     \"eab4b060672b4dd5a73ca7bb8f782cd2\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/base\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"LayoutModel\",\n",
+    "      \"state\": {\n",
+    "       \"display\": \"inline-flex\",\n",
+    "       \"flex_flow\": \"row wrap\",\n",
+    "       \"width\": \"100%\"\n",
+    "      }\n",
+    "     },\n",
+    "     \"f65266f861cf40ef84e9ec74a8e0b44c\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"HTMLModel\",\n",
+    "      \"state\": {\n",
+    "       \"layout\": \"IPY_MODEL_fff4199774534d9f982f03738fbb08e7\",\n",
+    "       \"style\": \"IPY_MODEL_e66368cda8124001b16459a0634029e2\",\n",
+    "       \"value\": \"Scanning SEG-Y for geometry attributes: 100%\"\n",
+    "      }\n",
+    "     },\n",
+    "     \"fdcea609ee7349629604217b625371d3\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"HTMLStyleModel\",\n",
+    "      \"state\": {\n",
+    "       \"description_width\": \"\",\n",
+    "       \"font_size\": null,\n",
+    "       \"text_color\": null\n",
+    "      }\n",
+    "     },\n",
+    "     \"fff4199774534d9f982f03738fbb08e7\": {\n",
+    "      \"model_module\": \"@jupyter-widgets/base\",\n",
+    "      \"model_module_version\": \"2.0.0\",\n",
+    "      \"model_name\": \"LayoutModel\",\n",
+    "      \"state\": {}\n",
+    "     }\n",
+    "    },\n",
+    "    \"version_major\": 2,\n",
+    "    \"version_minor\": 0\n",
+    "   }\n",
+    "  }\n",
+    " },\n",
+    " \"nbformat\": 4,\n",
+    " \"nbformat_minor\": 4\n",
+    "}\n"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2025-04-16T14:50:17.246513Z",
-     "start_time": "2025-04-16T14:50:17.111779Z"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "from mdio import create_empty_like\n",
-    "\n",
-    "copy_path = \"copy_of_existing.mdio\"\n",
-    "create_empty_like(create_conf.path, copy_path)\n",
-    "\n",
-    "copy_reader = MDIOReader(copy_path)\n",
-    "assert copy_reader.shape == reader.shape\n",
-    "assert copy_reader.binary_header == reader.binary_header\n",
-    "assert copy_reader.stats != reader.stats"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

From 3c8ea4dac89b261ea1002c1874b09e130ba06080 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 14:43:41 -0500
Subject: [PATCH 05/56] update docs dependencies

---
 docs/requirements.txt | 1 +
 uv.lock               | 2 +-
 2 files changed, 2 insertions(+), 1 deletion(-)

diff --git a/docs/requirements.txt b/docs/requirements.txt
index c80a7d9db..cb04269ca 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,3 +1,4 @@
+autodoc-pydantic==2.2.0
 furo==2024.8.6
 linkify-it-py==2.0.3
 myst-nb==1.2.0
diff --git a/uv.lock b/uv.lock
index 2e73c4199..92ce6cdc0 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1922,7 +1922,7 @@ docs = [
     { name = "furo", specifier = ">=2024.8.6" },
     { name = "linkify-it-py", specifier = ">=2.0.3" },
     { name = "myst-nb", specifier = ">=1.2.0" },
-    { name = "sphinx", specifier = ">=8.1.3,<9" },
+    { name = "sphinx", specifier = ">=8.2.3,<9" },
     { name = "sphinx-autobuild", specifier = ">=2024.10.3" },
     { name = "sphinx-click", specifier = ">=6.0.0,<7" },
     { name = "sphinx-copybutton", specifier = ">=0.5.2,<0.6" },

From 53ecaa9346b2be03e08ec4b986b28865a429a31d Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 14:43:58 -0500
Subject: [PATCH 06/56] add new docs

---
 docs/api_reference.md           |   1 +
 docs/conf.py                    |  10 ++
 docs/data_models/chunk_grids.md | 154 +++++++++++++++++++
 docs/data_models/compressors.md | 100 ++++++++++++
 docs/data_models/data_types.md  | 259 ++++++++++++++++++++++++++++++++
 docs/data_models/dimensions.md  |  33 ++++
 docs/data_models/index.md       |  10 ++
 docs/data_models/version_0.md   |  55 +++++++
 docs/data_models/version_1.md   | 131 ++++++++++++++++
 docs/index.md                   |  11 ++
 10 files changed, 764 insertions(+)
 create mode 100644 docs/data_models/chunk_grids.md
 create mode 100644 docs/data_models/compressors.md
 create mode 100644 docs/data_models/data_types.md
 create mode 100644 docs/data_models/dimensions.md
 create mode 100644 docs/data_models/index.md
 create mode 100644 docs/data_models/version_0.md
 create mode 100644 docs/data_models/version_1.md

diff --git a/docs/api_reference.md b/docs/api_reference.md
index 0ceba4f56..f2ce3639d 100644
--- a/docs/api_reference.md
+++ b/docs/api_reference.md
@@ -71,4 +71,5 @@ and
 ```{eval-rst}
 .. automodule:: mdio.core.serialization
    :members:
+   :exclude-members: create_rechunk_plan, write_rechunked_values
 ```
diff --git a/docs/conf.py b/docs/conf.py
index 899903246..aeb59636a 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -17,6 +17,7 @@
     "sphinx.ext.napoleon",
     "sphinx.ext.intersphinx",
     "sphinx.ext.autosummary",
+    "sphinxcontrib.autodoc_pydantic",
     "sphinx.ext.autosectionlabel",
     "sphinx_click",
     "sphinx_copybutton",
@@ -38,6 +39,7 @@
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
+    "pydantic": ("https://docs.pydantic.dev/latest/", None),
     "zarr": ("https://zarr.readthedocs.io/en/stable/", None),
 }
 
@@ -50,6 +52,14 @@
 autoclass_content = "class"
 autosectionlabel_prefix_document = True
 
+autodoc_pydantic_field_list_validators = False
+autodoc_pydantic_field_swap_name_and_alias = True
+autodoc_pydantic_field_show_alias = False
+autodoc_pydantic_model_show_config_summary = False
+autodoc_pydantic_model_show_validator_summary = False
+autodoc_pydantic_model_show_validator_members = False
+autodoc_pydantic_model_show_field_summary = False
+
 html_theme = "furo"
 
 myst_number_code_blocks = ["python"]
diff --git a/docs/data_models/chunk_grids.md b/docs/data_models/chunk_grids.md
new file mode 100644
index 000000000..5f178a04b
--- /dev/null
+++ b/docs/data_models/chunk_grids.md
@@ -0,0 +1,154 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.chunk_grid
+
+```
+
+# Chunk Grid Models
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+The variables in MDIO data model can represent different types of chunk grids.
+These grids are essential for managing multi-dimensional data arrays efficiently.
+In this breakdown, we will explore four distinct data models within the MDIO schema,
+each serving a specific purpose in data handling and organization.
+
+MDIO implements data models following the guidelines of the Zarr v3 spec and ZEPs:
+
+- [Zarr core specification (version 3)](https://zarr-specs.readthedocs.io/en/latest/v3/core/v3.0.html)
+- [ZEP 1 — Zarr specification version 3](https://zarr.dev/zeps/accepted/ZEP0001.html)
+- [ZEP 3 — Variable chunking](https://zarr.dev/zeps/draft/ZEP0003.html)
+
+## Regular Grid
+
+The regular grid models are designed to represent a rectangular and regularly
+paced chunk grid.
+
+```{eval-rst}
+.. autosummary::
+   RegularChunkGrid
+   RegularChunkShape
+```
+
+For 1D array with `size = 31`{l=python}, we can divide it into 5 equally sized
+chunks. Note that the last chunk will be truncated to match the size of the array.
+
+`{ "name": "regular", "configuration": { "chunkShape": [7] } }`{l=json}
+
+Using the above schema resulting array chunks will look like this:
+
+```bash
+ ←─ 7 ─→ ←─ 7 ─→ ←─ 7 ─→ ←─ 7 ─→  ↔ 3
+┌───────┬───────┬───────┬───────┬───┐
+└───────┴───────┴───────┴───────┴───┘
+```
+
+For 2D array with shape `rows, cols = (7, 17)`{l=python}, we can divide it into 9
+equally sized chunks.
+
+`{ "name": "regular", "configuration": { "chunkShape": [3, 7] } }`{l=json}
+
+Using the above schema, the resulting 2D array chunks will look like below.
+Note that the rows and columns are conceptual and visually not to scale.
+
+```bash
+ ←─ 7 ─→ ←─ 7 ─→  ↔ 3
+┌───────┬───────┬───┐
+│       ╎       ╎   │  ↑
+│       ╎       ╎   │  3
+│       ╎       ╎   │  ↓
+├╶╶╶╶╶╶╶┼╶╶╶╶╶╶╶┼╶╶╶┤
+│       ╎       ╎   │  ↑
+│       ╎       ╎   │  3
+│       ╎       ╎   │  ↓
+├╶╶╶╶╶╶╶┼╶╶╶╶╶╶╶┼╶╶╶┤
+│       ╎       ╎   │  ↕ 1
+└───────┴───────┴───┘
+```
+
+## Rectilinear Grid
+
+The [RectilinearChunkGrid](RectilinearChunkGrid) model extends
+the concept of chunk grids to accommodate rectangular and irregularly spaced chunks.
+This model is useful in data structures where non-uniform chunk sizes are necessary.
+[RectilinearChunkShape](RectilinearChunkShape) specifies the chunk sizes for each
+dimension as a list allowing for irregular intervals.
+
+```{eval-rst}
+.. autosummary::
+   RectilinearChunkGrid
+   RectilinearChunkShape
+```
+
+:::{note}
+It's important to ensure that the sum of the irregular spacings specified
+in the `chunkShape` matches the size of the respective array dimension.
+:::
+
+For 1D array with `size = 39`{l=python}, we can divide it into 5 irregular sized
+chunks.
+
+`{ "name": "rectilinear", "configuration": { "chunkShape": [[10, 7, 5, 7, 10]] } }`{l=json}
+
+Using the above schema resulting array chunks will look like this:
+
+```bash
+ ←── 10 ──→ ←─ 7 ─→ ← 5 → ←─ 7 ─→ ←── 10 ──→
+┌──────────┬───────┬─────┬───────┬──────────┐
+└──────────┴───────┴─────┴───────┴──────────┘
+```
+
+For 2D array with shape `rows, cols = (7, 25)`{l=python}, we can divide it into 12
+rectilinear (rectangular bur irregular) chunks. Note that the rows and columns are
+conceptual and visually not to scale.
+
+`{ "name": "rectilinear", "configuration": { "chunkShape": [[3, 1, 3], [10, 5, 7, 3]] } }`{l=json}
+
+```bash
+ ←── 10 ──→ ← 5 → ←─ 7 ─→  ↔ 3
+┌──────────┬─────┬───────┬───┐
+│          ╎     ╎       ╎   │  ↑
+│          ╎     ╎       ╎   │  3
+│          ╎     ╎       ╎   │  ↓
+├╶╶╶╶╶╶╶╶╶╶┼╶╶╶╶╶┼╶╶╶╶╶╶╶┼╶╶╶┤
+│          ╎     ╎       ╎   │  ↕ 1
+├╶╶╶╶╶╶╶╶╶╶┼╶╶╶╶╶┼╶╶╶╶╶╶╶┼╶╶╶┤
+│          ╎     ╎       ╎   │  ↑
+│          ╎     ╎       ╎   │  3
+│          ╎     ╎       ╎   │  ↓
+└──────────┴─────┴───────┴───┘
+```
+
+## Model Reference
+
+:::{dropdown} RegularChunkGrid
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autopydantic_model:: RegularChunkGrid
+
+----------
+
+.. autopydantic_model:: RegularChunkShape
+```
+
+:::
+:::{dropdown} RectilinearChunkGrid
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autopydantic_model:: RectilinearChunkGrid
+
+----------
+
+.. autopydantic_model:: RectilinearChunkShape
+```
+
+:::
diff --git a/docs/data_models/compressors.md b/docs/data_models/compressors.md
new file mode 100644
index 000000000..17a1afd87
--- /dev/null
+++ b/docs/data_models/compressors.md
@@ -0,0 +1,100 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.compressors
+
+```
+
+# Compressors
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+## Dataset Compression
+
+MDIO relies on [numcodecs] for data compression. We provide good defaults based
+on opinionated and limited heuristics for each compressor for various energy datasets.
+However, using these data models, the compression can be customized.
+
+[Numcodecs] is a project that a convenient interface to different compression
+libraries. We selected the [Blosc] and [ZFP] compressors for lossless and lossy
+compression of energy data.
+
+## Blosc
+
+A high-performance compressor optimized for binary data, combining fast compression
+with a byte-shuffle filter for enhanced efficiency, particularly effective with
+numerical arrays in multi-threaded environments.
+
+For more details about compression modes, see [Blosc Documentation].
+
+```{eval-rst}
+.. autosummary::
+   Blosc
+```
+
+## ZFP
+
+ZFP is a compression algorithm tailored for floating-point and integer arrays, offering
+lossy and lossless compression with customizable precision, well-suited for large
+scientific datasets with a focus on balancing data fidelity and compression ratio.
+
+For more details about compression modes, see [ZFP Documentation].
+
+```{eval-rst}
+.. autosummary::
+   ZFP
+```
+
+[numcodecs]: https://github.com/zarr-developers/numcodecs
+[blosc]: https://github.com/Blosc/c-blosc
+[blosc documentation]: https://www.blosc.org/python-blosc/python-blosc.html
+[zfp]: https://github.com/LLNL/zfp
+[zfp documentation]: https://computing.llnl.gov/projects/zfp
+
+## Model Reference
+
+:::
+:::{dropdown} Blosc
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autopydantic_model:: Blosc
+
+----------
+
+.. autoclass:: BloscAlgorithm()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+----------
+
+.. autoclass:: BloscShuffle()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+```
+
+:::
+
+:::{dropdown} ZFP
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autopydantic_model:: ZFP
+
+----------
+
+.. autoclass:: ZFPMode()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+```
+
+:::
diff --git a/docs/data_models/data_types.md b/docs/data_models/data_types.md
new file mode 100644
index 000000000..b58ff5357
--- /dev/null
+++ b/docs/data_models/data_types.md
@@ -0,0 +1,259 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.dtype
+
+```
+
+# Data Types
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+## Scalar Type
+
+Scalar types are used to represent numbers and boolean values in MDIO arrays.
+
+```{eval-rst}
+.. autosummary::
+   :nosignatures:
+
+   ScalarType
+```
+
+These numbers can be integers (whole numbers without a decimal
+point, like 1, -15, 204), floating-point numbers (numbers with a fractional part,
+like 3.14, -0.001, 2.71828) in various 16-64 bit formats like `float32` etc.
+
+It is important to choose the right type for the content of the data for type safety,
+memory efficiency, performance, and accuracy of the numbers represented. Most scientific
+datasets are `float16`, `float32`, or `float64` values. However, there are many good
+use cases for integer and complex values as well.
+
+The [`ScalarType`](#ScalarType)s MDIO supports can be viewed below with the tabs.
+
+:::::{tab-set}
+
+::::{tab-item} Boolean
+:::{table}
+:widths: auto
+:align: center
+
+| Data Type | Options         | Example Value |
+| --------- | --------------- | ------------- |
+| `bool`    | `False`, `True` | `True`        |
+
+:::
+::::
+
+::::{tab-item} Integers
+:::{table}
+:widths: auto
+:align: center
+
+| Data Type | Range                                                       | Example Value |
+| --------- | ----------------------------------------------------------- | ------------- |
+| `int8`    | `-128` to `127`                                             | `45`          |
+| `int16`   | `-32,768` to `32,767`                                       | `1,234`       |
+| `int32`   | `-2,147,483,648` to `2,147,483,647`                         | `2,024`       |
+| `int64`   | `-9,223,372,036,854,775,808` to `9,223,372,036,854,775,807` | `987,654,321` |
+
+:::
+::::
+
+::::{tab-item} Unsigned Integers
+:::{table}
+:widths: auto
+:align: center
+
+| Data Type | Range                               | Example Value   |
+| --------- | ----------------------------------- | --------------- |
+| `uint8`   | `0` to `255`                        | `200`           |
+| `uint16`  | `0` to `65,535`                     | `50,000`        |
+| `uint32`  | `0` to `4,294,967,295`              | `3,000,000`     |
+| `uint64`  | `0` to `18,446,744,073,709,551,615` | `5,000,000,000` |
+
+:::
+::::
+
+::::{tab-item} Floating Point
+:::{table}
+:widths: auto
+:align: center
+
+| Data Type | Range                                                   | Example Value        |
+| --------- | ------------------------------------------------------- | -------------------- |
+| `float16` | `-65,504` to `65,504`                                   | `10.10`              |
+| `float32` | `-3.4028235e+38` to `3.4028235e+38`                     | `0.1234567`          |
+| `float64` | `-1.7976931348623157e+308` to `1.7976931348623157e+308` | `3.1415926535897932` |
+
+:::
+
+**Precision**
+
+- `float16`: 2 decimal places
+- `float32`: 7 decimal places
+- `float32`: 16 decimal places
+
+::::
+
+::::{tab-item} Complex Numbers
+:::{table}
+:widths: auto
+:align: center
+
+| Data Type    | Range                                                   | Example Value      |
+| ------------ | ------------------------------------------------------- | ------------------ |
+| `complex64`  | `-3.4028235e+38` to `3.4028235e+38`                     | `3.14+2.71j`       |
+| `complex128` | `-1.7976931348623157e+308` to `1.7976931348623157e+308` | `2.71828+3.14159j` |
+
+:::
+Ranges are for both real and imaginary parts.
+::::
+
+:::::
+
+## Structured Type
+
+Structured data type organizes and stores data in a fixed arrangement, allowing memory
+efficient access and manipulation.
+
+```{eval-rst}
+.. autosummary::
+   :nosignatures:
+
+   StructuredType
+   StructuredField
+```
+
+Structured data types are an essential component in handling complex data structures,
+particularly in specialized domains like seismic data processing for subsurface
+imaging applications. These data types allow for the organization of heterogeneous
+data into a single, structured format.
+
+They are designed to be memory-efficient, which is vital for handling large seismic
+datasets. Structured data types are adaptable, allowing for the addition or
+modification of fields.
+
+A [`StructuredType`](#StructuredType) consists of [`StructuredField`](#StructuredField)s.
+Fields can be different [numeric types](#numeric-types), and each represent a specific
+attribute of the seismic data, like coordinate, line numbers, and time stamps.
+
+Each [`StructuredField`](#StructuredField) must specify a `name` and a data format
+(`format`).
+
+All the structured fields will be packed and there will be no gaps between them.
+
+## Examples
+
+The table below illustrate [ScalarType](#ScalarType) ranges and shows an example each
+type.
+
+Variable `foo` with type `float32`.
+
+```json
+{
+  "name": "foo",
+  "dataType": "float32",
+  "dimensions": ["x", "y"]
+}
+```
+
+Variable `bar` with type `uint8`.
+
+```json
+{
+  "name": "bar",
+  "dataType": "uint8",
+  "dimensions": ["x", "y"]
+}
+```
+
+Below are a couple examples of [StructuredType](#StructuredType) with varying lengths.
+
+We can specify a variable named `headers` that holds a 32-byte struct with
+four `int32` values.
+
+```json
+{
+  "name": "headers",
+  "dataType": {
+    "fields": [
+      { "name": "cdp-x", "format": "int32" },
+      { "name": "cdp-y", "format": "int32" },
+      { "name": "inline", "format": "int32" },
+      { "name": "crossline", "format": "int32" }
+    ]
+  },
+  "dimensions": ["inline", "crossline"]
+}
+```
+
+This will yield an in-memory or on-disk struct that looks like this (for each element):
+
+```bash
+ ←─ 4 ─→ ←─ 4 ─→ ←─ 4 ─→ ←─ 4 ─→  = 16-bytes
+┌───────┬───────┬───────┬───────┐
+│ int32 ╎ int32 ╎ int32 ╎ int32 │ ⋯ (next sample)
+└───────┴───────┴───────┴───────┘
+  └→ cdp-x └→ cdp-y └→ inline └→crossline
+```
+
+The below example shows mixing different data types.
+
+```json
+{
+  "name": "headers",
+  "dataType": {
+    "fields": [
+      { "name": "cdp", "format": "uint32" },
+      { "name": "offset", "format": "int16" },
+      { "name": "cdp-x", "format": "float64" },
+      { "name": "cdp-y", "format": "float64" }
+    ]
+  },
+  "dimensions": ["inline", "crossline"]
+}
+```
+
+This will yield an in-memory or on-disk struct that looks like this (for each element):
+
+```bash
+ ←── 4 ──→ ← 2 → ←─── 8 ───→ ←─── 8 ───→  = 24-bytes
+┌─────────┬─────┬───────────┬───────────┐
+│  int32  ╎int16╎  float64  ╎  float64  │ ⋯ (next sample)
+└─────────┴─────┴───────────┴───────────┘
+    └→ cdp  └→ offset └→ cdp-x    └→ cdp-y
+```
+
+## Model Reference
+
+:::{dropdown} Scalar Types
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autoclass:: ScalarType()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+```
+
+:::
+
+:::{dropdown} Structured Type
+:animate: fade-in-slide-down
+
+```{eval-rst}
+.. autopydantic_model:: StructuredType
+
+----------
+
+.. autopydantic_model:: StructuredField
+```
+
+:::
diff --git a/docs/data_models/dimensions.md b/docs/data_models/dimensions.md
new file mode 100644
index 000000000..c04b9206b
--- /dev/null
+++ b/docs/data_models/dimensions.md
@@ -0,0 +1,33 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.dimension
+
+```
+
+# Dimensions
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+## Intro
+
+```{eval-rst}
+.. autosummary:: NamedDimension
+```
+
+## Reference
+
+:::{dropdown} Dimension
+:open:
+
+```{eval-rst}
+.. autopydantic_model:: NamedDimension
+```
+
+:::
diff --git a/docs/data_models/index.md b/docs/data_models/index.md
new file mode 100644
index 000000000..191f937b7
--- /dev/null
+++ b/docs/data_models/index.md
@@ -0,0 +1,10 @@
+# Dataset Models
+
+This section contains the data models for the MDIO format.
+
+```{toctree}
+:maxdepth: 2
+
+version_0
+version_1
+```
diff --git a/docs/data_models/version_0.md b/docs/data_models/version_0.md
new file mode 100644
index 000000000..bac21ff6b
--- /dev/null
+++ b/docs/data_models/version_0.md
@@ -0,0 +1,55 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.v0.dataset
+
+```
+
+# MDIO v0
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+## Intro
+
+```{eval-rst}
+.. autosummary::
+
+   DatasetModelV0
+   VariableModelV0
+   DatasetMetadataModelV0
+   DimensionModelV0
+```
+
+## Reference
+
+:::{dropdown} Dataset
+:open:
+
+```{eval-rst}
+.. autopydantic_model:: DatasetModelV0
+    :inherited-members: BaseModel
+
+.. autopydantic_model:: DatasetMetadataModelV0
+    :inherited-members: BaseModel
+
+.. autopydantic_model:: DimensionModelV0
+    :inherited-members: BaseModel
+```
+
+:::
+
+:::{dropdown} Variable
+:open:
+
+```{eval-rst}
+.. autopydantic_model:: VariableModelV0
+    :inherited-members: BaseModel
+```
+
+:::
diff --git a/docs/data_models/version_1.md b/docs/data_models/version_1.md
new file mode 100644
index 000000000..caf0ed5c7
--- /dev/null
+++ b/docs/data_models/version_1.md
@@ -0,0 +1,131 @@
+```{eval-rst}
+:tocdepth: 3
+```
+
+```{currentModule} mdio.schemas.v1.dataset
+
+```
+
+# MDIO v1
+
+```{article-info}
+:author: Altay Sansal
+:date: "{sub-ref}`today`"
+:read-time: "{sub-ref}`wordcount-minutes` min read"
+:class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light
+```
+
+## Intro
+
+```{eval-rst}
+.. autosummary:: Dataset
+.. autosummary:: DatasetMetadata
+```
+
+## Reference
+
+:::{dropdown} Dataset
+:open:
+
+```{eval-rst}
+.. autopydantic_model:: Dataset
+    :inherited-members: BaseModel
+
+.. autopydantic_model:: DatasetMetadata
+    :inherited-members: BaseModel
+```
+
+:::
+:::{dropdown} Variable
+
+```{eval-rst}
+.. autopydantic_model:: mdio.schemas.v1.variable.Variable
+    :inherited-members: BaseModel
+
+.. autopydantic_model:: mdio.schemas.v1.variable.Coordinate
+    :inherited-members: BaseModel
+
+.. automodule:: mdio.schemas.metadata
+    :members: UserAttributes
+
+.. autopydantic_model:: mdio.schemas.v1.variable.VariableMetadata
+    :inherited-members: BaseModel
+```
+
+:::
+
+:::{dropdown} Units
+
+```{eval-rst}
+.. autopydantic_model:: mdio.schemas.v1.units.AllUnits
+```
+
+```{eval-rst}
+.. automodule:: mdio.schemas.v1.units
+    :members: LengthUnitModel,
+              TimeUnitModel,
+              AngleUnitModel,
+              DensityUnitModel,
+              SpeedUnitModel,
+              FrequencyUnitModel,
+              VoltageUnitModel
+```
+
+:::
+
+:::{dropdown} Stats
+
+```{eval-rst}
+.. autopydantic_model:: mdio.schemas.v1.stats.StatisticsMetadata
+
+.. autopydantic_model:: mdio.schemas.v1.stats.SummaryStatistics
+
+.. autopydantic_model:: mdio.schemas.v1.stats.EdgeDefinedHistogram
+    :inherited-members: BaseModel
+
+.. autopydantic_model:: mdio.schemas.v1.stats.CenteredBinHistogram
+    :inherited-members: BaseModel
+```
+
+:::
+
+:::{dropdown} Enums
+
+```{eval-rst}
+.. autoclass:: mdio.schemas.v1.units.AngleUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.DensityUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.FrequencyUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.LengthUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.SpeedUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.TimeUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+
+.. autoclass:: mdio.schemas.v1.units.VoltageUnitEnum()
+    :members:
+    :undoc-members:
+    :member-order: bysource
+```
+
+:::
diff --git a/docs/index.md b/docs/index.md
index 9b6741077..ba4db72de 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -26,6 +26,17 @@ tutorials/index
 api_reference
 ```
 
+```{toctree}
+:hidden:
+:caption: Core Concepts and Structures
+
+data_models/index
+data_models/dimensions
+data_models/chunk_grids
+data_models/data_types
+data_models/compressors
+```
+
 ```{toctree}
 :hidden:
 :caption: Community and Contribution

From da09c4b8f7c216b098ee4925b1eb86fc5b251806 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 14:55:26 -0500
Subject: [PATCH 07/56] remove incorrect exclude

---
 docs/api_reference.md | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/api_reference.md b/docs/api_reference.md
index f2ce3639d..0ceba4f56 100644
--- a/docs/api_reference.md
+++ b/docs/api_reference.md
@@ -71,5 +71,4 @@ and
 ```{eval-rst}
 .. automodule:: mdio.core.serialization
    :members:
-   :exclude-members: create_rechunk_plan, write_rechunked_values
 ```

From 0d59c9554f2b124fee50105fc20cbb31092d60ce Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 15:33:52 -0500
Subject: [PATCH 08/56] remove duplicate doc directive

---
 docs/tutorials/creation.ipynb | 1225 ++++++++++++++++++++++-----------
 1 file changed, 838 insertions(+), 387 deletions(-)

diff --git a/docs/tutorials/creation.ipynb b/docs/tutorials/creation.ipynb
index d154c63f8..25a67c4f8 100644
--- a/docs/tutorials/creation.ipynb
+++ b/docs/tutorials/creation.ipynb
@@ -7,396 +7,847 @@
     "{\n",
     " \"cells\": [\n",
     "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%% md\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"source\": [\n",
-    "    \"# Create an Empty MDIO\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"```{article-info}\\n\",\n",
-    "    \":author: Altay Sansal\\n\",\n",
-    "    \":date: \\\"{sub-ref}`today`\\\"\\n\",\n",
-    "    \":read-time: \\\"{sub-ref}`wordcount-minutes` min read\\\"\\n\",\n",
-    "    \":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\n\",\n",
-    "    \"```\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"Here we will create an empty MDIO file and populate its fields.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"```{warning}\\n\",\n",
-    "    \"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\n\",\n",
-    "    \"`pip install matplotlib` or `conda install matplotlib`.\\n\",\n",
-    "    \"```\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We first need to import the configuration classes and create function to be able to create the empty MDIO.\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 2,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:04.371422Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:04.368107Z\"\n",
-    "    },\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%%\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [],\n",
-    "   \"source\": [\n",
-    "    \"import matplotlib.pyplot as plt\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"from mdio import Dimension\\n\",\n",
-    "    \"from mdio import Grid\\n\",\n",
-    "    \"from mdio import MDIOCreateConfig\\n\",\n",
-    "    \"from mdio import MDIOReader\\n\",\n",
-    "    \"from mdio import MDIOVariableConfig\\n\",\n",
-    "    \"from mdio import MDIOWriter\\n\",\n",
-    "    \"from mdio import create_empty\\n\",\n",
-    "    \"from mdio.converters.segy import get_compressor\\n\",\n",
-    "    \"from mdio.segy.compat import mdio_segy_spec\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%% md\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"source\": [\n",
-    "    \"## Setting Up Grid Dimensions and Variable(s)\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\n\",\n",
-    "    \"dimensions. This is exactly like a 3D Post-Stack dataset.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We will use the standard `chunked_012` access pattern. All variable names must start\\n\",\n",
-    "    \"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We will also use an MDIO private utility function to get the compressor easily. The\\n\",\n",
-    "    \"compressor is fully customizable, but this function gives us ones available in SEG-Y\\n\",\n",
-    "    \"ingestion.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\n\",\n",
-    "    \"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"At the end we create empty MDIO on local disk or cloud, based on the path string.\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 3,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:06.121450Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:06.002634Z\"\n",
-    "    },\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%%\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [],\n",
-    "   \"source\": [\n",
-    "    \"grid = Grid(\\n\",\n",
-    "    \"    dims=[\\n\",\n",
-    "    \"        Dimension(name=\\\"inline\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\n\",\n",
-    "    \"        Dimension(name=\\\"crossline\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\n\",\n",
-    "    \"        Dimension(name=\\\"sample\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\n\",\n",
-    "    \"    ]\\n\",\n",
-    "    \")\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"compressor = get_compressor(lossless=True)\\n\",\n",
-    "    \"header_dtype = mdio_segy_spec().trace.header.dtype\\n\",\n",
-    "    \"variable = MDIOVariableConfig(\\n\",\n",
-    "    \"    name=\\\"chunked_012\\\",\\n\",\n",
-    "    \"    dtype=\\\"float32\\\",\\n\",\n",
-    "    \"    chunks=(128, 128, 128),\\n\",\n",
-    "    \"    compressors=compressor,\\n\",\n",
-    "    \"    header_dtype=header_dtype,\\n\",\n",
-    "    \")\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"create_conf = MDIOCreateConfig(path=\\\"demo.mdio\\\", grid=grid, variables=[variable])\\n\",\n",
-    "    \"create_empty(config=create_conf);\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
     "   \"metadata\": {},\n",
+    "   \"cell_type\": \"raw\",\n",
     "   \"source\": [\n",
-    "    \"## Populating the MDIO\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"Once empty MDIO is created, you can populate it with sample data, header data,\\n\",\n",
-    "    \"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\n\",\n",
-    "    \"every write. However, the consistency of the `live_mask` is up to the user. If\\n\",\n",
-    "    \"not populated correctly, at read time, traces may be skipped.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We will read the usual stats and as you can see they're all empty. Text header\\n\",\n",
-    "    \"and binary header are only required if we are going to export this back to SEG-Y,\\n\",\n",
-    "    \"and can be modified. We can edit these if necessary using the writer.\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 4,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:09.974442Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:09.951257Z\"\n",
-    "    },\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%%\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [\n",
-    "    {\n",
-    "     \"data\": {\n",
-    "      \"text/plain\": [\n",
-    "       \"(['C00                                                                             ',\\n\",\n",
-    "       \"  'C01                                                                             ',\\n\",\n",
-    "       \"  'C02                                                                             ',\\n\",\n",
-    "       \"  'C03                                                                             ',\\n\",\n",
-    "       \"  'C04                                                                             '],\\n\",\n",
-    "       \" {},\\n\",\n",
-    "       \" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\"\n",
-    "      ]\n",
-    "     },\n",
-    "     \"execution_count\": 4,\n",
-    "     \"metadata\": {},\n",
-    "     \"output_type\": \"execute_result\"\n",
-    "    }\n",
-    "   ],\n",
-    "   \"source\": [\n",
-    "    \"writer = MDIOWriter(create_conf.path)\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"# Truncate text header for display\\n\",\n",
-    "    \"writer.text_header[:5], writer.binary_header, writer.stats\"\n",
+    "    \"{\\n\",\n",
+    "    \" \\\"cells\\\": [\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%% md\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"# Create an Empty MDIO\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"```{article-info}\\\\n\\\",\\n\",\n",
+    "    \"    \\\":author: Altay Sansal\\\\n\\\",\\n\",\n",
+    "    \"    \\\":date: \\\\\\\"{sub-ref}`today`\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\":read-time: \\\\\\\"{sub-ref}`wordcount-minutes` min read\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\\\n\\\",\\n\",\n",
+    "    \"    \\\"```\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"Here we will create an empty MDIO file and populate its fields.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"```{warning}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\\\n\\\",\\n\",\n",
+    "    \"    \\\"`pip install matplotlib` or `conda install matplotlib`.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"```\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We first need to import the configuration classes and create function to be able to create the empty MDIO.\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 2,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:04.371422Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:04.368107Z\\\"\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"import matplotlib.pyplot as plt\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import Dimension\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import Grid\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import MDIOCreateConfig\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import MDIOReader\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import MDIOVariableConfig\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import MDIOWriter\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import create_empty\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio.converters.segy import get_compressor\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio.segy.compat import mdio_segy_spec\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%% md\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"## Setting Up Grid Dimensions and Variable(s)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\\\n\\\",\\n\",\n",
+    "    \"    \\\"dimensions. This is exactly like a 3D Post-Stack dataset.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We will use the standard `chunked_012` access pattern. All variable names must start\\\\n\\\",\\n\",\n",
+    "    \"    \\\"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We will also use an MDIO private utility function to get the compressor easily. The\\\\n\\\",\\n\",\n",
+    "    \"    \\\"compressor is fully customizable, but this function gives us ones available in SEG-Y\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ingestion.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"At the end we create empty MDIO on local disk or cloud, based on the path string.\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 3,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:06.121450Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:06.002634Z\\\"\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"grid = Grid(\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    dims=[\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        Dimension(name=\\\\\\\"inline\\\\\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        Dimension(name=\\\\\\\"crossline\\\\\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        Dimension(name=\\\\\\\"sample\\\\\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"compressor = get_compressor(lossless=True)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"header_dtype = mdio_segy_spec().trace.header.dtype\\\\n\\\",\\n\",\n",
+    "    \"    \\\"variable = MDIOVariableConfig(\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    name=\\\\\\\"chunked_012\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    dtype=\\\\\\\"float32\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    chunks=(128, 128, 128),\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    compressors=compressor,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    header_dtype=header_dtype,\\\\n\\\",\\n\",\n",
+    "    \"    \\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"create_conf = MDIOCreateConfig(path=\\\\\\\"demo.mdio\\\\\\\", grid=grid, variables=[variable])\\\\n\\\",\\n\",\n",
+    "    \"    \\\"create_empty(config=create_conf);\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"## Populating the MDIO\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"Once empty MDIO is created, you can populate it with sample data, header data,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\\\n\\\",\\n\",\n",
+    "    \"    \\\"every write. However, the consistency of the `live_mask` is up to the user. If\\\\n\\\",\\n\",\n",
+    "    \"    \\\"not populated correctly, at read time, traces may be skipped.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We will read the usual stats and as you can see they're all empty. Text header\\\\n\\\",\\n\",\n",
+    "    \"    \\\"and binary header are only required if we are going to export this back to SEG-Y,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"and can be modified. We can edit these if necessary using the writer.\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 4,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:09.974442Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:09.951257Z\\\"\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"data\\\": {\\n\",\n",
+    "    \"      \\\"text/plain\\\": [\\n\",\n",
+    "    \"       \\\"(['C00                                                                             ',\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'C01                                                                             ',\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'C02                                                                             ',\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'C03                                                                             ',\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'C04                                                                             '],\\\\n\\\",\\n\",\n",
+    "    \"       \\\" {},\\\\n\\\",\\n\",\n",
+    "    \"       \\\" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\\\"\\n\",\n",
+    "    \"      ]\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"execution_count\\\": 4,\\n\",\n",
+    "    \"     \\\"metadata\\\": {},\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"execute_result\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   ],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"writer = MDIOWriter(create_conf.path)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"# Truncate text header for display\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer.text_header[:5], writer.binary_header, writer.stats\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"## Updating File and Checking with `MDIOReader`.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We write traces here, the headers are still empty. If you need the headers\\\\n\\\",\\n\",\n",
+    "    \"    \\\"populated, this is where they would be written to file as well.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"All the extra metadata we are writing is so that we can export back to SEG-Y\\\\n\\\",\\n\",\n",
+    "    \"    \\\"in the future. If that's not a requirement most of the metadata can be\\\\n\\\",\\n\",\n",
+    "    \"    \\\"omitted.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"If you already have an MDIO prior to this, all the metadata can be copied\\\\n\\\",\\n\",\n",
+    "    \"    \\\"over from the previous version.\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 5,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:12.498287Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:11.670230Z\\\"\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    \\\"pycharm\\\": {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"data\\\": {\\n\",\n",
+    "    \"      \\\"text/plain\\\": [\\n\",\n",
+    "    \"       \\\"({'data_sample_format': 1,\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'sample_interval': 4,\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'samples_per_trace': 750,\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'segy_revision_major': 1,\\\\n\\\",\\n\",\n",
+    "    \"       \\\"  'segy_revision_minor': 0},\\\\n\\\",\\n\",\n",
+    "    \"       \\\" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\\\"\\n\",\n",
+    "    \"      ]\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"execution_count\\\": 5,\\n\",\n",
+    "    \"     \\\"metadata\\\": {},\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"execute_result\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   ],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"sample_dim = writer.grid.select_dim(\\\\\\\"sample\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\\\n\\\",\\n\",\n",
+    "    \"    \\\"num_samples = sample_dim.size\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer.binary_header = {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"data_sample_format\\\\\\\": 1,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"sample_interval\\\\\\\": sample_interval,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"samples_per_trace\\\\\\\": num_samples,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"segy_revision_major\\\\\\\": 1,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"segy_revision_minor\\\\\\\": 0,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"# Write some values to the file\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer[:5] = 1\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer[5:10] = 2\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer[50:100] = 3\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer[150:175] = -1\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"# Write some made up stats\\\\n\\\",\\n\",\n",
+    "    \"    \\\"writer.stats = {\\\\\\\"mean\\\\\\\": 12, \\\\\\\"std\\\\\\\": 5, \\\\\\\"rms\\\\\\\": 3, \\\\\\\"min\\\\\\\": -4, \\\\\\\"max\\\\\\\": 4}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"reader = MDIOReader(create_conf.path)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"reader.binary_header, reader.stats\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"source\\\": \\\"Plot some of the data we populated:\\\"\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 6,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:14.256953Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:14.036094Z\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"data\\\": {\\n\",\n",
+    "    \"      \\\"image/png\\\": 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yCsrRsXq3WvDhg3d8//orOC6bp1OPqvz9QBAIKOMAxA0ExTrSgDbtm0zkxU6dHJFXa7Fc1btC9FC8vDhw2aSQ52EFkDg0XtUneBaZ713Jli1wZWWcZRvQHCVbwEf7H755RezrInOiu1Jnzvr3mWnS514LneiKxg4S6gACGwHDx40s+Hb4lLLOMo3ILjLt4APdpdj3LhxZvmY7H78qpIUK5K3O/1HGtaQ1BOB++Pr8tRR6dwvePrnZKSLdKl7s2RmBE+Nhb9+x3t3RMuQTjde9e+bIemyTpaYmqlgllv5dv3o4RL6v0XbHY0bJEloSNZ5x/4wtapknf2/tZID0aMJX0vXltslWGRkhsi9zz4qmVn21FRfTHjSTxL+3yNX/ftmxRWWtDuu/o1SZnqabFv6Yp7Kt8BNJv9TsmRJsybn0aNHvV7X57rGXU60SUM7Insu4q79VTTUFSuatz+M8JBwCQsJ3B9fdGRYnq/VBhnpIRIWEh5UTVH++h0XiSlkftZX3f96C9v2O77UMi638k1DXfZgFx4TIYVCzw92YeFRkpUVuMEuOjo8uMq3zFDzOwsJomAXVijSL+VMVkiE+Vn7S17Kt4D/VxAREWEWQdZFmD37lOjz3BZDjoyMNIsxe24AYEMZR/kGBLfArXLyoHen3bt3lwYNGsitt94qb7zxhqSmpspjjz3m71MDgCtGGQcgqIJd586d5eeff5aRI0dKcnKy1KtXT5YuXXpeZ2MACESUcQCCKtipfv36mQ0AbEQZByAvAr6PHQAAAP4PwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAB9Zu3attGvXTsqVKychISGycOFCr/0ul0tGjhwpZcuWlejoaGnRooXs2bPH65hff/1VunbtKsWKFZO4uDjp2bOnnD59+ipfCYBAQbADAB9JTU2VunXryuTJk3PcP378eJk0aZJMmzZNNm3aJDExMZKQkCBpaWnuYzTU7dy5U1asWCGLFy82YbF3795X8SoABJIwf58AANiqdevWZsuJ1ta98cYbMnz4cGnfvr15bc6cOVK6dGlTs9elSxfZvXu3LF26VLZs2SINGjQwx7z11lvSpk0bmTBhgqkJBABP1NgBgB/s379fkpOTTfOrIzY2Vho1aiQbNmwwz/VRm1+dUKf0+NDQUFPDBwDZUWMHAH6goU5pDZ0nfe7s08dSpUp57Q8LC5PixYu7j8nu7NmzZnOcPHnSB2cPoKCixg4ALDJu3DhT8+ds5cuX9/cpAbiKCHYA4AdlypQxj0ePHvV6XZ87+/QxJSXFa39GRoYZKesck92wYcPkxIkT7u3gwYM+uwYABQ/BDgD8oHLlyiacJSYmejWbat+5+Ph481wfjx8/Ltu2bXMfs2rVKsnKyjJ98XISGRlppkbx3AAED/rYAYCP6Hxze/fu9RowsX37dtNHrkKFCjJgwAB54YUXpGrVqibojRgxwox07dChgzm+Ro0a0qpVK+nVq5eZEiU9PV369etnRswyIhZATgh2AOAjW7dulbvvvtv9fNCgQeaxe/fuMmvWLHnmmWfMXHc6L53WzDVp0sRMbxIVFeV+z/vvv2/CXPPmzc1o2E6dOpm57wAgJwQ7APCRpk2bmvnqcqOrUYwZM8ZsudHavblz5/roDAHYhj52AAAAliDYAQAAWIJgBwAAYIkCHexGjx5t+qB4btWrV3fv14Wy+/btKyVKlJAiRYqYTsXZ54QCAAAIFgU62KlatWrJkSNH3Nu6devc+wYOHCiLFi2S+fPny5o1a+Tw4cPSsWNHv54vAACAvxT4UbG6LmJOM6zrjOrvvvuuGS3WrFkz89rMmTPNvE8bN26Uxo0b++FsAQAA/KfA19jt2bPHTMR5ww03SNeuXeXAgQPmdZ2JXSfrbNGihftYbabVST83bNhwwc/UBbJ1hnfPDQAAINAV6GCnS+boJJ46YefUqVPNrO133HGHnDp1SpKTkyUiIkLi4uK83lO6dGmz70JYJBsAANioQDfFtm7d2v11nTp1TNCrWLGifPjhhxIdHX3Zn6uLZDszwCutsSPcAQCAQFega+yy09q5atWqmbUXtd/duXPnzDI8nnRUbE598jyxSDYAALBRaKAtqL1v3z4pW7as1K9fX8LDwyUxMdG9PykpyfTBi4+P9+t5AgAA+EOBboodPHiwtGvXzjS/6lQmo0aNkkKFCslDDz1k+sb17NnTNKnqWopa69a/f38T6hgRCwAAglGBDnaHDh0yIe7YsWNy7bXXSpMmTcxUJvq1mjhxooSGhpqJiXWka0JCgkyZMsXfpw0AAOAXBTrYzZs374L7o6KiZPLkyWYDAAAIdgHVxw4AAAC5I9gBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAPjAuHHjpGHDhlK0aFEpVaqUdOjQQZKSkryOSUtLk759+0qJEiWkSJEi0qlTJzl69KjXMQcOHJC2bdtK4cKFzecMGTJEMjIyrvLVAAgUBDsA8IE1a9aY0LZx40ZZsWKFpKenS8uWLSU1NdV9zMCBA2XRokUyf/58c/zhw4elY8eO7v2ZmZkm1J07d07Wr18vs2fPllmzZsnIkSP9dFUACrowf58AANho6dKlXs81kGmN27Zt2+TOO++UEydOyLvvvitz586VZs2amWNmzpwpNWrUMGGwcePGsnz5ctm1a5esXLlSSpcuLfXq1ZOxY8fK0KFDZfTo0RIREeGnqwNQUFFjBwBXgQY5Vbx4cfOoAU9r8Vq0aOE+pnr16lKhQgXZsGGDea6PtWvXNqHOkZCQICdPnpSdO3fm+H3Onj1r9ntuAIIHwQ4AfCwrK0sGDBggt99+u9x8883mteTkZFPjFhcX53Wshjjd5xzjGeqc/c6+3Pr2xcbGurfy5cv76KoAFEQEOwDwMe1r991338m8efN8/r2GDRtmaged7eDBgz7/ngAKDvrYAYAP9evXTxYvXixr166V66+/3v16mTJlzKCI48ePe9Xa6ahY3eccs3nzZq/Pc0bNOsdkFxkZaTYAwYkaOwDwAZfLZULdggULZNWqVVK5cmWv/fXr15fw8HBJTEx0v6bToej0JvHx8ea5Pu7YsUNSUlLcx+gI22LFiknNmjWv4tUACBTU2AGAj5pfdcTrp59+auayc/rEab+36Oho89izZ08ZNGiQGVChYa1///4mzOmIWKXTo2iA69atm4wfP958xvDhw81nUysHICcEOwDwgalTp5rHpk2ber2uU5r06NHDfD1x4kQJDQ01ExPraFYd8TplyhT3sYUKFTLNuH369DGBLyYmRrp37y5jxoy5ylcDIFAQ7ADAR02xFxMVFSWTJ082W24qVqwoS5YsyeezA2Ar+tgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJfwa7NauXSvt2rWTcuXKSUhIiCxcuNBrv8vlkpEjR0rZsmUlOjpaWrRoIXv27PE65tdff5WuXbtKsWLFJC4uTnr27CmnT5++ylcCAAAQ5MEuNTVV6tatK5MnT85x//jx42XSpEkybdo02bRpk8TExEhCQoKkpaW5j9FQt3PnTlmxYoUsXrzYhMXevXtfxasAAAAoGML8+c1bt25ttpxobd0bb7whw4cPl/bt25vX5syZI6VLlzY1e126dJHdu3fL0qVLZcuWLdKgQQNzzFtvvSVt2rSRCRMmmJpAAACAYFFg+9jt379fkpOTTfOrIzY2Vho1aiQbNmwwz/VRm1+dUKf0+NDQUFPDl5uzZ8/KyZMnvTYAAIBAV2CDnYY6pTV0nvS5s08fS5Uq5bU/LCxMihcv7j4mJ+PGjTMh0dnKly/vk2sAAAC4mgpssPOlYcOGyYkTJ9zbwYMH/X1KAAAA9ga7MmXKmMejR496va7PnX36mJKS4rU/IyPDjJR1jslJZGSkGUXruQEAAAS6AhvsKleubMJZYmKi+zXtC6d95+Lj481zfTx+/Lhs27bNfcyqVaskKyvL9MUDAAAIJn4dFavzze3du9drwMT27dtNH7kKFSrIgAED5IUXXpCqVauaoDdixAgz0rVDhw7m+Bo1akirVq2kV69eZkqU9PR06devnxkxy4hYAAAQbPwa7LZu3Sp33323+/mgQYPMY/fu3WXWrFnyzDPPmLnudF46rZlr0qSJmd4kKirK/Z7333/fhLnmzZub0bCdOnUyc98BAAAEG78Gu6ZNm5r56nKjq1GMGTPGbLnR2r25c+f66AwBAAACR4HtYwcAAIBLQ7ADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAHxg6tSpUqdOHSlWrJjZ4uPj5fPPP3fvT0tLk759+0qJEiWkSJEi0qlTJzl69KjXZxw4cEDatm0rhQsXllKlSsmQIUMkIyPDD1cDIFAQ7ADAB66//np5+eWXZdu2bbJ161Zp1qyZtG/fXnbu3Gn2Dxw4UBYtWiTz58+XNWvWyOHDh6Vjx47u92dmZppQd+7cOVm/fr3Mnj1bZs2aJSNHjvTjVQEo6ML8fQIAYKN27dp5PX/xxRdNLd7GjRtN6Hv33Xdl7ty5JvCpmTNnSo0aNcz+xo0by/Lly2XXrl2ycuVKKV26tNSrV0/Gjh0rQ4cOldGjR0tERISfrgxAQUaNHQD4mNa+zZs3T1JTU02TrNbipaenS4sWLdzHVK9eXSpUqCAbNmwwz/Wxdu3aJtQ5EhIS5OTJk+5av5ycPXvWHOO5AQgeBDsA8JEdO3aY/nORkZHyxBNPyIIFC6RmzZqSnJxsatzi4uK8jtcQp/uUPnqGOme/sy8348aNk9jYWPdWvnx5n1wbgIKJYAcAPnLTTTfJ9u3bZdOmTdKnTx/p3r27aV71pWHDhsmJEyfc28GDB336/QAULPSxAwAf0Vq5G2+80Xxdv3592bJli7z55pvSuXNnMyji+PHjXrV2Oiq2TJky5mt93Lx5s9fnOaNmnWNyorWDugEITtTYAcBVkpWVZfrAacgLDw+XxMRE976kpCQzvYn2wVP6qE25KSkp7mNWrFhhpk7R5lwAyAk1dgDgoybR1q1bmwERp06dMiNgV69eLcuWLTN933r27CmDBg2S4sWLm7DWv39/E+Z0RKxq2bKlCXDdunWT8ePHm351w4cPN3PfUSMHIDcEOwDwAa1pe/TRR+XIkSMmyOlkxRrq7rnnHrN/4sSJEhoaaiYm1lo8HfE6ZcoU9/sLFSokixcvNn3zNPDFxMSYPnpjxozx41UBKOgIdgDgAzpP3YVERUXJ5MmTzZabihUrypIlS3xwdgBsRR87AAAASxDsAAAALEGwAwAAsMQVBTudh0mH6GdkZOTfGQEAAODqBbszZ86YofqFCxeWWrVqmbmXlA7Xf/nlly/vTAAAAHD1g53Oz/TNN9+YOZl0ZJdDF7T+4IMPruyMAAAAcPWmO1m4cKEJcDqRZkhIiPt1rb3bt2/f5Z0JAAAArn6N3c8//yylSpU67/XU1FSvoAcAAIACHuwaNGgg//rXv9zPnTD3zjvvuNc5BAAAQAA0xb700ktmDcRdu3aZEbFvvvmm+Xr9+vWyZs2a/D9LALiK/v3vf8v06dNN15KPPvpIrrvuOnnvvfekcuXK0qRJE3+fHgDkb42dFmzbt283oa527dqyfPly0zS7YcMGqV+//uV8JAAUCB9//LFZtzU6Olq+/vprs46rOnHihLmpBQAr14qtUqWKzJgxI3/PBgD87IUXXpBp06bJo48+KvPmzXO/fvvtt5t9AGBlsMvKypK9e/dKSkqK+drTnXfemR/nBgBXnU66nlMZFhsbK8ePH/fLOQGAT4Pdxo0b5eGHH5Yff/xRXC6X1z4dSJGZmXk5HwsAflemTBlz01qpUiWv19etWyc33HCD384LAHwW7J544gn3yNiyZcsyxQkAa/Tq1Uv+8pe/yN///ndTth0+fNj0Hx48eLCMGDHC36cHAPkf7Pbs2WNGit14442X83YAKLCeffZZ072kefPmZvlEbZaNjIw0wU6XTQQA64Jdo0aNTFMFwQ6AbbSW7q9//asMGTLElHOnT5+WmjVrSpEiRfx9agDgm2Cnd61PP/20JCcnm+lOwsPDvfbXqVPncj4WAAqMiIgIE+gAwPpg16lTJ/P4+OOPe93l6kAKBk8ACDQdO3bM87GffPKJT88FAK56sNu/f/8VfVMAKEh0KhMACNpgV7Fixfw/EwDwk5kzZ/r7FADg6ga7zz77zKwPq/3p9OsLuffee/Pj3ADAb3TydZ2sWN10001m2UQAsCbYdejQwQyW0MJNv84NfewABLKTJ09K3759zXJiTllWqFAh6dy5s0yePJlmWwAFWmheD9R5nZw7Vv06t41QByDQJyjetGmTLF682Cwhppt+vXXrVvnzn//s79MDAN+sFQsANtIQt2zZMmnSpIn7tYSEBJkxY4a0atXKr+cGAPkW7CZNmpTXQ+Wpp57K87EAUJCUKFEix+ZWfe2aa67xyzkBQL4Hu4kTJ+bpOO1jR7ADEKiGDx8ugwYNkvfee0/KlCljXtP+xboSBWvFArAm2DF3HYBgMHXqVLOUWIUKFcymDhw4YNaL/fnnn2X69OnuY7/66is/nikA+KiPnQ6Y2LFjh5nf7lKaKtauXSuvvvqqbNu2TY4cOSILFizwGnHbo0cPmT17ttd7tK/L0qVL3c9//fVXs8TZokWLJDQ01KyK8eabb7KuI4DLcqFR/wBgZbAbMGCAWSO2Z8+eJtTdeeedsmHDBilcuLDpeNy0adM8fU5qaqrUrVvXLE2W25I+2lnZc/JQvWv21LVrVxMKV6xYIenp6fLYY49J7969Ze7cuZdzaQCC3KhRo/x9CgBwdYPdRx99JI888oj5WmvKfvjhB/nPf/5j+qT89a9/lS+//DJPn6MTHut2IRrknH4u2e3evdvU3m3ZskUaNGhgXnvrrbekTZs2MmHCBClXrtwlXxsAOE6fPm2mcfJUrFgxv50PAOTbPHaefvnlF3fYWrJkiTzwwANSrVo1U/OmTbL5afXq1Wb+PJ35vU+fPnLs2DH3Pq0ljIuLc4c61aJFC9Mkq/NQ5ebs2bNmElLPDQCc/sRt27aVmJgY90hY3bSsYVQsACtr7EqXLi27du2SsmXLmhoz7Wyszpw5Y2Zozy/aDKtNtJUrV5Z9+/bJc889Z2r4NNDp93FWwvAUFhYmxYsXN/tyM27cOHn++efz7TwB2ENbI1wul/z97383ZZ2O9AcAq4Od9mN78MEHTbDTQk9ryZTWklWvXj3fTq5Lly7ur7VPX506daRKlSqmFq958+aX/bnDhg0z0xk4tMaufPnyV3y+AALfN998YwZ0aSsBAARFsBs9erTcfPPNcvDgQdMM6wxo0Fq0Z599VnzlhhtukJIlS5qpCDTYaXOwLtTtKSMjw4yUza1fntLzzT4IAwBUw4YNTdlGsAMQVNOd3H///V7PdT3F7t27iy8dOnTI9LHTmkIVHx9vvq/eXdevX9+8tmrVKtPZuVGjRj49FwB2euedd+SJJ56Qn376ydzAhoeHe+3XlgMAsCrYvfLKK1KpUiXp3Lmzea7Nsh9//LEJXDqYIq8Fn44409o3z07L27dvN33kdNN+cDovnda+aR+7Z555Rm688UYzl52qUaOG6Yeni3ZPmzbNTHfSr18/04TLiFgAl0MnIdbyRrucOLTLifa700ed4gkArBoVqyHK6ZOm88fp9vnnn5uQNXjw4Dx/ztatW+UPf/iD2ZT2e9OvR44caZp1v/32W7n33nvNiFudM09r5f797397NaO+//77pl+fNs3qNCe6cPfbb799OZcFAGZ0v5ZDOkjr+++/Nzecno8AYF2NnY44dYKdTkisNXYtW7Y0tXiX0gSqExnrXXBuli1bdtHP0Jo9JiMGkF9+/PFH+eyzz0zrAAAERY2dzuWknYuVTnfijIrVkEYzBYBA1qxZMzMyFgCCJtjp3HIPP/yw3HPPPWYwg7N6xNdff81dLoCA1q5dOxk4cKAZ/a99h7X2znO7XC+//LLpo6dLMjrS0tKkb9++UqJECbO+tfYpPnr0qNf7Dhw4YCZM1iUbdd7OIUOGmNH/AJBvTbETJ040za5aazd+/HhTIClds/XJJ5+8nI8EgAJBR8SqMWPGnLfvcgdP6LKH06dPP29gmQbIf/3rXzJ//nyzyoUO/tIbZ2dZRv1eGup0ANn69etNGfvoo4+akbovvfTSZV8jAHtdVrDTQiWnQRJaSAFAIMu+NuyV0tH/Xbt2lRkzZsgLL7zgfv3EiRPy7rvvmj7C2vyrZs6caUb7b9y4URo3bizLly83q/ysXLnSrIJRr149GTt2rAwdOtTUKEZEROTruQII0qZYpdMB9O/f3/Sv0+2pp55ixBgAZKNNrVrr5vRFduj8mzpFk+frOsK/QoUKZkSu0kdddUdDnUOne9LVcnbu3HkVrwKA1TV2OlpVpyHRu8fbb7/dvKZNBzVr1pRFixaZvncAEKhSU1NlzZo1pn/buXPnvPbpTWxezZs3T7766ivTFJvT7AJa4xYXF+f1uoY4Z61rffQMdc5+Z19Ozp49azaHhkAAweOygp0uG6bNrtoZOPvr2kRAsAMQqHQQmM6JeebMGRPwdEqlX375xT14Ia/BTvsg/+UvfzHzfEZFRcnVMm7cODO5O4DgdFlNsbt37zYTBuc0saf2BwGAQKU3rToy9rfffpPo6GjT303nttMJ0idMmJDnz9GmVl3L+pZbbpGwsDCzaS3gpEmTzNda86a1gbosoicdFeusda2P2UfJOs9zWw972LBhpv+eszlTUwEIDpcV7K699lqz9Fd2+pre0QJAoNJy7Omnn5bQ0FCzAo42a+qE7DoDwHPPPZfnz9HVcHbs2GE+z9kaNGhgBlI4X+tAtMTERPd7kpKSTPOvroOt9FE/QwOiQ2sAixUrZrq+5ERX5tH9nhuA4HFZTbG6Nmvv3r3NYInbbrvN3cdO15DVZcEAIFBp2NJQp/RGVYOWjlTV6UgupfaraNGicvPNN3u9FhMTY+asc17Xlg8tM7W5VwOYDkjTMKcjYpWu6KMBrlu3biZYar+64cOHmwEZnksrAsAVBbsRI0aYQuu1114z1f6qXLlyZvj9pXQsBoCCRteJ1cEOVatWlbvuususXa197N57773zgtqV0jlBNUTqxMRaM6gjXqdMmeLerzWGumxjnz59TODTYNi9e/cc59gDgMsKdjrjuc67pCtPaF+UU6dOmdc16AFAoNOJf51y7cUXXzQTAmuwqlatmrzzzjtX9NmrV6/2eq6DKiZPnmy23FSsWFGWLFlyRd8XQPC45GCnnX51ZnYdQKEIdABsUqtWLbPutdMUO23aNFmwYIFpEtUpngDAusETt956q5kSAABs0759e5kzZ475Wkesan+3119/XTp06CBTp0719+kBQP73sdP1YHXU2KFDh8wUANrvw1P29RABIFDohMLa90199NFHZloSvZH9+OOPTX87bZYFAKuCXZcuXcyj50AJXRxbmy8ud5FsACgIdGJip4uJrtXasWNHM8BBa+50PjsAsC7Y7d+/P//PBAAKgBtvvFEWLlwo9913n1k+UQeJKZ1LjjnhAFjZx05Hxeqkmjpay3PT13RtRAAIVNrcOnjwYKlUqZI0atTIPVmw1t7pVCgAYF2wmz59ulSvXj3H0WQ6ggwAAtX9999vJiXeunWrLF261GslCafvHQBY1RSrs5+XLVs2x6XGjhw5kh/nBQB+o+uwZl+LVWcDAAAra+x03URdQiw7fU1XoAAAAEAArRU7YMAASU9Pl2bNmpnXtH/dM888Y6ZBAQAAQIAEuyFDhsixY8fMfHbnzp1zL40zdOhQ99qxAAAACIBgp3PVvfLKKzJixAiztFh0dLRZMDsyMjL/zxAAAAC+C3aOIkWKSMOGDa/kIwAAAODPwRMAAAAoeAh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwA+MHr0aAkJCfHaqlev7t6flpYmffv2lRIlSkiRIkWkU6dOcvToUa/POHDggLRt21YKFy4spUqVkiFDhkhGRoYfrgZAoPBrsBs3bpw0bNhQihYtagqtDh06SFJSktcxFH4AAlWtWrXkyJEj7m3dunXufQMHDpRFixbJ/PnzZc2aNXL48GHp2LGje39mZqYp186dOyfr16+X2bNny6xZs2TkyJF+uhoAgcCvwU4LMw1tGzdulBUrVkh6erq0bNlSUlNT3cdQ+AEIVGFhYVKmTBn3VrJkSfP6iRMn5N1335XXX39dmjVrJvXr15eZM2eaMkzLQ7V8+XLZtWuX/OMf/5B69epJ69atZezYsTJ58mRT3gFAgQt2S5culR49epi72rp165pAprVv27ZtM/sp/AAEsj179ki5cuXkhhtukK5du5ryTWkZpzeyLVq0cB+rzbQVKlSQDRs2mOf6WLt2bSldurT7mISEBDl58qTs3LnTD1cDIBAUqD52GuRU8eLFfVr4nT171uz33AAgPzVq1MjcrOoN7NSpU2X//v1yxx13yKlTpyQ5OVkiIiIkLi7O6z1ajuk+pY+e5Zqz39mXG8o3ILiFSQGRlZUlAwYMkNtvv11uvvlm85qvCj/t2/f888/76EoAQEzrgaNOnTom6FWsWFE+/PBDiY6O9tn3pXwDgluBqbHTvnbfffedzJs3z+ffa9iwYaZ20NkOHjzo8+8JILjpDWq1atVk7969pr+ddhU5fvy41zE6MEz3KX3MPlDMee4ckxPKNyC4FYhg169fP1m8eLF88cUXcv3117tf91XhFxkZKcWKFfPaAMCXTp8+Lfv27ZOyZcua/sLh4eGSmJjo3q8zAmgfvPj4ePNcH3fs2CEpKSnuY3SQmZZXNWvWzPX7UL4Bwc2vwc7lcplQt2DBAlm1apVUrlzZa78vCz8A8KXBgwebkfw//PCDGfB13333SaFCheShhx6S2NhY6dmzpwwaNMjc0Gp/4scee8yUZ40bNzbv1xkCtAzr1q2bfPPNN7Js2TIZPny4ad3Q8AYABa6PnRZQc+fOlU8//dTMZef0idNCT/ugeBZ+OqBCw1r//v1zLfzGjx9vPoPCD4C/HTp0yIS4Y8eOybXXXitNmjQxo/n1azVx4kQJDQ01c3PqgAcd9DVlyhT3+zUEaktGnz59TJkXExMj3bt3lzFjxvjxqgAUdH4NdjpSTDVt2tTrdZ3SRKdBURR+AALRxfoLR0VFmWmZdMuNDrZYsmSJD84OgK3C/N0UezEUfgAAAAE0eAIAAABXjmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAYCP/PTTT/LII49IiRIlJDo6WmrXri1bt25173e5XDJy5EgpW7as2d+iRQvZs2eP12f8+uuv0rVrVylWrJjExcVJz5495fTp0364GgCBgGAHAD7w22+/ye233y7h4eHy+eefy65du+S1116Ta665xn3M+PHjZdKkSTJt2jTZtGmTxMTESEJCgqSlpbmP0VC3c+dOWbFihSxevFjWrl0rvXv39tNVASjowvx9AgBgo1deeUXKly8vM2fOdL9WuXJlr9q6N954Q4YPHy7t27c3r82ZM0dKly4tCxculC5dusju3btl6dKlsmXLFmnQoIE55q233pI2bdrIhAkTpFy5cn64MgAFGTV2AOADn332mQljDzzwgJQqVUr+8Ic/yIwZM9z79+/fL8nJyab51REbGyuNGjWSDRs2mOf6qM2vTqhTenxoaKip4cvJ2bNn5eTJk14bgOBBsAMAH/j+++9l6tSpUrVqVVm2bJn06dNHnnrqKZk9e7bZr6FOaQ2dJ33u7NNHDYWewsLCpHjx4u5jshs3bpwJiM6mtYYAggfBDgB8ICsrS2655RZ56aWXTG2d9ovr1auX6U/nS8OGDZMTJ064t4MHD/r0+wEoWAh2AOADOtK1Zs2aXq/VqFFDDhw4YL4uU6aMeTx69KjXMfrc2aePKSkpXvszMjLMSFnnmOwiIyPNCFrPDUDwINgBgA/oiNikpCSv1/773/9KxYoV3QMpNJwlJia692t/OO07Fx8fb57r4/Hjx2Xbtm3uY1atWmVqA7UvHgBkx6hYAPCBgQMHym233WaaYh988EHZvHmzvP3222ZTISEhMmDAAHnhhRdMPzwNeiNGjDAjXTt06OCu4WvVqpW7CTc9PV369etnRswyIhZATgh2AOADDRs2lAULFpg+b2PGjDHBTac30XnpHM8884ykpqaa/ndaM9ekSRMzvUlUVJT7mPfff9+EuebNm5vRsJ06dTJz3wFATgh2AOAjf/zjH82WG62109CnW250BOzcuXN9dIYAbEMfOwAAAEsQ7AAAACzh12CnE2lqP5SiRYuaSTi1w3D2UWRNmzY1zRWe2xNPPOF1jE4f0LZtWylcuLD5nCFDhpgpAQAAAIKJX/vYrVmzRvr27WvCnQax5557Tlq2bGkWy9bFsB06IsyzD4oGOEdmZqYJdTptwPr16+XIkSPy6KOPmoW3dTQaAABAsPBrsNPRX55mzZplatx0zqY777zTK8jlNhnn8uXLTRBcuXKlWYqnXr16MnbsWBk6dKiMHj1aIiIifH4dAAAABUGB6mOny984o8A86XD/kiVLys0332ymDjhz5ox7ny6SXbt2ba/1FhMSEsxEnzt37szx+7BINgAAsFGBme5EZ1LXyTp1tnYNcI6HH37YzNSuk3F+++23piZO++F98sknZr8uhJ3TItrOvtz69j3//PM+vR4AAICgDXba1+67776TdevWeb2uE3c6tGZO11/UiTr37dsnVapUuazvpbV+gwYNcj/XGrvy5ctfwdkDAAD4X4FoitVZ1RcvXixffPGFXH/99Rc81lkfce/eveZR+97ltIi2sy8nLJINAABs5Ndg53K5TKjTZXd0YWtdcuditm/fbh615s5ZJHvHjh2SkpLiPmbFihUmrNWsWdOHZw8AAFCwhPm7+VWXyvn000/NXHZOn7jY2FiJjo42za26v02bNlKiRAnTx04X1tYRs3Xq1DHH6vQoGuC6desm48ePN58xfPhw89laMwcAABAs/FpjN3XqVDMSVich1ho4Z/vggw/Mfp2qRKcx0fBWvXp1efrpp80C2IsWLXJ/RqFChUwzrj5q7d0jjzxi5rG70NqLAAAANgrzd1PsheiABp3E+GJ01OySJUvy8cwAAAACT4EYPAEAAIArR7ADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7APCBSpUqSUhIyHlb3759zf60tDTzdYkSJaRIkSLSqVMnOXr0qNdnHDhwQNq2bSuFCxeWUqVKyZAhQyQjI8NPVwQgEBDsAMAHtmzZIkeOHHFvK1asMK8/8MAD5nHgwIGyaNEimT9/vqxZs0YOHz4sHTt2dL8/MzPThLpz587J+vXrZfbs2TJr1iwZOXKk364JQMFHsAMAH7j22mulTJky7m3x4sVSpUoVueuuu+TEiRPy7rvvyuuvvy7NmjWT+vXry8yZM02A27hxo3n/8uXLZdeuXfKPf/xD6tWrJ61bt5axY8fK5MmTTdgDgJwQ7ADAxzSIaUB7/PHHTXPstm3bJD09XVq0aOE+pnr16lKhQgXZsGGDea6PtWvXltKlS7uPSUhIkJMnT8rOnTtz/V5nz541x3huAIIHwQ4AfGzhwoVy/Phx6dGjh3menJwsEREREhcX53Wchjjd5xzjGeqc/c6+3IwbN05iY2PdW/ny5X1wRQAKKoIdAPiYNrtqU2q5cuV8/r2GDRtmmnqd7eDBgz7/ngAKjjB/nwAA2OzHH3+UlStXyieffOJ+TfvcafOs1uJ51trpqFjd5xyzefNmr89yRs06x+QkMjLSbACCEzV2AOBDOihCpyrREa4OHSwRHh4uiYmJ7teSkpLM9Cbx8fHmuT7u2LFDUlJS3MfoyNpixYpJzZo1r/JVAAgU1NgBgI9kZWWZYNe9e3cJC/v/xa32fevZs6cMGjRIihcvbsJa//79TZhr3LixOaZly5YmwHXr1k3Gjx9v+tUNHz7czH1HjRyA3BDsAMBHtAlWa+F0NGx2EydOlNDQUDMxsY5k1RGvU6ZMce8vVKiQmSKlT58+JvDFxMSYgDhmzJirfBUAAgnBDgB8RGvdXC5XjvuioqLMnHS65aZixYqyZMkSH54hANvQxw4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAAS4T5+wQKApfLZR5Pns7K83vSXemS8b/3BaLfz2bIyVN5v95Al5EukuFKl0xXiAQLf/2OT6dmmp/11ZYh6V5/zxCvn0dWWtp5+9JTz0lmyPn/RjLS0yQrvZAEqt9/Tw+u8i3TZX5nmVnBU1cTknlWQvxQzmS5zpmf9dWW+b/vmZfyLcRFKSjff/+9VKlSxd+nASAfHDx4UK6//np/n0aBcejQISlfvry/TwPAVSrfCHYicvz4cbnmmmvkwIEDEhsbK8Hg5MmTprDXfyTFihUT2wXb9QbjNWtRdurUKSlXrpyEhgZPzcXFZGVlSVJSktSsWTNo/i0E27/9YLzmYLte1yWUbzTFakfD//2QNNQFwz8QT3q9wXTNwXa9wXbNwXJjdqnl23XXXRd0/xaC8XqD8ZqD6Xpj81i+cVsLAABgCYIdAACAJQh2IhIZGSmjRo0yj8Ei2K452K43WK8ZOQu2fwvBdr3BeM3Bdr2XgsETAAAAlqDGDgAAwBIEOwAAAEsQ7AAAACxBsBORyZMnS6VKlSQqKkoaNWokmzdvFhuMHj1aQkJCvLbq1au796elpUnfvn2lRIkSUqRIEenUqZMcPXpUAsnatWulXbt2ZtJGvb6FCxd67dcupCNHjpSyZctKdHS0tGjRQvbs2eN1zK+//ipdu3Y1cyHFxcVJz5495fTp0xKI19ujR4/zfuetWrUK2OvFlbO1fAuGMi7YyjdFGXflgj7YffDBBzJo0CAzuuarr76SunXrSkJCgqSkpIgNatWqJUeOHHFv69atc+8bOHCgLFq0SObPny9r1qyRw4cPS8eOHSWQpKammt+Z/s8rJ+PHj5dJkybJtGnTZNOmTRITE2N+v1rgO7QA2Llzp6xYsUIWL15sCpbevXtLIF6v0kLO83f+z3/+02t/IF0vrozt5ZvtZVywlW+KMi4fuILcrbfe6urbt6/7eWZmpqtcuXKucePGuQLdqFGjXHXr1s1x3/Hjx13h4eGu+fPnu1/bvXu3jpB2bdiwwRWI9NwXLFjgfp6VleUqU6aM69VXX/W67sjISNc///lP83zXrl3mfVu2bHEf8/nnn7tCQkJcP/30kyuQrld1797d1b59+1zfE8jXi0tnc/kWbGVcsJVvijLu8gR1jd25c+dk27Ztpvrac/kdfb5hwwaxgVbLa5X2DTfcYO5idD1cpdednp7ude3ahFGhQgVrrn3//v2SnJzsdY26JIs2RznXqI9aVd+gQQP3MXq8/jvQO+BAtHr1ailVqpTcdNNN0qdPHzl27Jh7n43Xi+At34K5jAvW8k1Rxl1YUAe7X375RTIzM6V06dJer+tz/YMJdPoHPmvWLFm6dKlMnTrVFAR33HGHWUhYry8iIsL8Adh47cq5jgv9fvVRCwhPYWFhUrx48YD8OWgTxZw5cyQxMVFeeeUV0/zUunVr8+/cxutF8JZvwV7GBWP5pijjLi4sD8cgQOk/dkedOnVMIVixYkX58MMPTUdb2KdLly7ur2vXrm1+71WqVDF3uM2bN/fruQH5jTIu+FDGXVxQ19iVLFlSChUqdN4oKX1epkwZsY3euVarVk327t1rrk+bao4fP27ttTvXcaHfrz5m70iekZFhRlXZ8HPQ5in9d66/82C4XgRv+RZsZRzl2/+hjDtfUAc7raavX7++qdJ1ZGVlmefx8fFiGx3uvW/fPjM0Xq87PDzc69qTkpJM/xRbrr1y5crmD9nzGk+ePGn6WTjXqI9a8Gt/HMeqVavMvwO9+w90hw4dMv1P9HceDNeL4C3fgq2Mo3z7P5RxOXAFuXnz5plRRLNmzTKjaXr37u2Ki4tzJScnuwLd008/7Vq9erVr//79ri+//NLVokULV8mSJV0pKSlm/xNPPOGqUKGCa9WqVa6tW7e64uPjzRZITp065fr666/Npv+cX3/9dfP1jz/+aPa//PLL5vf56aefur799lszmqpy5cqu33//3f0ZrVq1cv3hD39wbdq0ybVu3TpX1apVXQ899JAr0K5X9w0ePNiM+NPf+cqVK1233HKLuZ60tLSAvF5cGZvLt2Ao44KtfFOUcVcu6IOdeuutt8wff0REhJkeYOPGjS4bdO7c2VW2bFlzXdddd515vnfvXvd+/eN/8sknXddcc42rcOHCrvvuu8915MgRVyD54osvzB9/9k2HxDtTAowYMcJVunRp8z+45s2bu5KSkrw+49ixY+aPvkiRIq5ixYq5HnvsMVOABNr1njlzxtWyZUvXtddea6Z5qFixoqtXr17n/U88kK4XV87W8i0YyrhgK98UZdyVC9H/5FSTBwAAgMAS1H3sAAAAbEKwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOxQ4DVt2lQGDBiQp2N/+OEHCQkJke3bt5vnq1evNs+zLwQOAAUFZRzyU1i+fhrgA5988olZzPty3HbbbXLkyBGJjY3N9/MCgPxAGYf8RLBDgVe8ePHLfm9ERISUKVMmX88HAPITZRzyE02xCKhmikqVKslLL70kjz/+uBQtWlQqVKggb7/9dq7vzd5MMWvWLImLi5Nly5ZJjRo1pEiRItKqVStzx+vpnXfeMfujoqKkevXqMmXKFB9fJYBgRRmH/ESwQ8B57bXXpEGDBvL111/Lk08+KX369JGkpKQ8v//MmTMyYcIEee+992Tt2rVy4MABGTx4sHv/+++/LyNHjpQXX3xRdu/ebQrZESNGyOzZs310RQDw/1HG4UoQ7BBw2rRpYwq7G2+8UYYOHSolS5aUL774Is/vT09Pl2nTppmC85ZbbpF+/fpJYmKie/+oUaNMwdqxY0epXLmyeRw4cKBMnz7dR1cEAP8fZRyuBH3sEHDq1Knj/lqbILR/SUpKSp7fX7hwYalSpYr7edmyZd3vT01NlX379knPnj2lV69e7mMyMjLonAzgqqCMw5Ug2CHgZB89pgVfVlbWFb3f5XKZr0+fPm0eZ8yYIY0aNfI6rlChQldw1gCQN5RxuBIEO8BD6dKlpVy5cvL9999L165d/X06AJCvKOPsR7ADsnn++eflqaeeMs0SOprs7NmzsnXrVvntt99k0KBB/j49ALgilHF2I9gB2fzpT38yfVReffVVGTJkiMTExEjt2rXzPDM8ABRklHF2C3E5De8AAAAIaEx3AgAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAiB3+H3QA/cU4rhHfAAAAAElFTkSuQmCC\\\",\\n\",\n",
+    "    \"      \\\"text/plain\\\": [\\n\",\n",
+    "    \"       \\\"<Figure size 640x480 with 2 Axes>\\\"\\n\",\n",
+    "    \"      ]\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"metadata\\\": {},\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"display_data\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   ],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"fig, ax = plt.subplots(1, 2, sharex=\\\\\\\"all\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[0].imshow(writer.live_mask[:].T, aspect=\\\\\\\"auto\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[1].imshow(reader[:, 150].T, aspect=\\\\\\\"auto\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[0].set_xlabel(\\\\\\\"inline\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[0].set_ylabel(\\\\\\\"crossline\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[1].set_xlabel(\\\\\\\"inline\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[1].set_ylabel(\\\\\\\"sample\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[0].set_title(\\\\\\\"Live Mask\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"ax[1].set_title(\\\\\\\"Middle Crossline\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"fig.tight_layout();\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"## Write to SEG-Y\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"Because we populated all the fields necessary for SEG-Y output, we can call the\\\\n\\\",\\n\",\n",
+    "    \"    \\\"MDIO to SEGY converter and get a file out.\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 7,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:15.788812Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:15.009889Z\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"stderr\\\",\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
+    "    \"     \\\"text\\\": [\\n\",\n",
+    "    \"      \\\"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\\\n\\\",\\n\",\n",
+    "    \"      \\\"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\\\"\\n\",\n",
+    "    \"     ]\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"stdout\\\",\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
+    "    \"     \\\"text\\\": [\\n\",\n",
+    "    \"      \\\"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\\\n\\\",\\n\",\n",
+    "    \"      \\\"[[1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
+    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
+    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
+    "    \"      \\\" ...\\\\n\\\",\\n\",\n",
+    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
+    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
+    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]]\\\\n\\\"\\n\",\n",
+    "    \"     ]\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    {\\n\",\n",
+    "    \"     \\\"name\\\": \\\"stderr\\\",\\n\",\n",
+    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
+    "    \"     \\\"text\\\": [\\n\",\n",
+    "    \"      \\\"\\\\n\\\"\\n\",\n",
+    "    \"     ]\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   ],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"from segy import SegyFile\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"from mdio import mdio_to_segy\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"mdio_to_segy(\\\\\\\"demo.mdio\\\\\\\", \\\\\\\"demo.segy\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"segy = SegyFile(\\\\\\\"demo.segy\\\\\\\")\\\\n\\\",\\n\",\n",
+    "    \"    \\\"print(segy.binary_header)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"print(segy.sample[:100])\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"## Copying an Existing MDIO without Data and Headers\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"We also provide a `create_empty_like` function which allows us to create an MDIO file\\\\n\\\",\\n\",\n",
+    "    \"    \\\"with the same structure and basic metadata as an existing one.\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"This will carry over:\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* All access patterns in source MDIO\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Grid (shape, coordinates, dimensions, etc)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Text Header\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Binary Header\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"It will **NOT** carry over:\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Trace data\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Header data\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Statistics\\\\n\\\",\\n\",\n",
+    "    \"    \\\"* Live Mask\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": 8,\\n\",\n",
+    "    \"   \\\"metadata\\\": {\\n\",\n",
+    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
+    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:17.246513Z\\\",\\n\",\n",
+    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:17.111779Z\\\"\\n\",\n",
+    "    \"    }\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"outputs\\\": [],\\n\",\n",
+    "    \"   \\\"source\\\": [\\n\",\n",
+    "    \"    \\\"from mdio import create_empty_like\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"copy_path = \\\\\\\"copy_of_existing.mdio\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"create_empty_like(create_conf.path, copy_path)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"copy_reader = MDIOReader(copy_path)\\\\n\\\",\\n\",\n",
+    "    \"    \\\"assert copy_reader.shape == reader.shape\\\\n\\\",\\n\",\n",
+    "    \"    \\\"assert copy_reader.binary_header == reader.binary_header\\\\n\\\",\\n\",\n",
+    "    \"    \\\"assert copy_reader.stats != reader.stats\\\"\\n\",\n",
+    "    \"   ]\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  {\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
+    "    \"   \\\"execution_count\\\": null,\\n\",\n",
+    "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"outputs\\\": [],\\n\",\n",
+    "    \"   \\\"source\\\": []\\n\",\n",
+    "    \"  }\\n\",\n",
+    "    \" ],\\n\",\n",
+    "    \" \\\"metadata\\\": {\\n\",\n",
+    "    \"  \\\"kernelspec\\\": {\\n\",\n",
+    "    \"   \\\"display_name\\\": \\\"Python 3 (ipykernel)\\\",\\n\",\n",
+    "    \"   \\\"language\\\": \\\"python\\\",\\n\",\n",
+    "    \"   \\\"name\\\": \\\"python3\\\"\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  \\\"language_info\\\": {\\n\",\n",
+    "    \"   \\\"codemirror_mode\\\": {\\n\",\n",
+    "    \"    \\\"name\\\": \\\"ipython\\\",\\n\",\n",
+    "    \"    \\\"version\\\": 3\\n\",\n",
+    "    \"   },\\n\",\n",
+    "    \"   \\\"file_extension\\\": \\\".py\\\",\\n\",\n",
+    "    \"   \\\"mimetype\\\": \\\"text/x-python\\\",\\n\",\n",
+    "    \"   \\\"name\\\": \\\"python\\\",\\n\",\n",
+    "    \"   \\\"nbconvert_exporter\\\": \\\"python\\\",\\n\",\n",
+    "    \"   \\\"pygments_lexer\\\": \\\"ipython3\\\",\\n\",\n",
+    "    \"   \\\"version\\\": \\\"3.12.3\\\"\\n\",\n",
+    "    \"  },\\n\",\n",
+    "    \"  \\\"widgets\\\": {\\n\",\n",
+    "    \"   \\\"application/vnd.jupyter.widget-state+json\\\": {\\n\",\n",
+    "    \"    \\\"state\\\": {\\n\",\n",
+    "    \"     \\\"104c0d4e90244ebc959e51a58794dcf4\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"display\\\": \\\"inline-flex\\\",\\n\",\n",
+    "    \"       \\\"flex_flow\\\": \\\"row wrap\\\",\\n\",\n",
+    "    \"       \\\"width\\\": \\\"100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"1c0f5b458ee1401eaa8de63c65802073\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"21b25dd6080d42368afc06770d5e1755\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_35fb49026dac479eba87217c2f6bcb9a\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_3ab3e27c83aa423d9ecdac94e576f0fe\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\"Ingesting SEG-Y in 6 chunks: 100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"2693aae410f04e7587f0400b5eef1079\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"ProgressStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"318aea09479a479981dcfa29bc856c67\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"ProgressStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"35fb49026dac479eba87217c2f6bcb9a\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"3ab3e27c83aa423d9ecdac94e576f0fe\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"420b4a9492c54eb48d7779f38a09fd20\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"flex\\\": \\\"2\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"42afe4fae9dd4bc4a341a231cf7a9c32\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"4df685a95de542ffab6f265df89b8949\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"58eaddb54c8840da83d1f6503d6ba64f\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"5b3e72b71f304230bc36bb91f9c173be\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"5c1fab0ccc7e42c69c2b663b67ca9e3c\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"63a54817ae8b4c8d85b30d8c97e7ed0d\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HBoxModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"children\\\": [\\n\",\n",
+    "    \"        \\\"IPY_MODEL_e170d60a55a14c489d32b101293a9d33\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_662ad93cf7b3470f8e197350441f09ca\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_ac4abab2367e461e956e4e0edb27be44\\\"\\n\",\n",
+    "    \"       ],\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_c59d6fe969a04f4da332ae2a6fdb9c77\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"63f87a2410ba47d38ad9f55a81357a29\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_ca48140488574a28a7469552441560e4\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_ae2037efb9cc459e84bcc28ca7243437\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\" 2/2 [00:03&lt;00:00,  3.01s/block]\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"64eb2b9c8a094a1ea5f1991e5f09f5d9\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"662ad93cf7b3470f8e197350441f09ca\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"FloatProgressModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"bar_style\\\": \\\"success\\\",\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_420b4a9492c54eb48d7779f38a09fd20\\\",\\n\",\n",
+    "    \"       \\\"max\\\": 1,\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_d16e93f72f3d4aeda2f5deee87e9754f\\\",\\n\",\n",
+    "    \"       \\\"value\\\": 1\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"74283969ff5446c89bb83b00a70226cf\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_5c1fab0ccc7e42c69c2b663b67ca9e3c\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_1c0f5b458ee1401eaa8de63c65802073\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\" 6/6 [00:09&lt;00:00,  2.48s/block]\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"75cf0c1ed25e47aab20b060f3bb44fb8\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HBoxModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"children\\\": [\\n\",\n",
+    "    \"        \\\"IPY_MODEL_21b25dd6080d42368afc06770d5e1755\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_c33f32b62a204ef094f67b10f8adbdc1\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_74283969ff5446c89bb83b00a70226cf\\\"\\n\",\n",
+    "    \"       ],\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_91df4ac76fd744539d4237d6099f34a5\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"7ff32d7deac14f21ab0f0939fe09e440\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"ProgressStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"91df4ac76fd744539d4237d6099f34a5\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"display\\\": \\\"inline-flex\\\",\\n\",\n",
+    "    \"       \\\"flex_flow\\\": \\\"row wrap\\\",\\n\",\n",
+    "    \"       \\\"width\\\": \\\"100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"981634b52a7a4ffdae6186061c0b6482\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HBoxModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"children\\\": [\\n\",\n",
+    "    \"        \\\"IPY_MODEL_f65266f861cf40ef84e9ec74a8e0b44c\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_9aaf514a5035413d8cbbad58aa0221f4\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_63f87a2410ba47d38ad9f55a81357a29\\\"\\n\",\n",
+    "    \"       ],\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_104c0d4e90244ebc959e51a58794dcf4\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"9aaf514a5035413d8cbbad58aa0221f4\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"FloatProgressModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"bar_style\\\": \\\"success\\\",\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_b25523a221fd4b5e9211d07ef39cccf5\\\",\\n\",\n",
+    "    \"       \\\"max\\\": 2,\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_318aea09479a479981dcfa29bc856c67\\\",\\n\",\n",
+    "    \"       \\\"value\\\": 2\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"9fe5348964cd4f7880bcd33204bbc7a2\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
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+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
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+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
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+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"FloatProgressModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"bar_style\\\": \\\"success\\\",\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_cfb02c9c7447491ca00bbb6acd99bb79\\\",\\n\",\n",
+    "    \"       \\\"max\\\": 26,\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_7ff32d7deac14f21ab0f0939fe09e440\\\",\\n\",\n",
+    "    \"       \\\"value\\\": 26\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"ac4abab2367e461e956e4e0edb27be44\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
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+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_58eaddb54c8840da83d1f6503d6ba64f\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_a03d238db31145b881a1be478f9eb72f\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\" 3/? [00:00&lt;00:00,  8.29block/s]\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"ae2037efb9cc459e84bcc28ca7243437\\\": {\\n\",\n",
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+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"b25523a221fd4b5e9211d07ef39cccf5\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
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+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"flex\\\": \\\"2\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"b9810ee38bbe43f4bba100e53379be65\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_42afe4fae9dd4bc4a341a231cf7a9c32\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_fdcea609ee7349629604217b625371d3\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\" 26/26 [00:01&lt;00:00, 18.92block/s]\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"c33f32b62a204ef094f67b10f8adbdc1\\\": {\\n\",\n",
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+    "    \"      \\\"model_name\\\": \\\"FloatProgressModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"bar_style\\\": \\\"success\\\",\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_d23d88490a1b4941b8ca228b7d4a39cb\\\",\\n\",\n",
+    "    \"       \\\"max\\\": 6,\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_2693aae410f04e7587f0400b5eef1079\\\",\\n\",\n",
+    "    \"       \\\"value\\\": 6\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"c59d6fe969a04f4da332ae2a6fdb9c77\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
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+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"display\\\": \\\"inline-flex\\\",\\n\",\n",
+    "    \"       \\\"flex_flow\\\": \\\"row wrap\\\",\\n\",\n",
+    "    \"       \\\"width\\\": \\\"100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"ca48140488574a28a7469552441560e4\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"cfb02c9c7447491ca00bbb6acd99bb79\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"flex\\\": \\\"2\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"d16e93f72f3d4aeda2f5deee87e9754f\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"ProgressStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"d23d88490a1b4941b8ca228b7d4a39cb\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"flex\\\": \\\"2\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"d565a20d37e84ed0a1195e9a90154960\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HBoxModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"children\\\": [\\n\",\n",
+    "    \"        \\\"IPY_MODEL_db696e15587c4a54b82886b3eb5a0c96\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_a6aabcd2e57348a49bb59477f6a9fd90\\\",\\n\",\n",
+    "    \"        \\\"IPY_MODEL_b9810ee38bbe43f4bba100e53379be65\\\"\\n\",\n",
+    "    \"       ],\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_eab4b060672b4dd5a73ca7bb8f782cd2\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"db696e15587c4a54b82886b3eb5a0c96\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_64eb2b9c8a094a1ea5f1991e5f09f5d9\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_5b3e72b71f304230bc36bb91f9c173be\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\"Step 1 / 2 Writing Blocks: 100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"e170d60a55a14c489d32b101293a9d33\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_9fe5348964cd4f7880bcd33204bbc7a2\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_4df685a95de542ffab6f265df89b8949\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\"Step 2 / 2 Concat Blocks: \\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"e66368cda8124001b16459a0634029e2\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"eab4b060672b4dd5a73ca7bb8f782cd2\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"display\\\": \\\"inline-flex\\\",\\n\",\n",
+    "    \"       \\\"flex_flow\\\": \\\"row wrap\\\",\\n\",\n",
+    "    \"       \\\"width\\\": \\\"100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"f65266f861cf40ef84e9ec74a8e0b44c\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"layout\\\": \\\"IPY_MODEL_fff4199774534d9f982f03738fbb08e7\\\",\\n\",\n",
+    "    \"       \\\"style\\\": \\\"IPY_MODEL_e66368cda8124001b16459a0634029e2\\\",\\n\",\n",
+    "    \"       \\\"value\\\": \\\"Scanning SEG-Y for geometry attributes: 100%\\\"\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"fdcea609ee7349629604217b625371d3\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/controls\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"HTMLStyleModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {\\n\",\n",
+    "    \"       \\\"description_width\\\": \\\"\\\",\\n\",\n",
+    "    \"       \\\"font_size\\\": null,\\n\",\n",
+    "    \"       \\\"text_color\\\": null\\n\",\n",
+    "    \"      }\\n\",\n",
+    "    \"     },\\n\",\n",
+    "    \"     \\\"fff4199774534d9f982f03738fbb08e7\\\": {\\n\",\n",
+    "    \"      \\\"model_module\\\": \\\"@jupyter-widgets/base\\\",\\n\",\n",
+    "    \"      \\\"model_module_version\\\": \\\"2.0.0\\\",\\n\",\n",
+    "    \"      \\\"model_name\\\": \\\"LayoutModel\\\",\\n\",\n",
+    "    \"      \\\"state\\\": {}\\n\",\n",
+    "    \"     }\\n\",\n",
+    "    \"    },\\n\",\n",
+    "    \"    \\\"version_major\\\": 2,\\n\",\n",
+    "    \"    \\\"version_minor\\\": 0\\n\",\n",
+    "    \"   }\\n\",\n",
+    "    \"  }\\n\",\n",
+    "    \" },\\n\",\n",
+    "    \" \\\"nbformat\\\": 4,\\n\",\n",
+    "    \" \\\"nbformat_minor\\\": 4\\n\",\n",
+    "    \"}\\n\"\n",
     "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {},\n",
-    "   \"source\": [\n",
-    "    \"## Updating File and Checking with `MDIOReader`.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We write traces here, the headers are still empty. If you need the headers\\n\",\n",
-    "    \"populated, this is where they would be written to file as well.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"All the extra metadata we are writing is so that we can export back to SEG-Y\\n\",\n",
-    "    \"in the future. If that's not a requirement most of the metadata can be\\n\",\n",
-    "    \"omitted.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"If you already have an MDIO prior to this, all the metadata can be copied\\n\",\n",
-    "    \"over from the previous version.\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 5,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:12.498287Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:11.670230Z\"\n",
-    "    },\n",
-    "    \"pycharm\": {\n",
-    "     \"name\": \"#%%\\n\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [\n",
-    "    {\n",
-    "     \"data\": {\n",
-    "      \"text/plain\": [\n",
-    "       \"({'data_sample_format': 1,\\n\",\n",
-    "       \"  'sample_interval': 4,\\n\",\n",
-    "       \"  'samples_per_trace': 750,\\n\",\n",
-    "       \"  'segy_revision_major': 1,\\n\",\n",
-    "       \"  'segy_revision_minor': 0},\\n\",\n",
-    "       \" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\"\n",
-    "      ]\n",
-    "     },\n",
-    "     \"execution_count\": 5,\n",
-    "     \"metadata\": {},\n",
-    "     \"output_type\": \"execute_result\"\n",
-    "    }\n",
-    "   ],\n",
-    "   \"source\": [\n",
-    "    \"sample_dim = writer.grid.select_dim(\\\"sample\\\")\\n\",\n",
-    "    \"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\n\",\n",
-    "    \"num_samples = sample_dim.size\\n\",\n",
-    "    \"writer.binary_header = {\\n\",\n",
-    "    \"    \\\"data_sample_format\\\": 1,\\n\",\n",
-    "    \"    \\\"sample_interval\\\": sample_interval,\\n\",\n",
-    "    \"    \\\"samples_per_trace\\\": num_samples,\\n\",\n",
-    "    \"    \\\"segy_revision_major\\\": 1,\\n\",\n",
-    "    \"    \\\"segy_revision_minor\\\": 0,\\n\",\n",
-    "    \"}\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"# Write some values to the file\\n\",\n",
-    "    \"writer[:5] = 1\\n\",\n",
-    "    \"writer[5:10] = 2\\n\",\n",
-    "    \"writer[50:100] = 3\\n\",\n",
-    "    \"writer[150:175] = -1\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"# Write some made up stats\\n\",\n",
-    "    \"writer.stats = {\\\"mean\\\": 12, \\\"std\\\": 5, \\\"rms\\\": 3, \\\"min\\\": -4, \\\"max\\\": 4}\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"reader = MDIOReader(create_conf.path)\\n\",\n",
-    "    \"reader.binary_header, reader.stats\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {},\n",
-    "   \"source\": \"Plot some of the data we populated:\"\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 6,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:14.256953Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:14.036094Z\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [\n",
-    "    {\n",
-    "     \"data\": {\n",
-    "      \"image/png\": 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\",\n",
-    "      \"text/plain\": [\n",
-    "       \"<Figure size 640x480 with 2 Axes>\"\n",
-    "      ]\n",
-    "     },\n",
-    "     \"metadata\": {},\n",
-    "     \"output_type\": \"display_data\"\n",
-    "    }\n",
-    "   ],\n",
-    "   \"source\": [\n",
-    "    \"fig, ax = plt.subplots(1, 2, sharex=\\\"all\\\")\\n\",\n",
-    "    \"ax[0].imshow(writer.live_mask[:].T, aspect=\\\"auto\\\")\\n\",\n",
-    "    \"ax[1].imshow(reader[:, 150].T, aspect=\\\"auto\\\")\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"ax[0].set_xlabel(\\\"inline\\\")\\n\",\n",
-    "    \"ax[0].set_ylabel(\\\"crossline\\\")\\n\",\n",
-    "    \"ax[1].set_xlabel(\\\"inline\\\")\\n\",\n",
-    "    \"ax[1].set_ylabel(\\\"sample\\\")\\n\",\n",
-    "    \"ax[0].set_title(\\\"Live Mask\\\")\\n\",\n",
-    "    \"ax[1].set_title(\\\"Middle Crossline\\\")\\n\",\n",
-    "    \"fig.tight_layout();\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {},\n",
-    "   \"source\": [\n",
-    "    \"## Write to SEG-Y\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"Because we populated all the fields necessary for SEG-Y output, we can call the\\n\",\n",
-    "    \"MDIO to SEGY converter and get a file out.\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 7,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:15.788812Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:15.009889Z\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [\n",
-    "    {\n",
-    "     \"name\": \"stderr\",\n",
-    "     \"output_type\": \"stream\",\n",
-    "     \"text\": [\n",
-    "      \"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\n\",\n",
-    "      \"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\"\n",
-    "     ]\n",
-    "    },\n",
-    "    {\n",
-    "     \"name\": \"stdout\",\n",
-    "     \"output_type\": \"stream\",\n",
-    "     \"text\": [\n",
-    "      \"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\n\",\n",
-    "      \"[[1. 1. 1. ... 1. 1. 1.]\\n\",\n",
-    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
-    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
-    "      \" ...\\n\",\n",
-    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
-    "      \" [1. 1. 1. ... 1. 1. 1.]\\n\",\n",
-    "      \" [1. 1. 1. ... 1. 1. 1.]]\\n\"\n",
-    "     ]\n",
-    "    },\n",
-    "    {\n",
-    "     \"name\": \"stderr\",\n",
-    "     \"output_type\": \"stream\",\n",
-    "     \"text\": [\n",
-    "      \"\\n\"\n",
-    "     ]\n",
-    "    }\n",
-    "   ],\n",
-    "   \"source\": [\n",
-    "    \"from segy import SegyFile\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"from mdio import mdio_to_segy\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"mdio_to_segy(\\\"demo.mdio\\\", \\\"demo.segy\\\")\\n\",\n",
-    "    \"segy = SegyFile(\\\"demo.segy\\\")\\n\",\n",
-    "    \"print(segy.binary_header)\\n\",\n",
-    "    \"print(segy.sample[:100])\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"markdown\",\n",
-    "   \"metadata\": {},\n",
-    "   \"source\": [\n",
-    "    \"## Copying an Existing MDIO without Data and Headers\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"We also provide a `create_empty_like` function which allows us to create an MDIO file\\n\",\n",
-    "    \"with the same structure and basic metadata as an existing one.\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"This will carry over:\\n\",\n",
-    "    \"* All access patterns in source MDIO\\n\",\n",
-    "    \"* Grid (shape, coordinates, dimensions, etc)\\n\",\n",
-    "    \"* Text Header\\n\",\n",
-    "    \"* Binary Header\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"It will **NOT** carry over:\\n\",\n",
-    "    \"* Trace data\\n\",\n",
-    "    \"* Header data\\n\",\n",
-    "    \"* Statistics\\n\",\n",
-    "    \"* Live Mask\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": 8,\n",
-    "   \"metadata\": {\n",
-    "    \"ExecuteTime\": {\n",
-    "     \"end_time\": \"2025-04-16T14:50:17.246513Z\",\n",
-    "     \"start_time\": \"2025-04-16T14:50:17.111779Z\"\n",
-    "    }\n",
-    "   },\n",
-    "   \"outputs\": [],\n",
-    "   \"source\": [\n",
-    "    \"from mdio import create_empty_like\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"copy_path = \\\"copy_of_existing.mdio\\\"\\n\",\n",
-    "    \"create_empty_like(create_conf.path, copy_path)\\n\",\n",
-    "    \"\\n\",\n",
-    "    \"copy_reader = MDIOReader(copy_path)\\n\",\n",
-    "    \"assert copy_reader.shape == reader.shape\\n\",\n",
-    "    \"assert copy_reader.binary_header == reader.binary_header\\n\",\n",
-    "    \"assert copy_reader.stats != reader.stats\"\n",
-    "   ]\n",
-    "  },\n",
-    "  {\n",
-    "   \"cell_type\": \"code\",\n",
-    "   \"execution_count\": null,\n",
-    "   \"metadata\": {},\n",
-    "   \"outputs\": [],\n",
-    "   \"source\": []\n",
     "  }\n",
     " ],\n",
     " \"metadata\": {\n",

From 793f3f149cf0ca0140b3f0051f37d4434905ab68 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 15:38:15 -0500
Subject: [PATCH 09/56] fix creation notebook

---
 docs/tutorials/creation.ipynb | 1225 ++++++++++++++++++++++-----------
 1 file changed, 838 insertions(+), 387 deletions(-)

diff --git a/docs/tutorials/creation.ipynb b/docs/tutorials/creation.ipynb
index 25a67c4f8..73ff5b67d 100644
--- a/docs/tutorials/creation.ipynb
+++ b/docs/tutorials/creation.ipynb
@@ -13,396 +13,847 @@
     "    \"{\\n\",\n",
     "    \" \\\"cells\\\": [\\n\",\n",
     "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%% md\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"# Create an Empty MDIO\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"```{article-info}\\\\n\\\",\\n\",\n",
-    "    \"    \\\":author: Altay Sansal\\\\n\\\",\\n\",\n",
-    "    \"    \\\":date: \\\\\\\"{sub-ref}`today`\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\":read-time: \\\\\\\"{sub-ref}`wordcount-minutes` min read\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\\\n\\\",\\n\",\n",
-    "    \"    \\\"```\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"Here we will create an empty MDIO file and populate its fields.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"```{warning}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\\\n\\\",\\n\",\n",
-    "    \"    \\\"`pip install matplotlib` or `conda install matplotlib`.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"```\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We first need to import the configuration classes and create function to be able to create the empty MDIO.\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 2,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:04.371422Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:04.368107Z\\\"\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"import matplotlib.pyplot as plt\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import Dimension\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import Grid\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import MDIOCreateConfig\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import MDIOReader\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import MDIOVariableConfig\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import MDIOWriter\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import create_empty\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio.converters.segy import get_compressor\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio.segy.compat import mdio_segy_spec\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%% md\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"## Setting Up Grid Dimensions and Variable(s)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\\\n\\\",\\n\",\n",
-    "    \"    \\\"dimensions. This is exactly like a 3D Post-Stack dataset.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We will use the standard `chunked_012` access pattern. All variable names must start\\\\n\\\",\\n\",\n",
-    "    \"    \\\"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We will also use an MDIO private utility function to get the compressor easily. The\\\\n\\\",\\n\",\n",
-    "    \"    \\\"compressor is fully customizable, but this function gives us ones available in SEG-Y\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ingestion.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"At the end we create empty MDIO on local disk or cloud, based on the path string.\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 3,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:06.121450Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:06.002634Z\\\"\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"grid = Grid(\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    dims=[\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        Dimension(name=\\\\\\\"inline\\\\\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        Dimension(name=\\\\\\\"crossline\\\\\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        Dimension(name=\\\\\\\"sample\\\\\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"compressor = get_compressor(lossless=True)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"header_dtype = mdio_segy_spec().trace.header.dtype\\\\n\\\",\\n\",\n",
-    "    \"    \\\"variable = MDIOVariableConfig(\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    name=\\\\\\\"chunked_012\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    dtype=\\\\\\\"float32\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    chunks=(128, 128, 128),\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    compressors=compressor,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    header_dtype=header_dtype,\\\\n\\\",\\n\",\n",
-    "    \"    \\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"create_conf = MDIOCreateConfig(path=\\\\\\\"demo.mdio\\\\\\\", grid=grid, variables=[variable])\\\\n\\\",\\n\",\n",
-    "    \"    \\\"create_empty(config=create_conf);\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
     "    \"   \\\"metadata\\\": {},\\n\",\n",
+    "    \"   \\\"cell_type\\\": \\\"raw\\\",\\n\",\n",
     "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"## Populating the MDIO\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"Once empty MDIO is created, you can populate it with sample data, header data,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\\\n\\\",\\n\",\n",
-    "    \"    \\\"every write. However, the consistency of the `live_mask` is up to the user. If\\\\n\\\",\\n\",\n",
-    "    \"    \\\"not populated correctly, at read time, traces may be skipped.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We will read the usual stats and as you can see they're all empty. Text header\\\\n\\\",\\n\",\n",
-    "    \"    \\\"and binary header are only required if we are going to export this back to SEG-Y,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"and can be modified. We can edit these if necessary using the writer.\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 4,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:09.974442Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:09.951257Z\\\"\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"data\\\": {\\n\",\n",
-    "    \"      \\\"text/plain\\\": [\\n\",\n",
-    "    \"       \\\"(['C00                                                                             ',\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'C01                                                                             ',\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'C02                                                                             ',\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'C03                                                                             ',\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'C04                                                                             '],\\\\n\\\",\\n\",\n",
-    "    \"       \\\" {},\\\\n\\\",\\n\",\n",
-    "    \"       \\\" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\\\"\\n\",\n",
-    "    \"      ]\\n\",\n",
-    "    \"     },\\n\",\n",
-    "    \"     \\\"execution_count\\\": 4,\\n\",\n",
-    "    \"     \\\"metadata\\\": {},\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"execute_result\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   ],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"writer = MDIOWriter(create_conf.path)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"# Truncate text header for display\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer.text_header[:5], writer.binary_header, writer.stats\\\"\\n\",\n",
+    "    \"    \\\"{\\\\n\\\",\\n\",\n",
+    "    \"    \\\" \\\\\\\"cells\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%% md\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"# Create an Empty MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"```{article-info}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\":author: Altay Sansal\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\":date: \\\\\\\\\\\\\\\"{sub-ref}`today`\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\":read-time: \\\\\\\\\\\\\\\"{sub-ref}`wordcount-minutes` min read\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"```\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"Here we will create an empty MDIO file and populate its fields.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"```{warning}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"`pip install matplotlib` or `conda install matplotlib`.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"```\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We first need to import the configuration classes and create function to be able to create the empty MDIO.\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 2,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:04.371422Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:04.368107Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"import matplotlib.pyplot as plt\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import Dimension\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import Grid\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import MDIOCreateConfig\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import MDIOReader\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import MDIOVariableConfig\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import MDIOWriter\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import create_empty\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio.converters.segy import get_compressor\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio.segy.compat import mdio_segy_spec\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%% md\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"## Setting Up Grid Dimensions and Variable(s)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"dimensions. This is exactly like a 3D Post-Stack dataset.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We will use the standard `chunked_012` access pattern. All variable names must start\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We will also use an MDIO private utility function to get the compressor easily. The\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"compressor is fully customizable, but this function gives us ones available in SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ingestion.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"At the end we create empty MDIO on local disk or cloud, based on the path string.\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 3,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:06.121450Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:06.002634Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"grid = Grid(\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    dims=[\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"crossline\\\\\\\\\\\\\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    ]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"compressor = get_compressor(lossless=True)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"header_dtype = mdio_segy_spec().trace.header.dtype\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"variable = MDIOVariableConfig(\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    name=\\\\\\\\\\\\\\\"chunked_012\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    dtype=\\\\\\\\\\\\\\\"float32\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    chunks=(128, 128, 128),\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    compressors=compressor,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    header_dtype=header_dtype,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"create_conf = MDIOCreateConfig(path=\\\\\\\\\\\\\\\"demo.mdio\\\\\\\\\\\\\\\", grid=grid, variables=[variable])\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"create_empty(config=create_conf);\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"## Populating the MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"Once empty MDIO is created, you can populate it with sample data, header data,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"every write. However, the consistency of the `live_mask` is up to the user. If\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"not populated correctly, at read time, traces may be skipped.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We will read the usual stats and as you can see they're all empty. Text header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"and binary header are only required if we are going to export this back to SEG-Y,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"and can be modified. We can edit these if necessary using the writer.\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 4,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:09.974442Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:09.951257Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"(['C00                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'C01                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'C02                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'C03                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'C04                                                                             '],\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\" {},\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"execution_count\\\\\\\": 4,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"execute_result\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer = MDIOWriter(create_conf.path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"# Truncate text header for display\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer.text_header[:5], writer.binary_header, writer.stats\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"## Updating File and Checking with `MDIOReader`.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We write traces here, the headers are still empty. If you need the headers\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"populated, this is where they would be written to file as well.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"All the extra metadata we are writing is so that we can export back to SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"in the future. If that's not a requirement most of the metadata can be\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"omitted.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"If you already have an MDIO prior to this, all the metadata can be copied\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"over from the previous version.\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 5,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:12.498287Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:11.670230Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"({'data_sample_format': 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'sample_interval': 4,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'samples_per_trace': 750,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'segy_revision_major': 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"  'segy_revision_minor': 0},\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"execution_count\\\\\\\": 5,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"execute_result\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"sample_dim = writer.grid.select_dim(\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"num_samples = sample_dim.size\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer.binary_header = {\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"data_sample_format\\\\\\\\\\\\\\\": 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"sample_interval\\\\\\\\\\\\\\\": sample_interval,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"samples_per_trace\\\\\\\\\\\\\\\": num_samples,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"segy_revision_major\\\\\\\\\\\\\\\": 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"segy_revision_minor\\\\\\\\\\\\\\\": 0,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"# Write some values to the file\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer[:5] = 1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer[5:10] = 2\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer[50:100] = 3\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer[150:175] = -1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"# Write some made up stats\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"writer.stats = {\\\\\\\\\\\\\\\"mean\\\\\\\\\\\\\\\": 12, \\\\\\\\\\\\\\\"std\\\\\\\\\\\\\\\": 5, \\\\\\\\\\\\\\\"rms\\\\\\\\\\\\\\\": 3, \\\\\\\\\\\\\\\"min\\\\\\\\\\\\\\\": -4, \\\\\\\\\\\\\\\"max\\\\\\\\\\\\\\\": 4}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"reader = MDIOReader(create_conf.path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"reader.binary_header, reader.stats\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": \\\\\\\"Plot some of the data we populated:\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 6,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:14.256953Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:14.036094Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"image/png\\\\\\\": 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UMYByCsrRsXq3WvDhg3d8//orOC6bp1OPqvz9QBAIKOMAxA0ExTrSgDbtm0zkxU6dHJFXa7Fc1btC9FC8vDhw2aSQ52EFkDg0XtUneBaZ713Jli1wZWWcZRvQHCVbwEf7H755RezrInOiu1Jnzvr3mWnS514LneiKxg4S6gACGwHDx40s+Hb4lLLOMo3ILjLt4APdpdj3LhxZvmY7H78qpIUK5K3O/1HGtaQ1BOB++Pr8tRR6dwvePrnZKSLdKl7s2RmBE+Nhb9+x3t3RMuQTjde9e+bIemyTpaYmqlgllv5dv3o4RL6v0XbHY0bJEloSNZ5x/4wtapknf2/tZID0aMJX0vXltslWGRkhsi9zz4qmVn21FRfTHjSTxL+3yNX/ftmxRWWtDuu/o1SZnqabFv6Yp7Kt8BNJv9TsmRJsybn0aNHvV7X57rGXU60SUM7Insu4q79VTTUFSuatz+M8JBwCQsJ3B9fdGRYnq/VBhnpIRIWEh5UTVH++h0XiSlkftZX3f96C9v2O77UMi638k1DXfZgFx4TIYVCzw92YeFRkpUVuMEuOjo8uMq3zFDzOwsJomAXVijSL+VMVkiE+Vn7S17Kt4D/VxAREWEWQdZFmD37lOjz3BZDjoyMNIsxe24AYEMZR/kGBLfArXLyoHen3bt3lwYNGsitt94qb7zxhqSmpspjjz3m71MDgCtGGQcgqIJd586d5eeff5aRI0dKcnKy1KtXT5YuXXpeZ2MACESUcQCCKtipfv36mQ0AbEQZByAvAr6PHQAAAP4PwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAB9Zu3attGvXTsqVKychISGycOFCr/0ul0tGjhwpZcuWlejoaGnRooXs2bPH65hff/1VunbtKsWKFZO4uDjp2bOnnD59+ipfCYBAQbADAB9JTU2VunXryuTJk3PcP378eJk0aZJMmzZNNm3aJDExMZKQkCBpaWnuYzTU7dy5U1asWCGLFy82YbF3795X8SoABJIwf58AANiqdevWZsuJ1ta98cYbMnz4cGnfvr15bc6cOVK6dGlTs9elSxfZvXu3LF26VLZs2SINGjQwx7z11lvSpk0bmTBhgqkJBABP1NgBgB/s379fkpOTTfOrIzY2Vho1aiQbNmwwz/VRm1+dUKf0+NDQUFPDBwDZUWMHAH6goU5pDZ0nfe7s08dSpUp57Q8LC5PixYu7j8nu7NmzZnOcPHnSB2cPoKCixg4ALDJu3DhT8+ds5cuX9/cpAbiKCHYA4AdlypQxj0ePHvV6XZ87+/QxJSXFa39GRoYZKesck92wYcPkxIkT7u3gwYM+uwYABQ/BDgD8oHLlyiacJSYmejWbat+5+Ph481wfjx8/Ltu2bXMfs2rVKsnKyjJ98XISGRlppkbx3AAED/rYAYCP6Hxze/fu9RowsX37dtNHrkKFCjJgwAB54YUXpGrVqibojRgxwox07dChgzm+Ro0a0qpVK+nVq5eZEiU9PV369etnRswyIhZATgh2AOAjW7dulbvvvtv9fNCgQeaxe/fuMmvWLHnmmWfMXHc6L53WzDVp0sRMbxIVFeV+z/vvv2/CXPPmzc1o2E6dOpm57wAgJwQ7APCRpk2bmvnqcqOrUYwZM8ZsudHavblz5/roDAHYhj52AAAAliDYAQAAWIJgBwAAYIkCHexGjx5t+qB4btWrV3fv14Wy+/btKyVKlJAiRYqYTsXZ54QCAAAIFgU62KlatWrJkSNH3Nu6devc+wYOHCiLFi2S+fPny5o1a+Tw4cPSsWNHv54vAACAvxT4UbG6LmJOM6zrjOrvvvuuGS3WrFkz89rMmTPNvE8bN26Uxo0b++FsAQAA/KfA19jt2bPHTMR5ww03SNeuXeXAgQPmdZ2JXSfrbNGihftYbabVST83bNhwwc/UBbJ1hnfPDQAAINAV6GCnS+boJJ46YefUqVPNrO133HGHnDp1SpKTkyUiIkLi4uK83lO6dGmz70JYJBsAANioQDfFtm7d2v11nTp1TNCrWLGifPjhhxIdHX3Zn6uLZDszwCutsSPcAQCAQFega+yy09q5atWqmbUXtd/duXPnzDI8nnRUbE598jyxSDYAALBRaKAtqL1v3z4pW7as1K9fX8LDwyUxMdG9PykpyfTBi4+P9+t5AgAA+EOBboodPHiwtGvXzjS/6lQmo0aNkkKFCslDDz1k+sb17NnTNKnqWopa69a/f38T6hgRCwAAglGBDnaHDh0yIe7YsWNy7bXXSpMmTcxUJvq1mjhxooSGhpqJiXWka0JCgkyZMsXfpw0AAOAXBTrYzZs374L7o6KiZPLkyWYDAAAIdgHVxw4AAAC5I9gBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAPjAuHHjpGHDhlK0aFEpVaqUdOjQQZKSkryOSUtLk759+0qJEiWkSJEi0qlTJzl69KjXMQcOHJC2bdtK4cKFzecMGTJEMjIyrvLVAAgUBDsA8IE1a9aY0LZx40ZZsWKFpKenS8uWLSU1NdV9zMCBA2XRokUyf/58c/zhw4elY8eO7v2ZmZkm1J07d07Wr18vs2fPllmzZsnIkSP9dFUACrowf58AANho6dKlXs81kGmN27Zt2+TOO++UEydOyLvvvitz586VZs2amWNmzpwpNWrUMGGwcePGsnz5ctm1a5esXLlSSpcuLfXq1ZOxY8fK0KFDZfTo0RIREeGnqwNQUFFjBwBXgQY5Vbx4cfOoAU9r8Vq0aOE+pnr16lKhQgXZsGGDea6PtWvXNqHOkZCQICdPnpSdO3fm+H3Onj1r9ntuAIIHwQ4AfCwrK0sGDBggt99+u9x8883mteTkZFPjFhcX53Wshjjd5xzjGeqc/c6+3Pr2xcbGurfy5cv76KoAFEQEOwDwMe1r991338m8efN8/r2GDRtmaged7eDBgz7/ngAKDvrYAYAP9evXTxYvXixr166V66+/3v16mTJlzKCI48ePe9Xa6ahY3eccs3nzZq/Pc0bNOsdkFxkZaTYAwYkaOwDwAZfLZULdggULZNWqVVK5cmWv/fXr15fw8HBJTEx0v6bToej0JvHx8ea5Pu7YsUNSUlLcx+gI22LFiknNmjWv4tUACBTU2AGAj5pfdcTrp59+auayc/rEab+36Oho89izZ08ZNGiQGVChYa1///4mzOmIWKXTo2iA69atm4wfP958xvDhw81nUysHICcEOwDwgalTp5rHpk2ber2uU5r06NHDfD1x4kQJDQ01ExPraFYd8TplyhT3sYUKFTLNuH369DGBLyYmRrp37y5jxoy5ylcDIFAQ7ADAR02xFxMVFSWTJ082W24qVqwoS5YsyeezA2Ar+tgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJfwa7NauXSvt2rWTcuXKSUhIiCxcuNBrv8vlkpEjR0rZsmUlOjpaWrRoIXv27PE65tdff5WuXbtKsWLFJC4uTnr27CmnT5++ylcCAAAQ5MEuNTVV6tatK5MnT85x//jx42XSpEkybdo02bRpk8TExEhCQoKkpaW5j9FQt3PnTlmxYoUsXrzYhMXevXtfxasAAAAoGML8+c1bt25ttpxobd0bb7whw4cPl/bt25vX5syZI6VLlzY1e126dJHdu3fL0qVLZcuWLdKgQQNzzFtvvSVt2rSRCRMmmJpAAACAYFFg+9jt379fkpOTTfOrIzY2Vho1aiQbNmwwz/VRm1+dUKf0+NDQUFPDl5uzZ8/KyZMnvTYAAIBAV2CDnYY6pTV0nvS5s08fS5Uq5bU/LCxMihcv7j4mJ+PGjTMh0dnKly/vk2sAAAC4mgpssPOlYcOGyYkTJ9zbwYMH/X1KAAAA9ga7MmXKmMejR496va7PnX36mJKS4rU/IyPDjJR1jslJZGSkGUXruQEAAAS6AhvsKleubMJZYmKi+zXtC6d95+Lj481zfTx+/Lhs27bNfcyqVaskKyvL9MUDAAAIJn4dFavzze3du9drwMT27dtNH7kKFSrIgAED5IUXXpCqVauaoDdixAgz0rVDhw7m+Bo1akirVq2kV69eZkqU9PR06devnxkxy4hYAAAQbPwa7LZu3Sp33323+/mgQYPMY/fu3WXWrFnyzDPPmLnudF46rZlr0qSJmd4kKirK/Z7333/fhLnmzZub0bCdOnUyc98BAAAEG78Gu6ZNm5r56nKjq1GMGTPGbLnR2r25c+f66AwBAAACR4HtYwcAAIBLQ7ADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAHxg6tSpUqdOHSlWrJjZ4uPj5fPPP3fvT0tLk759+0qJEiWkSJEi0qlTJzl69KjXZxw4cEDatm0rhQsXllKlSsmQIUMkIyPDD1cDIFAQ7ADAB66//np5+eWXZdu2bbJ161Zp1qyZtG/fXnbu3Gn2Dxw4UBYtWiTz58+XNWvWyOHDh6Vjx47u92dmZppQd+7cOVm/fr3Mnj1bZs2aJSNHjvTjVQEo6ML8fQIAYKN27dp5PX/xxRdNLd7GjRtN6Hv33Xdl7ty5JvCpmTNnSo0aNcz+xo0by/Lly2XXrl2ycuVKKV26tNSrV0/Gjh0rQ4cOldGjR0tERISfrgxAQUaNHQD4mNa+zZs3T1JTU02TrNbipaenS4sWLdzHVK9eXSpUqCAbNmwwz/Wxdu3aJtQ5EhIS5OTJk+5av5ycPXvWHOO5AQgeBDsA8JEdO3aY/nORkZHyxBNPyIIFC6RmzZqSnJxsatzi4uK8jtcQp/uUPnqGOme/sy8348aNk9jYWPdWvnx5n1wbgIKJYAcAPnLTTTfJ9u3bZdOmTdKnTx/p3r27aV71pWHDhsmJEyfc28GDB336/QAULPSxAwAf0Vq5G2+80Xxdv3592bJli7z55pvSuXNnMyji+PHjXrV2Oiq2TJky5mt93Lx5s9fnOaNmnWNyorWDugEITtTYAcBVkpWVZfrAacgLDw+XxMRE976kpCQzvYn2wVP6qE25KSkp7mNWrFhhpk7R5lwAyAk1dgDgoybR1q1bmwERp06dMiNgV69eLcuWLTN933r27CmDBg2S4sWLm7DWv39/E+Z0RKxq2bKlCXDdunWT8ePHm351w4cPN3PfUSMHIDcEOwDwAa1pe/TRR+XIkSMmyOlkxRrq7rnnHrN/4sSJEhoaaiYm1lo8HfE6ZcoU9/sLFSokixcvNn3zNPDFxMSYPnpjxozx41UBKOgIdgDgAzpP3YVERUXJ5MmTzZabihUrypIlS3xwdgBsRR87AAAASxDsAAAALEGwAwAAsMQVBTudh0mH6GdkZOTfGQEAAODqBbszZ86YofqFCxeWWrVqmbmXlA7Xf/nlly/vTAAAAHD1g53Oz/TNN9+YOZl0ZJdDF7T+4IMPruyMAAAAcPWmO1m4cKEJcDqRZkhIiPt1rb3bt2/f5Z0JAAAArn6N3c8//yylSpU67/XU1FSvoAcAAIACHuwaNGgg//rXv9zPnTD3zjvvuNc5BAAAQAA0xb700ktmDcRdu3aZEbFvvvmm+Xr9+vWyZs2a/D9LALiK/v3vf8v06dNN15KPPvpIrrvuOnnvvfekcuXK0qRJE3+fHgDkb42dFmzbt283oa527dqyfPly0zS7YcMGqV+//uV8JAAUCB9//LFZtzU6Olq+/vprs46rOnHihLmpBQAr14qtUqWKzJgxI3/PBgD87IUXXpBp06bJo48+KvPmzXO/fvvtt5t9AGBlsMvKypK9e/dKSkqK+drTnXfemR/nBgBXnU66nlMZFhsbK8ePH/fLOQGAT4Pdxo0b5eGHH5Yff/xRXC6X1z4dSJGZmXk5HwsAflemTBlz01qpUiWv19etWyc33HCD384LAHwW7J544gn3yNiyZcsyxQkAa/Tq1Uv+8pe/yN///ndTth0+fNj0Hx48eLCMGDHC36cHAPkf7Pbs2WNGit14442X83YAKLCeffZZ072kefPmZvlEbZaNjIw0wU6XTQQA64Jdo0aNTFMFwQ6AbbSW7q9//asMGTLElHOnT5+WmjVrSpEiRfx9agDgm2Cnd61PP/20JCcnm+lOwsPDvfbXqVPncj4WAAqMiIgIE+gAwPpg16lTJ/P4+OOPe93l6kAKBk8ACDQdO3bM87GffPKJT88FAK56sNu/f/8VfVMAKEh0KhMACNpgV7Fixfw/EwDwk5kzZ/r7FADg6ga7zz77zKwPq/3p9OsLuffee/Pj3ADAb3TydZ2sWN10001m2UQAsCbYdejQwQyW0MJNv84NfewABLKTJ09K3759zXJiTllWqFAh6dy5s0yePJlmWwAFWmheD9R5nZw7Vv06t41QByDQJyjetGmTLF682Cwhppt+vXXrVvnzn//s79MDAN+sFQsANtIQt2zZMmnSpIn7tYSEBJkxY4a0atXKr+cGAPkW7CZNmpTXQ+Wpp57K87EAUJCUKFEix+ZWfe2aa67xyzkBQL4Hu4kTJ+bpOO1jR7ADEKiGDx8ugwYNkvfee0/KlCljXtP+xboSBWvFArAm2DF3HYBgMHXqVLOUWIUKFcymDhw4YNaL/fnnn2X69OnuY7/66is/nikA+KiPnQ6Y2LFjh5nf7lKaKtauXSuvvvqqbNu2TY4cOSILFizwGnHbo0cPmT17ttd7tK/L0qVL3c9//fVXs8TZokWLJDQ01KyK8eabb7KuI4DLcqFR/wBgZbAbMGCAWSO2Z8+eJtTdeeedsmHDBilcuLDpeNy0adM8fU5qaqrUrVvXLE2W25I+2lnZc/JQvWv21LVrVxMKV6xYIenp6fLYY49J7969Ze7cuZdzaQCC3KhRo/x9CgBwdYPdRx99JI888oj5WmvKfvjhB/nPf/5j+qT89a9/lS+//DJPn6MTHut2IRrknH4u2e3evdvU3m3ZskUaNGhgXnvrrbekTZs2MmHCBClXrtwlXxsAOE6fPm2mcfJUrFgxv50PAOTbPHaefvnlF3fYWrJkiTzwwANSrVo1U/OmTbL5afXq1Wb+PJ35vU+fPnLs2DH3Pq0ljIuLc4c61aJFC9Mkq/NQ5ebs2bNmElLPDQCc/sRt27aVmJgY90hY3bSsYVQsACtr7EqXLi27du2SsmXLmhoz7Wyszpw5Y2Zozy/aDKtNtJUrV5Z9+/bJc889Z2r4NNDp93FWwvAUFhYmxYsXN/tyM27cOHn++efz7TwB2ENbI1wul/z97383ZZ2O9AcAq4Od9mN78MEHTbDTQk9ryZTWklWvXj3fTq5Lly7ur7VPX506daRKlSqmFq958+aX/bnDhg0z0xk4tMaufPnyV3y+AALfN998YwZ0aSsBAARFsBs9erTcfPPNcvDgQdMM6wxo0Fq0Z599VnzlhhtukJIlS5qpCDTYaXOwLtTtKSMjw4yUza1fntLzzT4IAwBUw4YNTdlGsAMQVNOd3H///V7PdT3F7t27iy8dOnTI9LHTmkIVHx9vvq/eXdevX9+8tmrVKtPZuVGjRj49FwB2euedd+SJJ56Qn376ydzAhoeHe+3XlgMAsCrYvfLKK1KpUiXp3Lmzea7Nsh9//LEJXDqYIq8Fn44409o3z07L27dvN33kdNN+cDovnda+aR+7Z555Rm688UYzl52qUaOG6Yeni3ZPmzbNTHfSr18/04TLiFgAl0MnIdbyRrucOLTLifa700ed4gkArBoVqyHK6ZOm88fp9vnnn5uQNXjw4Dx/ztatW+UPf/iD2ZT2e9OvR44caZp1v/32W7n33nvNiFudM09r5f797397NaO+//77pl+fNs3qNCe6cPfbb799OZcFAGZ0v5ZDOkjr+++/Nzecno8AYF2NnY44dYKdTkisNXYtW7Y0tXiX0gSqExnrXXBuli1bdtHP0Jo9JiMGkF9+/PFH+eyzz0zrAAAERY2dzuWknYuVTnfijIrVkEYzBYBA1qxZMzMyFgCCJtjp3HIPP/yw3HPPPWYwg7N6xNdff81dLoCA1q5dOxk4cKAZ/a99h7X2znO7XC+//LLpo6dLMjrS0tKkb9++UqJECbO+tfYpPnr0qNf7Dhw4YCZM1iUbdd7OIUOGmNH/AJBvTbETJ040za5aazd+/HhTIClds/XJJ5+8nI8EgAJBR8SqMWPGnLfvcgdP6LKH06dPP29gmQbIf/3rXzJ//nyzyoUO/tIbZ2dZRv1eGup0ANn69etNGfvoo4+akbovvfTSZV8jAHtdVrDTQiWnQRJaSAFAIMu+NuyV0tH/Xbt2lRkzZsgLL7zgfv3EiRPy7rvvmj7C2vyrZs6caUb7b9y4URo3bizLly83q/ysXLnSrIJRr149GTt2rAwdOtTUKEZEROTruQII0qZYpdMB9O/f3/Sv0+2pp55ixBgAZKNNrVrr5vRFduj8mzpFk+frOsK/QoUKZkSu0kdddUdDnUOne9LVcnbu3HkVrwKA1TV2OlpVpyHRu8fbb7/dvKZNBzVr1pRFixaZvncAEKhSU1NlzZo1pn/buXPnvPbpTWxezZs3T7766ivTFJvT7AJa4xYXF+f1uoY4Z61rffQMdc5+Z19Ozp49azaHhkAAweOygp0uG6bNrtoZOPvr2kRAsAMQqHQQmM6JeebMGRPwdEqlX375xT14Ia/BTvsg/+UvfzHzfEZFRcnVMm7cODO5O4DgdFlNsbt37zYTBuc0saf2BwGAQKU3rToy9rfffpPo6GjT303nttMJ0idMmJDnz9GmVl3L+pZbbpGwsDCzaS3gpEmTzNda86a1gbosoicdFeusda2P2UfJOs9zWw972LBhpv+eszlTUwEIDpcV7K699lqz9Fd2+pre0QJAoNJy7Omnn5bQ0FCzAo42a+qE7DoDwHPPPZfnz9HVcHbs2GE+z9kaNGhgBlI4X+tAtMTERPd7kpKSTPOvroOt9FE/QwOiQ2sAixUrZrq+5ERX5tH9nhuA4HFZTbG6Nmvv3r3NYInbbrvN3cdO15DVZcEAIFBp2NJQp/RGVYOWjlTV6UgupfaraNGicvPNN3u9FhMTY+asc17Xlg8tM7W5VwOYDkjTMKcjYpWu6KMBrlu3biZYar+64cOHmwEZnksrAsAVBbsRI0aYQuu1114z1f6qXLlyZvj9pXQsBoCCRteJ1cEOVatWlbvuususXa197N57773zgtqV0jlBNUTqxMRaM6gjXqdMmeLerzWGumxjnz59TODTYNi9e/cc59gDgMsKdjrjuc67pCtPaF+UU6dOmdc16AFAoNOJf51y7cUXXzQTAmuwqlatmrzzzjtX9NmrV6/2eq6DKiZPnmy23FSsWFGWLFlyRd8XQPC45GCnnX51ZnYdQKEIdABsUqtWLbPutdMUO23aNFmwYIFpEtUpngDAusETt956q5kSAABs0759e5kzZ475Wkesan+3119/XTp06CBTp0719+kBQP73sdP1YHXU2KFDh8wUANrvw1P29RABIFDohMLa90199NFHZloSvZH9+OOPTX87bZYFAKuCXZcuXcyj50AJXRxbmy8ud5FsACgIdGJip4uJrtXasWNHM8BBa+50PjsAsC7Y7d+/P//PBAAKgBtvvFEWLlwo9913n1k+UQeJKZ1LjjnhAFjZx05Hxeqkmjpay3PT13RtRAAIVNrcOnjwYKlUqZI0atTIPVmw1t7pVCgAYF2wmz59ulSvXj3H0WQ6ggwAAtX9999vJiXeunWrLF261GslCafvHQBY1RSrs5+XLVs2x6XGjhw5kh/nBQB+o+uwZl+LVWcDAAAra+x03URdQiw7fU1XoAAAAEAArRU7YMAASU9Pl2bNmpnXtH/dM888Y6ZBAQAAQIAEuyFDhsixY8fMfHbnzp1zL40zdOhQ99qxAAAACIBgp3PVvfLKKzJixAiztFh0dLRZMDsyMjL/zxAAAAC+C3aOIkWKSMOGDa/kIwAAAODPwRMAAAAoeAh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwA+MHr0aAkJCfHaqlev7t6flpYmffv2lRIlSkiRIkWkU6dOcvToUa/POHDggLRt21YKFy4spUqVkiFDhkhGRoYfrgZAoPBrsBs3bpw0bNhQihYtagqtDh06SFJSktcxFH4AAlWtWrXkyJEj7m3dunXufQMHDpRFixbJ/PnzZc2aNXL48GHp2LGje39mZqYp186dOyfr16+X2bNny6xZs2TkyJF+uhoAgcCvwU4LMw1tGzdulBUrVkh6erq0bNlSUlNT3cdQ+AEIVGFhYVKmTBn3VrJkSfP6iRMn5N1335XXX39dmjVrJvXr15eZM2eaMkzLQ7V8+XLZtWuX/OMf/5B69epJ69atZezYsTJ58mRT3gFAgQt2S5culR49epi72rp165pAprVv27ZtM/sp/AAEsj179ki5cuXkhhtukK5du5ryTWkZpzeyLVq0cB+rzbQVKlSQDRs2mOf6WLt2bSldurT7mISEBDl58qTs3LnTD1cDIBAUqD52GuRU8eLFfVr4nT171uz33AAgPzVq1MjcrOoN7NSpU2X//v1yxx13yKlTpyQ5OVkiIiIkLi7O6z1ajuk+pY+e5Zqz39mXG8o3ILiFSQGRlZUlAwYMkNtvv11uvvlm85qvCj/t2/f888/76EoAQEzrgaNOnTom6FWsWFE+/PBDiY6O9tn3pXwDgluBqbHTvnbfffedzJs3z+ffa9iwYaZ20NkOHjzo8+8JILjpDWq1atVk7969pr+ddhU5fvy41zE6MEz3KX3MPlDMee4ckxPKNyC4FYhg169fP1m8eLF88cUXcv3117tf91XhFxkZKcWKFfPaAMCXTp8+Lfv27ZOyZcua/sLh4eGSmJjo3q8zAmgfvPj4ePNcH3fs2CEpKSnuY3SQmZZXNWvWzPX7UL4Bwc2vwc7lcplQt2DBAlm1apVUrlzZa78vCz8A8KXBgwebkfw//PCDGfB13333SaFCheShhx6S2NhY6dmzpwwaNMjc0Gp/4scee8yUZ40bNzbv1xkCtAzr1q2bfPPNN7Js2TIZPny4ad3Q8AYABa6PnRZQc+fOlU8//dTMZef0idNCT/ugeBZ+OqBCw1r//v1zLfzGjx9vPoPCD4C/HTp0yIS4Y8eOybXXXitNmjQxo/n1azVx4kQJDQ01c3PqgAcd9DVlyhT3+zUEaktGnz59TJkXExMj3bt3lzFjxvjxqgAUdH4NdjpSTDVt2tTrdZ3SRKdBURR+AALRxfoLR0VFmWmZdMuNDrZYsmSJD84OgK3C/N0UezEUfgAAAAE0eAIAAABXjmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAWIJgBwAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAYCP/PTTT/LII49IiRIlJDo6WmrXri1bt25173e5XDJy5EgpW7as2d+iRQvZs2eP12f8+uuv0rVrVylWrJjExcVJz5495fTp0364GgCBgGAHAD7w22+/ye233y7h4eHy+eefy65du+S1116Ta665xn3M+PHjZdKkSTJt2jTZtGmTxMTESEJCgqSlpbmP0VC3c+dOWbFihSxevFjWrl0rvXv39tNVASjowvx9AgBgo1deeUXKly8vM2fOdL9WuXJlr9q6N954Q4YPHy7t27c3r82ZM0dKly4tCxculC5dusju3btl6dKlsmXLFmnQoIE55q233pI2bdrIhAkTpFy5cn64MgAFGTV2AOADn332mQljDzzwgJQqVUr+8Ic/yIwZM9z79+/fL8nJyab51REbGyuNGjWSDRs2mOf6qM2vTqhTenxoaKip4cvJ2bNn5eTJk14bgOBBsAMAH/j+++9l6tSpUrVqVVm2bJn06dNHnnrqKZk9e7bZr6FOaQ2dJ33u7NNHDYWewsLCpHjx4u5jshs3bpwJiM6mtYYAggfBDgB8ICsrS2655RZ56aWXTG2d9ovr1auX6U/nS8OGDZMTJ064t4MHD/r0+wEoWAh2AOADOtK1Zs2aXq/VqFFDDhw4YL4uU6aMeTx69KjXMfrc2aePKSkpXvszMjLMSFnnmOwiIyPNCFrPDUDwINgBgA/oiNikpCSv1/773/9KxYoV3QMpNJwlJia692t/OO07Fx8fb57r4/Hjx2Xbtm3uY1atWmVqA7UvHgBkx6hYAPCBgQMHym233WaaYh988EHZvHmzvP3222ZTISEhMmDAAHnhhRdMPzwNeiNGjDAjXTt06OCu4WvVqpW7CTc9PV369etnRswyIhZATgh2AOADDRs2lAULFpg+b2PGjDHBTac30XnpHM8884ykpqaa/ndaM9ekSRMzvUlUVJT7mPfff9+EuebNm5vRsJ06dTJz3wFATgh2AOAjf/zjH82WG62109CnW250BOzcuXN9dIYAbEMfOwAAAEsQ7AAAACzh12CnE2lqP5SiRYuaSTi1w3D2UWRNmzY1zRWe2xNPPOF1jE4f0LZtWylcuLD5nCFDhpgpAQAAAIKJX/vYrVmzRvr27WvCnQax5557Tlq2bGkWy9bFsB06IsyzD4oGOEdmZqYJdTptwPr16+XIkSPy6KOPmoW3dTQaAABAsPBrsNPRX55mzZplatx0zqY777zTK8jlNhnn8uXLTRBcuXKlWYqnXr16MnbsWBk6dKiMHj1aIiIifH4dAAAABUGB6mOny984o8A86XD/kiVLys0332ymDjhz5ox7ny6SXbt2ba/1FhMSEsxEnzt37szx+7BINgAAsFGBme5EZ1LXyTp1tnYNcI6HH37YzNSuk3F+++23piZO++F98sknZr8uhJ3TItrOvtz69j3//PM+vR4AAICgDXba1+67776TdevWeb2uE3c6tGZO11/UiTr37dsnVapUuazvpbV+gwYNcj/XGrvy5ctfwdkDAAD4X4FoitVZ1RcvXixffPGFXH/99Rc81lkfce/eveZR+97ltIi2sy8nLJINAABs5Ndg53K5TKjTZXd0YWtdcuditm/fbh615s5ZJHvHjh2SkpLiPmbFihUmrNWsWdOHZw8AAFCwhPm7+VWXyvn000/NXHZOn7jY2FiJjo42za26v02bNlKiRAnTx04X1tYRs3Xq1DHH6vQoGuC6desm48ePN58xfPhw89laMwcAABAs/FpjN3XqVDMSVich1ho4Z/vggw/Mfp2qRKcx0fBWvXp1efrpp80C2IsWLXJ/RqFChUwzrj5q7d0jjzxi5rG70NqLAAAANgrzd1PsheiABp3E+GJ01OySJUvy8cwAAAACT4EYPAEAAIArR7ADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7APCBSpUqSUhIyHlb3759zf60tDTzdYkSJaRIkSLSqVMnOXr0qNdnHDhwQNq2bSuFCxeWUqVKyZAhQyQjI8NPVwQgEBDsAMAHtmzZIkeOHHFvK1asMK8/8MAD5nHgwIGyaNEimT9/vqxZs0YOHz4sHTt2dL8/MzPThLpz587J+vXrZfbs2TJr1iwZOXKk364JQMFHsAMAH7j22mulTJky7m3x4sVSpUoVueuuu+TEiRPy7rvvyuuvvy7NmjWT+vXry8yZM02A27hxo3n/8uXLZdeuXfKPf/xD6tWrJ61bt5axY8fK5MmTTdgDgJwQ7ADAxzSIaUB7/PHHTXPstm3bJD09XVq0aOE+pnr16lKhQgXZsGGDea6PtWvXltKlS7uPSUhIkJMnT8rOnTtz/V5nz541x3huAIIHwQ4AfGzhwoVy/Phx6dGjh3menJwsEREREhcX53Wchjjd5xzjGeqc/c6+3IwbN05iY2PdW/ny5X1wRQAKKoIdAPiYNrtqU2q5cuV8/r2GDRtmmnqd7eDBgz7/ngAKjjB/nwAA2OzHH3+UlStXyieffOJ+TfvcafOs1uJ51trpqFjd5xyzefNmr89yRs06x+QkMjLSbACCEzV2AOBDOihCpyrREa4OHSwRHh4uiYmJ7teSkpLM9Cbx8fHmuT7u2LFDUlJS3MfoyNpixYpJzZo1r/JVAAgU1NgBgI9kZWWZYNe9e3cJC/v/xa32fevZs6cMGjRIihcvbsJa//79TZhr3LixOaZly5YmwHXr1k3Gjx9v+tUNHz7czH1HjRyA3BDsAMBHtAlWa+F0NGx2EydOlNDQUDMxsY5k1RGvU6ZMce8vVKiQmSKlT58+JvDFxMSYgDhmzJirfBUAAgnBDgB8RGvdXC5XjvuioqLMnHS65aZixYqyZMkSH54hANvQxw4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAASxDsAAAALEGwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOwAAAAsQbADAACwBMEOAADAEgQ7AAAAS4T5+wQKApfLZR5Pns7K83vSXemS8b/3BaLfz2bIyVN5v95Al5EukuFKl0xXiAQLf/2OT6dmmp/11ZYh6V5/zxCvn0dWWtp5+9JTz0lmyPn/RjLS0yQrvZAEqt9/Tw+u8i3TZX5nmVnBU1cTknlWQvxQzmS5zpmf9dWW+b/vmZfyLcRFKSjff/+9VKlSxd+nASAfHDx4UK6//np/n0aBcejQISlfvry/TwPAVSrfCHYicvz4cbnmmmvkwIEDEhsbK8Hg5MmTprDXfyTFihUT2wXb9QbjNWtRdurUKSlXrpyEhgZPzcXFZGVlSVJSktSsWTNo/i0E27/9YLzmYLte1yWUbzTFakfD//2QNNQFwz8QT3q9wXTNwXa9wXbNwXJjdqnl23XXXRd0/xaC8XqD8ZqD6Xpj81i+cVsLAABgCYIdAACAJQh2IhIZGSmjRo0yj8Ei2K452K43WK8ZOQu2fwvBdr3BeM3Bdr2XgsETAAAAlqDGDgAAwBIEOwAAAEsQ7AAAACxBsBORyZMnS6VKlSQqKkoaNWokmzdvFhuMHj1aQkJCvLbq1au796elpUnfvn2lRIkSUqRIEenUqZMcPXpUAsnatWulXbt2ZtJGvb6FCxd67dcupCNHjpSyZctKdHS0tGjRQvbs2eN1zK+//ipdu3Y1cyHFxcVJz5495fTp0xKI19ujR4/zfuetWrUK2OvFlbO1fAuGMi7YyjdFGXflgj7YffDBBzJo0CAzuuarr76SunXrSkJCgqSkpIgNatWqJUeOHHFv69atc+8bOHCgLFq0SObPny9r1qyRw4cPS8eOHSWQpKammt+Z/s8rJ+PHj5dJkybJtGnTZNOmTRITE2N+v1rgO7QA2Llzp6xYsUIWL15sCpbevXtLIF6v0kLO83f+z3/+02t/IF0vrozt5ZvtZVywlW+KMi4fuILcrbfe6urbt6/7eWZmpqtcuXKucePGuQLdqFGjXHXr1s1x3/Hjx13h4eGu+fPnu1/bvXu3jpB2bdiwwRWI9NwXLFjgfp6VleUqU6aM69VXX/W67sjISNc///lP83zXrl3mfVu2bHEf8/nnn7tCQkJcP/30kyuQrld1797d1b59+1zfE8jXi0tnc/kWbGVcsJVvijLu8gR1jd25c+dk27Ztpvrac/kdfb5hwwaxgVbLa5X2DTfcYO5idD1cpdednp7ude3ahFGhQgVrrn3//v2SnJzsdY26JIs2RznXqI9aVd+gQQP3MXq8/jvQO+BAtHr1ailVqpTcdNNN0qdPHzl27Jh7n43Xi+At34K5jAvW8k1Rxl1YUAe7X375RTIzM6V06dJer+tz/YMJdPoHPmvWLFm6dKlMnTrVFAR33HGHWUhYry8iIsL8Adh47cq5jgv9fvVRCwhPYWFhUrx48YD8OWgTxZw5cyQxMVFeeeUV0/zUunVr8+/cxutF8JZvwV7GBWP5pijjLi4sD8cgQOk/dkedOnVMIVixYkX58MMPTUdb2KdLly7ur2vXrm1+71WqVDF3uM2bN/fruQH5jTIu+FDGXVxQ19iVLFlSChUqdN4oKX1epkwZsY3euVarVk327t1rrk+bao4fP27ttTvXcaHfrz5m70iekZFhRlXZ8HPQ5in9d66/82C4XgRv+RZsZRzl2/+hjDtfUAc7raavX7++qdJ1ZGVlmefx8fFiGx3uvW/fPjM0Xq87PDzc69qTkpJM/xRbrr1y5crmD9nzGk+ePGn6WTjXqI9a8Gt/HMeqVavMvwO9+w90hw4dMv1P9HceDNeL4C3fgq2Mo3z7P5RxOXAFuXnz5plRRLNmzTKjaXr37u2Ki4tzJScnuwLd008/7Vq9erVr//79ri+//NLVokULV8mSJV0pKSlm/xNPPOGqUKGCa9WqVa6tW7e64uPjzRZITp065fr666/Npv+cX3/9dfP1jz/+aPa//PLL5vf56aefur799lszmqpy5cqu33//3f0ZrVq1cv3hD39wbdq0ybVu3TpX1apVXQ899JAr0K5X9w0ePNiM+NPf+cqVK1233HKLuZ60tLSAvF5cGZvLt2Ao44KtfFOUcVcu6IOdeuutt8wff0REhJkeYOPGjS4bdO7c2VW2bFlzXdddd515vnfvXvd+/eN/8sknXddcc42rcOHCrvvuu8915MgRVyD54osvzB9/9k2HxDtTAowYMcJVunRp8z+45s2bu5KSkrw+49ixY+aPvkiRIq5ixYq5HnvsMVOABNr1njlzxtWyZUvXtddea6Z5qFixoqtXr17n/U88kK4XV87W8i0YyrhgK98UZdyVC9H/5FSTBwAAgMAS1H3sAAAAbEKwAwAAsATBDgAAwBIEOwAAAEsQ7AAAACxBsAMAALAEwQ4AAMASBDsAAABLEOxQ4DVt2lQGDBiQp2N/+OEHCQkJke3bt5vnq1evNs+zLwQOAAUFZRzyU1i+fhrgA5988olZzPty3HbbbXLkyBGJjY3N9/MCgPxAGYf8RLBDgVe8ePHLfm9ERISUKVMmX88HAPITZRzyE02xCKhmikqVKslLL70kjz/+uBQtWlQqVKggb7/9dq7vzd5MMWvWLImLi5Nly5ZJjRo1pEiRItKqVStzx+vpnXfeMfujoqKkevXqMmXKFB9fJYBgRRmH/ESwQ8B57bXXpEGDBvL111/Lk08+KX369JGkpKQ8v//MmTMyYcIEee+992Tt2rVy4MABGTx4sHv/+++/LyNHjpQXX3xRdu/ebQrZESNGyOzZs310RQDw/1HG4UoQ7BBw2rRpYwq7G2+8UYYOHSolS5aUL774Is/vT09Pl2nTppmC85ZbbpF+/fpJYmKie/+oUaNMwdqxY0epXLmyeRw4cKBMnz7dR1cEAP8fZRyuBH3sEHDq1Knj/lqbILR/SUpKSp7fX7hwYalSpYr7edmyZd3vT01NlX379knPnj2lV69e7mMyMjLonAzgqqCMw5Ug2CHgZB89pgVfVlbWFb3f5XKZr0+fPm0eZ8yYIY0aNfI6rlChQldw1gCQN5RxuBIEO8BD6dKlpVy5cvL9999L165d/X06AJCvKOPsR7ADsnn++eflqaeeMs0SOprs7NmzsnXrVvntt99k0KBB/j49ALgilHF2I9gB2fzpT38yfVReffVVGTJkiMTExEjt2rXzPDM8ABRklHF2C3E5De8AAAAIaEx3AgAAYAmCHQAAgCUIdgAAAJYg2AEAAFiCYAcAAGAJgh0AAIAlCHYAAACWINgBAABYgmAHAABgCYIdAACAJQh2AAAAliDYAQAAiB3+H3QA/cU4rhHfAAAAAElFTkSuQmCC\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"<Figure size 640x480 with 2 Axes>\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"display_data\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"fig, ax = plt.subplots(1, 2, sharex=\\\\\\\\\\\\\\\"all\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[0].imshow(writer.live_mask[:].T, aspect=\\\\\\\\\\\\\\\"auto\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[1].imshow(reader[:, 150].T, aspect=\\\\\\\\\\\\\\\"auto\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[0].set_xlabel(\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[0].set_ylabel(\\\\\\\\\\\\\\\"crossline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[1].set_xlabel(\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[1].set_ylabel(\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[0].set_title(\\\\\\\\\\\\\\\"Live Mask\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ax[1].set_title(\\\\\\\\\\\\\\\"Middle Crossline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"fig.tight_layout();\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"## Write to SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"Because we populated all the fields necessary for SEG-Y output, we can call the\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"MDIO to SEGY converter and get a file out.\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 7,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:15.788812Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:15.009889Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stderr\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stdout\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"[[1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" ...\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]]\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stderr\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from segy import SegyFile\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import mdio_to_segy\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"mdio_to_segy(\\\\\\\\\\\\\\\"demo.mdio\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"demo.segy\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"segy = SegyFile(\\\\\\\\\\\\\\\"demo.segy\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"print(segy.binary_header)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"print(segy.sample[:100])\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"## Copying an Existing MDIO without Data and Headers\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"We also provide a `create_empty_like` function which allows us to create an MDIO file\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"with the same structure and basic metadata as an existing one.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"This will carry over:\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* All access patterns in source MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Grid (shape, coordinates, dimensions, etc)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Text Header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Binary Header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"It will **NOT** carry over:\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Trace data\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Header data\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Statistics\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"* Live Mask\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 8,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:17.246513Z\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:17.111779Z\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"from mdio import create_empty_like\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"copy_path = \\\\\\\\\\\\\\\"copy_of_existing.mdio\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"create_empty_like(create_conf.path, copy_path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"copy_reader = MDIOReader(copy_path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"assert copy_reader.shape == reader.shape\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"assert copy_reader.binary_header == reader.binary_header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"assert copy_reader.stats != reader.stats\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"source\\\\\\\": []\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  }\\\\n\\\",\\n\",\n",
+    "    \"    \\\" ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\" \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  \\\\\\\"kernelspec\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"display_name\\\\\\\": \\\\\\\"Python 3 (ipykernel)\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"name\\\\\\\": \\\\\\\"python3\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  \\\\\\\"language_info\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"codemirror_mode\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"name\\\\\\\": \\\\\\\"ipython\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"version\\\\\\\": 3\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"file_extension\\\\\\\": \\\\\\\".py\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"mimetype\\\\\\\": \\\\\\\"text/x-python\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"name\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"nbconvert_exporter\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"pygments_lexer\\\\\\\": \\\\\\\"ipython3\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"version\\\\\\\": \\\\\\\"3.12.3\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  \\\\\\\"widgets\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   \\\\\\\"application/vnd.jupyter.widget-state+json\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"104c0d4e90244ebc959e51a58794dcf4\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"display\\\\\\\": \\\\\\\"inline-flex\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"flex_flow\\\\\\\": \\\\\\\"row wrap\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"width\\\\\\\": \\\\\\\"100%\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"1c0f5b458ee1401eaa8de63c65802073\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"21b25dd6080d42368afc06770d5e1755\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_35fb49026dac479eba87217c2f6bcb9a\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"style\\\\\\\": \\\\\\\"IPY_MODEL_3ab3e27c83aa423d9ecdac94e576f0fe\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"value\\\\\\\": \\\\\\\"Ingesting SEG-Y in 6 chunks: 100%\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"2693aae410f04e7587f0400b5eef1079\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"ProgressStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"318aea09479a479981dcfa29bc856c67\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"ProgressStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"35fb49026dac479eba87217c2f6bcb9a\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"3ab3e27c83aa423d9ecdac94e576f0fe\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"420b4a9492c54eb48d7779f38a09fd20\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"flex\\\\\\\": \\\\\\\"2\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"42afe4fae9dd4bc4a341a231cf7a9c32\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"4df685a95de542ffab6f265df89b8949\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"58eaddb54c8840da83d1f6503d6ba64f\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"5b3e72b71f304230bc36bb91f9c173be\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"5c1fab0ccc7e42c69c2b663b67ca9e3c\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"63a54817ae8b4c8d85b30d8c97e7ed0d\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HBoxModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"children\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_e170d60a55a14c489d32b101293a9d33\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_662ad93cf7b3470f8e197350441f09ca\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_ac4abab2367e461e956e4e0edb27be44\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_c59d6fe969a04f4da332ae2a6fdb9c77\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"63f87a2410ba47d38ad9f55a81357a29\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
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+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HBoxModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"children\\\\\\\": [\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_db696e15587c4a54b82886b3eb5a0c96\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_a6aabcd2e57348a49bb59477f6a9fd90\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"        \\\\\\\"IPY_MODEL_b9810ee38bbe43f4bba100e53379be65\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       ],\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_eab4b060672b4dd5a73ca7bb8f782cd2\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"db696e15587c4a54b82886b3eb5a0c96\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_64eb2b9c8a094a1ea5f1991e5f09f5d9\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"style\\\\\\\": \\\\\\\"IPY_MODEL_5b3e72b71f304230bc36bb91f9c173be\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"value\\\\\\\": \\\\\\\"Step 1 / 2 Writing Blocks: 100%\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"e170d60a55a14c489d32b101293a9d33\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_9fe5348964cd4f7880bcd33204bbc7a2\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"style\\\\\\\": \\\\\\\"IPY_MODEL_4df685a95de542ffab6f265df89b8949\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"value\\\\\\\": \\\\\\\"Step 2 / 2 Concat Blocks: \\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"e66368cda8124001b16459a0634029e2\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"eab4b060672b4dd5a73ca7bb8f782cd2\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"display\\\\\\\": \\\\\\\"inline-flex\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"flex_flow\\\\\\\": \\\\\\\"row wrap\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"width\\\\\\\": \\\\\\\"100%\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"f65266f861cf40ef84e9ec74a8e0b44c\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_fff4199774534d9f982f03738fbb08e7\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"style\\\\\\\": \\\\\\\"IPY_MODEL_e66368cda8124001b16459a0634029e2\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"value\\\\\\\": \\\\\\\"Scanning SEG-Y for geometry attributes: 100%\\\\\\\"\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"fdcea609ee7349629604217b625371d3\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     \\\\\\\"fff4199774534d9f982f03738fbb08e7\\\\\\\": {\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
+    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
+    "    \"    \\\"     }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"version_major\\\\\\\": 2,\\\\n\\\",\\n\",\n",
+    "    \"    \\\"    \\\\\\\"version_minor\\\\\\\": 0\\\\n\\\",\\n\",\n",
+    "    \"    \\\"   }\\\\n\\\",\\n\",\n",
+    "    \"    \\\"  }\\\\n\\\",\\n\",\n",
+    "    \"    \\\" },\\\\n\\\",\\n\",\n",
+    "    \"    \\\" \\\\\\\"nbformat\\\\\\\": 4,\\\\n\\\",\\n\",\n",
+    "    \"    \\\" \\\\\\\"nbformat_minor\\\\\\\": 4\\\\n\\\",\\n\",\n",
+    "    \"    \\\"}\\\\n\\\"\\n\",\n",
     "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"## Updating File and Checking with `MDIOReader`.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We write traces here, the headers are still empty. If you need the headers\\\\n\\\",\\n\",\n",
-    "    \"    \\\"populated, this is where they would be written to file as well.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"All the extra metadata we are writing is so that we can export back to SEG-Y\\\\n\\\",\\n\",\n",
-    "    \"    \\\"in the future. If that's not a requirement most of the metadata can be\\\\n\\\",\\n\",\n",
-    "    \"    \\\"omitted.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"If you already have an MDIO prior to this, all the metadata can be copied\\\\n\\\",\\n\",\n",
-    "    \"    \\\"over from the previous version.\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 5,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:12.498287Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:11.670230Z\\\"\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    \\\"pycharm\\\": {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"#%%\\\\n\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"data\\\": {\\n\",\n",
-    "    \"      \\\"text/plain\\\": [\\n\",\n",
-    "    \"       \\\"({'data_sample_format': 1,\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'sample_interval': 4,\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'samples_per_trace': 750,\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'segy_revision_major': 1,\\\\n\\\",\\n\",\n",
-    "    \"       \\\"  'segy_revision_minor': 0},\\\\n\\\",\\n\",\n",
-    "    \"       \\\" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\\\"\\n\",\n",
-    "    \"      ]\\n\",\n",
-    "    \"     },\\n\",\n",
-    "    \"     \\\"execution_count\\\": 5,\\n\",\n",
-    "    \"     \\\"metadata\\\": {},\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"execute_result\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   ],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"sample_dim = writer.grid.select_dim(\\\\\\\"sample\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\\\n\\\",\\n\",\n",
-    "    \"    \\\"num_samples = sample_dim.size\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer.binary_header = {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"data_sample_format\\\\\\\": 1,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"sample_interval\\\\\\\": sample_interval,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"samples_per_trace\\\\\\\": num_samples,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"segy_revision_major\\\\\\\": 1,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"segy_revision_minor\\\\\\\": 0,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"# Write some values to the file\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer[:5] = 1\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer[5:10] = 2\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer[50:100] = 3\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer[150:175] = -1\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"# Write some made up stats\\\\n\\\",\\n\",\n",
-    "    \"    \\\"writer.stats = {\\\\\\\"mean\\\\\\\": 12, \\\\\\\"std\\\\\\\": 5, \\\\\\\"rms\\\\\\\": 3, \\\\\\\"min\\\\\\\": -4, \\\\\\\"max\\\\\\\": 4}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"reader = MDIOReader(create_conf.path)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"reader.binary_header, reader.stats\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"source\\\": \\\"Plot some of the data we populated:\\\"\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 6,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:14.256953Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:14.036094Z\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"data\\\": {\\n\",\n",
-    "    \"      \\\"image/png\\\": 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\\\",\\n\",\n",
-    "    \"      \\\"text/plain\\\": [\\n\",\n",
-    "    \"       \\\"<Figure size 640x480 with 2 Axes>\\\"\\n\",\n",
-    "    \"      ]\\n\",\n",
-    "    \"     },\\n\",\n",
-    "    \"     \\\"metadata\\\": {},\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"display_data\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   ],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"fig, ax = plt.subplots(1, 2, sharex=\\\\\\\"all\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[0].imshow(writer.live_mask[:].T, aspect=\\\\\\\"auto\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[1].imshow(reader[:, 150].T, aspect=\\\\\\\"auto\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[0].set_xlabel(\\\\\\\"inline\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[0].set_ylabel(\\\\\\\"crossline\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[1].set_xlabel(\\\\\\\"inline\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[1].set_ylabel(\\\\\\\"sample\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[0].set_title(\\\\\\\"Live Mask\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"ax[1].set_title(\\\\\\\"Middle Crossline\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"fig.tight_layout();\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"## Write to SEG-Y\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"Because we populated all the fields necessary for SEG-Y output, we can call the\\\\n\\\",\\n\",\n",
-    "    \"    \\\"MDIO to SEGY converter and get a file out.\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 7,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:15.788812Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:15.009889Z\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"stderr\\\",\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
-    "    \"     \\\"text\\\": [\\n\",\n",
-    "    \"      \\\"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\\\n\\\",\\n\",\n",
-    "    \"      \\\"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\\\"\\n\",\n",
-    "    \"     ]\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"stdout\\\",\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
-    "    \"     \\\"text\\\": [\\n\",\n",
-    "    \"      \\\"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\\\n\\\",\\n\",\n",
-    "    \"      \\\"[[1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
-    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
-    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
-    "    \"      \\\" ...\\\\n\\\",\\n\",\n",
-    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
-    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]\\\\n\\\",\\n\",\n",
-    "    \"      \\\" [1. 1. 1. ... 1. 1. 1.]]\\\\n\\\"\\n\",\n",
-    "    \"     ]\\n\",\n",
-    "    \"    },\\n\",\n",
-    "    \"    {\\n\",\n",
-    "    \"     \\\"name\\\": \\\"stderr\\\",\\n\",\n",
-    "    \"     \\\"output_type\\\": \\\"stream\\\",\\n\",\n",
-    "    \"     \\\"text\\\": [\\n\",\n",
-    "    \"      \\\"\\\\n\\\"\\n\",\n",
-    "    \"     ]\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   ],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"from segy import SegyFile\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"from mdio import mdio_to_segy\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"mdio_to_segy(\\\\\\\"demo.mdio\\\\\\\", \\\\\\\"demo.segy\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"segy = SegyFile(\\\\\\\"demo.segy\\\\\\\")\\\\n\\\",\\n\",\n",
-    "    \"    \\\"print(segy.binary_header)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"print(segy.sample[:100])\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"markdown\\\",\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"## Copying an Existing MDIO without Data and Headers\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"We also provide a `create_empty_like` function which allows us to create an MDIO file\\\\n\\\",\\n\",\n",
-    "    \"    \\\"with the same structure and basic metadata as an existing one.\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"This will carry over:\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* All access patterns in source MDIO\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Grid (shape, coordinates, dimensions, etc)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Text Header\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Binary Header\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"It will **NOT** carry over:\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Trace data\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Header data\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Statistics\\\\n\\\",\\n\",\n",
-    "    \"    \\\"* Live Mask\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": 8,\\n\",\n",
-    "    \"   \\\"metadata\\\": {\\n\",\n",
-    "    \"    \\\"ExecuteTime\\\": {\\n\",\n",
-    "    \"     \\\"end_time\\\": \\\"2025-04-16T14:50:17.246513Z\\\",\\n\",\n",
-    "    \"     \\\"start_time\\\": \\\"2025-04-16T14:50:17.111779Z\\\"\\n\",\n",
-    "    \"    }\\n\",\n",
-    "    \"   },\\n\",\n",
-    "    \"   \\\"outputs\\\": [],\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"from mdio import create_empty_like\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"copy_path = \\\\\\\"copy_of_existing.mdio\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"create_empty_like(create_conf.path, copy_path)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"copy_reader = MDIOReader(copy_path)\\\\n\\\",\\n\",\n",
-    "    \"    \\\"assert copy_reader.shape == reader.shape\\\\n\\\",\\n\",\n",
-    "    \"    \\\"assert copy_reader.binary_header == reader.binary_header\\\\n\\\",\\n\",\n",
-    "    \"    \\\"assert copy_reader.stats != reader.stats\\\"\\n\",\n",
-    "    \"   ]\\n\",\n",
-    "    \"  },\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"code\\\",\\n\",\n",
-    "    \"   \\\"execution_count\\\": null,\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"outputs\\\": [],\\n\",\n",
-    "    \"   \\\"source\\\": []\\n\",\n",
     "    \"  }\\n\",\n",
     "    \" ],\\n\",\n",
     "    \" \\\"metadata\\\": {\\n\",\n",

From 0e64e09d4e9aabb303aa3270c5caa174e82d916d Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 29 Apr 2025 16:10:07 -0500
Subject: [PATCH 10/56] Add basic unit test for v1 dataset schema validation

---
 tests/unit/test_schema.py | 54 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)
 create mode 100644 tests/unit/test_schema.py

diff --git a/tests/unit/test_schema.py b/tests/unit/test_schema.py
new file mode 100644
index 000000000..1bccde5a0
--- /dev/null
+++ b/tests/unit/test_schema.py
@@ -0,0 +1,54 @@
+"""Test the schema for the v1 dataset."""
+
+from mdio.schemas.v1 import Dataset as V1Dataset
+
+
+TEST_SCHEMA = {
+    "metadata": {
+        "name": "test_dataset",
+        "api_version": "1.0.0",
+        "created_on": "2023-01-01T00:00:00Z",
+    },
+    "variables": [
+        {
+            "name": "actual_variable",
+            "data_type": "float32",
+            "dimensions": ["dim0", "dim1"],
+            "compressor": {"name": "blosc", "level": 3},
+            "coordinates": ["coord"],
+            "metadata": {
+                "chunk_grid": {
+                    "name": "regular",
+                    "configuration": {"chunk_shape": [10, 20]},
+                },
+            },
+        },
+        {
+            "name": "coord",
+            "data_type": "float32",
+            "dimensions": ["dim0", "dim1"],
+            "metadata": {
+                "chunk_grid": {
+                    "name": "regular",
+                    "configuration": {"chunk_shape": [10, 20]},
+                },
+                "units_v1": {"length": "m"},
+            },
+        },
+        {
+            "name": "dim0",
+            "data_type": "int32",
+            "dimensions": [{"name": "dim0", "size": 100}],
+        },
+        {
+            "name": "dim1",
+            "data_type": "int32",
+            "dimensions": [{"name": "dim1", "size": 200}],
+        },
+    ],
+}
+
+
+def test_dataset_schema_validation():
+    """Test that the dataset schema validates correctly."""
+    V1Dataset.model_validate(TEST_SCHEMA)

From a1a312e41f7e79a98c04b1b5591a193fa5efa321 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Wed, 30 Apr 2025 09:56:44 -0500
Subject: [PATCH 11/56] update lockfile

---
 uv.lock | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/uv.lock b/uv.lock
index 92ce6cdc0..68edf47f8 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1890,7 +1890,7 @@ requires-dist = [
     { name = "segy", specifier = ">=0.4.0,<0.5.0" },
     { name = "tqdm", specifier = ">=4.67.0,<5.0.0" },
     { name = "xarray", specifier = ">=2025.3.1" },
-    { name = "zarr", specifier = ">=3.0.6,<4.0.0" },
+    { name = "zarr", specifier = ">=3.0.3,<3.0.7" },
     { name = "zfpy", marker = "extra == 'lossy'", specifier = ">=1.0.1,<2.0.0" },
 ]
 provides-extras = ["cloud", "distributed", "lossy"]

From dfe775198e0f0289eddf7e0c9fd94142f67762bf Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Wed, 7 May 2025 09:32:28 -0500
Subject: [PATCH 12/56] fix broken creation nb

---
 docs/tutorials/creation.ipynb | 2127 ++++++---------------------------
 1 file changed, 387 insertions(+), 1740 deletions(-)

diff --git a/docs/tutorials/creation.ipynb b/docs/tutorials/creation.ipynb
index 73ff5b67d..af4d3b65d 100644
--- a/docs/tutorials/creation.ipynb
+++ b/docs/tutorials/creation.ipynb
@@ -1,1749 +1,396 @@
 {
  "cells": [
   {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "# Create an Empty MDIO\n",
+    "\n",
+    "```{article-info}\n",
+    ":author: Altay Sansal\n",
+    ":date: \"{sub-ref}`today`\"\n",
+    ":read-time: \"{sub-ref}`wordcount-minutes` min read\"\n",
+    ":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\n",
+    "```\n",
+    "\n",
+    "Here we will create an empty MDIO file and populate its fields.\n",
+    "\n",
+    "```{warning}\n",
+    "For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\n",
+    "`pip install matplotlib` or `conda install matplotlib`.\n",
+    "```\n",
+    "\n",
+    "We first need to import the configuration classes and create function to be able to create the empty MDIO."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:04.371422Z",
+     "start_time": "2025-04-16T14:50:04.368107Z"
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from mdio import Dimension\n",
+    "from mdio import Grid\n",
+    "from mdio import MDIOCreateConfig\n",
+    "from mdio import MDIOReader\n",
+    "from mdio import MDIOVariableConfig\n",
+    "from mdio import MDIOWriter\n",
+    "from mdio import create_empty\n",
+    "from mdio.converters.segy import get_compressor\n",
+    "from mdio.segy.compat import mdio_segy_spec"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   },
+   "source": [
+    "## Setting Up Grid Dimensions and Variable(s)\n",
+    "\n",
+    "Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\n",
+    "dimensions. This is exactly like a 3D Post-Stack dataset.\n",
+    "\n",
+    "We will use the standard `chunked_012` access pattern. All variable names must start\n",
+    "with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\n",
+    "\n",
+    "We will also use an MDIO private utility function to get the compressor easily. The\n",
+    "compressor is fully customizable, but this function gives us ones available in SEG-Y\n",
+    "ingestion.\n",
+    "\n",
+    "If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\n",
+    "we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\n",
+    "\n",
+    "At the end we create empty MDIO on local disk or cloud, based on the path string."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:06.121450Z",
+     "start_time": "2025-04-16T14:50:06.002634Z"
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "grid = Grid(\n",
+    "    dims=[\n",
+    "        Dimension(name=\"inline\", coords=range(100, 300, 1)),  # 100-300 with step 1\n",
+    "        Dimension(name=\"crossline\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\n",
+    "        Dimension(name=\"sample\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "compressor = get_compressor(lossless=True)\n",
+    "header_dtype = mdio_segy_spec().trace.header.dtype\n",
+    "variable = MDIOVariableConfig(\n",
+    "    name=\"chunked_012\",\n",
+    "    dtype=\"float32\",\n",
+    "    chunks=(128, 128, 128),\n",
+    "    compressors=compressor,\n",
+    "    header_dtype=header_dtype,\n",
+    ")\n",
+    "\n",
+    "create_conf = MDIOCreateConfig(path=\"demo.mdio\", grid=grid, variables=[variable])\n",
+    "create_empty(config=create_conf);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Populating the MDIO\n",
+    "\n",
+    "Once empty MDIO is created, you can populate it with sample data, header data,\n",
+    "metadata, and statistics. The `live_mask` is automatically flipped to 1 after\n",
+    "every write. However, the consistency of the `live_mask` is up to the user. If\n",
+    "not populated correctly, at read time, traces may be skipped.\n",
+    "\n",
+    "We will read the usual stats and as you can see they're all empty. Text header\n",
+    "and binary header are only required if we are going to export this back to SEG-Y,\n",
+    "and can be modified. We can edit these if necessary using the writer."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:09.974442Z",
+     "start_time": "2025-04-16T14:50:09.951257Z"
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(['C00                                                                             ',\n",
+       "  'C01                                                                             ',\n",
+       "  'C02                                                                             ',\n",
+       "  'C03                                                                             ',\n",
+       "  'C04                                                                             '],\n",
+       " {},\n",
+       " {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "writer = MDIOWriter(create_conf.path)\n",
+    "\n",
+    "# Truncate text header for display\n",
+    "writer.text_header[:5], writer.binary_header, writer.stats"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Updating File and Checking with `MDIOReader`.\n",
+    "\n",
+    "We write traces here, the headers are still empty. If you need the headers\n",
+    "populated, this is where they would be written to file as well.\n",
+    "\n",
+    "All the extra metadata we are writing is so that we can export back to SEG-Y\n",
+    "in the future. If that's not a requirement most of the metadata can be\n",
+    "omitted.\n",
+    "\n",
+    "If you already have an MDIO prior to this, all the metadata can be copied\n",
+    "over from the previous version."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:12.498287Z",
+     "start_time": "2025-04-16T14:50:11.670230Z"
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "({'data_sample_format': 1,\n",
+       "  'sample_interval': 4,\n",
+       "  'samples_per_trace': 750,\n",
+       "  'segy_revision_major': 1,\n",
+       "  'segy_revision_minor': 0},\n",
+       " {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sample_dim = writer.grid.select_dim(\"sample\")\n",
+    "sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\n",
+    "num_samples = sample_dim.size\n",
+    "writer.binary_header = {\n",
+    "    \"data_sample_format\": 1,\n",
+    "    \"sample_interval\": sample_interval,\n",
+    "    \"samples_per_trace\": num_samples,\n",
+    "    \"segy_revision_major\": 1,\n",
+    "    \"segy_revision_minor\": 0,\n",
+    "}\n",
+    "\n",
+    "# Write some values to the file\n",
+    "writer[:5] = 1\n",
+    "writer[5:10] = 2\n",
+    "writer[50:100] = 3\n",
+    "writer[150:175] = -1\n",
+    "\n",
+    "# Write some made up stats\n",
+    "writer.stats = {\"mean\": 12, \"std\": 5, \"rms\": 3, \"min\": -4, \"max\": 4}\n",
+    "\n",
+    "reader = MDIOReader(create_conf.path)\n",
+    "reader.binary_header, reader.stats"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": "Plot some of the data we populated:"
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:14.256953Z",
+     "start_time": "2025-04-16T14:50:14.036094Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, sharex=\"all\")\n",
+    "ax[0].imshow(writer.live_mask[:].T, aspect=\"auto\")\n",
+    "ax[1].imshow(reader[:, 150].T, aspect=\"auto\")\n",
+    "\n",
+    "ax[0].set_xlabel(\"inline\")\n",
+    "ax[0].set_ylabel(\"crossline\")\n",
+    "ax[1].set_xlabel(\"inline\")\n",
+    "ax[1].set_ylabel(\"sample\")\n",
+    "ax[0].set_title(\"Live Mask\")\n",
+    "ax[1].set_title(\"Middle Crossline\")\n",
+    "fig.tight_layout();"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Write to SEG-Y\n",
+    "\n",
+    "Because we populated all the fields necessary for SEG-Y output, we can call the\n",
+    "MDIO to SEGY converter and get a file out."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:15.788812Z",
+     "start_time": "2025-04-16T14:50:15.009889Z"
+    }
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\n",
+      "Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\n",
+      "[[1. 1. 1. ... 1. 1. 1.]\n",
+      " [1. 1. 1. ... 1. 1. 1.]\n",
+      " [1. 1. 1. ... 1. 1. 1.]\n",
+      " ...\n",
+      " [1. 1. 1. ... 1. 1. 1.]\n",
+      " [1. 1. 1. ... 1. 1. 1.]\n",
+      " [1. 1. 1. ... 1. 1. 1.]]\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "from segy import SegyFile\n",
+    "\n",
+    "from mdio import mdio_to_segy\n",
+    "\n",
+    "mdio_to_segy(\"demo.mdio\", \"demo.segy\")\n",
+    "segy = SegyFile(\"demo.segy\")\n",
+    "print(segy.binary_header)\n",
+    "print(segy.sample[:100])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
    "metadata": {},
-   "cell_type": "raw",
    "source": [
-    "{\n",
-    " \"cells\": [\n",
-    "  {\n",
-    "   \"metadata\": {},\n",
-    "   \"cell_type\": \"raw\",\n",
-    "   \"source\": [\n",
-    "    \"{\\n\",\n",
-    "    \" \\\"cells\\\": [\\n\",\n",
-    "    \"  {\\n\",\n",
-    "    \"   \\\"metadata\\\": {},\\n\",\n",
-    "    \"   \\\"cell_type\\\": \\\"raw\\\",\\n\",\n",
-    "    \"   \\\"source\\\": [\\n\",\n",
-    "    \"    \\\"{\\\\n\\\",\\n\",\n",
-    "    \"    \\\" \\\\\\\"cells\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%% md\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"# Create an Empty MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"```{article-info}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\":author: Altay Sansal\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\":date: \\\\\\\\\\\\\\\"{sub-ref}`today`\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\":read-time: \\\\\\\\\\\\\\\"{sub-ref}`wordcount-minutes` min read\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\":class-container: sd-p-0 sd-outline-muted sd-rounded-3 sd-font-weight-light\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"```\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"Here we will create an empty MDIO file and populate its fields.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"```{warning}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"For plotting, the notebook requires [Matplotlib](https://matplotlib.org/) as a dependency. Please install it before executing using\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"`pip install matplotlib` or `conda install matplotlib`.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"```\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We first need to import the configuration classes and create function to be able to create the empty MDIO.\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 2,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:04.371422Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:04.368107Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"import matplotlib.pyplot as plt\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import Dimension\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import Grid\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import MDIOCreateConfig\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import MDIOReader\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import MDIOVariableConfig\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import MDIOWriter\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import create_empty\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio.converters.segy import get_compressor\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio.segy.compat import mdio_segy_spec\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%% md\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"## Setting Up Grid Dimensions and Variable(s)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"Let's try to create an MDIO file in 3D with known `inline`, `crossline`, and `sample`\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"dimensions. This is exactly like a 3D Post-Stack dataset.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We will use the standard `chunked_012` access pattern. All variable names must start\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"with `chunked_*` for `MDIOReader` to be able to open them with any access pattern.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We will also use an MDIO private utility function to get the compressor easily. The\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"compressor is fully customizable, but this function gives us ones available in SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ingestion.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"If we want headers, we can also provide `header_dtype` which is a Numpy `dtype`. Again,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"we will be using the standard one MDIO uses for ingesting SEG-Ys. (Similar to SEG-Y Rev1).\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"At the end we create empty MDIO on local disk or cloud, based on the path string.\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 3,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:06.121450Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:06.002634Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"grid = Grid(\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    dims=[\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\", coords=range(100, 300, 1)),  # 100-300 with step 1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"crossline\\\\\\\\\\\\\\\", coords=range(1000, 1600, 2)),  # 1000-1600 with step 2\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"        Dimension(name=\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\", coords=range(0, 3000, 4)),  # 0-3 seconds 4ms sample rate\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    ]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"compressor = get_compressor(lossless=True)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"header_dtype = mdio_segy_spec().trace.header.dtype\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"variable = MDIOVariableConfig(\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    name=\\\\\\\\\\\\\\\"chunked_012\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    dtype=\\\\\\\\\\\\\\\"float32\\\\\\\\\\\\\\\",\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    chunks=(128, 128, 128),\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    compressors=compressor,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    header_dtype=header_dtype,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"create_conf = MDIOCreateConfig(path=\\\\\\\\\\\\\\\"demo.mdio\\\\\\\\\\\\\\\", grid=grid, variables=[variable])\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"create_empty(config=create_conf);\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"## Populating the MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"Once empty MDIO is created, you can populate it with sample data, header data,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"metadata, and statistics. The `live_mask` is automatically flipped to 1 after\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"every write. However, the consistency of the `live_mask` is up to the user. If\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"not populated correctly, at read time, traces may be skipped.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We will read the usual stats and as you can see they're all empty. Text header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"and binary header are only required if we are going to export this back to SEG-Y,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"and can be modified. We can edit these if necessary using the writer.\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 4,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:09.974442Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:09.951257Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"(['C00                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'C01                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'C02                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'C03                                                                             ',\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'C04                                                                             '],\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\" {},\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\" {'rms': 0, 'min': 0, 'mean': 0, 'max': 0, 'std': 0})\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"execution_count\\\\\\\": 4,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"execute_result\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer = MDIOWriter(create_conf.path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"# Truncate text header for display\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer.text_header[:5], writer.binary_header, writer.stats\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"## Updating File and Checking with `MDIOReader`.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We write traces here, the headers are still empty. If you need the headers\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"populated, this is where they would be written to file as well.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"All the extra metadata we are writing is so that we can export back to SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"in the future. If that's not a requirement most of the metadata can be\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"omitted.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"If you already have an MDIO prior to this, all the metadata can be copied\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"over from the previous version.\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 5,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:12.498287Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:11.670230Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"pycharm\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"#%%\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"({'data_sample_format': 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'sample_interval': 4,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'samples_per_trace': 750,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'segy_revision_major': 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"  'segy_revision_minor': 0},\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\" {'rms': 3, 'min': -4, 'mean': 12, 'max': 4, 'std': 5})\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"execution_count\\\\\\\": 5,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"execute_result\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"sample_dim = writer.grid.select_dim(\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"sample_interval = int(sample_dim.coords[1] - sample_dim.coords[0])\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"num_samples = sample_dim.size\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer.binary_header = {\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"data_sample_format\\\\\\\\\\\\\\\": 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"sample_interval\\\\\\\\\\\\\\\": sample_interval,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"samples_per_trace\\\\\\\\\\\\\\\": num_samples,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"segy_revision_major\\\\\\\\\\\\\\\": 1,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"    \\\\\\\\\\\\\\\"segy_revision_minor\\\\\\\\\\\\\\\": 0,\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"# Write some values to the file\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer[:5] = 1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer[5:10] = 2\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer[50:100] = 3\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer[150:175] = -1\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"# Write some made up stats\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"writer.stats = {\\\\\\\\\\\\\\\"mean\\\\\\\\\\\\\\\": 12, \\\\\\\\\\\\\\\"std\\\\\\\\\\\\\\\": 5, \\\\\\\\\\\\\\\"rms\\\\\\\\\\\\\\\": 3, \\\\\\\\\\\\\\\"min\\\\\\\\\\\\\\\": -4, \\\\\\\\\\\\\\\"max\\\\\\\\\\\\\\\": 4}\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"reader = MDIOReader(create_conf.path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"reader.binary_header, reader.stats\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": \\\\\\\"Plot some of the data we populated:\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 6,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:14.256953Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:14.036094Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"data\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"image/png\\\\\\\": 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\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"text/plain\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"<Figure size 640x480 with 2 Axes>\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"display_data\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"fig, ax = plt.subplots(1, 2, sharex=\\\\\\\\\\\\\\\"all\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[0].imshow(writer.live_mask[:].T, aspect=\\\\\\\\\\\\\\\"auto\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[1].imshow(reader[:, 150].T, aspect=\\\\\\\\\\\\\\\"auto\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[0].set_xlabel(\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[0].set_ylabel(\\\\\\\\\\\\\\\"crossline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[1].set_xlabel(\\\\\\\\\\\\\\\"inline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[1].set_ylabel(\\\\\\\\\\\\\\\"sample\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[0].set_title(\\\\\\\\\\\\\\\"Live Mask\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ax[1].set_title(\\\\\\\\\\\\\\\"Middle Crossline\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"fig.tight_layout();\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"## Write to SEG-Y\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"Because we populated all the fields necessary for SEG-Y output, we can call the\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"MDIO to SEGY converter and get a file out.\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 7,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:15.788812Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:15.009889Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stderr\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"Unwrapping MDIO Blocks: 100%|██████████| 7/7 [00:00<00:00, 10.55it/s]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"Merging lines: 100%|██████████| 1/1 [00:00<00:00, 17.26it/s]\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stdout\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"[(0, 0, 0, 0, 0, 4, 4000, 750, 750, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0)]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"[[1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" ...\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\" [1. 1. 1. ... 1. 1. 1.]]\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"name\\\\\\\": \\\\\\\"stderr\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"output_type\\\\\\\": \\\\\\\"stream\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"text\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"\\\\\\\\n\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from segy import SegyFile\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import mdio_to_segy\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"mdio_to_segy(\\\\\\\\\\\\\\\"demo.mdio\\\\\\\\\\\\\\\", \\\\\\\\\\\\\\\"demo.segy\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"segy = SegyFile(\\\\\\\\\\\\\\\"demo.segy\\\\\\\\\\\\\\\")\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"print(segy.binary_header)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"print(segy.sample[:100])\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"markdown\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"## Copying an Existing MDIO without Data and Headers\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"We also provide a `create_empty_like` function which allows us to create an MDIO file\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"with the same structure and basic metadata as an existing one.\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"This will carry over:\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* All access patterns in source MDIO\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Grid (shape, coordinates, dimensions, etc)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Text Header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Binary Header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"It will **NOT** carry over:\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Trace data\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Header data\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Statistics\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"* Live Mask\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": 8,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"ExecuteTime\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"end_time\\\\\\\": \\\\\\\"2025-04-16T14:50:17.246513Z\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"start_time\\\\\\\": \\\\\\\"2025-04-16T14:50:17.111779Z\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"from mdio import create_empty_like\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"copy_path = \\\\\\\\\\\\\\\"copy_of_existing.mdio\\\\\\\\\\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"create_empty_like(create_conf.path, copy_path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"copy_reader = MDIOReader(copy_path)\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"assert copy_reader.shape == reader.shape\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"assert copy_reader.binary_header == reader.binary_header\\\\\\\\n\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"assert copy_reader.stats != reader.stats\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   ]\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"cell_type\\\\\\\": \\\\\\\"code\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"execution_count\\\\\\\": null,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"metadata\\\\\\\": {},\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"outputs\\\\\\\": [],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"source\\\\\\\": []\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  }\\\\n\\\",\\n\",\n",
-    "    \"    \\\" ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\" \\\\\\\"metadata\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  \\\\\\\"kernelspec\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"display_name\\\\\\\": \\\\\\\"Python 3 (ipykernel)\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"language\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"name\\\\\\\": \\\\\\\"python3\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  \\\\\\\"language_info\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"codemirror_mode\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"name\\\\\\\": \\\\\\\"ipython\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"version\\\\\\\": 3\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"file_extension\\\\\\\": \\\\\\\".py\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"mimetype\\\\\\\": \\\\\\\"text/x-python\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"name\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"nbconvert_exporter\\\\\\\": \\\\\\\"python\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"pygments_lexer\\\\\\\": \\\\\\\"ipython3\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"version\\\\\\\": \\\\\\\"3.12.3\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"  \\\\\\\"widgets\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"   \\\\\\\"application/vnd.jupyter.widget-state+json\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"    \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"104c0d4e90244ebc959e51a58794dcf4\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"display\\\\\\\": \\\\\\\"inline-flex\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"flex_flow\\\\\\\": \\\\\\\"row wrap\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"width\\\\\\\": \\\\\\\"100%\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"1c0f5b458ee1401eaa8de63c65802073\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"21b25dd6080d42368afc06770d5e1755\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_35fb49026dac479eba87217c2f6bcb9a\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"style\\\\\\\": \\\\\\\"IPY_MODEL_3ab3e27c83aa423d9ecdac94e576f0fe\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"value\\\\\\\": \\\\\\\"Ingesting SEG-Y in 6 chunks: 100%\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"2693aae410f04e7587f0400b5eef1079\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"ProgressStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"318aea09479a479981dcfa29bc856c67\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"ProgressStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"35fb49026dac479eba87217c2f6bcb9a\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"3ab3e27c83aa423d9ecdac94e576f0fe\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"420b4a9492c54eb48d7779f38a09fd20\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"flex\\\\\\\": \\\\\\\"2\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"42afe4fae9dd4bc4a341a231cf7a9c32\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"4df685a95de542ffab6f265df89b8949\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"58eaddb54c8840da83d1f6503d6ba64f\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"5b3e72b71f304230bc36bb91f9c173be\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HTMLStyleModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"description_width\\\\\\\": \\\\\\\"\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"font_size\\\\\\\": null,\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"text_color\\\\\\\": null\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"5c1fab0ccc7e42c69c2b663b67ca9e3c\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/base\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"LayoutModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {}\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"63a54817ae8b4c8d85b30d8c97e7ed0d\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_name\\\\\\\": \\\\\\\"HBoxModel\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"state\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"children\\\\\\\": [\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        \\\\\\\"IPY_MODEL_e170d60a55a14c489d32b101293a9d33\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        \\\\\\\"IPY_MODEL_662ad93cf7b3470f8e197350441f09ca\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"        \\\\\\\"IPY_MODEL_ac4abab2367e461e956e4e0edb27be44\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       ],\\\\n\\\",\\n\",\n",
-    "    \"    \\\"       \\\\\\\"layout\\\\\\\": \\\\\\\"IPY_MODEL_c59d6fe969a04f4da332ae2a6fdb9c77\\\\\\\"\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      }\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     },\\\\n\\\",\\n\",\n",
-    "    \"    \\\"     \\\\\\\"63f87a2410ba47d38ad9f55a81357a29\\\\\\\": {\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module\\\\\\\": \\\\\\\"@jupyter-widgets/controls\\\\\\\",\\\\n\\\",\\n\",\n",
-    "    \"    \\\"      \\\\\\\"model_module_version\\\\\\\": \\\\\\\"2.0.0\\\\\\\",\\\\n\\\",\\n\",\n",
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-    "       \"value\": \" 26/26 [00:01&lt;00:00, 18.92block/s]\"\n",
-    "      }\n",
-    "     },\n",
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-    "      \"model_name\": \"FloatProgressModel\",\n",
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-    "       \"bar_style\": \"success\",\n",
-    "       \"layout\": \"IPY_MODEL_d23d88490a1b4941b8ca228b7d4a39cb\",\n",
-    "       \"max\": 6,\n",
-    "       \"style\": \"IPY_MODEL_2693aae410f04e7587f0400b5eef1079\",\n",
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-    "     \"d565a20d37e84ed0a1195e9a90154960\": {\n",
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-    "      \"model_name\": \"HBoxModel\",\n",
-    "      \"state\": {\n",
-    "       \"children\": [\n",
-    "        \"IPY_MODEL_db696e15587c4a54b82886b3eb5a0c96\",\n",
-    "        \"IPY_MODEL_a6aabcd2e57348a49bb59477f6a9fd90\",\n",
-    "        \"IPY_MODEL_b9810ee38bbe43f4bba100e53379be65\"\n",
-    "       ],\n",
-    "       \"layout\": \"IPY_MODEL_eab4b060672b4dd5a73ca7bb8f782cd2\"\n",
-    "      }\n",
-    "     },\n",
-    "     \"db696e15587c4a54b82886b3eb5a0c96\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"HTMLModel\",\n",
-    "      \"state\": {\n",
-    "       \"layout\": \"IPY_MODEL_64eb2b9c8a094a1ea5f1991e5f09f5d9\",\n",
-    "       \"style\": \"IPY_MODEL_5b3e72b71f304230bc36bb91f9c173be\",\n",
-    "       \"value\": \"Step 1 / 2 Writing Blocks: 100%\"\n",
-    "      }\n",
-    "     },\n",
-    "     \"e170d60a55a14c489d32b101293a9d33\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"HTMLModel\",\n",
-    "      \"state\": {\n",
-    "       \"layout\": \"IPY_MODEL_9fe5348964cd4f7880bcd33204bbc7a2\",\n",
-    "       \"style\": \"IPY_MODEL_4df685a95de542ffab6f265df89b8949\",\n",
-    "       \"value\": \"Step 2 / 2 Concat Blocks: \"\n",
-    "      }\n",
-    "     },\n",
-    "     \"e66368cda8124001b16459a0634029e2\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"HTMLStyleModel\",\n",
-    "      \"state\": {\n",
-    "       \"description_width\": \"\",\n",
-    "       \"font_size\": null,\n",
-    "       \"text_color\": null\n",
-    "      }\n",
-    "     },\n",
-    "     \"eab4b060672b4dd5a73ca7bb8f782cd2\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/base\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"LayoutModel\",\n",
-    "      \"state\": {\n",
-    "       \"display\": \"inline-flex\",\n",
-    "       \"flex_flow\": \"row wrap\",\n",
-    "       \"width\": \"100%\"\n",
-    "      }\n",
-    "     },\n",
-    "     \"f65266f861cf40ef84e9ec74a8e0b44c\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"HTMLModel\",\n",
-    "      \"state\": {\n",
-    "       \"layout\": \"IPY_MODEL_fff4199774534d9f982f03738fbb08e7\",\n",
-    "       \"style\": \"IPY_MODEL_e66368cda8124001b16459a0634029e2\",\n",
-    "       \"value\": \"Scanning SEG-Y for geometry attributes: 100%\"\n",
-    "      }\n",
-    "     },\n",
-    "     \"fdcea609ee7349629604217b625371d3\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/controls\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"HTMLStyleModel\",\n",
-    "      \"state\": {\n",
-    "       \"description_width\": \"\",\n",
-    "       \"font_size\": null,\n",
-    "       \"text_color\": null\n",
-    "      }\n",
-    "     },\n",
-    "     \"fff4199774534d9f982f03738fbb08e7\": {\n",
-    "      \"model_module\": \"@jupyter-widgets/base\",\n",
-    "      \"model_module_version\": \"2.0.0\",\n",
-    "      \"model_name\": \"LayoutModel\",\n",
-    "      \"state\": {}\n",
-    "     }\n",
-    "    },\n",
-    "    \"version_major\": 2,\n",
-    "    \"version_minor\": 0\n",
-    "   }\n",
-    "  }\n",
-    " },\n",
-    " \"nbformat\": 4,\n",
-    " \"nbformat_minor\": 4\n",
-    "}\n"
+    "## Copying an Existing MDIO without Data and Headers\n",
+    "\n",
+    "We also provide a `create_empty_like` function which allows us to create an MDIO file\n",
+    "with the same structure and basic metadata as an existing one.\n",
+    "\n",
+    "This will carry over:\n",
+    "* All access patterns in source MDIO\n",
+    "* Grid (shape, coordinates, dimensions, etc)\n",
+    "* Text Header\n",
+    "* Binary Header\n",
+    "\n",
+    "It will **NOT** carry over:\n",
+    "* Trace data\n",
+    "* Header data\n",
+    "* Statistics\n",
+    "* Live Mask"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-04-16T14:50:17.246513Z",
+     "start_time": "2025-04-16T14:50:17.111779Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "from mdio import create_empty_like\n",
+    "\n",
+    "copy_path = \"copy_of_existing.mdio\"\n",
+    "create_empty_like(create_conf.path, copy_path)\n",
+    "\n",
+    "copy_reader = MDIOReader(copy_path)\n",
+    "assert copy_reader.shape == reader.shape\n",
+    "assert copy_reader.binary_header == reader.binary_header\n",
+    "assert copy_reader.stats != reader.stats"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

From f6b2c34487b912f8bbd21ba263a26efa2a652105 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Wed, 7 May 2025 09:34:33 -0500
Subject: [PATCH 13/56] update lockfile

---
 uv.lock | 291 ++++++--------------------------------------------------
 1 file changed, 28 insertions(+), 263 deletions(-)

diff --git a/uv.lock b/uv.lock
index 68edf47f8..f68944290 100644
--- a/uv.lock
+++ b/uv.lock
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@@ -1839,23 +1702,14 @@ lossy = [
 
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@@ -3571,18 +3357,6 @@ wheels = [
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From dbec58e9f5339ff5db71bc56351a7821c552a1bd Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Wed, 7 May 2025 09:37:45 -0500
Subject: [PATCH 14/56] lint v1 files

---
 src/mdio/schemas/__init__.py    |  1 -
 src/mdio/schemas/base.py        |  5 +----
 src/mdio/schemas/builder.py     |  2 --
 src/mdio/schemas/compressors.py |  4 +---
 src/mdio/schemas/dtype.py       |  4 +---
 src/mdio/schemas/v0/__init__.py |  1 -
 src/mdio/schemas/v0/dataset.py  | 12 +++---------
 src/mdio/schemas/v1/__init__.py |  1 -
 src/mdio/schemas/v1/stats.py    |  8 ++------
 src/mdio/schemas/v1/units.py    | 13 +++----------
 src/mdio/schemas/v1/variable.py |  4 +---
 tests/unit/test_schema.py       |  3 +--
 12 files changed, 13 insertions(+), 45 deletions(-)

diff --git a/src/mdio/schemas/__init__.py b/src/mdio/schemas/__init__.py
index 17ae4dd3f..8d9d8b86e 100644
--- a/src/mdio/schemas/__init__.py
+++ b/src/mdio/schemas/__init__.py
@@ -7,7 +7,6 @@
 from mdio.schemas.dtype import StructuredField
 from mdio.schemas.dtype import StructuredType
 
-
 __all__ = [
     "Blosc",
     "ZFP",
diff --git a/src/mdio/schemas/base.py b/src/mdio/schemas/base.py
index d4bdfd480..5684fa108 100644
--- a/src/mdio/schemas/base.py
+++ b/src/mdio/schemas/base.py
@@ -10,7 +10,6 @@
 from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import DataTypeModel
 
-
 JSON_SCHEMA_DIALECT = GenerateJsonSchema.schema_dialect
 
 
@@ -31,9 +30,7 @@ class BaseArray(DataTypeModel, CamelCaseStrictModel):
     dimensions: list[NamedDimension] | list[str] = Field(
         ..., description="List of Dimension collection or reference to dimension names."
     )
-    compressor: Blosc | ZFP | None = Field(
-        default=None, description="Compression settings."
-    )
+    compressor: Blosc | ZFP | None = Field(default=None, description="Compression settings.")
 
 
 class NamedArray(BaseArray):
diff --git a/src/mdio/schemas/builder.py b/src/mdio/schemas/builder.py
index 9a0e6cbbb..40908ff02 100644
--- a/src/mdio/schemas/builder.py
+++ b/src/mdio/schemas/builder.py
@@ -15,7 +15,6 @@ class VariableBuilder:
     """Dataset builder."""
 
     def __init__(self) -> None:
-        """Initialize the builder."""
         self.name = None
         self.long_name = None
         self.dtype = None
@@ -126,7 +125,6 @@ class DatasetBuilder:
     """Dataset builder."""
 
     def __init__(self) -> None:
-        """Initialize the builder."""
         self.variables = []
         self.name = None
         self.metadata = None
diff --git a/src/mdio/schemas/compressors.py b/src/mdio/schemas/compressors.py
index b550b98dd..e17948da2 100644
--- a/src/mdio/schemas/compressors.py
+++ b/src/mdio/schemas/compressors.py
@@ -154,6 +154,4 @@ def make_instance(self):  # noqa: ANN201
 class CompressorModel(CamelCaseStrictModel):
     """Model representing compressor configuration."""
 
-    compressor: Blosc | ZFP | None = Field(
-        default=None, description="Compression settings."
-    )
+    compressor: Blosc | ZFP | None = Field(default=None, description="Compression settings.")
diff --git a/src/mdio/schemas/dtype.py b/src/mdio/schemas/dtype.py
index 5c2427b00..af7f65820 100644
--- a/src/mdio/schemas/dtype.py
+++ b/src/mdio/schemas/dtype.py
@@ -50,6 +50,4 @@ class StructuredType(CamelCaseStrictModel):
 class DataTypeModel(CamelCaseStrictModel):
     """Structured array type with fields and total item size."""
 
-    data_type: ScalarType | StructuredType = Field(
-        ..., description="Type of the array."
-    )
+    data_type: ScalarType | StructuredType = Field(..., description="Type of the array.")
diff --git a/src/mdio/schemas/v0/__init__.py b/src/mdio/schemas/v0/__init__.py
index e74f484f1..9b9533049 100644
--- a/src/mdio/schemas/v0/__init__.py
+++ b/src/mdio/schemas/v0/__init__.py
@@ -2,5 +2,4 @@
 
 from mdio.schemas.v0.dataset import DatasetModelV0
 
-
 __all__ = ["DatasetModelV0"]
diff --git a/src/mdio/schemas/v0/dataset.py b/src/mdio/schemas/v0/dataset.py
index 58c3ae72b..50103736c 100644
--- a/src/mdio/schemas/v0/dataset.py
+++ b/src/mdio/schemas/v0/dataset.py
@@ -42,13 +42,9 @@ class DatasetMetadataModelV0(StrictModel):
     )
 
     # Statistical information
-    std: float | None = Field(
-        default=None, description="Standard deviation of the samples."
-    )
+    std: float | None = Field(default=None, description="Standard deviation of the samples.")
 
-    rms: float | None = Field(
-        default=None, description="Root mean squared value of the samples."
-    )
+    rms: float | None = Field(default=None, description="Root mean squared value of the samples.")
 
     min: float | None = Field(
         default=None,
@@ -60,9 +56,7 @@ class DatasetMetadataModelV0(StrictModel):
         description="Maximum value of the samples.",
     )
 
-    trace_count: int | None = Field(
-        default=None, description="Number of traces in the SEG-Y file."
-    )
+    trace_count: int | None = Field(default=None, description="Number of traces in the SEG-Y file.")
 
 
 class VariableModelV0(BaseArray):
diff --git a/src/mdio/schemas/v1/__init__.py b/src/mdio/schemas/v1/__init__.py
index 4f9bcdf36..fb98d55ec 100644
--- a/src/mdio/schemas/v1/__init__.py
+++ b/src/mdio/schemas/v1/__init__.py
@@ -2,5 +2,4 @@
 
 from mdio.schemas.v1.dataset import Dataset
 
-
 __all__ = ["Dataset"]
diff --git a/src/mdio/schemas/v1/stats.py b/src/mdio/schemas/v1/stats.py
index a8a319c02..29d50add8 100644
--- a/src/mdio/schemas/v1/stats.py
+++ b/src/mdio/schemas/v1/stats.py
@@ -41,12 +41,8 @@ class CenteredBinHistogram(BaseHistogram):
 class EdgeDefinedHistogram(BaseHistogram):
     """A class representing an edge-defined histogram."""
 
-    bin_edges: list[float | int] = Field(
-        ..., description="The left edges of the histogram bins."
-    )
-    bin_widths: list[float | int] = Field(
-        ..., description="The widths of the histogram bins."
-    )
+    bin_edges: list[float | int] = Field(..., description="The left edges of the histogram bins.")
+    bin_widths: list[float | int] = Field(..., description="The widths of the histogram bins.")
 
 
 Histogram: TypeAlias = CenteredBinHistogram | EdgeDefinedHistogram
diff --git a/src/mdio/schemas/v1/units.py b/src/mdio/schemas/v1/units.py
index dd46296c0..1913ff2ed 100644
--- a/src/mdio/schemas/v1/units.py
+++ b/src/mdio/schemas/v1/units.py
@@ -11,7 +11,6 @@
 from mdio.schemas.units import UnitEnum
 from mdio.schemas.units import create_unit_model
 
-
 ureg = UnitRegistry()
 ureg.default_format = "~C"  # compact, abbreviated (symbol).
 
@@ -30,9 +29,7 @@ class LengthUnitEnum(UnitEnum):
     MILE = ureg.mile
 
 
-LengthUnitModel = create_unit_model(
-    LengthUnitEnum, "LengthUnitModel", "length", __name__
-)
+LengthUnitModel = create_unit_model(LengthUnitEnum, "LengthUnitModel", "length", __name__)
 
 
 class TimeUnitEnum(UnitEnum):
@@ -58,9 +55,7 @@ class DensityUnitEnum(UnitEnum):
     POUNDS_PER_GAL = ureg.pounds / ureg.gallon
 
 
-DensityUnitModel = create_unit_model(
-    DensityUnitEnum, "DensityUnitModel", "density", __name__
-)
+DensityUnitModel = create_unit_model(DensityUnitEnum, "DensityUnitModel", "density", __name__)
 
 
 class SpeedUnitEnum(UnitEnum):
@@ -102,9 +97,7 @@ class VoltageUnitEnum(UnitEnum):
     VOLT = ureg.volt
 
 
-VoltageUnitModel = create_unit_model(
-    VoltageUnitEnum, "VoltageUnitModel", "voltage", __name__
-)
+VoltageUnitModel = create_unit_model(VoltageUnitEnum, "VoltageUnitModel", "voltage", __name__)
 
 
 # Composite model types
diff --git a/src/mdio/schemas/v1/variable.py b/src/mdio/schemas/v1/variable.py
index 22ad0bf33..519a89f42 100644
--- a/src/mdio/schemas/v1/variable.py
+++ b/src/mdio/schemas/v1/variable.py
@@ -50,6 +50,4 @@ class Variable(NamedArray):
         default=None,
         description="Coordinates of the MDIO variable dimensions.",
     )
-    metadata: VariableMetadata | None = Field(
-        default=None, description="Variable metadata."
-    )
+    metadata: VariableMetadata | None = Field(default=None, description="Variable metadata.")
diff --git a/tests/unit/test_schema.py b/tests/unit/test_schema.py
index 1bccde5a0..0b2a9f545 100644
--- a/tests/unit/test_schema.py
+++ b/tests/unit/test_schema.py
@@ -2,7 +2,6 @@
 
 from mdio.schemas.v1 import Dataset as V1Dataset
 
-
 TEST_SCHEMA = {
     "metadata": {
         "name": "test_dataset",
@@ -49,6 +48,6 @@
 }
 
 
-def test_dataset_schema_validation():
+def test_dataset_schema_validation() -> None:
     """Test that the dataset schema validates correctly."""
     V1Dataset.model_validate(TEST_SCHEMA)

From ecb69d6d2a9ef4a8695243afda69c07c13de5d51 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 27 May 2025 09:05:14 -0500
Subject: [PATCH 15/56] update lock file

---
 uv.lock | 1873 +++++++++++++++++++++++++++++--------------------------
 1 file changed, 1001 insertions(+), 872 deletions(-)

diff --git a/uv.lock b/uv.lock
index f68944290..de95c4e6f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -26,7 +26,7 @@ wheels = [
 
 [[package]]
 name = "aiobotocore"
-version = "2.21.1"
+version = "2.22.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
@@ -37,9 +37,9 @@ dependencies = [
     { name = "python-dateutil" },
     { name = "wrapt" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/d2/dc/f5f872fb01ce37c09525cedc7ecfad7002ffe2a8a23f77d7d2c234399b51/aiobotocore-2.21.1.tar.gz", hash = "sha256:010357f43004413e92a9d066bb0db1f241aeb29ffed306e9197061ffc94e6577", size = 108900 }
+sdist = { url = "https://files.pythonhosted.org/packages/9c/4c/113c4f5611103bba8e5252805fbee7944f5d9541addba9a96b091c0c4308/aiobotocore-2.22.0.tar.gz", hash = "sha256:11091477266b75c2b5d28421c1f2bc9a87d175d0b8619cb830805e7a113a170b", size = 110322 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/95/67/026598918f92145156f2feb7957f57daefda20375cc2ac1a0692a9b8010b/aiobotocore-2.21.1-py3-none-any.whl", hash = "sha256:bd7c49a6d6f8a3d9444b0a94417c8da13813b5c7eec1c4f0ec2db7e8ce8f23e7", size = 78313 },
+    { url = "https://files.pythonhosted.org/packages/00/8e/ffa5840cb7de19ada85bda1fae1ae22671a18992e9373f2e2df9db5389b5/aiobotocore-2.22.0-py3-none-any.whl", hash = "sha256:b4e6306f79df9d81daff1f9d63189a2dbee4b77ce3ab937304834e35eaaeeccf", size = 78930 },
 ]
 
 [[package]]
@@ -53,7 +53,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.11.15"
+version = "3.12.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -64,56 +64,59 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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-wheels = [
-    { url = "https://files.pythonhosted.org/packages/44/31/5c8552b13041decee3facbe4a8e6342e9227cc472d7835df7f148049550a/aiohttp-3.11.15-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:5bd37d615cd26d09321bd0168305f8508778712cf38aeffeed550274fb48a2ee", size = 708642 },
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+    { url = "https://files.pythonhosted.org/packages/4c/f6/0873a05563e5df29ccf35345a6ae0ac9e66588b41fdb7043a65848f03139/yarl-1.20.0-cp313-cp313t-musllinux_1_2_s390x.whl", hash = "sha256:3b60a86551669c23dc5445010534d2c5d8a4e012163218fc9114e857c0586fdd", size = 423792 },
+    { url = "https://files.pythonhosted.org/packages/9e/35/43fbbd082708fa42e923f314c24f8277a28483d219e049552e5007a9aaca/yarl-1.20.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:3e429857e341d5e8e15806118e0294f8073ba9c4580637e59ab7b238afca836f", size = 422242 },
+    { url = "https://files.pythonhosted.org/packages/ed/f7/f0f2500cf0c469beb2050b522c7815c575811627e6d3eb9ec7550ddd0bfe/yarl-1.20.0-cp313-cp313t-win32.whl", hash = "sha256:65a4053580fe88a63e8e4056b427224cd01edfb5f951498bfefca4052f0ce0ac", size = 93816 },
+    { url = "https://files.pythonhosted.org/packages/3f/93/f73b61353b2a699d489e782c3f5998b59f974ec3156a2050a52dfd7e8946/yarl-1.20.0-cp313-cp313t-win_amd64.whl", hash = "sha256:53b2da3a6ca0a541c1ae799c349788d480e5144cac47dba0266c7cb6c76151fe", size = 101093 },
+    { url = "https://files.pythonhosted.org/packages/ea/1f/70c57b3d7278e94ed22d85e09685d3f0a38ebdd8c5c73b65ba4c0d0fe002/yarl-1.20.0-py3-none-any.whl", hash = "sha256:5d0fe6af927a47a230f31e6004621fd0959eaa915fc62acfafa67ff7229a3124", size = 46124 },
 ]
 
 [[package]]
 name = "zarr"
-version = "3.0.6"
+version = "3.0.8"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "donfig" },
@@ -3825,9 +3954,9 @@ dependencies = [
     { name = "packaging" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/6f/bf/2820e8ad5f086ea5cd4c4d65eb5e0113f98145ddf5810cec1c75fb10fb98/zarr-3.0.6.tar.gz", hash = "sha256:6ef23c740e34917a2a1099471361537732942e49f0cabe95c9b7124cd0d6d84f", size = 240812 }
+sdist = { url = "https://files.pythonhosted.org/packages/52/60/9652fd0536fbaca8d08cbc1a5572c52e0ce01773297df75da8bb47e45907/zarr-3.0.8.tar.gz", hash = "sha256:88505d095af899a88ae8ac4db02f4650ef0801d2ff6f65b6d1f0a45dcf760a6d", size = 256825 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/fb/38/56a1c129577d20dc975a934ccc3f7f16276eab04ff0ffbe02ea348407a37/zarr-3.0.6-py3-none-any.whl", hash = "sha256:dba078726b6e4defb0ae6a852b7e7035ce163d89d485961681ece49191dcce82", size = 196357 },
+    { url = "https://files.pythonhosted.org/packages/00/3b/e20bdf84088c11f2c396d034506cbffadd53e024111c1aa4585c2aba1523/zarr-3.0.8-py3-none-any.whl", hash = "sha256:7f81e7aec086437d98882aa432209107114bd7f3a9f4958b2af9c6b5928a70a7", size = 205364 },
 ]
 
 [[package]]
@@ -3863,9 +3992,9 @@ wheels = [
 
 [[package]]
 name = "zipp"
-version = "3.21.0"
+version = "3.22.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/3f/50/bad581df71744867e9468ebd0bcd6505de3b275e06f202c2cb016e3ff56f/zipp-3.21.0.tar.gz", hash = "sha256:2c9958f6430a2040341a52eb608ed6dd93ef4392e02ffe219417c1b28b5dd1f4", size = 24545 }
+sdist = { url = "https://files.pythonhosted.org/packages/12/b6/7b3d16792fdf94f146bed92be90b4eb4563569eca91513c8609aebf0c167/zipp-3.22.0.tar.gz", hash = "sha256:dd2f28c3ce4bc67507bfd3781d21b7bb2be31103b51a4553ad7d90b84e57ace5", size = 25257 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl", hash = "sha256:ac1bbe05fd2991f160ebce24ffbac5f6d11d83dc90891255885223d42b3cd931", size = 9630 },
+    { url = "https://files.pythonhosted.org/packages/ad/da/f64669af4cae46f17b90798a827519ce3737d31dbafad65d391e49643dc4/zipp-3.22.0-py3-none-any.whl", hash = "sha256:fe208f65f2aca48b81f9e6fd8cf7b8b32c26375266b009b413d45306b6148343", size = 9796 },
 ]

From 9dd9fbc88cadd4e23a0ddfd6cc1689db8aa26c17 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Tue, 24 Jun 2025 20:17:55 +0000
Subject: [PATCH 16/56] schema_v1-dataset_builder-add_dimension

---
 .devcontainer/Dockerfile.cli                  |  47 +++
 .devcontainer/Dockerfile.dev                  |  61 ++++
 .devcontainer/Dockerfile.nox                  |  49 +++
 .devcontainer/devcontainer.json               |  19 +-
 DEVELOPER_NOTES.md                            | 107 ++++++
 src/mdio/schemas/v1/dataset_builder.py        | 195 +++++++++++
 tests/unit/v1/__init__.py                     |   1 +
 .../v1/test_dataset_builder_add_dimension.py  | 307 ++++++++++++++++++
 .../unit/v1/test_dataset_builder_internals.py | 208 ++++++++++++
 tests/unit/v1/test_dataset_builder_state.py   |  88 +++++
 10 files changed, 1073 insertions(+), 9 deletions(-)
 create mode 100644 .devcontainer/Dockerfile.cli
 create mode 100644 .devcontainer/Dockerfile.dev
 create mode 100644 .devcontainer/Dockerfile.nox
 create mode 100644 DEVELOPER_NOTES.md
 create mode 100644 src/mdio/schemas/v1/dataset_builder.py
 create mode 100644 tests/unit/v1/__init__.py
 create mode 100644 tests/unit/v1/test_dataset_builder_add_dimension.py
 create mode 100644 tests/unit/v1/test_dataset_builder_internals.py
 create mode 100644 tests/unit/v1/test_dataset_builder_state.py

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
new file mode 100644
index 000000000..92720e34e
--- /dev/null
+++ b/.devcontainer/Dockerfile.cli
@@ -0,0 +1,47 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# * Clone mdio-python and build a Docker image:
+#      git clone https://github.com/TGSAI/mdio-python.git
+#      cd mdio-python
+#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
+# * Run /bin/bash in the Docker container:
+#
+#
+# USAGE:
+#  docker run -it --rm --name mdio-cli mdio-cli --version
+#  docker run -it --rm --name mdio-cli mdio-cli --help
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy import \
+#     /DATA/segy_file.segy \
+#     /DATA/mdio_file.mdio \
+#     -loc 181,185 \
+#     -names inline,crossline
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy export \
+#     /DATA/mdio_file.mdio \
+#     /DATA/segy_file_copy.segy
+#
+FROM python:3.13-bookworm
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
+
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install .
+
+ENTRYPOINT ["mdio"]
+CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
new file mode 100644
index 000000000..05f135799
--- /dev/null
+++ b/.devcontainer/Dockerfile.dev
@@ -0,0 +1,61 @@
+# USAGE: 
+#   This file will be used by the VS Code DevContainer extension 
+#   to create a development environment for the mdio-python project.
+# HOW TO RUN TESTS
+#    1. Open the project in VS Code.
+#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
+#    3. Once the container is running, open a terminal in VS Code.
+#    4. Run the tests using the command: `nox -s test`.
+# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
+#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
+#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
+# NOTES: 
+#  1. The container will be run as the non-root user 'vscode' with UID 1000.
+#  2. The virtual environment will be setup at /home/vscode/venv 
+#  3. The project source code will be mounted at /workspaces/mdio-python
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
+
+# Install git for nox pre-commit
+RUN apt-get update \
+  && apt-get install -y --no-install-recommends \
+    git \
+  && rm -rf /var/lib/apt/lists/*
+
+ENV USERNAME="vscode"
+USER $USERNAME
+
+# # Add path to the user-installed packages
+# ENV PYTHONUSERBASE=/home/$USERNAME/.local
+# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
+
+WORKDIR /workspaces/mdio-python
+
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+# Initialize virtual environement in the container
+ENV VIRTUAL_ENV="/home/$USERNAME/venv"
+RUN python3 -m venv $VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+
+# installing pytest is required for VS Code Python Testing
+RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
+
+# Install the project in editable mode
+# This allows for live reloading of the code during development
+RUN pip install -e .
+
+# RUN uv pip install snakeviz
+
+
+
+
+
+
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
new file mode 100644
index 000000000..103673fd2
--- /dev/null
+++ b/.devcontainer/Dockerfile.nox
@@ -0,0 +1,49 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# 1. Make sure you have Docker installed and running.
+# 2. Clone mdio-python and build the Docker image:
+#    git clone https://github.com/TGSAI/mdio-python.git
+#    cd mdio-python
+#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
+# 3. Run /bin/bash in the Docker container :
+#    LOCAL_DATA_DIR=$(pwd); \
+#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
+#
+# USAGE:
+#   docker run -it --rm mdio-nox --list
+#   docker run -it --rm mdio-nox -s tests-3.13
+#   docker run -it --rm mdio-nox --no-stop-on-first-error
+#
+# NOTE: nox will fail if run in the directory mounted from the host machine
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
+ARG PYTHON_VERSION
+ARG LINUX_DISTRO
+RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install .
+
+# Install UV dependency manager and Nox test automator
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+ENTRYPOINT ["nox"]
+CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index b618a5260..ea5dc99ef 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile",
+    "dockerfile": "Dockerfile.dev",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    "post_create_script": "bash ./.devcontainer/post-install.sh"
+    // "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,8 +16,9 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-        "python.terminal.activateEnvInCurrentTerminal": true,
-        "python.defaultInterpreterPath": "/opt/venv/bin/python"
+      "python.testing.pytestArgs": ["tests"], 
+          "python.testing.unittestEnabled": false,
+          "python.testing.pytestEnabled": true
       },
       "extensions": [
         "ms-python.python",
@@ -27,17 +28,17 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker"
+        "streetsidesoftware.code-spell-checker",
+        "eamodio.gitlens"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
+  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
+  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // Re-use local Git configuration
-    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
+    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
   ]
 }
diff --git a/DEVELOPER_NOTES.md b/DEVELOPER_NOTES.md
new file mode 100644
index 000000000..7dcda95de
--- /dev/null
+++ b/DEVELOPER_NOTES.md
@@ -0,0 +1,107 @@
+# Developer Notes
+What are the goals for MDIO v1:
+
+## Overall API design and implementation
+1. Do we want to have a strongly-typed (see pydantic) or dynamic-typed (see dictionary args) API?  
+  For example
+```Python
+    # Strongly typed
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata=[
+            AllUnits(units_v1=LengthUnitModel(
+                length=LengthUnitEnum.FOOT)),
+            UserAttributes(
+                attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(
+                        chunk_shape=[20]))),
+            StatisticsMetadata(stats_v1=SummaryStatistics(
+                count=100,
+                sum=1215.1,
+                sumSquares=125.12,
+                min=5.61,
+                max=10.84,
+                histogram=CenteredBinHistogram(
+                    binCenters=[1, 2], 
+                    counts=[10, 15])))
+        ]
+    )
+
+    # dynamically-typed
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={
+            "unitsV1": {"length": "m"},
+            "attributes": {"MGA": 51},
+            "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
+            "statsV1": {
+                "count": 100,
+                "sum": 1215.1,
+                "sumSquares": 125.12,
+                "min": 5.61,
+                "max": 10.84,
+                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
+            },
+        },
+    )
+```
+2. How extensive the handling of the edge cases and the invalid arguments should be? This affects the ammount of validation code that needs to be written    
+   For example,
+    * Should we validate in the code that the units list contain a single item for the dimensions units    
+      or should we expect the developer to always pass a single-item list?
+    * Should we test the statistics for count > 0 or dim(binCenter) == dim(count) in the case above?
+
+## V1 Schema questions
+1. Why do we allow default / empty names?
+2. Adding a dimension with the same name multiple times: is it allowed or should it raise an error?
+   * It is currently allowed: the second request is ignored
+   * Adding a dimension with the same name, but the different size currently throws an error
+3. Why do we allow methods with dictionary parameters (non-strongly-typed)?
+4. For the add_dimension():
+   * Can AllUnits / UserAttributes / ChunkGridMetadata / StatisticsMetadata be repeated in the metadata list?
+   * For units, chunkGrid, statsV1 dict should we validate structure of the data passed in?
+   * Do we validate the unit string supplied in dictionary parameters? What what if someone supplies ftUS instead of ft?
+   * Are multiple dimension attributes allowed (I assume yes)?
+5. It is not clear, how RectilinearChunkGrid can be mapped to a single dimension
+   ```RectilinearChunkGrid(configuration=RectilinearChunkShape(chunk_shape=[[2,3,4],[2,3,4]]))```
+6. StatisticsMetadata accepts list[SummaryStatistics]. what does this mean and does it need to be tested?
+7. The pydentic attribute names are different from the v1 schema attributes names.
+    'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
+    Tgus, we will pass `units_v1` if we use the typesafe API and `'unitsV1` if we use dictionary API
+8. Can we add two variables with the same name?
+9. Why histogram (e.g., SummaryStatistics) does not have a `histogram_type` attribute?
+10. Why 'ftUS' is not supported by the schema?
+    Units: what foot does the MDIO uses: the U.S. survey foot or the International Foot?
+    The U.S. survey foot is defined as 1200/3937 meters, while the international foot is defined as exactly 0.3048 meters.
+    https://www.axiomint.com/survey-foot-versus-international-foot-whats-the-difference/ 
+    "The REAL issue is when ... applied to State Plane coordinates in the N2,000,000 and E6,000,000 range! 
+    This ... moves a State Plane coordinate position 4 feet by 12 feet.
+
+## Unclear
+* Did we have a notion of the fixed increment for inline & xline annotations?
+* How is rotation of East/North axes relatively to inline/xline axes is handled
+* How is right-handed and left-handed surveys are handled? 
+* add_variable - should dimensions argument be required??
+  
+(src/mdio/schemas/v1/dataset_builder.py)
+## Design suggestions
+1. Instead of trying to track the state, should we just return a wrapper/pimpl class with the permitted methods?
+2. Should we rename add_dimension to add_dimension_variable / add_dimension_annotation to indicate that we not just 
+   providing the dimension name, but also creating the dimension variable
+4. add_variable - should we call it `append_variable`. add implies that either name or index must be provided.
+
+## Under constructions
+* TODO: ??? refactor _BuilderState to make inner class ???
+* TODO: Need an example of EdgeDefinedHistogram for add_dimension with histogram
+
+## Bugs
+1. I assume we do not want attribute.attribute in the contract (see docs\tutorials\builder.ipynb)
+   'metadata': {'unitsV1': {'length': 'm'}, 'attributes': {'attributes': {'MGA': 51}}}
+
+https://osdu.pages.opengroup.org/platform/domain-data-mgmt-services/seismic/open-vds/vds/specification/Metadata.html
\ No newline at end of file
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
new file mode 100644
index 000000000..ea431e4c3
--- /dev/null
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -0,0 +1,195 @@
+"""Builder pattern implementation for MDIO v1 schema models."""
+
+from collections.abc import Mapping
+from datetime import UTC
+from datetime import datetime
+from enum import Enum
+from enum import auto
+from typing import Any
+
+from pydantic import BaseModel
+from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
+
+from mdio.schemas.compressors import ZFP
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import ScalarType, StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.stats import StatisticsMetadata, SummaryStatistics
+from mdio.schemas.v1.units import AllUnitModel, AllUnits
+from mdio.schemas.v1.variable import Coordinate, Variable, VariableMetadata
+
+# TODO: Why do we allow default names?
+# TODO: Instead of trying to track the state, should we just return a wrapper class with permitted methods?
+# TODO: refactor to make inner class
+class _BuilderState(Enum):
+    """States for the template builder."""
+
+    INITIAL = auto()
+    HAS_DIMENSIONS = auto()
+    HAS_COORDINATES = auto()
+    HAS_VARIABLES = auto()
+
+def contains_dimension(dimensions: list[NamedDimension], name_or_NamedDimension: str | NamedDimension) -> bool:
+    """Check if a dimension with the given name exists in the list."""
+    if isinstance(name_or_NamedDimension, str):
+        name = name_or_NamedDimension
+        return get_dimension(dimensions, name) is not None
+    elif isinstance(name_or_NamedDimension, NamedDimension):
+        named_dimension = name_or_NamedDimension
+        return get_dimension(dimensions, named_dimension.name, named_dimension.size) is not None
+    else:
+        msg = f"Expected str or NamedDimension, got {type(name_or_NamedDimension).__name__}"
+        raise TypeError(msg)
+
+def get_dimension(dimensions: list[NamedDimension], name: str, size: int | None = None) -> NamedDimension | None:
+    """Get a dimension by name from the list."""
+    if dimensions is None:
+        return False
+    if not isinstance(name, str):
+        raise TypeError(f"Expected str, got {type(name).__name__}")
+
+    nd = next((dim for dim in dimensions if dim.name == name), None)
+    if nd is None:
+        return None
+    if size is not None and nd.size != size:
+        msg = f"Dimension {name!r} found but size {nd.size} does not match expected size {size}"
+        raise ValueError(msg)
+    return nd
+
+def to_dictionary(val: BaseModel) -> dict[str, Any]:
+    """Convert a pydantic BaseModel to a dictionary."""
+    if not isinstance(val, BaseModel):
+        raise TypeError(f"Expected BaseModel, got {type(val).__name__}")
+    return val.model_dump(mode="json", by_alias=True) 
+
+class MDIODatasetBuilder:
+    """Builder for creating MDIO datasets with enforced build order.
+
+    This builder implements the builder pattern to create MDIO datasets with a v1 schema.
+    It enforces a specific build order to ensure valid dataset construction:
+    1. Must add dimensions first via add_dimension()
+    2. Can optionally add coordinates via add_coordinate()
+    3. Must add variables via add_variable()
+    4. Must call build() to create the dataset.
+    """
+
+    def __init__(self, name: str, attributes: dict[str, Any] | None = None):
+        self.name = name
+        self.api_version = "1.0.0"  # TODO(BrianMichell, #0): Pull from package metadata
+        self.created_on = datetime.now(UTC)
+        self.attributes = attributes
+        self._dimensions: list[NamedDimension] = []
+        self._coordinates: list[Coordinate] = []
+        self._variables: list[Variable] = []
+        self._state = _BuilderState.INITIAL
+        self._unnamed_variable_counter = 0
+
+
+    def _add_named_dimensions(self, dimensions: list[NamedDimension | str] | None) -> list[NamedDimension]:
+        if dimensions is None:
+            return []
+
+        added_dims = []
+        for dim in dimensions:
+            if isinstance(dim, str):
+                if not contains_dimension(self._dimensions, dim):
+                    raise ValueError(f"Dimension named {dim!r} is not found")
+            else:
+                if not isinstance(dim, NamedDimension):
+                    raise TypeError(f"Expected NamedDimension or str, got {type(dim).__name__}")
+                if  contains_dimension(self._dimensions, dim):
+                    continue
+                self._dimensions.append(dim)
+                added_dims.append(dim)
+        return added_dims
+
+
+    def _make_VariableMetadata_from_list(metadata: list[AllUnits | UserAttributes]) -> Any:
+        metadata_dict = {}
+        for md in metadata:
+            # NOTE: the pydentic attribute names are different from the v1 schema attributes names
+            #       'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
+            if isinstance(md, AllUnits):
+                val = md.units_v1
+                metadata_dict["unitsV1"] = to_dictionary(val)
+            elif isinstance(md, UserAttributes):
+                # NOTE: md.attributes is not pydantic type, but a dictionary
+                metadata_dict["attributes"] = to_dictionary(md)["attributes"]
+            elif isinstance(md, ChunkGridMetadata):
+                val = md.chunk_grid
+                metadata_dict["chunkGrid"] = to_dictionary(val)
+            elif isinstance(md, StatisticsMetadata):
+                val = md.stats_v1
+                metadata_dict["statsV1"] = to_dictionary(val)
+            else:
+                raise TypeError(f"Unsupported metadata type: {type(md)}")
+        return VariableMetadata(**metadata_dict)
+
+
+    def _make_VariableMetadata_from_dict(metadata: dict[str, Any]) -> type[BaseModel]:
+        converted_dict = {}
+        for key, value in metadata.items():
+            if key == "unitsV1" or key == "statsV1" or key == "chunkGrid" or key == "attributes":
+                # TODO: Should we validate the structure of the value passed in?
+                if not isinstance(value, dict):
+                    raise TypeError(f"Invalid value for key '{key}': {value!r}. Expected a dictionary.")
+            else:
+                raise TypeError(f"Unsupported metadata key: '{key}'. Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1.")
+            converted_dict[key] = value
+        return VariableMetadata(**converted_dict)
+
+
+    def _make_VariableMetadata(metadata: list[AllUnits | UserAttributes] | dict[str, Any] | None = None) -> Any | None:
+        if metadata is None:
+            return None
+        
+        if isinstance(metadata, list):
+            return MDIODatasetBuilder._make_VariableMetadata_from_list(metadata)
+        
+        if isinstance(metadata, dict):
+            return MDIODatasetBuilder._make_VariableMetadata_from_dict(metadata)
+
+        raise TypeError(f"Unsupported metadata type: {type(metadata)}")
+
+
+    def add_dimension(  # noqa: PLR0913
+        self,
+        name: str,
+        size: int,
+        long_name: str = None,
+        data_type: ScalarType | StructuredType = ScalarType.INT32,
+        metadata: list[AllUnits | UserAttributes] | None | dict[str, Any] = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a dimension.
+
+        This must be called at least once before adding coordinates or variables.
+
+        Args:
+            name: Name of the dimension
+            size: Size of the dimension
+            long_name: Optional long name for the dimension variable
+            data_type: Data type for the dimension variable (defaults to INT32)
+            metadata: Optional metadata for the dimension variable
+
+        Returns:
+            self: Returns self for method chaining
+        """
+
+        added_dims = self._add_named_dimensions([NamedDimension(name=name, size=size)])
+        if added_dims:
+            # Create a variable for the dimension
+            dim_var = Variable(
+                name=name,
+                longName=long_name,
+                dimensions=added_dims,
+                dataType=data_type,
+                compressor=None,
+                coordinates=None,
+                metadata=MDIODatasetBuilder._make_VariableMetadata(metadata)
+            )
+            self._variables.append(dim_var)
+
+        self._state = _BuilderState.HAS_DIMENSIONS
+        return self
diff --git a/tests/unit/v1/__init__.py b/tests/unit/v1/__init__.py
new file mode 100644
index 000000000..3db3a8e50
--- /dev/null
+++ b/tests/unit/v1/__init__.py
@@ -0,0 +1 @@
+"""Unit tests for parts of the MDIO package related to the v1 schema"""
\ No newline at end of file
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
new file mode 100644
index 000000000..bac9a8383
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -0,0 +1,307 @@
+
+import pytest
+
+from datetime import datetime
+
+from mdio.schemas.chunk_grid import RectilinearChunkGrid, RectilinearChunkShape, RegularChunkGrid, RegularChunkShape
+from mdio.schemas.dtype import ScalarType, StructuredType
+
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension, get_dimension, _BuilderState
+from mdio.schemas.v1.stats import CenteredBinHistogram, Histogram, StatisticsMetadata, SummaryStatistics
+from mdio.schemas.v1.units import AllUnits, LengthUnitEnum, LengthUnitModel
+
+def test_add_dimension() -> None:
+    """Test adding a dimension to the dataset builder."""
+    builder = MDIODatasetBuilder("Test Dataset Builder")
+
+    builder.add_dimension(name="inline", size=2, long_name="Inline dimension")
+    assert len(builder._dimensions) == 1
+    assert builder._dimensions[0] == NamedDimension(name="inline", size=2)  
+    assert len(builder._variables) == 1
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+
+
+def test_add_dimension() -> None:
+    """Test dimension builder state transitions and functionality."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # First dimension should change state to HAS_DIMENSIONS and create a variable
+    builder.add_dimension("x", 100, long_name="X Dimension")
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+    assert len(builder._dimensions) == 1  # noqa: PLR2004
+    assert len(builder._variables) == 1  # noqa: PLR2004
+    assert builder._dimensions[0].name == "x"
+    assert builder._dimensions[0].size == 100  # noqa: PLR2004
+    var0 = builder._variables[0]
+    assert var0.name == "x"
+    assert var0.long_name == "X Dimension"
+    assert var0.data_type == ScalarType.INT32
+    assert var0.dimensions[0].name == "x"
+
+    # Adding another dimension should maintain state and create another variable
+    builder.add_dimension("y", 200, data_type=ScalarType.UINT32)
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+    assert len(builder._dimensions) == 2  # noqa: PLR2004
+    assert len(builder._variables) == 2  # noqa: PLR2004
+    assert builder._dimensions[1].name == "y"
+    assert builder._dimensions[1].size == 200  # noqa: PLR2004
+    var1 = builder._variables[1]
+    assert var1.name == "y"
+    assert var1.data_type == ScalarType.UINT32
+    assert var1.dimensions[0].name == "y"
+
+    # TODO: Adding a dimension with the same: is allowed allowed (currently ignored) or should have raise an error?
+    builder.add_dimension("x", 100, long_name="X Dimension")
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+    assert len(builder._dimensions) == 2  # noqa: PLR2004
+    assert len(builder._variables) == 2  # noqa: PLR2004
+
+    # Adding a dimension with the same name and different size throws an error
+    with pytest.raises(ValueError, match="Dimension 'x' found but size 100 does not match expected size 200"):
+        builder.add_dimension("x", 200, long_name="X Dimension") 
+        assert builder._state == _BuilderState.HAS_DIMENSIONS  
+
+
+
+def test_add_dimension_with_units() -> None:
+    """Test adding dimensions with units."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Add dimension with units as a dictionary
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={"unitsV1": {"length": "m"}},
+    )
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "depth"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.units_v1.length == "m"
+
+    # Add dimension with strongly-typed unit list of single-item
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT64,
+        metadata=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))],
+    )
+    assert len(builder._variables) == 2
+    var1 = builder._variables[1]
+    assert var1.name == "length"
+    assert var1.data_type == ScalarType.FLOAT64
+    assert var1.metadata.units_v1.length == "ft"
+
+
+def test_add_dimension_with_attributes() -> None:
+    """Test adding dimensions with attributes."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Add dimension with attributes as dictionary
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={"attributes": {"MGA": 51, "UnitSystem": "Imperial"}}
+    )
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "depth"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.attributes["MGA"] == 51  # noqa: PLR2004
+    assert var0.metadata.attributes["UnitSystem"] == "Imperial"
+
+    # Add dimension with strongly-typed attribute list
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
+    )
+    assert len(builder._variables) == 2
+    var1 = builder._variables[1]
+    assert var1.name == "length"
+    assert var1.data_type == ScalarType.FLOAT32
+    assert var1.metadata.attributes["MGA"] == 51  # noqa: PLR2004
+    assert var1.metadata.attributes["UnitSystem"] == "Imperial"
+
+
+def test_add_dimension_with_chunk_grid() -> None:
+    """Test adding dimensions with chunk grid."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Add dimension with chunk grid as dictionary
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={"chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}}},
+    )
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "depth"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.chunk_grid.name == "regular"
+    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]
+
+
+    # Add dimension with strongly-typed chunk grid
+    # TODO: It is not clear, how RectilinearChunkGrid can be mapped to a single dimension
+    # grid_definition = RectilinearChunkGrid(configuration=RectilinearChunkShape(chunk_shape=[[2,3,4],[2,3,4]]))
+    grid_definition = RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata=[ChunkGridMetadata(chunk_grid=grid_definition)]
+    )
+    assert len(builder._variables) == 2
+    var1 = builder._variables[1]
+    assert var1.name == "length"
+    assert var1.data_type == ScalarType.FLOAT32
+    assert var1.metadata.chunk_grid.name == "regular"
+    assert var1.metadata.chunk_grid.configuration.chunk_shape == [20]
+
+def test_add_dimension_with_stats() -> None:
+    """Test adding dimensions with stats."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # TODO: Are multiple statistic object supported?
+    # TODO: StatisticsMetadata accepts list[SummaryStatistics], what does this mean and does it need to be tested?
+
+    # TODO:  What is the proper spelling 'statsV1' or 'stats_v1'? Needs to be documented.
+    
+    # Add dimension with strongly-typed stats
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata=[StatisticsMetadata(stats_v1=SummaryStatistics(
+            count=100,
+            sum=1215.1,
+            sumSquares=125.12,
+            min=5.61,
+            max=10.84,
+            # TODO: Also test EdgeDefinedHistogram
+            histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])
+        ))]
+    )
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "depth"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.stats_v1.count == 100  # noqa: PLR2004
+    assert var0.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
+
+    # Add dimension with dictionary stats
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={
+            "statsV1": {
+                "count": 100,
+                "sum": 1215.1,
+                "sumSquares": 125.12,
+                "min": 5.61,
+                "max": 10.84,
+                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
+            }
+        },
+    )
+    assert len(builder._variables) == 2
+    var1 = builder._variables[1]
+    assert var1.name == "length"
+    assert var1.data_type == ScalarType.FLOAT32
+    assert var1.metadata.stats_v1.count == 100  # noqa: PLR2004
+    assert var1.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
+
+def test_add_dimension_with_full_metadata() -> None:
+    """Test adding dimensions with all metadata."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Add dimension with all metadata as dictionary
+    builder.add_dimension(
+        "depth",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata={
+            "unitsV1": {"length": "m"},
+            "attributes": {"MGA": 51},
+            "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
+            "statsV1": {
+                "count": 100,
+                "sum": 1215.1,
+                "sumSquares": 125.12,
+                "min": 5.61,
+                "max": 10.84,
+                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
+            },
+        },
+    )
+
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "depth"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.units_v1.length == "m"
+    assert var0.metadata.attributes["MGA"] == 51  # noqa: PLR2004
+    assert var0.metadata.chunk_grid.name == "regular"
+    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]  # noqa: PLR2004
+    assert var0.metadata.stats_v1.count == 100  # noqa: PLR2004
+    assert var0.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
+    assert var0.metadata.stats_v1.sum_squares == 125.12  # noqa: PLR2004
+    assert var0.metadata.stats_v1.min == 5.61  # noqa: PLR2004
+    assert var0.metadata.stats_v1.max == 10.84  # noqa: PLR2004
+    assert var0.metadata.stats_v1.histogram.bin_centers == [1, 2]  # noqa: PLR2004
+    assert var0.metadata.stats_v1.histogram.counts == [10, 15]  # noqa: PLR2004
+
+    # Add dimension with all strongly-typed metadata
+    builder.add_dimension(
+        "length",
+        size=100,
+        data_type=ScalarType.FLOAT32,
+        metadata=[
+            AllUnits(units_v1=LengthUnitModel(
+                length=LengthUnitEnum.FOOT)),
+            UserAttributes(
+                attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(
+                        chunk_shape=[20]))),
+            StatisticsMetadata(stats_v1=SummaryStatistics(
+                count=100,
+                sum=1215.1,
+                sumSquares=125.12,
+                min=5.61,
+                max=10.84,
+                histogram=CenteredBinHistogram(
+                    binCenters=[1, 2], 
+                    counts=[10, 15])))
+        ]
+    )
+
+    assert len(builder._variables) == 2
+    var1 = builder._variables[1]
+    assert var1.name == "length"
+    assert var1.data_type == ScalarType.FLOAT32
+    assert var1.metadata.units_v1.length == "ft"
+    assert var1.metadata.attributes["MGA"] == 51  # noqa: PLR2004
+    assert var1.metadata.attributes["UnitSystem"] == "Imperial"  # noqa: PLR2004
+    assert var1.metadata.chunk_grid.name == "regular"
+    assert var1.metadata.chunk_grid.configuration.chunk_shape == [20]  # noqa: PLR2004
+    assert var1.metadata.stats_v1.count == 100  # noqa: PLR2004
+    assert var1.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
+    assert var1.metadata.stats_v1.sum_squares == 125.12  # noqa: PLR2004
+    assert var1.metadata.stats_v1.min == 5.61  # noqa: PLR2004
+    assert var1.metadata.stats_v1.max == 10.84  # noqa: PLR2004
+    assert var1.metadata.stats_v1.histogram.bin_centers == [1, 2]  # noqa: PLR2004
+    assert var1.metadata.stats_v1.histogram.counts == [10, 15]  # noqa: PLR2004
+
+
+    # j = builder.build().json()
+    # print(j)
\ No newline at end of file
diff --git a/tests/unit/v1/test_dataset_builder_internals.py b/tests/unit/v1/test_dataset_builder_internals.py
new file mode 100644
index 000000000..100b55254
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_internals.py
@@ -0,0 +1,208 @@
+
+from datetime import datetime
+from pydantic import BaseModel, Field
+import pytest
+from mdio.schemas.core import StrictModel
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension, get_dimension, to_dictionary
+from mdio.schemas.v1.units import LengthUnitEnum, LengthUnitModel
+from mdio.schemas.v1.variable import VariableMetadata, AllUnits, UserAttributes
+
+def test__get_dimension() -> None:
+    """Test getting a dimension by name from the list of dimensions."""
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+
+    assert get_dimension([], "inline") is None
+
+    assert get_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
+    assert get_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
+    assert get_dimension(dimensions, "time") is None
+
+    with pytest.raises(TypeError, match="Expected str, got NoneType"):
+        get_dimension(dimensions, None) 
+    with pytest.raises(TypeError, match="Expected str, got int"):
+        get_dimension(dimensions, 42)
+    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
+        get_dimension(dimensions, "inline", size=200)
+
+
+def test__contains_dimension() -> None:
+    """Test if a dimension with a given name exists in the list of dimensions."""
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+
+    assert contains_dimension([], "inline") is False
+
+    assert contains_dimension(dimensions, "inline") is True
+    assert contains_dimension(dimensions, "crossline") is True
+    assert contains_dimension(dimensions, "time") is False
+
+    with pytest.raises(TypeError, match="Expected str or NamedDimension, got NoneType"):
+        contains_dimension(dimensions, None)
+    with pytest.raises(TypeError, match="Expected str or NamedDimension, got int"):
+        contains_dimension(dimensions, 42)
+    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
+        contains_dimension(dimensions, NamedDimension(name="inline", size=200))   
+
+
+
+def test__add_named_dimensions() -> None:
+    """Test adding named dimensions to a dataset."""
+
+    builder = MDIODatasetBuilder("Test Dataset Builder")
+    #
+    # Validate initial state
+    #
+    assert builder._dimensions is not None
+    assert len(builder._dimensions) == 0
+
+    #
+    # Validate that adding empty dimensions does not change the state
+    #
+    added_dims = builder._add_named_dimensions(None)
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+    added_dims = builder._add_named_dimensions([])
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+    added_dims = builder._add_named_dimensions({})
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+
+    #
+    # Add named dimensions
+    #
+    inline_dim = NamedDimension(name="inline", size=2)
+    added_dims = builder._add_named_dimensions([inline_dim])
+    assert len(builder._dimensions) == 1
+    assert len(added_dims) == 1
+    assert contains_dimension(added_dims, inline_dim)
+
+    crossline_dim = NamedDimension(name="crossline", size=3)
+    time_dim = NamedDimension(name="time", size=4)
+    added_dims = builder._add_named_dimensions([crossline_dim, time_dim])
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert contains_dimension(added_dims, crossline_dim)
+    assert contains_dimension(added_dims, time_dim)
+
+    #
+    # Add invalid object type
+    #
+    with pytest.raises(TypeError, match="Expected NamedDimension or str, got int"):
+        builder._add_named_dimensions([42])
+        assert len(builder._dimensions) == 3
+
+    #
+    # Add dimensions with the same names again does nothing
+    # (make sure we are passing different instances)
+    #
+    inline_dim2 = NamedDimension(name=inline_dim.name, size=inline_dim.size)
+    crossline_dim2 = NamedDimension(name=crossline_dim.name, size=crossline_dim.size)
+    time_dim2 = NamedDimension(name=time_dim.name, size=time_dim.size)
+    added_dims = builder._add_named_dimensions([inline_dim2, crossline_dim2, time_dim2])
+    # Validate that the dimensions and variables are not duplicated
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert len(added_dims) == 0
+
+    # Add dimensions with the same name, but different size again
+    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
+        inline_dim2 = NamedDimension(name="inline", size=200)
+        builder._add_named_dimensions([inline_dim2])
+        assert len(builder._dimensions) == 3
+    #
+    # Add existing dimension using its name
+    #
+    added_dims = builder._add_named_dimensions(["inline", "crossline"])
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert len(added_dims) == 0
+
+    #
+    # Add non-existing dimension using its name is not allowed
+    #
+    with pytest.raises(ValueError, match="Dimension named 'offset' is not found"):
+        builder._add_named_dimensions(["offset"])
+        assert len(builder._dimensions) == 3
+        assert contains_dimension(builder._dimensions, inline_dim)
+        assert contains_dimension(builder._dimensions, crossline_dim)
+        assert contains_dimension(builder._dimensions, time_dim)
+
+
+def test__to_dictionary() -> None:
+    """Test converting a BaseModel to a dictionary."""
+
+    with pytest.raises(TypeError, match="Expected BaseModel, got datetime"):
+        # This should raise an error because datetime is not a BaseModel
+        to_dictionary(datetime.now()) 
+
+    class SomeModel(StrictModel):
+        count: int = Field(default=None, description="Samples count")
+        samples: list[float] = Field(default_factory=list, description="Samples.")
+        created: datetime = Field(default_factory=datetime.now, description="Creation time with TZ info.")
+
+    m = SomeModel(  
+        count = 3,
+        samples = [1.0, 2.0, 3.0],
+        created = datetime(2023, 10, 1, 12, 0, 0, tzinfo=None)
+    )
+    result = to_dictionary(m)
+    assert isinstance(result, dict)
+    assert result == {'count': 3, 'created': '2023-10-01T12:00:00', 'samples': [1.0, 2.0, 3.0]}
+
+
+def test__make_VariableMetadata_from_list() -> None:
+    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
+
+    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
+    meta_list=[units, attrs] 
+
+    # TODO: I assume we do not want attribute.attribute in the contract:
+    # 'metadata': {'unitsV1': {'length': 'm'}, 'attributes': {'attributes': {'MGA': 51}}}
+    # TODO: Are multiple attributes allowed (I assume they are)?
+    metadata = MDIODatasetBuilder._make_VariableMetadata_from_list(meta_list)
+    assert isinstance(metadata, VariableMetadata)
+    assert metadata.units_v1.length == "ft"
+    assert metadata.attributes["MGA"] == 51 
+    assert metadata.attributes["UnitSystem"] == "Imperial"
+
+    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
+        meta_list = ["ft"]
+        MDIODatasetBuilder._make_VariableMetadata_from_list(meta_list)
+
+def test__make_VariableMetadata_from_dict() -> None:
+    """Test creating VariableMetadata from a dictionary."""
+
+    # TODO: What is the key for units: it unitsV1 or units_v1?
+    # TODO: Are multiple attributes allowed (I assume they are)?
+    # TODO: Do we validate the unit string supplied in dictionary parameters? What what if someone supplies ftUS instead of ft?
+    meta_dict={"unitsV1": {"length": "ft"}, "attributes": {"MGA": 51, "UnitSystem": "Imperial"}}
+    metadata = MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)
+    assert isinstance(metadata, VariableMetadata)
+    assert metadata.units_v1.length == "ft"
+    assert metadata.attributes["MGA"] == 51
+    assert metadata.attributes["UnitSystem"] == "Imperial"
+
+    with pytest.raises(TypeError, match="Unsupported metadata key: 'units_v1'. Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1."):
+        meta_dict = {"units_v1": "ft"}
+        MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)
+
+    with pytest.raises(TypeError, match="Invalid value for key 'attributes': 42. Expected a dictionary."):
+        meta_dict = {"attributes": 42}
+        MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)  
+
+    # *** We currently do not validate the structure of the value dictionaries ***
+    # Pass unit object with invalid structure
+    # with pytest.raises(TypeError, match="Invalid value format for key 'unitsV1': {'length': 'm', 'time': 'sec'}. "):
+    #     meta_dict1 = {"unitsV1": {"length": "m", "time": "sec"}}
+    #     MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict1)
+
+
+
diff --git a/tests/unit/v1/test_dataset_builder_state.py b/tests/unit/v1/test_dataset_builder_state.py
new file mode 100644
index 000000000..31c570a85
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_state.py
@@ -0,0 +1,88 @@
+
+from datetime import datetime
+import pytest
+
+from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
+
+def test_builder_initialization() -> None:
+    """Test basic builder initialization."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder.name == "test_dataset"
+    assert builder.api_version == "1.0.0"
+    assert isinstance(builder.created_on, datetime)
+    assert len(builder._dimensions) == 0
+    assert len(builder._coordinates) == 0
+    assert len(builder._variables) == 0
+    assert builder._state == _BuilderState.INITIAL
+
+def test_builder_add_dimension_state() -> None:
+    """Test coordinate builder before and after add_dimension."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+
+    # One should be able to add dimension any time after the builder has been created
+
+    # Add dimensions first
+    builder = builder.add_dimension("x", 100)
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+    builder = builder.add_dimension("y", 200)
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+
+@pytest.mark.skip(reason="Under construction.")
+def test_coordinate_builder_state() -> None:
+    """Test coordinate builder state transitions and functionality."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Should not be able to add coordinates before dimensions
+    with pytest.raises(
+        ValueError, match="Must add at least one dimension before adding coordinates"
+    ):
+        builder.add_coordinate("x_coord", dimensions=["x"])
+
+    # Add dimensions first
+    builder = builder.add_dimension("x", 100)
+    builder = builder.add_dimension("y", 200)
+
+    # Adding coordinate should change state to HAS_COORDINATES
+    builder = builder.add_coordinate("x_coord", dimensions=["x"], long_name="X Coordinate")
+    assert builder._state == _BuilderState.HAS_COORDINATES
+    assert len(builder._coordinates) == 1  # noqa: PLR2004
+    assert builder._coordinates[0].name == "x_coord"
+    assert builder._coordinates[0].long_name == "X Coordinate"
+    assert builder._coordinates[0].dimensions[0].name == "x"
+
+    # Adding another coordinate should maintain state
+    builder = builder.add_coordinate("y_coord", dimensions=["y"])
+    assert builder._state == _BuilderState.HAS_COORDINATES
+    assert len(builder._coordinates) == 2  # noqa: PLR2004
+    assert builder._coordinates[1].name == "y_coord"
+    assert builder._coordinates[1].dimensions[0].name == "y"
+
+@pytest.mark.skip(reason="Under construction.")
+def test_variable_builder_state() -> None:
+    """Test variable builder state transitions and functionality."""
+    builder = MDIODatasetBuilder("test_dataset")
+
+    # Should not be able to add variables before dimensions
+    with pytest.raises(ValueError, match="Must add at least one dimension before adding variables"):
+        builder.add_variable("data", dimensions=["x"])
+
+    # Add dimension first
+    builder = builder.add_dimension("x", 100)
+
+    # Adding variable should change state to HAS_VARIABLES
+    builder = builder.add_variable("data", dimensions=["x"], long_name="Data Variable")
+    assert builder._state == _BuilderState.HAS_VARIABLES
+    # One for dimension, one for variable
+    assert len(builder._variables) == 2  # noqa: PLR2004
+    assert builder._variables[1].name == "data"
+    assert builder._variables[1].long_name == "Data Variable"
+    assert builder._variables[1].dimensions[0].name == "x"
+
+    # Adding another variable should maintain state
+    builder = builder.add_variable("data2", dimensions=["x"])
+    assert builder._state == _BuilderState.HAS_VARIABLES
+    # One for dimension, two for variables
+    assert len(builder._variables) == 3  # noqa: PLR2004
+    assert builder._variables[2].name == "data2"
+    assert builder._variables[2].dimensions[0].name == "x"
\ No newline at end of file

From 5816f8367cd5d6b07ee4b9074bacb131ed00aa35 Mon Sep 17 00:00:00 2001
From: Brian Michell <brianm314@comcast.net>
Date: Thu, 26 Jun 2025 08:54:16 -0500
Subject: [PATCH 17/56] V1 schema review (#553)

* Update from list to discrete values for coordinate metadata

* Add docs to help users understand difference

* Update docs and fix case sensitivity.

* Linting

* Add CoordianteMetadata to docs
---
 docs/data_models/version_1.md   |  3 +++
 src/mdio/schemas/v1/variable.py | 26 ++++++++++++++++++--------
 2 files changed, 21 insertions(+), 8 deletions(-)

diff --git a/docs/data_models/version_1.md b/docs/data_models/version_1.md
index caf0ed5c7..2fd397538 100644
--- a/docs/data_models/version_1.md
+++ b/docs/data_models/version_1.md
@@ -45,6 +45,9 @@
 .. autopydantic_model:: mdio.schemas.v1.variable.Coordinate
     :inherited-members: BaseModel
 
+.. autopydantic_model:: mdio.schemas.v1.variable.CoordinateMetadata
+    :inherited-members: BaseModel
+
 .. automodule:: mdio.schemas.metadata
     :members: UserAttributes
 
diff --git a/src/mdio/schemas/v1/variable.py b/src/mdio/schemas/v1/variable.py
index 519a89f42..93b591177 100644
--- a/src/mdio/schemas/v1/variable.py
+++ b/src/mdio/schemas/v1/variable.py
@@ -23,14 +23,23 @@
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.units import AllUnits
 
+CoordinateMetadata = create_model(
+    "CoordinateMetadata",
+    **model_fields(AllUnits),
+    **model_fields(UserAttributes),
+    __base__=CamelCaseStrictModel,
+    __doc__="Reduced Metadata, perfect for simple Coordinates.",
+)
+
 
 class Coordinate(NamedArray):
-    """An MDIO coordinate array with metadata."""
+    """A simple MDIO Coordinate array with metadata.
 
-    data_type: ScalarType = Field(..., description="Data type of coordinate.")
-    metadata: list[AllUnits | UserAttributes] | None = Field(
-        default=None, description="Coordinate metadata."
-    )
+    For large or complex Coordinates, define a Variable instead.
+    """
+
+    data_type: ScalarType = Field(..., description="Data type of Coordinate.")
+    metadata: CoordinateMetadata | None = Field(default=None, description="Coordinate Metadata.")
 
 
 VariableMetadata = create_model(
@@ -40,14 +49,15 @@ class Coordinate(NamedArray):
     **model_fields(StatisticsMetadata),
     **model_fields(UserAttributes),
     __base__=CamelCaseStrictModel,
+    __doc__="Complete Metadata for Variables and complex or large Coordinates.",
 )
 
 
 class Variable(NamedArray):
-    """An MDIO variable that has coordinates and metadata."""
+    """An MDIO Variable that has coordinates and metadata."""
 
     coordinates: list[Coordinate] | list[str] | None = Field(
         default=None,
-        description="Coordinates of the MDIO variable dimensions.",
+        description="Coordinates of the MDIO Variable dimensions.",
     )
-    metadata: VariableMetadata | None = Field(default=None, description="Variable metadata.")
+    metadata: VariableMetadata | None = Field(default=None, description="Variable Metadata.")

From 1358f95bea4ad3f781cb353fc6f1d6d27ba99dab Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Fri, 27 Jun 2025 00:22:28 +0000
Subject: [PATCH 18/56] First take on add_dimension(), add_coordinate(),
 add_variable()

---
 DEVELOPER_NOTES.md                            | 213 ++++++-----
 src/mdio/schemas/v1/dataset_builder.py        | 282 +++++++++-----
 tests/unit/v1/__init__.py                     |   2 +-
 .../v1/test_dataset_builder_add_coordinate.py | 144 ++++++++
 .../v1/test_dataset_builder_add_dimension.py  | 348 +++++++-----------
 .../v1/test_dataset_builder_add_variable.py   | 123 +++++++
 tests/unit/v1/test_dataset_builder_helpers.py | 265 +++++++++++++
 .../unit/v1/test_dataset_builder_internals.py | 208 -----------
 tests/unit/v1/test_dataset_builder_state.py   |  88 -----
 9 files changed, 963 insertions(+), 710 deletions(-)
 create mode 100644 tests/unit/v1/test_dataset_builder_add_coordinate.py
 create mode 100644 tests/unit/v1/test_dataset_builder_add_variable.py
 create mode 100644 tests/unit/v1/test_dataset_builder_helpers.py
 delete mode 100644 tests/unit/v1/test_dataset_builder_internals.py
 delete mode 100644 tests/unit/v1/test_dataset_builder_state.py

diff --git a/DEVELOPER_NOTES.md b/DEVELOPER_NOTES.md
index 7dcda95de..427801ee0 100644
--- a/DEVELOPER_NOTES.md
+++ b/DEVELOPER_NOTES.md
@@ -1,107 +1,126 @@
 # Developer Notes
-What are the goals for MDIO v1:
+
+## MDIO v1 scope of work
+
+### TASK 1: Creation an empty MDIO v1 dataset with metadata defined using the v1 schema   
+#### DESCRIPTION
+In the v0, the following code was used to create an empty dataset:  
+
+```Python
+grid = Grid([Dimension("inline",...), Dimension("crossline", ...), Dimension("depth", ...)])
+variable = MDIOVariableConfig("stack_amplitude", ...)
+create_conf = MDIOCreateConfig(path="demo.mdio", grid=grid, variables=[variable])
+create_empty(config=create_conf)
+```
+
+In the v1 it is replaced with the following API, which uses v1 schema:
+
+```Python
+builder = MDIODatasetBuilder(...)
+builder.add_dimension("inline", ...)
+builder.add_dimension("crossline",...)
+builder.add_dimension("depth", ...)
+builder.add_coordinate("cdp_x",...)
+builder.add_coordinate("cdp_y",...)
+builder.add_variable("stack_amplitude",...)
+builder.to_mdio(store="demo.mdio")
+```
+
+#### DEFINITION OF DONE
+* The resulting v1 MDIO control `demo.mdio` file structure must be identical between Python and C++
+* Code coverage 90%
+* Code documentation will be updated:
+    * API doc strings are reviewed
+    * docs/tutorials/creation.ipynb - current version describes v0 API. Should be updated with v1 API
+    * docs/api_reference.md - will be updated with new API
+
+#### ASSUMPTIONS
+We expect that the following v0 workflows to keep working with this change
+* Populating MDIOs
+* Updating File and Checking with MDIOReader
+* Write to SEG-Y
 
 ## Overall API design and implementation
-1. Do we want to have a strongly-typed (see pydantic) or dynamic-typed (see dictionary args) API?  
-  For example
+We will have only a strongly-typed (see pydantic) API. For example:
+
 ```Python
-    # Strongly typed
-    builder.add_dimension(
-        "length",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata=[
-            AllUnits(units_v1=LengthUnitModel(
-                length=LengthUnitEnum.FOOT)),
-            UserAttributes(
-                attributes={"MGA": 51, "UnitSystem": "Imperial"}),
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(
-                        chunk_shape=[20]))),
-            StatisticsMetadata(stats_v1=SummaryStatistics(
-                count=100,
-                sum=1215.1,
-                sumSquares=125.12,
-                min=5.61,
-                max=10.84,
-                histogram=CenteredBinHistogram(
-                    binCenters=[1, 2], 
-                    counts=[10, 15])))
-        ]
-    )
-
-    # dynamically-typed
-    builder.add_dimension(
-        "depth",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={
-            "unitsV1": {"length": "m"},
-            "attributes": {"MGA": 51},
-            "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
-            "statsV1": {
-                "count": 100,
-                "sum": 1215.1,
-                "sumSquares": 125.12,
-                "min": 5.61,
-                "max": 10.84,
-                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
-            },
-        },
-    )
+VariableMetadataList: TypeAlias = list[AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata]
+def add_dimension(
+    self,
+    name: str,
+    size: int,
+    long_name: str = None,
+    data_type: ScalarType | StructuredType = ScalarType.INT32,
+    metadata_info: VariableMetadataList | None = None,
+) -> "MDIODatasetBuilder":
 ```
-2. How extensive the handling of the edge cases and the invalid arguments should be? This affects the ammount of validation code that needs to be written    
-   For example,
-    * Should we validate in the code that the units list contain a single item for the dimensions units    
-      or should we expect the developer to always pass a single-item list?
-    * Should we test the statistics for count > 0 or dim(binCenter) == dim(count) in the case above?
-
-## V1 Schema questions
-1. Why do we allow default / empty names?
-2. Adding a dimension with the same name multiple times: is it allowed or should it raise an error?
-   * It is currently allowed: the second request is ignored
-   * Adding a dimension with the same name, but the different size currently throws an error
-3. Why do we allow methods with dictionary parameters (non-strongly-typed)?
-4. For the add_dimension():
-   * Can AllUnits / UserAttributes / ChunkGridMetadata / StatisticsMetadata be repeated in the metadata list?
-   * For units, chunkGrid, statsV1 dict should we validate structure of the data passed in?
-   * Do we validate the unit string supplied in dictionary parameters? What what if someone supplies ftUS instead of ft?
-   * Are multiple dimension attributes allowed (I assume yes)?
-5. It is not clear, how RectilinearChunkGrid can be mapped to a single dimension
-   ```RectilinearChunkGrid(configuration=RectilinearChunkShape(chunk_shape=[[2,3,4],[2,3,4]]))```
-6. StatisticsMetadata accepts list[SummaryStatistics]. what does this mean and does it need to be tested?
-7. The pydentic attribute names are different from the v1 schema attributes names.
-    'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
-    Tgus, we will pass `units_v1` if we use the typesafe API and `'unitsV1` if we use dictionary API
-8. Can we add two variables with the same name?
-9. Why histogram (e.g., SummaryStatistics) does not have a `histogram_type` attribute?
-10. Why 'ftUS' is not supported by the schema?
-    Units: what foot does the MDIO uses: the U.S. survey foot or the International Foot?
-    The U.S. survey foot is defined as 1200/3937 meters, while the international foot is defined as exactly 0.3048 meters.
+
+Which will be used as following:
+
+```Python
+builder.add_dimension(
+    "length",
+    size=100,
+    data_type=ScalarType.FLOAT32,
+    metadata_info=[
+        AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+        UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+        ChunkGridMetadata(
+            chunk_grid=RegularChunkGrid(
+                configuration=RegularChunkShape(
+                    chunk_shape=[20]))),
+        StatisticsMetadata(stats_v1=SummaryStatistics(
+            count=100,
+            sum=1215.1,
+            sumSquares=125.12,
+            min=5.61,
+            max=10.84,
+            histogram=CenteredBinHistogram(
+                binCenters=[1, 2], 
+                counts=[10, 15])))
+    ]
+)
+```
+### Notes
+* When a coordinate or a variable is created, their schema allows to store their dimensions either as
+    * list of dimensions name `list[str]`, where the names refer to the dimensions defined in the builder._dimensions 
+    * list of named dimensions `list[NamedDimension]`, which duplicate the dimensions defined in the builder._dimensions
+    * Mixture of the two above `list[NamedDimension | str]`  
+
+    We will be using the first approach.  
+
+    **IMPORTANT: For binary compatibility, We need to ensure that the C++ code follows the same logic**
+
+* Metadata population from a dictionary in add_coordinate() and add_variable() will not be supported to ensure that the API is strongly-typed. If it is needed, such conversion should be done as a separate step:
+    ```Python
+    def make_variable_metadata_list_from_dict(metadata: dict[str, Any]) -> VariableMetadataList:
+        # Implementation goes here
+    def make_coordinate_metadata_list_from_dict(metadata: dict[str, Any]) -> CoordinateMetadataList:
+        # Implementation goes here
+    ```
+
+## Schema V1 questions
+
+* add_dimension(): Can a dimension with the same name be added multiple times. Options:
+   * Allowed: the second request is ignored (current implementation)
+      * Adding a dimension with the same name, but the different size currently throws an error
+   * Not Allowed: should it raise an error?
+* The pydantic attribute names are different from the v1 schema attributes names.  What are the repercussions?
+    ```
+    'statsV1' <-> 'stats_v1'
+    'unitsV1' <-> 'units_v1'
+    'chunkGrid' <-> 'chunk_grid'
+    ```
+* Should histogram (e.g., SummaryStatistics) have a `histogram_type` attribute?
+* Units
+  * Why 'ftUS' is not supported by the schema? U.S. survey foot vs the International Foot:  
+    *"The U.S. survey foot is defined as 1200/3937 meters, while the international foot is defined as exactly 0.3048 meters.
     https://www.axiomint.com/survey-foot-versus-international-foot-whats-the-difference/ 
     "The REAL issue is when ... applied to State Plane coordinates in the N2,000,000 and E6,000,000 range! 
-    This ... moves a State Plane coordinate position 4 feet by 12 feet.
-
-## Unclear
-* Did we have a notion of the fixed increment for inline & xline annotations?
-* How is rotation of East/North axes relatively to inline/xline axes is handled
-* How is right-handed and left-handed surveys are handled? 
-* add_variable - should dimensions argument be required??
-  
-(src/mdio/schemas/v1/dataset_builder.py)
-## Design suggestions
-1. Instead of trying to track the state, should we just return a wrapper/pimpl class with the permitted methods?
-2. Should we rename add_dimension to add_dimension_variable / add_dimension_annotation to indicate that we not just 
-   providing the dimension name, but also creating the dimension variable
-4. add_variable - should we call it `append_variable`. add implies that either name or index must be provided.
+    This ... moves a State Plane coordinate position 4 feet by 12 feet."*
+  * Why there are no dimensionless unis (for seismic amplitudes, inlines, etc.)
 
-## Under constructions
-* TODO: ??? refactor _BuilderState to make inner class ???
-* TODO: Need an example of EdgeDefinedHistogram for add_dimension with histogram
+## Design suggestions
+* Should we rename add_dimension to add_dimension_variable (or similar) to indicate that we not just providing the dimension name, but also creating the dimension variable
 
-## Bugs
-1. I assume we do not want attribute.attribute in the contract (see docs\tutorials\builder.ipynb)
-   'metadata': {'unitsV1': {'length': 'm'}, 'attributes': {'attributes': {'MGA': 51}}}
 
-https://osdu.pages.opengroup.org/platform/domain-data-mgmt-services/seismic/open-vds/vds/specification/Metadata.html
\ No newline at end of file
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index ea431e4c3..b97ae7ee2 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -1,28 +1,31 @@
 """Builder pattern implementation for MDIO v1 schema models."""
 
-from collections.abc import Mapping
 from datetime import UTC
 from datetime import datetime
 from enum import Enum
 from enum import auto
 from typing import Any
+from typing import TypeAlias
 
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
 
-from mdio.schemas.compressors import ZFP
-from mdio.schemas.compressors import Blosc
+from mdio.schemas.compressors import ZFP, Blosc
 from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.dtype import ScalarType, StructuredType
-from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
-from mdio.schemas.v1.dataset import Dataset
-from mdio.schemas.v1.stats import StatisticsMetadata, SummaryStatistics
-from mdio.schemas.v1.units import AllUnitModel, AllUnits
-from mdio.schemas.v1.variable import Coordinate, Variable, VariableMetadata
-
-# TODO: Why do we allow default names?
-# TODO: Instead of trying to track the state, should we just return a wrapper class with permitted methods?
-# TODO: refactor to make inner class
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.variable import Coordinate, CoordinateMetadata
+from mdio.schemas.v1.variable import Variable
+from mdio.schemas.v1.variable import VariableMetadata
+
+
+CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
+VariableMetadataList: TypeAlias = list[AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata]
+
 class _BuilderState(Enum):
     """States for the template builder."""
 
@@ -31,24 +34,30 @@ class _BuilderState(Enum):
     HAS_COORDINATES = auto()
     HAS_VARIABLES = auto()
 
-def contains_dimension(dimensions: list[NamedDimension], name_or_NamedDimension: str | NamedDimension) -> bool:
+
+def contains_dimension(
+    dimensions: list[NamedDimension], name_or_dimension: str | NamedDimension
+) -> bool:
     """Check if a dimension with the given name exists in the list."""
-    if isinstance(name_or_NamedDimension, str):
-        name = name_or_NamedDimension
+    if isinstance(name_or_dimension, str):
+        name = name_or_dimension
         return get_dimension(dimensions, name) is not None
-    elif isinstance(name_or_NamedDimension, NamedDimension):
-        named_dimension = name_or_NamedDimension
-        return get_dimension(dimensions, named_dimension.name, named_dimension.size) is not None
-    else:
-        msg = f"Expected str or NamedDimension, got {type(name_or_NamedDimension).__name__}"
-        raise TypeError(msg)
+    if isinstance(name_or_dimension, NamedDimension):
+        dimension = name_or_dimension
+        return get_dimension(dimensions, dimension.name, dimension.size) is not None
+    msg = f"Expected str or NamedDimension, got {type(name_or_dimension).__name__}"
+    raise TypeError(msg)
+
 
-def get_dimension(dimensions: list[NamedDimension], name: str, size: int | None = None) -> NamedDimension | None:
+def get_dimension(
+    dimensions: list[NamedDimension], name: str, size: int | None = None
+) -> NamedDimension | None:
     """Get a dimension by name from the list."""
     if dimensions is None:
         return False
     if not isinstance(name, str):
-        raise TypeError(f"Expected str, got {type(name).__name__}")
+        msg = f"Expected str, got {type(name).__name__}"
+        raise TypeError(msg)
 
     nd = next((dim for dim in dimensions if dim.name == name), None)
     if nd is None:
@@ -58,11 +67,71 @@ def get_dimension(dimensions: list[NamedDimension], name: str, size: int | None
         raise ValueError(msg)
     return nd
 
-def to_dictionary(val: BaseModel) -> dict[str, Any]:
+
+def get_dimension_names( dimensions: list[NamedDimension | str]) -> list[str]:
+    """Get a dimension by name from the list."""
+    names = []
+    if dimensions is None:
+        return names
+    for dim in dimensions:
+        if isinstance(dim, NamedDimension):
+            names.append(dim.name)
+        elif isinstance(dim, str):
+            names.append(dim)
+    return names
+
+
+def _to_dictionary(val: BaseModel) -> dict[str, Any]:
     """Convert a pydantic BaseModel to a dictionary."""
     if not isinstance(val, BaseModel):
-        raise TypeError(f"Expected BaseModel, got {type(val).__name__}")
-    return val.model_dump(mode="json", by_alias=True) 
+        msg = f"Expected BaseModel, got {type(val).__name__}"
+        raise TypeError(msg)
+    return val.model_dump(mode="json", by_alias=True)
+
+def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> CoordinateMetadata | None:
+    if metadata is None or not metadata:
+        return None
+    
+    metadata_dict = {}
+    for md in metadata:
+        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
+        #       'unitsV1' <-> 'units_v1'
+        if isinstance(md, AllUnits):
+            val = md.units_v1
+            metadata_dict["unitsV1"] = _to_dictionary(val)
+        elif isinstance(md, UserAttributes):
+            # NOTE: md.attributes is not pydantic type, but a dictionary
+            metadata_dict["attributes"] = _to_dictionary(md)["attributes"]
+        else:
+            msg = f"Unsupported metadata type: {type(md)}"
+            raise TypeError(msg)
+    return CoordinateMetadata(**metadata_dict)
+
+
+def _make_variable_metadata(metadata: VariableMetadataList | None) -> VariableMetadata | None:
+    if metadata is None or not metadata:
+        return None
+    
+    metadata_dict = {}
+    for md in metadata:
+        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
+        #       'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
+        if isinstance(md, AllUnits):
+            val = md.units_v1
+            metadata_dict["unitsV1"] = _to_dictionary(val)
+        elif isinstance(md, UserAttributes):
+            # NOTE: md.attributes is not pydantic type, but a dictionary
+            metadata_dict["attributes"] = _to_dictionary(md)["attributes"]
+        elif isinstance(md, ChunkGridMetadata):
+            val = md.chunk_grid
+            metadata_dict["chunkGrid"] = _to_dictionary(val)
+        elif isinstance(md, StatisticsMetadata):
+            val = md.stats_v1
+            metadata_dict["statsV1"] = _to_dictionary(val)
+        else:
+            msg = f"Unsupported metadata type: {type(md)}"
+            raise TypeError(msg)
+    return VariableMetadata(**metadata_dict)
 
 class MDIODatasetBuilder:
     """Builder for creating MDIO datasets with enforced build order.
@@ -77,7 +146,8 @@ class MDIODatasetBuilder:
 
     def __init__(self, name: str, attributes: dict[str, Any] | None = None):
         self.name = name
-        self.api_version = "1.0.0"  # TODO(BrianMichell, #0): Pull from package metadata
+        # TODO(BrianMichell, #0): Pull from package metadata
+        self.api_version = "1.0.0"
         self.created_on = datetime.now(UTC)
         self.attributes = attributes
         self._dimensions: list[NamedDimension] = []
@@ -86,8 +156,9 @@ def __init__(self, name: str, attributes: dict[str, Any] | None = None):
         self._state = _BuilderState.INITIAL
         self._unnamed_variable_counter = 0
 
-
-    def _add_named_dimensions(self, dimensions: list[NamedDimension | str] | None) -> list[NamedDimension]:
+    def _add_dimensions_if_needed(
+        self, dimensions: list[NamedDimension | str] | None
+    ) -> list[NamedDimension]:
         if dimensions is None:
             return []
 
@@ -95,72 +166,27 @@ def _add_named_dimensions(self, dimensions: list[NamedDimension | str] | None) -
         for dim in dimensions:
             if isinstance(dim, str):
                 if not contains_dimension(self._dimensions, dim):
-                    raise ValueError(f"Dimension named {dim!r} is not found")
+                    msg = f"Pre-existing dimension named {dim!r} is not found"
+                    raise ValueError(msg)
             else:
                 if not isinstance(dim, NamedDimension):
-                    raise TypeError(f"Expected NamedDimension or str, got {type(dim).__name__}")
-                if  contains_dimension(self._dimensions, dim):
+                    msg = f"Expected NamedDimension or str, got {type(dim).__name__}"
+                    raise TypeError(msg)
+                if contains_dimension(self._dimensions, dim):
                     continue
-                self._dimensions.append(dim)
-                added_dims.append(dim)
+                # Use value instead of a reference
+                d = NamedDimension(name=dim.name, size=dim.size)
+                self._dimensions.append(d)
+                added_dims.append(d)
         return added_dims
 
-
-    def _make_VariableMetadata_from_list(metadata: list[AllUnits | UserAttributes]) -> Any:
-        metadata_dict = {}
-        for md in metadata:
-            # NOTE: the pydentic attribute names are different from the v1 schema attributes names
-            #       'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
-            if isinstance(md, AllUnits):
-                val = md.units_v1
-                metadata_dict["unitsV1"] = to_dictionary(val)
-            elif isinstance(md, UserAttributes):
-                # NOTE: md.attributes is not pydantic type, but a dictionary
-                metadata_dict["attributes"] = to_dictionary(md)["attributes"]
-            elif isinstance(md, ChunkGridMetadata):
-                val = md.chunk_grid
-                metadata_dict["chunkGrid"] = to_dictionary(val)
-            elif isinstance(md, StatisticsMetadata):
-                val = md.stats_v1
-                metadata_dict["statsV1"] = to_dictionary(val)
-            else:
-                raise TypeError(f"Unsupported metadata type: {type(md)}")
-        return VariableMetadata(**metadata_dict)
-
-
-    def _make_VariableMetadata_from_dict(metadata: dict[str, Any]) -> type[BaseModel]:
-        converted_dict = {}
-        for key, value in metadata.items():
-            if key == "unitsV1" or key == "statsV1" or key == "chunkGrid" or key == "attributes":
-                # TODO: Should we validate the structure of the value passed in?
-                if not isinstance(value, dict):
-                    raise TypeError(f"Invalid value for key '{key}': {value!r}. Expected a dictionary.")
-            else:
-                raise TypeError(f"Unsupported metadata key: '{key}'. Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1.")
-            converted_dict[key] = value
-        return VariableMetadata(**converted_dict)
-
-
-    def _make_VariableMetadata(metadata: list[AllUnits | UserAttributes] | dict[str, Any] | None = None) -> Any | None:
-        if metadata is None:
-            return None
-        
-        if isinstance(metadata, list):
-            return MDIODatasetBuilder._make_VariableMetadata_from_list(metadata)
-        
-        if isinstance(metadata, dict):
-            return MDIODatasetBuilder._make_VariableMetadata_from_dict(metadata)
-
-        raise TypeError(f"Unsupported metadata type: {type(metadata)}")
-
-
     def add_dimension(  # noqa: PLR0913
         self,
         name: str,
         size: int,
-        long_name: str = None,
-        data_type: ScalarType | StructuredType = ScalarType.INT32,
-        metadata: list[AllUnits | UserAttributes] | None | dict[str, Any] = None,
+        var_long_name: str = None,
+        var_data_type: ScalarType | StructuredType = ScalarType.INT32,
+        var_metadata_info: VariableMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
         """Add a dimension.
 
@@ -171,25 +197,97 @@ def add_dimension(  # noqa: PLR0913
             size: Size of the dimension
             long_name: Optional long name for the dimension variable
             data_type: Data type for the dimension variable (defaults to INT32)
-            metadata: Optional metadata for the dimension variable
+            metadata_info: Optional metadata information for the dimension variable
 
         Returns:
             self: Returns self for method chaining
         """
+        if not name:
+            raise ValueError("'name' must be a non-empty string")
 
-        added_dims = self._add_named_dimensions([NamedDimension(name=name, size=size)])
+        added_dims = self._add_dimensions_if_needed(
+            [NamedDimension(name=name, size=size)])
         if added_dims:
             # Create a variable for the dimension
             dim_var = Variable(
                 name=name,
-                longName=long_name,
+                longName=var_long_name,
                 dimensions=added_dims,
-                dataType=data_type,
+                dataType=var_data_type,
                 compressor=None,
                 coordinates=None,
-                metadata=MDIODatasetBuilder._make_VariableMetadata(metadata)
+                metadata=_make_variable_metadata(var_metadata_info),
             )
             self._variables.append(dim_var)
 
         self._state = _BuilderState.HAS_DIMENSIONS
         return self
+
+    def add_coordinate(  # noqa: PLR0913
+        self,
+        name: str,
+        *,
+        long_name: str = None,
+        dimensions: list[NamedDimension | str],
+        data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
+        metadata_info: CoordinateMetadataList | None = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a coordinate after adding at least one dimension."""
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before adding coordinates"
+            raise ValueError(msg)
+        if not name:
+            raise ValueError("'name' must be a non-empty string")
+        if dimensions is None or not dimensions:
+            raise ValueError("'dimensions' must be a non-empty list")
+
+        self._add_dimensions_if_needed(dimensions)
+        dim_names = get_dimension_names(dimensions)
+        self._coordinates.append(
+            Coordinate(
+                name=name,
+                longName=long_name,
+                dimensions=dim_names, # We ass names: sts, not list[NamedDimension | str]
+                dataType=data_type,
+                metadata=_make_coordinate_metadata(metadata_info),
+            )
+        )
+        self._state = _BuilderState.HAS_COORDINATES
+        return self
+
+
+    def add_variable(  # noqa: PLR0913
+        self,
+        name: str,
+        *,
+        long_name: str = None,
+        dimensions: list[NamedDimension | str],
+        data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
+        compressor: Blosc | ZFP | None = None,
+        coordinates: list[Coordinate | str] | None = None,
+        metadata_info: VariableMetadataList | None = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a variable after adding at least one dimension."""
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before adding variables"
+            raise ValueError(msg)
+        if not name:
+            raise ValueError("'name' must be a non-empty string")
+        if dimensions is None or not dimensions:
+            raise ValueError("'dimensions' must be a non-empty list")
+
+        self._add_dimensions_if_needed(dimensions)
+        dim_names = get_dimension_names(dimensions)
+        self._variables.append(
+            Variable(
+                name=name,
+                long_name=long_name,
+                dimensions=dim_names,
+                data_type=data_type,
+                compressor=compressor,
+                coordinates=coordinates,
+                metadata=_make_variable_metadata(metadata_info),
+            )
+        )
+        self._state = _BuilderState.HAS_VARIABLES
+        return self
diff --git a/tests/unit/v1/__init__.py b/tests/unit/v1/__init__.py
index 3db3a8e50..fa2ea633b 100644
--- a/tests/unit/v1/__init__.py
+++ b/tests/unit/v1/__init__.py
@@ -1 +1 @@
-"""Unit tests for parts of the MDIO package related to the v1 schema"""
\ No newline at end of file
+"""Unit tests for parts of the MDIO package related to the v1 schema."""
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
new file mode 100644
index 000000000..b38da14be
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -0,0 +1,144 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_coordinate() public API."""
+
+import pytest
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+
+
+def test_add_coordinate() -> None:
+    """Test adding coordinates. Check the state transition and validate required parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+    
+    with pytest.raises(ValueError, match="Must add at least one dimension before adding coordinates"):
+        builder.add_coordinate("amplitude", dimensions=["speed"])
+
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_coordinate(bad_name, dimensions=["speed"])
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_coordinate("", dimensions=["speed"])
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_coordinate("amplitude", dimensions=None)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_coordinate("amplitude", dimensions=[])
+
+    builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+    assert builder._state == _BuilderState.HAS_COORDINATES
+    assert len(builder._dimensions) == 2 
+    assert len(builder._variables) == 2 
+    assert len(builder._coordinates) == 1  
+
+def test_add_coordinate_with_defaults() -> None:
+    """Test adding coordinates with default arguments."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    # Add coordinate using defaults
+    builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+    assert len(builder._dimensions) == 2 
+    assert len(builder._variables) == 2 
+    assert len(builder._coordinates) == 1
+    # NOTE: add_variable() stores dimensions as names
+    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert crd0 is not None
+    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert crd0.long_name is None               # Default value
+    assert crd0.data_type == ScalarType.FLOAT32 # Default value
+    assert crd0.metadata is None                # Default value
+ 
+def test_coordinate_with_units() -> None:
+    """Test adding coordinates with units."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    # Add coordinate with units
+    builder.add_coordinate(
+        "cdp", 
+        dimensions=["inline", "crossline"],
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
+    )
+    assert len(builder._dimensions) == 2 
+    assert len(builder._variables) == 2  
+    assert len(builder._coordinates) == 1 
+    # NOTE: add_coordinate() stores dimensions as names
+    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert crd0 is not None
+    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert crd0.long_name is None               # Default value
+    assert crd0.data_type == ScalarType.FLOAT32 # Default value
+    assert crd0.metadata.attributes is None
+    assert crd0.metadata.units_v1.length == "ft"
+
+
+def test_coordinate_with_attributes() -> None:
+    """Test adding coordinates with attributes."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    # Add coordinate with attributes
+    builder.add_coordinate(
+        "cdp", 
+        dimensions=["inline", "crossline"], 
+        metadata_info=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})],
+    )
+    assert len(builder._dimensions) == 2 
+    assert len(builder._variables) == 2  
+    assert len(builder._coordinates) == 1 
+    # NOTE: add_coordinate() stores dimensions as names
+    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert crd0 is not None
+    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert crd0.long_name is None               # Default value
+    assert crd0.data_type == ScalarType.FLOAT32 # Default value
+    assert crd0.metadata.attributes["MGA"] == 51
+    assert crd0.metadata.attributes["UnitSystem"] == "Imperial"
+    assert crd0.metadata.units_v1 is None
+
+
+def test_coordinate_with_full_metadata() -> None:
+    """Test adding coordinates with all metadata."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    # Add coordinate with all metadata
+    builder.add_coordinate(
+        "cdp",
+        dimensions=["inline", "crossline"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
+    )
+    assert len(builder._dimensions) == 2 
+    assert len(builder._variables) == 2  
+    assert len(builder._coordinates) == 1 
+    # NOTE: add_coordinate() stores dimensions as names
+    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert crd0 is not None
+    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert crd0.long_name is None               # Default value
+    assert crd0.data_type == ScalarType.FLOAT32 # Default value
+    assert crd0.metadata.attributes["MGA"] == 51
+    assert crd0.metadata.attributes["UnitSystem"] == "Imperial"
+    assert crd0.metadata.units_v1.length == "ft"
+
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index bac9a8383..7adebb4b5 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -1,307 +1,207 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_dimension() public API."""
 
 import pytest
 
-from datetime import datetime
-
-from mdio.schemas.chunk_grid import RectilinearChunkGrid, RectilinearChunkShape, RegularChunkGrid, RegularChunkShape
-from mdio.schemas.dtype import ScalarType, StructuredType
-
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension, get_dimension, _BuilderState
-from mdio.schemas.v1.stats import CenteredBinHistogram, Histogram, StatisticsMetadata, SummaryStatistics
-from mdio.schemas.v1.units import AllUnits, LengthUnitEnum, LengthUnitModel
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+
 
 def test_add_dimension() -> None:
-    """Test adding a dimension to the dataset builder."""
-    builder = MDIODatasetBuilder("Test Dataset Builder")
+    """Test adding dimension. Check the state transition and validate required parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
 
-    builder.add_dimension(name="inline", size=2, long_name="Inline dimension")
-    assert len(builder._dimensions) == 1
-    assert builder._dimensions[0] == NamedDimension(name="inline", size=2)  
-    assert len(builder._variables) == 1
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_dimension(bad_name, 200)
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_dimension("", 200)
+
+    # First dimension should change state to HAS_DIMENSIONS and create a variable
+    builder.add_dimension("x", 100)
     assert builder._state == _BuilderState.HAS_DIMENSIONS
+    assert len(builder._dimensions) == 1  
+    assert builder._dimensions[0] == NamedDimension(name="x", size=100)
+    assert len(builder._variables) == 1  
 
+    # Adding a dimension with the same name as an existing dimension.
+    # Currently, it does not raise an error, but just ignores this call
+    builder.add_dimension("x", 100, var_long_name="X Dimension")
+    assert builder._state == _BuilderState.HAS_DIMENSIONS
+    assert len(builder._dimensions) == 1  
+    assert len(builder._variables) == 1  
 
-def test_add_dimension() -> None:
+    # Adding a dimension with the same name and different size throws an error
+    err_msg = "Dimension 'x' found but size 100 does not match expected size 200"
+    with pytest.raises(ValueError, match=err_msg):
+        builder.add_dimension("x", 200, var_long_name="X Dimension")
+
+def test_add_dimension_with_defaults() -> None:
     """Test dimension builder state transitions and functionality."""
     builder = MDIODatasetBuilder("test_dataset")
 
     # First dimension should change state to HAS_DIMENSIONS and create a variable
-    builder.add_dimension("x", 100, long_name="X Dimension")
+    builder.add_dimension("x", 100)
     assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 1  # noqa: PLR2004
-    assert len(builder._variables) == 1  # noqa: PLR2004
-    assert builder._dimensions[0].name == "x"
-    assert builder._dimensions[0].size == 100  # noqa: PLR2004
+    assert len(builder._dimensions) == 1  
+    assert builder._dimensions[0] == NamedDimension(name="x", size=100)
+    assert len(builder._variables) == 1  
     var0 = builder._variables[0]
     assert var0.name == "x"
-    assert var0.long_name == "X Dimension"
+    assert var0.long_name is None
     assert var0.data_type == ScalarType.INT32
-    assert var0.dimensions[0].name == "x"
-
-    # Adding another dimension should maintain state and create another variable
-    builder.add_dimension("y", 200, data_type=ScalarType.UINT32)
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 2  # noqa: PLR2004
-    assert len(builder._variables) == 2  # noqa: PLR2004
-    assert builder._dimensions[1].name == "y"
-    assert builder._dimensions[1].size == 200  # noqa: PLR2004
-    var1 = builder._variables[1]
-    assert var1.name == "y"
-    assert var1.data_type == ScalarType.UINT32
-    assert var1.dimensions[0].name == "y"
-
-    # TODO: Adding a dimension with the same: is allowed allowed (currently ignored) or should have raise an error?
-    builder.add_dimension("x", 100, long_name="X Dimension")
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 2  # noqa: PLR2004
-    assert len(builder._variables) == 2  # noqa: PLR2004
-
-    # Adding a dimension with the same name and different size throws an error
-    with pytest.raises(ValueError, match="Dimension 'x' found but size 100 does not match expected size 200"):
-        builder.add_dimension("x", 200, long_name="X Dimension") 
-        assert builder._state == _BuilderState.HAS_DIMENSIONS  
-
-
+    assert var0.compressor is None
+    assert var0.coordinates is None
+    assert var0.metadata is None
 
 def test_add_dimension_with_units() -> None:
     """Test adding dimensions with units."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with units as a dictionary
-    builder.add_dimension(
-        "depth",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={"unitsV1": {"length": "m"}},
-    )
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "depth"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.units_v1.length == "m"
-
     # Add dimension with strongly-typed unit list of single-item
     builder.add_dimension(
         "length",
         size=100,
-        data_type=ScalarType.FLOAT64,
-        metadata=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))],
+        var_data_type=ScalarType.FLOAT64,
+        var_metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
     )
-    assert len(builder._variables) == 2
-    var1 = builder._variables[1]
-    assert var1.name == "length"
-    assert var1.data_type == ScalarType.FLOAT64
-    assert var1.metadata.units_v1.length == "ft"
-
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "length"
+    assert var0.long_name is None
+    assert var0.data_type == ScalarType.FLOAT64
+    assert var0.compressor is None
+    assert var0.coordinates is None
+    assert var0.metadata.units_v1.length == "ft"
 
 def test_add_dimension_with_attributes() -> None:
     """Test adding dimensions with attributes."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with attributes as dictionary
+    # Add dimension with strongly-typed attribute list
     builder.add_dimension(
-        "depth",
+        "length",
         size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={"attributes": {"MGA": 51, "UnitSystem": "Imperial"}}
+        var_data_type=ScalarType.FLOAT32,
+        var_metadata_info=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})],
     )
     assert len(builder._variables) == 1
     var0 = builder._variables[0]
-    assert var0.name == "depth"
+    assert var0.name == "length"
     assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.attributes["MGA"] == 51  # noqa: PLR2004
+    assert var0.metadata.attributes["MGA"] == 51
     assert var0.metadata.attributes["UnitSystem"] == "Imperial"
 
-    # Add dimension with strongly-typed attribute list
-    builder.add_dimension(
-        "length",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
-    )
-    assert len(builder._variables) == 2
-    var1 = builder._variables[1]
-    assert var1.name == "length"
-    assert var1.data_type == ScalarType.FLOAT32
-    assert var1.metadata.attributes["MGA"] == 51  # noqa: PLR2004
-    assert var1.metadata.attributes["UnitSystem"] == "Imperial"
-
 
 def test_add_dimension_with_chunk_grid() -> None:
     """Test adding dimensions with chunk grid."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with chunk grid as dictionary
+    # Add dimension with strongly-typed chunk grid
+    grid_definition = RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
     builder.add_dimension(
-        "depth",
+        "length",
         size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={"chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}}},
+        var_data_type=ScalarType.FLOAT32,
+        var_metadata_info=[ChunkGridMetadata(chunk_grid=grid_definition)],
     )
     assert len(builder._variables) == 1
     var0 = builder._variables[0]
-    assert var0.name == "depth"
+    assert var0.name == "length"
     assert var0.data_type == ScalarType.FLOAT32
     assert var0.metadata.chunk_grid.name == "regular"
     assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]
 
 
-    # Add dimension with strongly-typed chunk grid
-    # TODO: It is not clear, how RectilinearChunkGrid can be mapped to a single dimension
-    # grid_definition = RectilinearChunkGrid(configuration=RectilinearChunkShape(chunk_shape=[[2,3,4],[2,3,4]]))
-    grid_definition = RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
-    builder.add_dimension(
-        "length",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata=[ChunkGridMetadata(chunk_grid=grid_definition)]
-    )
-    assert len(builder._variables) == 2
-    var1 = builder._variables[1]
-    assert var1.name == "length"
-    assert var1.data_type == ScalarType.FLOAT32
-    assert var1.metadata.chunk_grid.name == "regular"
-    assert var1.metadata.chunk_grid.configuration.chunk_shape == [20]
-
 def test_add_dimension_with_stats() -> None:
     """Test adding dimensions with stats."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # TODO: Are multiple statistic object supported?
-    # TODO: StatisticsMetadata accepts list[SummaryStatistics], what does this mean and does it need to be tested?
-
-    # TODO:  What is the proper spelling 'statsV1' or 'stats_v1'? Needs to be documented.
-    
     # Add dimension with strongly-typed stats
     builder.add_dimension(
         "depth",
         size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata=[StatisticsMetadata(stats_v1=SummaryStatistics(
-            count=100,
-            sum=1215.1,
-            sumSquares=125.12,
-            min=5.61,
-            max=10.84,
-            # TODO: Also test EdgeDefinedHistogram
-            histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])
-        ))]
+        var_data_type=ScalarType.FLOAT32,
+        var_metadata_info=[
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    # TODO(DmitriyRepin, #0): Also test EdgeDefinedHistogram
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            )
+        ],
     )
     assert len(builder._variables) == 1
     var0 = builder._variables[0]
     assert var0.name == "depth"
     assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.stats_v1.count == 100  # noqa: PLR2004
-    assert var0.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
+    assert var0.metadata.stats_v1.count == 100  
+    assert var0.metadata.stats_v1.sum == 1215.1  
 
-    # Add dimension with dictionary stats
-    builder.add_dimension(
-        "length",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={
-            "statsV1": {
-                "count": 100,
-                "sum": 1215.1,
-                "sumSquares": 125.12,
-                "min": 5.61,
-                "max": 10.84,
-                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
-            }
-        },
-    )
-    assert len(builder._variables) == 2
-    var1 = builder._variables[1]
-    assert var1.name == "length"
-    assert var1.data_type == ScalarType.FLOAT32
-    assert var1.metadata.stats_v1.count == 100  # noqa: PLR2004
-    assert var1.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
 
 def test_add_dimension_with_full_metadata() -> None:
     """Test adding dimensions with all metadata."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with all metadata as dictionary
-    builder.add_dimension(
-        "depth",
-        size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata={
-            "unitsV1": {"length": "m"},
-            "attributes": {"MGA": 51},
-            "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
-            "statsV1": {
-                "count": 100,
-                "sum": 1215.1,
-                "sumSquares": 125.12,
-                "min": 5.61,
-                "max": 10.84,
-                "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
-            },
-        },
-    )
-
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "depth"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.units_v1.length == "m"
-    assert var0.metadata.attributes["MGA"] == 51  # noqa: PLR2004
-    assert var0.metadata.chunk_grid.name == "regular"
-    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]  # noqa: PLR2004
-    assert var0.metadata.stats_v1.count == 100  # noqa: PLR2004
-    assert var0.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
-    assert var0.metadata.stats_v1.sum_squares == 125.12  # noqa: PLR2004
-    assert var0.metadata.stats_v1.min == 5.61  # noqa: PLR2004
-    assert var0.metadata.stats_v1.max == 10.84  # noqa: PLR2004
-    assert var0.metadata.stats_v1.histogram.bin_centers == [1, 2]  # noqa: PLR2004
-    assert var0.metadata.stats_v1.histogram.counts == [10, 15]  # noqa: PLR2004
 
     # Add dimension with all strongly-typed metadata
     builder.add_dimension(
         "length",
         size=100,
-        data_type=ScalarType.FLOAT32,
-        metadata=[
-            AllUnits(units_v1=LengthUnitModel(
-                length=LengthUnitEnum.FOOT)),
-            UserAttributes(
-                attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+        var_data_type=ScalarType.FLOAT32,
+        var_metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
             ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(
-                        chunk_shape=[20]))),
-            StatisticsMetadata(stats_v1=SummaryStatistics(
-                count=100,
-                sum=1215.1,
-                sumSquares=125.12,
-                min=5.61,
-                max=10.84,
-                histogram=CenteredBinHistogram(
-                    binCenters=[1, 2], 
-                    counts=[10, 15])))
-        ]
+                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+        ],
     )
 
-    assert len(builder._variables) == 2
-    var1 = builder._variables[1]
-    assert var1.name == "length"
-    assert var1.data_type == ScalarType.FLOAT32
-    assert var1.metadata.units_v1.length == "ft"
-    assert var1.metadata.attributes["MGA"] == 51  # noqa: PLR2004
-    assert var1.metadata.attributes["UnitSystem"] == "Imperial"  # noqa: PLR2004
-    assert var1.metadata.chunk_grid.name == "regular"
-    assert var1.metadata.chunk_grid.configuration.chunk_shape == [20]  # noqa: PLR2004
-    assert var1.metadata.stats_v1.count == 100  # noqa: PLR2004
-    assert var1.metadata.stats_v1.sum == 1215.1  # noqa: PLR2004
-    assert var1.metadata.stats_v1.sum_squares == 125.12  # noqa: PLR2004
-    assert var1.metadata.stats_v1.min == 5.61  # noqa: PLR2004
-    assert var1.metadata.stats_v1.max == 10.84  # noqa: PLR2004
-    assert var1.metadata.stats_v1.histogram.bin_centers == [1, 2]  # noqa: PLR2004
-    assert var1.metadata.stats_v1.histogram.counts == [10, 15]  # noqa: PLR2004
-
-
-    # j = builder.build().json()
-    # print(j)
\ No newline at end of file
+    assert len(builder._variables) == 1
+    var0 = builder._variables[0]
+    assert var0.name == "length"
+    assert var0.data_type == ScalarType.FLOAT32
+    assert var0.metadata.units_v1.length == "ft"
+    assert var0.metadata.attributes["MGA"] == 51  
+    assert var0.metadata.attributes["UnitSystem"] == "Imperial"  
+    assert var0.metadata.chunk_grid.name == "regular"
+    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]  
+    assert var0.metadata.stats_v1.count == 100  
+    assert var0.metadata.stats_v1.sum == 1215.1  
+    assert var0.metadata.stats_v1.sum_squares == 125.12  
+    assert var0.metadata.stats_v1.min == 5.61  
+    assert var0.metadata.stats_v1.max == 10.84  
+    assert var0.metadata.stats_v1.histogram.bin_centers == [1, 2]  
+    assert var0.metadata.stats_v1.histogram.counts == [10, 15]  
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
new file mode 100644
index 000000000..bc168df21
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -0,0 +1,123 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 Variable public API."""
+
+import pytest
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.variable import VariableMetadata
+
+def test_dataset_builder_add_variable() -> None:
+    """Test adding variable. Check the state transition and validate required parameters.."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+    
+    with pytest.raises(ValueError, match="Must add at least one dimension before adding variables"):
+        builder.add_variable("amplitude", dimensions=["speed"])
+
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    builder.add_dimension("depth", 100)
+
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_variable(bad_name, dimensions=["speed"])
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_variable("", dimensions=["speed"])
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_variable("amplitude", dimensions=None)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_variable("amplitude", dimensions=[])
+
+    builder.add_variable("seismic_amplitude", dimensions=["inline", "crossline", "depth"])
+    assert builder._state == _BuilderState.HAS_VARIABLES
+    assert len(builder._dimensions) == 3 
+    assert len(builder._variables) == 4 
+    assert len(builder._coordinates) == 0  
+
+def test_add_variable_with_defaults() -> None:
+    """Test adding variable with default arguments."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    builder.add_dimension("depth", 100)
+    # Add variable using defaults
+    builder.add_variable("seismic_amplitude", dimensions=["inline", "crossline", "depth"])
+    assert len(builder._dimensions) == 3 
+    assert len(builder._variables) == 4 
+    assert len(builder._coordinates) == 0 
+    var0 = next((e for e in builder._variables if e.name == "seismic_amplitude"), None)
+    assert var0 is not None
+    # NOTE: add_variable() stores dimensions as names
+    assert set(var0.dimensions) == set(["inline", "crossline", "depth"])
+    assert var0.long_name is None               # Default value
+    assert var0.data_type == ScalarType.FLOAT32 # Default value
+    assert var0.compressor is None              # Default value
+    assert var0.coordinates is None             # Default value
+    assert var0.metadata is None                # Default value
+
+# def test__make_variable_metadata() -> None:
+#     """Test creating VariableMetadata from a dictionary."""
+
+#     meta_dict = None
+#     metadata = make_variable_metadata_list(meta_dict)
+#     assert metadata is None
+
+#     meta_dict = {}
+#     metadata = make_variable_metadata_list(meta_dict)
+#     assert metadata is None
+
+#     meta_dict = {
+#         "unitsV1": {"length": "m"},
+#         "attributes": {"MGA": 51},
+#         "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
+#         "statsV1": {
+#             "count": 100,
+#             "sum": 1215.1,
+#             "sumSquares": 125.12,
+#             "min": 5.61,
+#             "max": 10.84,
+#             "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
+#         },
+#     }
+#     metadata = make_variable_metadata_list(meta_dict)
+#     assert isinstance(metadata, VariableMetadata)
+#     assert metadata.units_v1.length == "m"
+#     assert metadata.attributes["MGA"] == 51  
+#     assert metadata.chunk_grid.name == "regular"
+#     assert metadata.chunk_grid.configuration.chunk_shape == [20]  
+#     assert metadata.stats_v1.count == 100  
+#     assert metadata.stats_v1.sum == 1215.1  
+#     assert metadata.stats_v1.sum_squares == 125.12  
+#     assert metadata.stats_v1.min == 5.61  
+#     assert metadata.stats_v1.max == 10.84  
+#     assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
+#     assert metadata.stats_v1.histogram.counts == [10, 15]  
+
+#     # NOTE: the v1 schema has 'units_v1' property, but pydantic requires 'unitsV1' for CamelCaseStrictModel
+#     meta_dict = {"units_v1": {"length": "m"}}
+#     err_msg = (
+#         "Unsupported metadata key: 'units_v1'. "
+#         "Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1."
+#     )
+#     with pytest.raises(TypeError, match=err_msg):
+#         make_variable_metadata_list(meta_dict)
+
+#     meta_dict = {"attributes": 42}
+#     with pytest.raises(
+#         TypeError, match="Invalid value for key 'attributes': 42. Expected a dictionary."
+#     ):
+#         make_variable_metadata_list(meta_dict)
+
+#     # *** We currently do not validate the structure of the value dictionaries ***
+#     # Pass unit object with invalid structure
+#     # with pytest.raises(
+#     # TypeError, match="Invalid value format for key 'unitsV1': {'length': 'm', 'time': 'sec'}. "):
+#     #     meta_dict1 = {"unitsV1": {"length": "m", "time": "sec"}}
+#     #     _make_VariableMetadata_from_dict(meta_dict1)
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
new file mode 100644
index 000000000..b9343b997
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -0,0 +1,265 @@
+# ruff: noqa: PLR2004 
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert. 
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder internal methods."""
+
+from datetime import UTC
+from datetime import datetime
+
+import pytest
+from pydantic import Field
+
+from mdio.schemas.chunk_grid import RegularChunkGrid, RegularChunkShape
+from mdio.schemas.core import StrictModel
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _make_coordinate_metadata
+from mdio.schemas.v1.dataset_builder import get_dimension_names
+from mdio.schemas.v1.dataset_builder import _make_variable_metadata
+from mdio.schemas.v1.dataset_builder import _to_dictionary
+from mdio.schemas.v1.dataset_builder import contains_dimension
+from mdio.schemas.v1.dataset_builder import get_dimension
+from mdio.schemas.v1.stats import CenteredBinHistogram, StatisticsMetadata, SummaryStatistics
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.variable import AllUnits, CoordinateMetadata
+from mdio.schemas.v1.variable import UserAttributes
+from mdio.schemas.v1.variable import VariableMetadata
+
+
+def test__get_dimension() -> None:
+    """Test getting a dimension by name from the list of dimensions."""
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+
+    assert get_dimension([], "inline") is None
+
+    assert get_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
+    assert get_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
+    assert get_dimension(dimensions, "time") is None
+
+    with pytest.raises(TypeError, match="Expected str, got NoneType"):
+        get_dimension(dimensions, None)
+    with pytest.raises(TypeError, match="Expected str, got int"):
+        get_dimension(dimensions, 42)
+    with pytest.raises(
+        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
+    ):
+        get_dimension(dimensions, "inline", size=200)
+
+
+def test__contains_dimension() -> None:
+    """Test if a dimension with a given name exists in the list of dimensions."""
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+
+    assert contains_dimension([], "inline") is False
+
+    assert contains_dimension(dimensions, "inline") is True
+    assert contains_dimension(dimensions, "crossline") is True
+    assert contains_dimension(dimensions, "time") is False
+
+    with pytest.raises(TypeError, match="Expected str or NamedDimension, got NoneType"):
+        contains_dimension(dimensions, None)
+    with pytest.raises(TypeError, match="Expected str or NamedDimension, got int"):
+        contains_dimension(dimensions, 42)
+    with pytest.raises(
+        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
+    ):
+        contains_dimension(dimensions, NamedDimension(name="inline", size=200))
+
+
+def test_get_dimension_names() -> None:
+    """Test getting a list of dimension names from list[NamedDimension | str]."""
+
+    empty_list = get_dimension_names(None)
+    assert empty_list is not None
+    assert isinstance(empty_list, list)
+    assert len(empty_list) == 0
+
+    empty_list = get_dimension_names([])
+    assert empty_list is not None
+    assert isinstance(empty_list, list)
+    assert len(empty_list) == 0
+
+    dim_list = get_dimension_names([
+        NamedDimension(name="inline", size=2), 
+        "amplitude",
+        NamedDimension(name="crossline", size=3)
+    ])
+    assert dim_list is not None
+    assert isinstance(dim_list, list)
+    assert set(dim_list) == set(["inline", "amplitude", "crossline"])
+
+
+def test_add_dimensions_if_needed() -> None:
+    """Test adding named dimensions to a dataset."""
+    builder = MDIODatasetBuilder("Test Dataset Builder")
+    #
+    # Validate initial state
+    #
+    assert builder._dimensions is not None
+    assert len(builder._dimensions) == 0
+
+    #
+    # Validate that adding empty dimensions does not change the state
+    #
+    added_dims = builder._add_dimensions_if_needed(None)
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+    added_dims = builder._add_dimensions_if_needed([])
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+    added_dims = builder._add_dimensions_if_needed({})
+    assert len(builder._dimensions) == 0
+    assert len(added_dims) == 0
+
+    #
+    # Add named dimensions
+    #
+    inline_dim = NamedDimension(name="inline", size=2)
+    added_dims = builder._add_dimensions_if_needed([inline_dim])
+    assert len(builder._dimensions) == 1
+    assert len(added_dims) == 1
+    assert contains_dimension(added_dims, inline_dim)
+
+    crossline_dim = NamedDimension(name="crossline", size=3)
+    time_dim = NamedDimension(name="time", size=4)
+    added_dims = builder._add_dimensions_if_needed([crossline_dim, time_dim])
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert contains_dimension(added_dims, crossline_dim)
+    assert contains_dimension(added_dims, time_dim)
+
+    #
+    # Add invalid object type
+    #
+    with pytest.raises(TypeError, match="Expected NamedDimension or str, got int"):
+        builder._add_dimensions_if_needed([42])
+    # Assert that the number of dimensions has not increased
+    assert len(builder._dimensions) == 3
+
+def test__add_dimensions_if_needed_when_one_already_exists() -> None:
+    """Test adding existing named dimensions to a dataset."""
+    builder = MDIODatasetBuilder("Test Dataset Builder")
+
+    inline_dim = NamedDimension(name="inline", size=2)
+    crossline_dim = NamedDimension(name="crossline", size=3)
+    time_dim = NamedDimension(name="time", size=4)
+    #
+    # Add dimensions with the same names again does nothing
+    # (make sure we are passing different instances)
+    #
+    inline_dim2 = NamedDimension(name=inline_dim.name, size=inline_dim.size)
+    crossline_dim2 = NamedDimension(name=crossline_dim.name, size=crossline_dim.size)
+    time_dim2 = NamedDimension(name=time_dim.name, size=time_dim.size)
+    builder._add_dimensions_if_needed([inline_dim2, crossline_dim2, time_dim2])
+    added_dims = builder._add_dimensions_if_needed([inline_dim2, crossline_dim2, time_dim2])
+    # Validate that the dimensions and variables are not duplicated
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert len(added_dims) == 0
+
+    # Add dimensions with the same name, but different size again
+    with pytest.raises(
+        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
+    ):
+        builder._add_dimensions_if_needed([NamedDimension(name="inline", size=200)])
+    # Assert that the number of dimensions has not increased
+    assert len(builder._dimensions) == 3
+
+    #
+    # Add existing dimension using its name
+    #
+    added_dims = builder._add_dimensions_if_needed(["inline", "crossline"])
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+    assert len(added_dims) == 0
+
+    #
+    # Add non-existing dimension using its name is not allowed
+    #
+    with pytest.raises(ValueError, match="Pre-existing dimension named 'offset' is not found"):
+        builder._add_dimensions_if_needed(["offset"])
+    assert len(builder._dimensions) == 3
+    assert contains_dimension(builder._dimensions, inline_dim)
+    assert contains_dimension(builder._dimensions, crossline_dim)
+    assert contains_dimension(builder._dimensions, time_dim)
+
+def test__to_dictionary() -> None:
+    """Test converting a BaseModel to a dictionary."""
+    with pytest.raises(TypeError, match="Expected BaseModel, got datetime"):
+        # This should raise an error because datetime is not a BaseModel
+        _to_dictionary(datetime.now(UTC))
+
+    class SomeModel(StrictModel):
+        count: int = Field(default=None, description="Samples count")
+        samples: list[float] = Field(default_factory=list, description="Samples.")
+        created: datetime = Field(
+            default_factory=datetime.now, description="Creation time with TZ info."
+        )
+
+    m = SomeModel(count=3, 
+                  samples=[1.0, 2.0, 3.0], 
+                  created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC))
+    result = _to_dictionary(m)
+    assert isinstance(result, dict)
+    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
+
+
+def test__make_coordinate_metadata() -> None:
+    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
+    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
+    meta_list = [units, attrs]
+
+    # Assume that multiple attributes are allowed
+    metadata = _make_coordinate_metadata(meta_list)
+    assert isinstance(metadata, CoordinateMetadata)
+    assert metadata.units_v1.length == "ft"
+    assert metadata.attributes["MGA"] == 51
+    assert metadata.attributes["UnitSystem"] == "Imperial"
+
+    meta_list = ["ft"]
+    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
+        _make_variable_metadata(meta_list)
+
+def test__make_variable_metadata() -> None:
+    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
+    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
+    chgrd = ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[20])))
+    stats = StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])))
+    metadata_info = [units, attrs, chgrd, stats]
+    metadata = _make_variable_metadata(metadata_info)
+    assert isinstance(metadata, VariableMetadata)
+    assert metadata.units_v1.length == "ft"
+    assert metadata.attributes["MGA"] == 51  
+    assert metadata.attributes["UnitSystem"] == "Imperial"  
+    assert metadata.chunk_grid.name == "regular"
+    assert metadata.chunk_grid.configuration.chunk_shape == [20]  
+    assert metadata.stats_v1.count == 100  
+    assert metadata.stats_v1.sum == 1215.1  
+    assert metadata.stats_v1.sum_squares == 125.12  
+    assert metadata.stats_v1.min == 5.61  
+    assert metadata.stats_v1.max == 10.84  
+    assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
+    assert metadata.stats_v1.histogram.counts == [10, 15]  
+
+    meta_list = ["ft"]
+    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
+        _make_variable_metadata(meta_list)
diff --git a/tests/unit/v1/test_dataset_builder_internals.py b/tests/unit/v1/test_dataset_builder_internals.py
deleted file mode 100644
index 100b55254..000000000
--- a/tests/unit/v1/test_dataset_builder_internals.py
+++ /dev/null
@@ -1,208 +0,0 @@
-
-from datetime import datetime
-from pydantic import BaseModel, Field
-import pytest
-from mdio.schemas.core import StrictModel
-from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension, get_dimension, to_dictionary
-from mdio.schemas.v1.units import LengthUnitEnum, LengthUnitModel
-from mdio.schemas.v1.variable import VariableMetadata, AllUnits, UserAttributes
-
-def test__get_dimension() -> None:
-    """Test getting a dimension by name from the list of dimensions."""
-    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
-
-    assert get_dimension([], "inline") is None
-
-    assert get_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
-    assert get_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
-    assert get_dimension(dimensions, "time") is None
-
-    with pytest.raises(TypeError, match="Expected str, got NoneType"):
-        get_dimension(dimensions, None) 
-    with pytest.raises(TypeError, match="Expected str, got int"):
-        get_dimension(dimensions, 42)
-    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
-        get_dimension(dimensions, "inline", size=200)
-
-
-def test__contains_dimension() -> None:
-    """Test if a dimension with a given name exists in the list of dimensions."""
-    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
-
-    assert contains_dimension([], "inline") is False
-
-    assert contains_dimension(dimensions, "inline") is True
-    assert contains_dimension(dimensions, "crossline") is True
-    assert contains_dimension(dimensions, "time") is False
-
-    with pytest.raises(TypeError, match="Expected str or NamedDimension, got NoneType"):
-        contains_dimension(dimensions, None)
-    with pytest.raises(TypeError, match="Expected str or NamedDimension, got int"):
-        contains_dimension(dimensions, 42)
-    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
-        contains_dimension(dimensions, NamedDimension(name="inline", size=200))   
-
-
-
-def test__add_named_dimensions() -> None:
-    """Test adding named dimensions to a dataset."""
-
-    builder = MDIODatasetBuilder("Test Dataset Builder")
-    #
-    # Validate initial state
-    #
-    assert builder._dimensions is not None
-    assert len(builder._dimensions) == 0
-
-    #
-    # Validate that adding empty dimensions does not change the state
-    #
-    added_dims = builder._add_named_dimensions(None)
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-    added_dims = builder._add_named_dimensions([])
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-    added_dims = builder._add_named_dimensions({})
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-
-    #
-    # Add named dimensions
-    #
-    inline_dim = NamedDimension(name="inline", size=2)
-    added_dims = builder._add_named_dimensions([inline_dim])
-    assert len(builder._dimensions) == 1
-    assert len(added_dims) == 1
-    assert contains_dimension(added_dims, inline_dim)
-
-    crossline_dim = NamedDimension(name="crossline", size=3)
-    time_dim = NamedDimension(name="time", size=4)
-    added_dims = builder._add_named_dimensions([crossline_dim, time_dim])
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert contains_dimension(added_dims, crossline_dim)
-    assert contains_dimension(added_dims, time_dim)
-
-    #
-    # Add invalid object type
-    #
-    with pytest.raises(TypeError, match="Expected NamedDimension or str, got int"):
-        builder._add_named_dimensions([42])
-        assert len(builder._dimensions) == 3
-
-    #
-    # Add dimensions with the same names again does nothing
-    # (make sure we are passing different instances)
-    #
-    inline_dim2 = NamedDimension(name=inline_dim.name, size=inline_dim.size)
-    crossline_dim2 = NamedDimension(name=crossline_dim.name, size=crossline_dim.size)
-    time_dim2 = NamedDimension(name=time_dim.name, size=time_dim.size)
-    added_dims = builder._add_named_dimensions([inline_dim2, crossline_dim2, time_dim2])
-    # Validate that the dimensions and variables are not duplicated
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert len(added_dims) == 0
-
-    # Add dimensions with the same name, but different size again
-    with pytest.raises(ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"):
-        inline_dim2 = NamedDimension(name="inline", size=200)
-        builder._add_named_dimensions([inline_dim2])
-        assert len(builder._dimensions) == 3
-    #
-    # Add existing dimension using its name
-    #
-    added_dims = builder._add_named_dimensions(["inline", "crossline"])
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert len(added_dims) == 0
-
-    #
-    # Add non-existing dimension using its name is not allowed
-    #
-    with pytest.raises(ValueError, match="Dimension named 'offset' is not found"):
-        builder._add_named_dimensions(["offset"])
-        assert len(builder._dimensions) == 3
-        assert contains_dimension(builder._dimensions, inline_dim)
-        assert contains_dimension(builder._dimensions, crossline_dim)
-        assert contains_dimension(builder._dimensions, time_dim)
-
-
-def test__to_dictionary() -> None:
-    """Test converting a BaseModel to a dictionary."""
-
-    with pytest.raises(TypeError, match="Expected BaseModel, got datetime"):
-        # This should raise an error because datetime is not a BaseModel
-        to_dictionary(datetime.now()) 
-
-    class SomeModel(StrictModel):
-        count: int = Field(default=None, description="Samples count")
-        samples: list[float] = Field(default_factory=list, description="Samples.")
-        created: datetime = Field(default_factory=datetime.now, description="Creation time with TZ info.")
-
-    m = SomeModel(  
-        count = 3,
-        samples = [1.0, 2.0, 3.0],
-        created = datetime(2023, 10, 1, 12, 0, 0, tzinfo=None)
-    )
-    result = to_dictionary(m)
-    assert isinstance(result, dict)
-    assert result == {'count': 3, 'created': '2023-10-01T12:00:00', 'samples': [1.0, 2.0, 3.0]}
-
-
-def test__make_VariableMetadata_from_list() -> None:
-    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
-
-    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
-    meta_list=[units, attrs] 
-
-    # TODO: I assume we do not want attribute.attribute in the contract:
-    # 'metadata': {'unitsV1': {'length': 'm'}, 'attributes': {'attributes': {'MGA': 51}}}
-    # TODO: Are multiple attributes allowed (I assume they are)?
-    metadata = MDIODatasetBuilder._make_VariableMetadata_from_list(meta_list)
-    assert isinstance(metadata, VariableMetadata)
-    assert metadata.units_v1.length == "ft"
-    assert metadata.attributes["MGA"] == 51 
-    assert metadata.attributes["UnitSystem"] == "Imperial"
-
-    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
-        meta_list = ["ft"]
-        MDIODatasetBuilder._make_VariableMetadata_from_list(meta_list)
-
-def test__make_VariableMetadata_from_dict() -> None:
-    """Test creating VariableMetadata from a dictionary."""
-
-    # TODO: What is the key for units: it unitsV1 or units_v1?
-    # TODO: Are multiple attributes allowed (I assume they are)?
-    # TODO: Do we validate the unit string supplied in dictionary parameters? What what if someone supplies ftUS instead of ft?
-    meta_dict={"unitsV1": {"length": "ft"}, "attributes": {"MGA": 51, "UnitSystem": "Imperial"}}
-    metadata = MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)
-    assert isinstance(metadata, VariableMetadata)
-    assert metadata.units_v1.length == "ft"
-    assert metadata.attributes["MGA"] == 51
-    assert metadata.attributes["UnitSystem"] == "Imperial"
-
-    with pytest.raises(TypeError, match="Unsupported metadata key: 'units_v1'. Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1."):
-        meta_dict = {"units_v1": "ft"}
-        MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)
-
-    with pytest.raises(TypeError, match="Invalid value for key 'attributes': 42. Expected a dictionary."):
-        meta_dict = {"attributes": 42}
-        MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict)  
-
-    # *** We currently do not validate the structure of the value dictionaries ***
-    # Pass unit object with invalid structure
-    # with pytest.raises(TypeError, match="Invalid value format for key 'unitsV1': {'length': 'm', 'time': 'sec'}. "):
-    #     meta_dict1 = {"unitsV1": {"length": "m", "time": "sec"}}
-    #     MDIODatasetBuilder._make_VariableMetadata_from_dict(meta_dict1)
-
-
-
diff --git a/tests/unit/v1/test_dataset_builder_state.py b/tests/unit/v1/test_dataset_builder_state.py
deleted file mode 100644
index 31c570a85..000000000
--- a/tests/unit/v1/test_dataset_builder_state.py
+++ /dev/null
@@ -1,88 +0,0 @@
-
-from datetime import datetime
-import pytest
-
-from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
-
-def test_builder_initialization() -> None:
-    """Test basic builder initialization."""
-    builder = MDIODatasetBuilder("test_dataset")
-    assert builder.name == "test_dataset"
-    assert builder.api_version == "1.0.0"
-    assert isinstance(builder.created_on, datetime)
-    assert len(builder._dimensions) == 0
-    assert len(builder._coordinates) == 0
-    assert len(builder._variables) == 0
-    assert builder._state == _BuilderState.INITIAL
-
-def test_builder_add_dimension_state() -> None:
-    """Test coordinate builder before and after add_dimension."""
-    builder = MDIODatasetBuilder("test_dataset")
-    assert builder._state == _BuilderState.INITIAL
-
-    # One should be able to add dimension any time after the builder has been created
-
-    # Add dimensions first
-    builder = builder.add_dimension("x", 100)
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    builder = builder.add_dimension("y", 200)
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-
-@pytest.mark.skip(reason="Under construction.")
-def test_coordinate_builder_state() -> None:
-    """Test coordinate builder state transitions and functionality."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    # Should not be able to add coordinates before dimensions
-    with pytest.raises(
-        ValueError, match="Must add at least one dimension before adding coordinates"
-    ):
-        builder.add_coordinate("x_coord", dimensions=["x"])
-
-    # Add dimensions first
-    builder = builder.add_dimension("x", 100)
-    builder = builder.add_dimension("y", 200)
-
-    # Adding coordinate should change state to HAS_COORDINATES
-    builder = builder.add_coordinate("x_coord", dimensions=["x"], long_name="X Coordinate")
-    assert builder._state == _BuilderState.HAS_COORDINATES
-    assert len(builder._coordinates) == 1  # noqa: PLR2004
-    assert builder._coordinates[0].name == "x_coord"
-    assert builder._coordinates[0].long_name == "X Coordinate"
-    assert builder._coordinates[0].dimensions[0].name == "x"
-
-    # Adding another coordinate should maintain state
-    builder = builder.add_coordinate("y_coord", dimensions=["y"])
-    assert builder._state == _BuilderState.HAS_COORDINATES
-    assert len(builder._coordinates) == 2  # noqa: PLR2004
-    assert builder._coordinates[1].name == "y_coord"
-    assert builder._coordinates[1].dimensions[0].name == "y"
-
-@pytest.mark.skip(reason="Under construction.")
-def test_variable_builder_state() -> None:
-    """Test variable builder state transitions and functionality."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    # Should not be able to add variables before dimensions
-    with pytest.raises(ValueError, match="Must add at least one dimension before adding variables"):
-        builder.add_variable("data", dimensions=["x"])
-
-    # Add dimension first
-    builder = builder.add_dimension("x", 100)
-
-    # Adding variable should change state to HAS_VARIABLES
-    builder = builder.add_variable("data", dimensions=["x"], long_name="Data Variable")
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    # One for dimension, one for variable
-    assert len(builder._variables) == 2  # noqa: PLR2004
-    assert builder._variables[1].name == "data"
-    assert builder._variables[1].long_name == "Data Variable"
-    assert builder._variables[1].dimensions[0].name == "x"
-
-    # Adding another variable should maintain state
-    builder = builder.add_variable("data2", dimensions=["x"])
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    # One for dimension, two for variables
-    assert len(builder._variables) == 3  # noqa: PLR2004
-    assert builder._variables[2].name == "data2"
-    assert builder._variables[2].dimensions[0].name == "x"
\ No newline at end of file

From e5261cb1af1a6cfadb6ddf9eac7c0c34bf544054 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Sat, 28 Jun 2025 00:11:13 +0000
Subject: [PATCH 19/56] Finished add_dimension, add_coordinate, add_variable

---
 DEVELOPER_NOTES.md                            |  16 +-
 src/mdio/schemas/v1/dataset_builder.py        |  60 +++++---
 .../v1/test_dataset_builder_add_coordinate.py |  31 ++--
 .../v1/test_dataset_builder_add_dimension.py  |  15 +-
 .../v1/test_dataset_builder_add_variable.py   | 143 ++++++++++--------
 tests/unit/v1/test_dataset_builder_helpers.py |  21 +--
 6 files changed, 167 insertions(+), 119 deletions(-)

diff --git a/DEVELOPER_NOTES.md b/DEVELOPER_NOTES.md
index 427801ee0..dec21dfe2 100644
--- a/DEVELOPER_NOTES.md
+++ b/DEVELOPER_NOTES.md
@@ -85,9 +85,11 @@ builder.add_dimension(
 * When a coordinate or a variable is created, their schema allows to store their dimensions either as
     * list of dimensions name `list[str]`, where the names refer to the dimensions defined in the builder._dimensions 
     * list of named dimensions `list[NamedDimension]`, which duplicate the dimensions defined in the builder._dimensions
-    * Mixture of the two above `list[NamedDimension | str]`  
+    * Mixture of the two above `list[NamedDimension | str]` 
 
-    We will be using the first approach.  
+    which approach should be used?  
+    
+    `RESOLUTION: We will be using the first approach.`
 
     **IMPORTANT: For binary compatibility, We need to ensure that the C++ code follows the same logic**
 
@@ -98,20 +100,25 @@ builder.add_dimension(
     def make_coordinate_metadata_list_from_dict(metadata: dict[str, Any]) -> CoordinateMetadataList:
         # Implementation goes here
     ```
+    `RESOLUTION: The approach confirmed.`
 
 ## Schema V1 questions
 
 * add_dimension(): Can a dimension with the same name be added multiple times. Options:
    * Allowed: the second request is ignored (current implementation)
-      * Adding a dimension with the same name, but the different size currently throws an error
    * Not Allowed: should it raise an error?
+
+    `RESOLUTION: The dimensions with the same name are not allowed`
 * The pydantic attribute names are different from the v1 schema attributes names.  What are the repercussions?
     ```
     'statsV1' <-> 'stats_v1'
     'unitsV1' <-> 'units_v1'
     'chunkGrid' <-> 'chunk_grid'
     ```
+    `Under investigation`
 * Should histogram (e.g., SummaryStatistics) have a `histogram_type` attribute?
+
+  `Under investigation`
 * Units
   * Why 'ftUS' is not supported by the schema? U.S. survey foot vs the International Foot:  
     *"The U.S. survey foot is defined as 1200/3937 meters, while the international foot is defined as exactly 0.3048 meters.
@@ -120,7 +127,10 @@ builder.add_dimension(
     This ... moves a State Plane coordinate position 4 feet by 12 feet."*
   * Why there are no dimensionless unis (for seismic amplitudes, inlines, etc.)
 
+  `Under investigation`
+
 ## Design suggestions
 * Should we rename add_dimension to add_dimension_variable (or similar) to indicate that we not just providing the dimension name, but also creating the dimension variable
 
+    `RESOLUTION: Shorter names are preferable for public API. The function behavior will be described in the docs`
 
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index b97ae7ee2..2cc65812b 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -10,7 +10,8 @@
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
 
-from mdio.schemas.compressors import ZFP, Blosc
+from mdio.schemas.compressors import ZFP
+from mdio.schemas.compressors import Blosc
 from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.dtype import StructuredType
@@ -18,13 +19,18 @@
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.units import AllUnits
-from mdio.schemas.v1.variable import Coordinate, CoordinateMetadata
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import CoordinateMetadata
 from mdio.schemas.v1.variable import Variable
 from mdio.schemas.v1.variable import VariableMetadata
 
+CoordinateMetadataList: TypeAlias = list[AllUnits |
+                                         UserAttributes]
+VariableMetadataList: TypeAlias = list[AllUnits |
+                                       UserAttributes |
+                                       ChunkGridMetadata |
+                                       StatisticsMetadata]
 
-CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
-VariableMetadataList: TypeAlias = list[AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata]
 
 class _BuilderState(Enum):
     """States for the template builder."""
@@ -68,7 +74,7 @@ def get_dimension(
     return nd
 
 
-def get_dimension_names( dimensions: list[NamedDimension | str]) -> list[str]:
+def get_dimension_names(dimensions: list[NamedDimension | str]) -> list[str]:
     """Get a dimension by name from the list."""
     names = []
     if dimensions is None:
@@ -88,10 +94,11 @@ def _to_dictionary(val: BaseModel) -> dict[str, Any]:
         raise TypeError(msg)
     return val.model_dump(mode="json", by_alias=True)
 
+
 def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> CoordinateMetadata | None:
     if metadata is None or not metadata:
         return None
-    
+
     metadata_dict = {}
     for md in metadata:
         # NOTE: the pydantic attribute names are different from the v1 schema attributes names
@@ -111,7 +118,7 @@ def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> Coordi
 def _make_variable_metadata(metadata: VariableMetadataList | None) -> VariableMetadata | None:
     if metadata is None or not metadata:
         return None
-    
+
     metadata_dict = {}
     for md in metadata:
         # NOTE: the pydantic attribute names are different from the v1 schema attributes names
@@ -133,6 +140,7 @@ def _make_variable_metadata(metadata: VariableMetadataList | None) -> VariableMe
             raise TypeError(msg)
     return VariableMetadata(**metadata_dict)
 
+
 class MDIODatasetBuilder:
     """Builder for creating MDIO datasets with enforced build order.
 
@@ -191,19 +199,25 @@ def add_dimension(  # noqa: PLR0913
         """Add a dimension.
 
         This must be called at least once before adding coordinates or variables.
+        This call will create a variable, if one does not yet exists
 
         Args:
             name: Name of the dimension
             size: Size of the dimension
-            long_name: Optional long name for the dimension variable
-            data_type: Data type for the dimension variable (defaults to INT32)
-            metadata_info: Optional metadata information for the dimension variable
+            var_long_name: Optional long name for the dimension variable
+            var_data_type: Data type for the dimension variable (defaults to INT32)
+            var_metadata_info: Optional metadata information for the dimension variable
 
         Returns:
             self: Returns self for method chaining
         """
         if not name:
-            raise ValueError("'name' must be a non-empty string")
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
+        old_var = next((e for e in self._dimensions if e.name == name), None)
+        if old_var is not None:
+            msg = "Adding dimension with the same name twice is not allowed"
+            raise ValueError(msg)
 
         added_dims = self._add_dimensions_if_needed(
             [NamedDimension(name=name, size=size)])
@@ -237,9 +251,15 @@ def add_coordinate(  # noqa: PLR0913
             msg = "Must add at least one dimension before adding coordinates"
             raise ValueError(msg)
         if not name:
-            raise ValueError("'name' must be a non-empty string")
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
         if dimensions is None or not dimensions:
-            raise ValueError("'dimensions' must be a non-empty list")
+            msg = "'dimensions' must be a non-empty list"
+            raise ValueError(msg)
+        old_var = next((e for e in self._coordinates if e.name == name), None)
+        if old_var is not None:
+            msg = "Adding coordinate with the same name twice is not allowed"
+            raise ValueError(msg)
 
         self._add_dimensions_if_needed(dimensions)
         dim_names = get_dimension_names(dimensions)
@@ -247,7 +267,8 @@ def add_coordinate(  # noqa: PLR0913
             Coordinate(
                 name=name,
                 longName=long_name,
-                dimensions=dim_names, # We ass names: sts, not list[NamedDimension | str]
+                # We ass names: sts, not list[NamedDimension | str]
+                dimensions=dim_names,
                 dataType=data_type,
                 metadata=_make_coordinate_metadata(metadata_info),
             )
@@ -255,7 +276,6 @@ def add_coordinate(  # noqa: PLR0913
         self._state = _BuilderState.HAS_COORDINATES
         return self
 
-
     def add_variable(  # noqa: PLR0913
         self,
         name: str,
@@ -272,9 +292,15 @@ def add_variable(  # noqa: PLR0913
             msg = "Must add at least one dimension before adding variables"
             raise ValueError(msg)
         if not name:
-            raise ValueError("'name' must be a non-empty string")
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
         if dimensions is None or not dimensions:
-            raise ValueError("'dimensions' must be a non-empty list")
+            msg = "'dimensions' must be a non-empty list"
+            raise ValueError(msg)
+        old_var = next((e for e in self._variables if e.name == name), None)
+        if old_var is not None:
+            msg = "Adding variable with the same name twice is not allowed"
+            raise ValueError(msg)
 
         self._add_dimensions_if_needed(dimensions)
         dim_names = get_dimension_names(dimensions)
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index b38da14be..659fedacf 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -6,17 +6,10 @@
 
 import pytest
 
-from mdio.schemas.chunk_grid import RegularChunkGrid
-from mdio.schemas.chunk_grid import RegularChunkShape
-from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import ScalarType
-from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, contains_dimension
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
-from mdio.schemas.v1.stats import CenteredBinHistogram
-from mdio.schemas.v1.stats import StatisticsMetadata
-from mdio.schemas.v1.stats import SummaryStatistics
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
@@ -27,8 +20,9 @@ def test_add_coordinate() -> None:
     builder = MDIODatasetBuilder("test_dataset")
     assert builder._state == _BuilderState.INITIAL
     
-    with pytest.raises(ValueError, match="Must add at least one dimension before adding coordinates"):
-        builder.add_coordinate("amplitude", dimensions=["speed"])
+    msg = "Must add at least one dimension before adding coordinates"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
 
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 100)
@@ -49,6 +43,11 @@ def test_add_coordinate() -> None:
     assert len(builder._variables) == 2 
     assert len(builder._coordinates) == 1  
 
+    # Adding coordinate with the same name twice
+    msg="Adding coordinate with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+
 def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
     builder = MDIODatasetBuilder("test_dataset")
@@ -59,10 +58,10 @@ def test_add_coordinate_with_defaults() -> None:
     assert len(builder._dimensions) == 2 
     assert len(builder._variables) == 2 
     assert len(builder._coordinates) == 1
-    # NOTE: add_variable() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
-    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    # NOTE: add_variable() stores dimensions as names
+    assert set(crd0.dimensions) == {"inline", "crossline"}
     assert crd0.long_name is None               # Default value
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata is None                # Default value
@@ -81,10 +80,10 @@ def test_coordinate_with_units() -> None:
     assert len(builder._dimensions) == 2 
     assert len(builder._variables) == 2  
     assert len(builder._coordinates) == 1 
-    # NOTE: add_coordinate() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
-    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    # NOTE: add_coordinate() stores dimensions as names
+    assert set(crd0.dimensions) == {"inline", "crossline"}
     assert crd0.long_name is None               # Default value
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata.attributes is None
@@ -108,7 +107,7 @@ def test_coordinate_with_attributes() -> None:
     # NOTE: add_coordinate() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
-    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert set(crd0.dimensions) == {"inline", "crossline"}
     assert crd0.long_name is None               # Default value
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata.attributes["MGA"] == 51
@@ -135,7 +134,7 @@ def test_coordinate_with_full_metadata() -> None:
     # NOTE: add_coordinate() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
-    assert set(crd0.dimensions) == set(["inline", "crossline"])
+    assert set(crd0.dimensions) == {"inline", "crossline"}
     assert crd0.long_name is None               # Default value
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata.attributes["MGA"] == 51
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index 7adebb4b5..6ff1f2590 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -40,17 +40,10 @@ def test_add_dimension() -> None:
     assert builder._dimensions[0] == NamedDimension(name="x", size=100)
     assert len(builder._variables) == 1  
 
-    # Adding a dimension with the same name as an existing dimension.
-    # Currently, it does not raise an error, but just ignores this call
-    builder.add_dimension("x", 100, var_long_name="X Dimension")
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 1  
-    assert len(builder._variables) == 1  
-
-    # Adding a dimension with the same name and different size throws an error
-    err_msg = "Dimension 'x' found but size 100 does not match expected size 200"
-    with pytest.raises(ValueError, match=err_msg):
-        builder.add_dimension("x", 200, var_long_name="X Dimension")
+    # Adding dimension with the same name twice
+    msg="Adding dimension with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_dimension("x", 200)
 
 def test_add_dimension_with_defaults() -> None:
     """Test dimension builder state transitions and functionality."""
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index bc168df21..7c0b46ba5 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -5,20 +5,31 @@
 """Tests the schema v1 Variable public API."""
 
 import pytest
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
 from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.variable import VariableMetadata
 
-def test_dataset_builder_add_variable() -> None:
+
+def test_add_variable() -> None:
     """Test adding variable. Check the state transition and validate required parameters.."""
     builder = MDIODatasetBuilder("test_dataset")
     assert builder._state == _BuilderState.INITIAL
     
-    with pytest.raises(ValueError, match="Must add at least one dimension before adding variables"):
+    msg = "Must add at least one dimension before adding variables"
+    with pytest.raises(ValueError, match=msg):
         builder.add_variable("amplitude", dimensions=["speed"])
 
     builder.add_dimension("inline", 100)
@@ -35,12 +46,18 @@ def test_dataset_builder_add_variable() -> None:
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
         builder.add_variable("amplitude", dimensions=[])
 
-    builder.add_variable("seismic_amplitude", dimensions=["inline", "crossline", "depth"])
+    builder.add_variable("amplitude", dimensions=["inline", "crossline", "depth"])
     assert builder._state == _BuilderState.HAS_VARIABLES
     assert len(builder._dimensions) == 3 
     assert len(builder._variables) == 4 
     assert len(builder._coordinates) == 0  
 
+    # Adding variable with the same name twice
+    msg="Adding variable with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable("amplitude", dimensions=["inline", "crossline", "depth"])
+
+
 def test_add_variable_with_defaults() -> None:
     """Test adding variable with default arguments."""
     builder = MDIODatasetBuilder("test_dataset")
@@ -55,69 +72,69 @@ def test_add_variable_with_defaults() -> None:
     var0 = next((e for e in builder._variables if e.name == "seismic_amplitude"), None)
     assert var0 is not None
     # NOTE: add_variable() stores dimensions as names
-    assert set(var0.dimensions) == set(["inline", "crossline", "depth"])
+    assert set(var0.dimensions) == {"inline", "crossline", "depth"}
     assert var0.long_name is None               # Default value
     assert var0.data_type == ScalarType.FLOAT32 # Default value
     assert var0.compressor is None              # Default value
     assert var0.coordinates is None             # Default value
     assert var0.metadata is None                # Default value
 
-# def test__make_variable_metadata() -> None:
-#     """Test creating VariableMetadata from a dictionary."""
-
-#     meta_dict = None
-#     metadata = make_variable_metadata_list(meta_dict)
-#     assert metadata is None
-
-#     meta_dict = {}
-#     metadata = make_variable_metadata_list(meta_dict)
-#     assert metadata is None
-
-#     meta_dict = {
-#         "unitsV1": {"length": "m"},
-#         "attributes": {"MGA": 51},
-#         "chunkGrid": {"name": "regular", "configuration": {"chunkShape": [20]}},
-#         "statsV1": {
-#             "count": 100,
-#             "sum": 1215.1,
-#             "sumSquares": 125.12,
-#             "min": 5.61,
-#             "max": 10.84,
-#             "histogram": {"binCenters": [1, 2], "counts": [10, 15]},
-#         },
-#     }
-#     metadata = make_variable_metadata_list(meta_dict)
-#     assert isinstance(metadata, VariableMetadata)
-#     assert metadata.units_v1.length == "m"
-#     assert metadata.attributes["MGA"] == 51  
-#     assert metadata.chunk_grid.name == "regular"
-#     assert metadata.chunk_grid.configuration.chunk_shape == [20]  
-#     assert metadata.stats_v1.count == 100  
-#     assert metadata.stats_v1.sum == 1215.1  
-#     assert metadata.stats_v1.sum_squares == 125.12  
-#     assert metadata.stats_v1.min == 5.61  
-#     assert metadata.stats_v1.max == 10.84  
-#     assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
-#     assert metadata.stats_v1.histogram.counts == [10, 15]  
-
-#     # NOTE: the v1 schema has 'units_v1' property, but pydantic requires 'unitsV1' for CamelCaseStrictModel
-#     meta_dict = {"units_v1": {"length": "m"}}
-#     err_msg = (
-#         "Unsupported metadata key: 'units_v1'. "
-#         "Expected 'unitsV1', 'attributes', 'chunkGrid', or 'statsV1."
-#     )
-#     with pytest.raises(TypeError, match=err_msg):
-#         make_variable_metadata_list(meta_dict)
-
-#     meta_dict = {"attributes": 42}
-#     with pytest.raises(
-#         TypeError, match="Invalid value for key 'attributes': 42. Expected a dictionary."
-#     ):
-#         make_variable_metadata_list(meta_dict)
+def test_add_variable_full_parameters() -> None:
+    """Test adding variable with full parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 100)
+    builder.add_dimension("depth", 100)
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
+    builder.add_variable("seismic_amplitude", 
+        long_name="Amplitude (dimensionless)",
+        dimensions=["inline", "crossline", "depth"],    
+        data_type=ScalarType.FLOAT64, 
+        compressor=Blosc(algorithm="zstd"), 
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+        ])
+    assert len(builder._dimensions) == 3
+    assert len(builder._coordinates) == 2  
+    assert len(builder._variables) == 4 
+    v = next((v for v in builder._variables if v.name == "seismic_amplitude"), None)
+    assert v is not None
+    assert v.long_name == "Amplitude (dimensionless)"
+    # NOTE: add_variable() stores dimensions as names
+    assert set(v.dimensions) == {"inline", "crossline", "depth"}
+    assert v.data_type == ScalarType.FLOAT64
+    assert isinstance(v.compressor, Blosc)
+    assert v.compressor.algorithm == "zstd"
+    # NOTE: add_variable() stores coordinates as names
+    assert set(v.coordinates) == {"inline", "crossline", "depth", "cdp-x", "cdp-y"}
+    assert v.metadata.stats_v1.count == 100 
+    assert isinstance(v.metadata, VariableMetadata)
+    assert v.metadata.units_v1.length == "ft"
+    assert v.metadata.attributes["MGA"] == 51
+    assert v.metadata.attributes["UnitSystem"] == "Imperial"  
+    assert v.metadata.chunk_grid.name == "regular"
+    assert v.metadata.chunk_grid.configuration.chunk_shape == [20]  
+    assert v.metadata.stats_v1.count == 100  
+    assert v.metadata.stats_v1.sum == 1215.1  
+    assert v.metadata.stats_v1.sum_squares == 125.12  
+    assert v.metadata.stats_v1.min == 5.61  
+    assert v.metadata.stats_v1.max == 10.84  
+    assert v.metadata.stats_v1.histogram.bin_centers == [1, 2]  
+    assert v.metadata.stats_v1.histogram.counts == [10, 15]  
 
-#     # *** We currently do not validate the structure of the value dictionaries ***
-#     # Pass unit object with invalid structure
-#     # with pytest.raises(
-#     # TypeError, match="Invalid value format for key 'unitsV1': {'length': 'm', 'time': 'sec'}. "):
-#     #     meta_dict1 = {"unitsV1": {"length": "m", "time": "sec"}}
-#     #     _make_VariableMetadata_from_dict(meta_dict1)
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index b9343b997..d3df78af3 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -10,30 +10,34 @@
 import pytest
 from pydantic import Field
 
-from mdio.schemas.chunk_grid import RegularChunkGrid, RegularChunkShape
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.core import StrictModel
 from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.metadata import ChunkGridMetadata
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _make_coordinate_metadata
-from mdio.schemas.v1.dataset_builder import get_dimension_names
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _make_coordinate_metadata
 from mdio.schemas.v1.dataset_builder import _make_variable_metadata
 from mdio.schemas.v1.dataset_builder import _to_dictionary
 from mdio.schemas.v1.dataset_builder import contains_dimension
 from mdio.schemas.v1.dataset_builder import get_dimension
-from mdio.schemas.v1.stats import CenteredBinHistogram, StatisticsMetadata, SummaryStatistics
+from mdio.schemas.v1.dataset_builder import get_dimension_names
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
-from mdio.schemas.v1.variable import AllUnits, CoordinateMetadata
+from mdio.schemas.v1.variable import AllUnits
+from mdio.schemas.v1.variable import CoordinateMetadata
 from mdio.schemas.v1.variable import UserAttributes
 from mdio.schemas.v1.variable import VariableMetadata
 
 
-def test__get_dimension() -> None:
+def test__get_dimension_by_name() -> None:
     """Test getting a dimension by name from the list of dimensions."""
     dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
 
     assert get_dimension([], "inline") is None
-
     assert get_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
     assert get_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
     assert get_dimension(dimensions, "time") is None
@@ -70,7 +74,6 @@ def test__contains_dimension() -> None:
 
 def test_get_dimension_names() -> None:
     """Test getting a list of dimension names from list[NamedDimension | str]."""
-
     empty_list = get_dimension_names(None)
     assert empty_list is not None
     assert isinstance(empty_list, list)
@@ -88,7 +91,7 @@ def test_get_dimension_names() -> None:
     ])
     assert dim_list is not None
     assert isinstance(dim_list, list)
-    assert set(dim_list) == set(["inline", "amplitude", "crossline"])
+    assert set(dim_list) == {"inline", "amplitude", "crossline"}
 
 
 def test_add_dimensions_if_needed() -> None:

From 95c01d8c02b9bf62f237097d86e358ed6a368406 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 30 Jun 2025 16:09:13 -0500
Subject: [PATCH 20/56] Work on build

---
 src/mdio/schemas/v1/dataset_builder.py        | 170 +++++++++++++++---
 tests/unit/v1/test_dataset_builder_helpers.py |   8 +
 2 files changed, 155 insertions(+), 23 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 2cc65812b..7db49947c 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -7,6 +7,8 @@
 from typing import Any
 from typing import TypeAlias
 
+import xarray as xr
+
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
 
@@ -23,6 +25,8 @@
 from mdio.schemas.v1.variable import CoordinateMetadata
 from mdio.schemas.v1.variable import Variable
 from mdio.schemas.v1.variable import VariableMetadata
+from mdio.schemas.v1.dataset import Dataset, DatasetInfo
+from mdio.schemas.v1.dataset import DatasetMetadata
 
 CoordinateMetadataList: TypeAlias = list[AllUnits |
                                          UserAttributes]
@@ -30,8 +34,8 @@
                                        UserAttributes |
                                        ChunkGridMetadata |
                                        StatisticsMetadata]
-
-
+DatasetMetadataList: TypeAlias = list[DatasetInfo |
+                                       UserAttributes ]
 class _BuilderState(Enum):
     """States for the template builder."""
 
@@ -87,12 +91,14 @@ def get_dimension_names(dimensions: list[NamedDimension | str]) -> list[str]:
     return names
 
 
-def _to_dictionary(val: BaseModel) -> dict[str, Any]:
-    """Convert a pydantic BaseModel to a dictionary."""
-    if not isinstance(val, BaseModel):
-        msg = f"Expected BaseModel, got {type(val).__name__}"
-        raise TypeError(msg)
-    return val.model_dump(mode="json", by_alias=True)
+def _to_dictionary(val: BaseModel | dict[str, Any]) -> dict[str, Any]:
+    """Convert a dictionary or pydantic BaseModel to a dictionary."""
+    if isinstance(val, BaseModel):
+        return val.model_dump(mode="json", by_alias=True)
+    if isinstance(val, dict):
+        return val
+    msg = f"Expected BaseModel, got {type(val).__name__}"
+    raise TypeError(msg)
 
 
 def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> CoordinateMetadata | None:
@@ -104,11 +110,10 @@ def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> Coordi
         # NOTE: the pydantic attribute names are different from the v1 schema attributes names
         #       'unitsV1' <-> 'units_v1'
         if isinstance(md, AllUnits):
-            val = md.units_v1
-            metadata_dict["unitsV1"] = _to_dictionary(val)
+            metadata_dict["unitsV1"] = _to_dictionary(md.units_v1)
         elif isinstance(md, UserAttributes):
             # NOTE: md.attributes is not pydantic type, but a dictionary
-            metadata_dict["attributes"] = _to_dictionary(md)["attributes"]
+            metadata_dict["attributes"] = _to_dictionary(md.attributes)
         else:
             msg = f"Unsupported metadata type: {type(md)}"
             raise TypeError(msg)
@@ -124,22 +129,38 @@ def _make_variable_metadata(metadata: VariableMetadataList | None) -> VariableMe
         # NOTE: the pydantic attribute names are different from the v1 schema attributes names
         #       'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
         if isinstance(md, AllUnits):
-            val = md.units_v1
-            metadata_dict["unitsV1"] = _to_dictionary(val)
+            metadata_dict["unitsV1"] = _to_dictionary(md.units_v1)
         elif isinstance(md, UserAttributes):
             # NOTE: md.attributes is not pydantic type, but a dictionary
-            metadata_dict["attributes"] = _to_dictionary(md)["attributes"]
+            metadata_dict["attributes"] = _to_dictionary(md.attributes)
         elif isinstance(md, ChunkGridMetadata):
-            val = md.chunk_grid
-            metadata_dict["chunkGrid"] = _to_dictionary(val)
+            metadata_dict["chunkGrid"] = _to_dictionary(md.chunk_grid)
         elif isinstance(md, StatisticsMetadata):
-            val = md.stats_v1
-            metadata_dict["statsV1"] = _to_dictionary(val)
+            metadata_dict["statsV1"] = _to_dictionary(md.stats_v1)
         else:
             msg = f"Unsupported metadata type: {type(md)}"
             raise TypeError(msg)
     return VariableMetadata(**metadata_dict)
 
+def _make_datasetinfo_metadata(metadata: DatasetInfo | None) -> DatasetMetadata | None:
+    if metadata is None or not metadata:
+        return None
+
+    metadata_dict = {}
+    for md in metadata:
+        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
+        #       'apiVersion' <-> 'api_version', 'created_on' <-> 'createdOn'
+        if isinstance(md, DatasetInfo):
+            metadata_dict["name"] = md.name
+            metadata_dict["apiVersion"] = _to_dictionary(md.api_version)
+            metadata_dict["createdOn"] = _to_dictionary(md.created_on)
+        elif isinstance(md, UserAttributes):
+            # NOTE: md.attributes is not pydantic type, but a dictionary
+            metadata_dict["attributes"] = _to_dictionary(md.attributes)
+        else:
+            msg = f"Unsupported metadata type: {type(md)}"
+            raise TypeError(msg)
+    return DatasetMetadata(**metadata_dict)
 
 class MDIODatasetBuilder:
     """Builder for creating MDIO datasets with enforced build order.
@@ -152,12 +173,14 @@ class MDIODatasetBuilder:
     4. Must call build() to create the dataset.
     """
 
-    def __init__(self, name: str, attributes: dict[str, Any] | None = None):
-        self.name = name
+    def __init__(self, name: str, attributes: UserAttributes | None = None):
+
         # TODO(BrianMichell, #0): Pull from package metadata
-        self.api_version = "1.0.0"
-        self.created_on = datetime.now(UTC)
-        self.attributes = attributes
+        self._info = DatasetInfo(
+            name=name,
+            api_version="1.0.0",
+            created_on= datetime.now(UTC)),
+        self._attributes = attributes
         self._dimensions: list[NamedDimension] = []
         self._coordinates: list[Coordinate] = []
         self._variables: list[Variable] = []
@@ -317,3 +340,104 @@ def add_variable(  # noqa: PLR0913
         )
         self._state = _BuilderState.HAS_VARIABLES
         return self
+
+    def build(self) -> Dataset:
+        """Build the final dataset."""
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before building"
+            raise ValueError(msg)
+
+        return Dataset(
+            variables=self._variables,
+            metadata=DatasetMetadata(self._info, 
+                                     self._attributes)
+        )
+
+
+    # def to_mdio(
+    #     self,
+    #     store: str,
+    #     mode: str = "w",
+    #     compute: bool = False,
+    #     **kwargs: Mapping[str, str | int | float | bool],
+    # ) -> Dataset:
+    #     """Write the dataset to a Zarr store and return the constructed mdio.Dataset.
+
+    #     This function constructs an mdio.Dataset from the MDIO dataset and writes its metadata
+    #     to a Zarr store. The actual data is not written, only the metadata structure is created.
+    #     """
+    #     return write_mdio_metadata(self.build(), store, mode, compute, **kwargs)
+
+# def write_mdio_metadata(
+#     mdio_ds: Dataset,
+#     store: str,
+#     mode: str = "w",
+#     compute: bool = False,
+#     **kwargs: Mapping[str, str | int | float | bool],
+# ) -> mdio.Dataset:
+#     """Write MDIO metadata to a Zarr store and return the constructed mdio.Dataset.
+
+#     This function constructs an mdio.Dataset from the MDIO dataset and writes its metadata
+#     to a Zarr store. The actual data is not written, only the metadata structure is created.
+
+#     Args:
+#         mdio_ds: The MDIO dataset to serialize
+#         store: Path to the Zarr or .mdio store
+#         mode: Write mode to pass to to_mdio(), e.g. 'w' or 'a'
+#         compute: Whether to compute (write) array chunks (True) or only metadata (False)
+#         **kwargs: Additional arguments to pass to to_mdio()
+
+#     Returns:
+#         The constructed xarray Dataset with MDIO extensions
+#     """
+#     ds = _construct_mdio_dataset(mdio_ds)
+
+#     def _generate_encodings() -> dict:
+#         """Generate encodings for each variable in the MDIO dataset.
+
+#         Returns:
+#             Dictionary mapping variable names to their encoding configurations.
+#         """
+#         # TODO(Anybody, #10274): Re-enable chunk_key_encoding when supported by xarray
+#         # dimension_separator_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
+        
+#         # Collect dimension sizes (same approach as _construct_mdio_dataset)
+#         dims: dict[str, int] = {}
+#         for var in mdio_ds.variables:
+#             for d in var.dimensions:
+#                 if isinstance(d, NamedDimension):
+#                     dims[d.name] = d.size
+        
+#         global_encodings = {}
+#         for var in mdio_ds.variables:
+#             fill_value = 0
+#             if isinstance(var.data_type, StructuredType):
+#                 continue
+#             chunks = None
+#             if var.metadata is not None and var.metadata.chunk_grid is not None:
+#                 chunks = var.metadata.chunk_grid.configuration.chunk_shape
+#             else:
+#                 # When no chunk_grid is provided, set chunks to shape to avoid chunking
+#                 dim_names = [d.name if isinstance(d, NamedDimension) else d for d in var.dimensions]
+#                 chunks = tuple(dims[name] for name in dim_names)
+#             global_encodings[var.name] = {
+#                 "chunks": chunks,
+#                 # TODO(Anybody, #10274): Re-enable chunk_key_encoding when supported by xarray
+#                 # "chunk_key_encoding": dimension_separator_encoding,
+#                 "_FillValue": fill_value,
+#                 "dtype": var.data_type,
+#                 "compressors": _convert_compressor(var.compressor),
+#             }
+#         return global_encodings
+
+#     ds.to_mdio(
+#         store,
+#         mode=mode,
+#         zarr_format=2,
+#         consolidated=True,
+#         safe_chunks=False,
+#         compute=compute,
+#         encoding=_generate_encodings(),
+#         **kwargs,
+#     )
+#     return ds
\ No newline at end of file
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index d3df78af3..fdaef83d5 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -214,6 +214,14 @@ class SomeModel(StrictModel):
     assert isinstance(result, dict)
     assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
 
+    d = {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)}
+    result = _to_dictionary(m)
+    assert isinstance(result, dict)
+    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
+
 
 def test__make_coordinate_metadata() -> None:
     """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""

From 46f82f01b9f0491d763cded3da1dca289406286a Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Tue, 1 Jul 2025 16:23:56 +0000
Subject: [PATCH 21/56] Generalize _to_dictionary()

---
 .devcontainer/devcontainer.json               |   3 +-
 src/mdio/schemas/v1/dataset_builder.py        | 105 +++++------------
 tests/unit/v1/test_dataset_builder_build.py   |  53 +++++++++
 tests/unit/v1/test_dataset_builder_helpers.py | 106 +++++++++---------
 4 files changed, 135 insertions(+), 132 deletions(-)
 create mode 100644 tests/unit/v1/test_dataset_builder_build.py

diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index ea5dc99ef..dc80446c6 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -29,7 +29,8 @@
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
         "streetsidesoftware.code-spell-checker",
-        "eamodio.gitlens"
+        "eamodio.gitlens",
+        "visualstudioexptteam.vscodeintellicode"
       ]
     }
   },
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 7db49947c..8b885b288 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -28,14 +28,17 @@
 from mdio.schemas.v1.dataset import Dataset, DatasetInfo
 from mdio.schemas.v1.dataset import DatasetMetadata
 
-CoordinateMetadataList: TypeAlias = list[AllUnits |
-                                         UserAttributes]
+AnyMetadataList : TypeAlias = list[AllUnits | 
+                               UserAttributes |
+                               ChunkGridMetadata |
+                               StatisticsMetadata | 
+                               DatasetInfo]
+CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
 VariableMetadataList: TypeAlias = list[AllUnits |
                                        UserAttributes |
                                        ChunkGridMetadata |
                                        StatisticsMetadata]
-DatasetMetadataList: TypeAlias = list[DatasetInfo |
-                                       UserAttributes ]
+DatasetMetadataList: TypeAlias = list[DatasetInfo | UserAttributes]
 class _BuilderState(Enum):
     """States for the template builder."""
 
@@ -91,77 +94,24 @@ def get_dimension_names(dimensions: list[NamedDimension | str]) -> list[str]:
     return names
 
 
-def _to_dictionary(val: BaseModel | dict[str, Any]) -> dict[str, Any]:
-    """Convert a dictionary or pydantic BaseModel to a dictionary."""
+def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList)-> dict[str, Any]:
+    """Convert a dictionary, list or pydantic BaseModel to a dictionary."""
+    if val is None:
+        return None
     if isinstance(val, BaseModel):
         return val.model_dump(mode="json", by_alias=True)
     if isinstance(val, dict):
         return val
-    msg = f"Expected BaseModel, got {type(val).__name__}"
+    if isinstance(val, list):
+        metadata_dict = {}
+        for md in val:
+            if md is None:
+                continue
+            metadata_dict.update(_to_dictionary(md))
+        return metadata_dict
+    msg = f"Expected BaseModel, dict or list, got {type(val).__name__}"
     raise TypeError(msg)
 
-
-def _make_coordinate_metadata(metadata: CoordinateMetadataList | None) -> CoordinateMetadata | None:
-    if metadata is None or not metadata:
-        return None
-
-    metadata_dict = {}
-    for md in metadata:
-        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
-        #       'unitsV1' <-> 'units_v1'
-        if isinstance(md, AllUnits):
-            metadata_dict["unitsV1"] = _to_dictionary(md.units_v1)
-        elif isinstance(md, UserAttributes):
-            # NOTE: md.attributes is not pydantic type, but a dictionary
-            metadata_dict["attributes"] = _to_dictionary(md.attributes)
-        else:
-            msg = f"Unsupported metadata type: {type(md)}"
-            raise TypeError(msg)
-    return CoordinateMetadata(**metadata_dict)
-
-
-def _make_variable_metadata(metadata: VariableMetadataList | None) -> VariableMetadata | None:
-    if metadata is None or not metadata:
-        return None
-
-    metadata_dict = {}
-    for md in metadata:
-        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
-        #       'statsV1' <-> 'stats_v1', 'unitsV1' <-> 'units_v1', 'chunkGrid' <-> 'chunk_grid'
-        if isinstance(md, AllUnits):
-            metadata_dict["unitsV1"] = _to_dictionary(md.units_v1)
-        elif isinstance(md, UserAttributes):
-            # NOTE: md.attributes is not pydantic type, but a dictionary
-            metadata_dict["attributes"] = _to_dictionary(md.attributes)
-        elif isinstance(md, ChunkGridMetadata):
-            metadata_dict["chunkGrid"] = _to_dictionary(md.chunk_grid)
-        elif isinstance(md, StatisticsMetadata):
-            metadata_dict["statsV1"] = _to_dictionary(md.stats_v1)
-        else:
-            msg = f"Unsupported metadata type: {type(md)}"
-            raise TypeError(msg)
-    return VariableMetadata(**metadata_dict)
-
-def _make_datasetinfo_metadata(metadata: DatasetInfo | None) -> DatasetMetadata | None:
-    if metadata is None or not metadata:
-        return None
-
-    metadata_dict = {}
-    for md in metadata:
-        # NOTE: the pydantic attribute names are different from the v1 schema attributes names
-        #       'apiVersion' <-> 'api_version', 'created_on' <-> 'createdOn'
-        if isinstance(md, DatasetInfo):
-            metadata_dict["name"] = md.name
-            metadata_dict["apiVersion"] = _to_dictionary(md.api_version)
-            metadata_dict["createdOn"] = _to_dictionary(md.created_on)
-        elif isinstance(md, UserAttributes):
-            # NOTE: md.attributes is not pydantic type, but a dictionary
-            metadata_dict["attributes"] = _to_dictionary(md.attributes)
-        else:
-            msg = f"Unsupported metadata type: {type(md)}"
-            raise TypeError(msg)
-    return DatasetMetadata(**metadata_dict)
-
 class MDIODatasetBuilder:
     """Builder for creating MDIO datasets with enforced build order.
 
@@ -175,11 +125,13 @@ class MDIODatasetBuilder:
 
     def __init__(self, name: str, attributes: UserAttributes | None = None):
 
-        # TODO(BrianMichell, #0): Pull from package metadata
-        self._info = DatasetInfo(
+        info = DatasetInfo(
             name=name,
             api_version="1.0.0",
-            created_on= datetime.now(UTC)),
+            created_on=datetime.now(UTC)
+        )
+        # TODO(BrianMichell, #0): Pull from package metadata
+        self._info = info
         self._attributes = attributes
         self._dimensions: list[NamedDimension] = []
         self._coordinates: list[Coordinate] = []
@@ -253,7 +205,7 @@ def add_dimension(  # noqa: PLR0913
                 dataType=var_data_type,
                 compressor=None,
                 coordinates=None,
-                metadata=_make_variable_metadata(var_metadata_info),
+                metadata=_to_dictionary(var_metadata_info),
             )
             self._variables.append(dim_var)
 
@@ -293,7 +245,7 @@ def add_coordinate(  # noqa: PLR0913
                 # We ass names: sts, not list[NamedDimension | str]
                 dimensions=dim_names,
                 dataType=data_type,
-                metadata=_make_coordinate_metadata(metadata_info),
+                metadata=_to_dictionary(metadata_info),
             )
         )
         self._state = _BuilderState.HAS_COORDINATES
@@ -335,7 +287,7 @@ def add_variable(  # noqa: PLR0913
                 data_type=data_type,
                 compressor=compressor,
                 coordinates=coordinates,
-                metadata=_make_variable_metadata(metadata_info),
+                metadata=_to_dictionary(metadata_info),
             )
         )
         self._state = _BuilderState.HAS_VARIABLES
@@ -349,8 +301,7 @@ def build(self) -> Dataset:
 
         return Dataset(
             variables=self._variables,
-            metadata=DatasetMetadata(self._info, 
-                                     self._attributes)
+            metadata=_to_dictionary([self._info, self._attributes])
         )
 
 
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
new file mode 100644
index 000000000..ab2d64af2
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -0,0 +1,53 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_coordinate() public API."""
+
+from datetime import UTC, datetime
+import pytest
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import DatasetInfo, DatasetMetadata
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.variable import VariableMetadata
+
+def test_build() -> None:
+    """Test adding coordinates. Check the state transition and validate required parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+
+    builder.add_dimension("x", 100)
+    builder.add_dimension("y", 100)
+
+    builder.build()
+
+def test_play() -> None:
+    """Test adding coordinates. Check the state transition and validate required parameters."""
+    # builder = MDIODatasetBuilder("test_dataset")
+
+    u = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+    
+    u_dict = u.model_dump(mode="json", by_alias=True)
+    vm = VariableMetadata(**u_dict)
+    vm_dict = vm.dict()
+    vm_json = vm.model_dump(mode="json", by_alias=True)
+
+#     vm = VariableMetadata(u)
+    
+#     dInfo = DatasetInfo(
+#             name="My Dataset",
+#             api_version="1.0.0",
+#             created_on= datetime.now(UTC)),
+    
+#     d = dict(dInfo.model_dump(mode="json", by_alias=True))
+ 
+#     meta = DatasetMetadata(d)
+#     print(dInfo.dict())
+
+#     i = 0
\ No newline at end of file
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index fdaef83d5..e5078a5ef 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -16,8 +16,6 @@
 from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
-from mdio.schemas.v1.dataset_builder import _make_coordinate_metadata
-from mdio.schemas.v1.dataset_builder import _make_variable_metadata
 from mdio.schemas.v1.dataset_builder import _to_dictionary
 from mdio.schemas.v1.dataset_builder import contains_dimension
 from mdio.schemas.v1.dataset_builder import get_dimension
@@ -196,7 +194,7 @@ def test__add_dimensions_if_needed_when_one_already_exists() -> None:
 
 def test__to_dictionary() -> None:
     """Test converting a BaseModel to a dictionary."""
-    with pytest.raises(TypeError, match="Expected BaseModel, got datetime"):
+    with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got datetime"):
         # This should raise an error because datetime is not a BaseModel
         _to_dictionary(datetime.now(UTC))
 
@@ -223,54 +221,54 @@ class SomeModel(StrictModel):
     assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
 
 
-def test__make_coordinate_metadata() -> None:
-    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
-    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
-    meta_list = [units, attrs]
-
-    # Assume that multiple attributes are allowed
-    metadata = _make_coordinate_metadata(meta_list)
-    assert isinstance(metadata, CoordinateMetadata)
-    assert metadata.units_v1.length == "ft"
-    assert metadata.attributes["MGA"] == 51
-    assert metadata.attributes["UnitSystem"] == "Imperial"
-
-    meta_list = ["ft"]
-    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
-        _make_variable_metadata(meta_list)
-
-def test__make_variable_metadata() -> None:
-    """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
-    units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-    attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
-    chgrd = ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[20])))
-    stats = StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])))
-    metadata_info = [units, attrs, chgrd, stats]
-    metadata = _make_variable_metadata(metadata_info)
-    assert isinstance(metadata, VariableMetadata)
-    assert metadata.units_v1.length == "ft"
-    assert metadata.attributes["MGA"] == 51  
-    assert metadata.attributes["UnitSystem"] == "Imperial"  
-    assert metadata.chunk_grid.name == "regular"
-    assert metadata.chunk_grid.configuration.chunk_shape == [20]  
-    assert metadata.stats_v1.count == 100  
-    assert metadata.stats_v1.sum == 1215.1  
-    assert metadata.stats_v1.sum_squares == 125.12  
-    assert metadata.stats_v1.min == 5.61  
-    assert metadata.stats_v1.max == 10.84  
-    assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
-    assert metadata.stats_v1.histogram.counts == [10, 15]  
-
-    meta_list = ["ft"]
-    with pytest.raises(TypeError, match="Unsupported metadata type: <class 'str'>"):
-        _make_variable_metadata(meta_list)
+# def test__make_coordinate_metadata() -> None:
+#     """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
+#     units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+#     attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
+#     meta_list = [units, attrs]
+
+#     # Assume that multiple attributes are allowed
+#     metadata = _make_coordinate_metadata(meta_list)
+#     assert isinstance(metadata, CoordinateMetadata)
+#     assert metadata.units_v1.length == "ft"
+#     assert metadata.attributes["MGA"] == 51
+#     assert metadata.attributes["UnitSystem"] == "Imperial"
+
+#     meta_list = ["ft"]
+#     with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got str"):
+#         _make_variable_metadata(meta_list)
+
+# def test__make_variable_metadata() -> None:
+#     """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
+#     units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+#     attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
+#     chgrd = ChunkGridMetadata(
+#                 chunk_grid=RegularChunkGrid(
+#                     configuration=RegularChunkShape(chunk_shape=[20])))
+#     stats = StatisticsMetadata(
+#                 stats_v1=SummaryStatistics(
+#                     count=100,
+#                     sum=1215.1,
+#                     sumSquares=125.12,
+#                     min=5.61,
+#                     max=10.84,
+#                     histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])))
+#     metadata_info = [units, attrs, chgrd, stats]
+#     metadata = _make_variable_metadata(metadata_info)
+#     assert isinstance(metadata, VariableMetadata)
+#     assert metadata.units_v1.length == "ft"
+#     assert metadata.attributes["MGA"] == 51  
+#     assert metadata.attributes["UnitSystem"] == "Imperial"  
+#     assert metadata.chunk_grid.name == "regular"
+#     assert metadata.chunk_grid.configuration.chunk_shape == [20]  
+#     assert metadata.stats_v1.count == 100  
+#     assert metadata.stats_v1.sum == 1215.1  
+#     assert metadata.stats_v1.sum_squares == 125.12  
+#     assert metadata.stats_v1.min == 5.61  
+#     assert metadata.stats_v1.max == 10.84  
+#     assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
+#     assert metadata.stats_v1.histogram.counts == [10, 15]  
+
+#     meta_list = ["ft"]
+#     with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got str"):
+#         _make_variable_metadata(meta_list)

From 0dc7cc86856dbdc234760cc36b898a2cb6e9a9e2 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Tue, 1 Jul 2025 23:37:52 +0000
Subject: [PATCH 22/56] build

---
 src/mdio/schemas/v1/dataset_builder.py        |  78 ++++--
 .../v1/test_dataset_builder_add_coordinate.py |  24 +-
 .../v1/test_dataset_builder_add_dimension.py  |   5 +
 .../v1/test_dataset_builder_add_variable.py   |   4 +-
 tests/unit/v1/test_dataset_builder_build.py   | 258 ++++++++++++++++--
 tests/unit/v1/test_dataset_builder_helpers.py |   2 +-
 6 files changed, 309 insertions(+), 62 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 8b885b288..8b1698789 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -28,17 +28,19 @@
 from mdio.schemas.v1.dataset import Dataset, DatasetInfo
 from mdio.schemas.v1.dataset import DatasetMetadata
 
-AnyMetadataList : TypeAlias = list[AllUnits | 
-                               UserAttributes |
-                               ChunkGridMetadata |
-                               StatisticsMetadata | 
-                               DatasetInfo]
+AnyMetadataList: TypeAlias = list[AllUnits |
+                                  UserAttributes |
+                                  ChunkGridMetadata |
+                                  StatisticsMetadata |
+                                  DatasetInfo]
 CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
 VariableMetadataList: TypeAlias = list[AllUnits |
                                        UserAttributes |
                                        ChunkGridMetadata |
                                        StatisticsMetadata]
 DatasetMetadataList: TypeAlias = list[DatasetInfo | UserAttributes]
+
+
 class _BuilderState(Enum):
     """States for the template builder."""
 
@@ -94,7 +96,7 @@ def get_dimension_names(dimensions: list[NamedDimension | str]) -> list[str]:
     return names
 
 
-def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList)-> dict[str, Any]:
+def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList) -> dict[str, Any]:
     """Convert a dictionary, list or pydantic BaseModel to a dictionary."""
     if val is None:
         return None
@@ -112,6 +114,7 @@ def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList)-> dict[str
     msg = f"Expected BaseModel, dict or list, got {type(val).__name__}"
     raise TypeError(msg)
 
+
 class MDIODatasetBuilder:
     """Builder for creating MDIO datasets with enforced build order.
 
@@ -194,18 +197,21 @@ def add_dimension(  # noqa: PLR0913
             msg = "Adding dimension with the same name twice is not allowed"
             raise ValueError(msg)
 
-        added_dims = self._add_dimensions_if_needed(
-            [NamedDimension(name=name, size=size)])
+        added_dims = self._add_dimensions_if_needed([NamedDimension(name=name, size=size)])
         if added_dims:
+            meta_dict = _to_dictionary(var_metadata_info)
             # Create a variable for the dimension
             dim_var = Variable(
                 name=name,
                 longName=var_long_name,
+                # IMPORTANT: we always use NamedDimension here, not the dimension name
+                # Since the Dataset does not have a dimension list, we need to preserve NamedDimension
+                # somewhere. Namely, in the variable created for the dimension
                 dimensions=added_dims,
                 dataType=var_data_type,
                 compressor=None,
                 coordinates=None,
-                metadata=_to_dictionary(var_metadata_info),
+                metadata=meta_dict,
             )
             self._variables.append(dim_var)
 
@@ -217,6 +223,7 @@ def add_coordinate(  # noqa: PLR0913
         name: str,
         *,
         long_name: str = None,
+        #TODO Only allow adding dimensions by name, not by NamedDimension object
         dimensions: list[NamedDimension | str],
         data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
         metadata_info: CoordinateMetadataList | None = None,
@@ -238,16 +245,33 @@ def add_coordinate(  # noqa: PLR0913
 
         self._add_dimensions_if_needed(dimensions)
         dim_names = get_dimension_names(dimensions)
-        self._coordinates.append(
-            Coordinate(
-                name=name,
-                longName=long_name,
-                # We ass names: sts, not list[NamedDimension | str]
-                dimensions=dim_names,
-                dataType=data_type,
-                metadata=_to_dictionary(metadata_info),
-            )
+        meta_dict = _to_dictionary(metadata_info)
+        coord = Coordinate(
+            name=name,
+            longName=long_name,
+            # We ass names: sts, not list[NamedDimension | str]
+            dimensions=dim_names,
+            dataType=data_type,
+            metadata=meta_dict
+        )
+        self._coordinates.append(coord)
+
+        # Add coordinate as variables to the dataset
+        var_meta_dict = _to_dictionary(coord.metadata)
+        coord_var = Variable(
+            name=coord.name,
+            longName=coord.long_name,
+            dimensions=coord.dimensions,
+            dataType=coord.data_type,
+            compressor=None,
+            # IMPORTANT: we always use Coordinate here, not the coordinate name
+            # Since the Dataset does not have a coordinate list, we need to preserve Coordinate
+            # somewhere. Namely, in the variable created for the coordinate
+            coordinates=[coord],
+            metadata=var_meta_dict
         )
+        self._variables.append(coord_var)
+
         self._state = _BuilderState.HAS_COORDINATES
         return self
 
@@ -256,9 +280,11 @@ def add_variable(  # noqa: PLR0913
         name: str,
         *,
         long_name: str = None,
+        #TODO Only allow adding dimensions by name, not by NamedDimension object
         dimensions: list[NamedDimension | str],
         data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
         compressor: Blosc | ZFP | None = None,
+        #TODO Only allow adding coordinates by name, not by Coordinate object
         coordinates: list[Coordinate | str] | None = None,
         metadata_info: VariableMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
@@ -279,6 +305,7 @@ def add_variable(  # noqa: PLR0913
 
         self._add_dimensions_if_needed(dimensions)
         dim_names = get_dimension_names(dimensions)
+        meta_dict = _to_dictionary(metadata_info)
         self._variables.append(
             Variable(
                 name=name,
@@ -287,7 +314,7 @@ def add_variable(  # noqa: PLR0913
                 data_type=data_type,
                 compressor=compressor,
                 coordinates=coordinates,
-                metadata=_to_dictionary(metadata_info),
+                metadata=meta_dict,
             )
         )
         self._state = _BuilderState.HAS_VARIABLES
@@ -299,11 +326,10 @@ def build(self) -> Dataset:
             msg = "Must add at least one dimension before building"
             raise ValueError(msg)
 
-        return Dataset(
-            variables=self._variables,
-            metadata=_to_dictionary([self._info, self._attributes])
-        )
+        var_meta_dict = _to_dictionary([self._info, self._attributes])
+        dataset = Dataset(variables=self._variables, metadata=var_meta_dict)
 
+        return dataset
 
     # def to_mdio(
     #     self,
@@ -351,14 +377,14 @@ def build(self) -> Dataset:
 #         """
 #         # TODO(Anybody, #10274): Re-enable chunk_key_encoding when supported by xarray
 #         # dimension_separator_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
-        
+
 #         # Collect dimension sizes (same approach as _construct_mdio_dataset)
 #         dims: dict[str, int] = {}
 #         for var in mdio_ds.variables:
 #             for d in var.dimensions:
 #                 if isinstance(d, NamedDimension):
 #                     dims[d.name] = d.size
-        
+
 #         global_encodings = {}
 #         for var in mdio_ds.variables:
 #             fill_value = 0
@@ -391,4 +417,4 @@ def build(self) -> Dataset:
 #         encoding=_generate_encodings(),
 #         **kwargs,
 #     )
-#     return ds
\ No newline at end of file
+#     return ds
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 659fedacf..e6fa4bcf1 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -40,8 +40,16 @@ def test_add_coordinate() -> None:
     builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
     assert builder._state == _BuilderState.HAS_COORDINATES
     assert len(builder._dimensions) == 2 
-    assert len(builder._variables) == 2 
-    assert len(builder._coordinates) == 1  
+    # 2 variables for dimensions, 1 variable for coordinates
+    assert len(builder._variables) == 3 
+    assert len(builder._coordinates) == 1
+    
+    # Validate that we created a coordinate variable
+    var_cdp = next(e for e in builder._variables if e.name == "cdp")
+    assert var_cdp is not None
+    assert len(var_cdp.dimensions) == 2
+    assert len(var_cdp.coordinates) == 1
+    assert next(e for e in var_cdp.coordinates if e.name == "cdp") is not None
 
     # Adding coordinate with the same name twice
     msg="Adding coordinate with the same name twice is not allowed"
@@ -56,7 +64,8 @@ def test_add_coordinate_with_defaults() -> None:
     # Add coordinate using defaults
     builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
     assert len(builder._dimensions) == 2 
-    assert len(builder._variables) == 2 
+    # 2 variables for dimensions, 1 variable for coordinates
+    assert len(builder._variables) == 3
     assert len(builder._coordinates) == 1
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
@@ -78,7 +87,8 @@ def test_coordinate_with_units() -> None:
         metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
     )
     assert len(builder._dimensions) == 2 
-    assert len(builder._variables) == 2  
+    # 2 variables for dimensions, 1 variable for coordinates
+    assert len(builder._variables) == 3  
     assert len(builder._coordinates) == 1 
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
     assert crd0 is not None
@@ -102,7 +112,8 @@ def test_coordinate_with_attributes() -> None:
         metadata_info=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})],
     )
     assert len(builder._dimensions) == 2 
-    assert len(builder._variables) == 2  
+    # 2 variables for dimensions, 1 variable for coordinates
+    assert len(builder._variables) == 3  
     assert len(builder._coordinates) == 1 
     # NOTE: add_coordinate() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
@@ -129,7 +140,8 @@ def test_coordinate_with_full_metadata() -> None:
             UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
     )
     assert len(builder._dimensions) == 2 
-    assert len(builder._variables) == 2  
+    # 2 variables for dimensions, 1 variable for coordinates
+    assert len(builder._variables) == 3  
     assert len(builder._coordinates) == 1 
     # NOTE: add_coordinate() stores dimensions as names
     crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index 6ff1f2590..a6a12e85f 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -40,6 +40,11 @@ def test_add_dimension() -> None:
     assert builder._dimensions[0] == NamedDimension(name="x", size=100)
     assert len(builder._variables) == 1  
 
+    # Validate that we created a dimension variable properly
+    var_x = next(e for e in builder._variables if e.name == "x")
+    assert var_x is not None
+    assert len(var_x.dimensions) == 1
+
     # Adding dimension with the same name twice
     msg="Adding dimension with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 7c0b46ba5..1181e10d7 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -112,7 +112,9 @@ def test_add_variable_full_parameters() -> None:
         ])
     assert len(builder._dimensions) == 3
     assert len(builder._coordinates) == 2  
-    assert len(builder._variables) == 4 
+    # We expect 6 variables:
+    # 3 variables for dimensions, 2 variables for coordinates, and 1 variable for seismic_amplitude
+    assert len(builder._variables) == 6 
     v = next((v for v in builder._variables if v.name == "seismic_amplitude"), None)
     assert v is not None
     assert v.long_name == "Amplitude (dimensionless)"
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index ab2d64af2..64dfead0c 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -5,18 +5,26 @@
 """Tests the schema v1 dataset_builder.add_coordinate() public API."""
 
 from datetime import UTC, datetime
+import json
+import os
+from pathlib import Path
 import pytest
 
-from mdio.schemas.dtype import ScalarType
-from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset import DatasetInfo, DatasetMetadata
+from mdio.schemas import builder
+from mdio.schemas.chunk_grid import RegularChunkGrid, RegularChunkShape
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType, StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
+from mdio.schemas.v1.dataset import Dataset, DatasetInfo, DatasetMetadata
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
-from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.stats import CenteredBinHistogram, StatisticsMetadata, SummaryStatistics
+from mdio.schemas.v1.units import AllUnits, SpeedUnitEnum, SpeedUnitModel
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.variable import VariableMetadata
 
+
 def test_build() -> None:
     """Test adding coordinates. Check the state transition and validate required parameters."""
     builder = MDIODatasetBuilder("test_dataset")
@@ -27,27 +35,221 @@ def test_build() -> None:
 
     builder.build()
 
-def test_play() -> None:
-    """Test adding coordinates. Check the state transition and validate required parameters."""
-    # builder = MDIODatasetBuilder("test_dataset")
-
-    u = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-    
-    u_dict = u.model_dump(mode="json", by_alias=True)
-    vm = VariableMetadata(**u_dict)
-    vm_dict = vm.dict()
-    vm_json = vm.model_dump(mode="json", by_alias=True)
-
-#     vm = VariableMetadata(u)
-    
-#     dInfo = DatasetInfo(
-#             name="My Dataset",
-#             api_version="1.0.0",
-#             created_on= datetime.now(UTC)),
-    
-#     d = dict(dInfo.model_dump(mode="json", by_alias=True))
- 
-#     meta = DatasetMetadata(d)
-#     print(dInfo.dict())
-
-#     i = 0
\ No newline at end of file
+
+def test_build_dataset() -> None:
+    """Test building a complete dataset."""
+    dataset = (
+        MDIODatasetBuilder("test_dataset")
+        .add_dimension("x", 100)
+        .add_dimension("y", 200)
+        .add_coordinate("x_coord", dimensions=["x"])
+        .add_coordinate("y_coord", dimensions=["y"])
+        .add_variable("data", dimensions=["x", "y"], long_name="Test Data")
+        .build()
+    )
+    assert isinstance(dataset, Dataset)
+    assert dataset.metadata.name == "test_dataset"
+    # 2 dimension variables + 1 data variable + 2 coordinate variables
+    assert len(dataset.variables) == 5
+    assert next(v for v in dataset.variables if v.name == "x") is not None
+    assert next(v for v in dataset.variables if v.name == "y") is not None
+    var_data = next(v for v in dataset.variables if v.name == "data")
+    assert var_data is not None
+    assert var_data.long_name == "Test Data"
+    assert len(var_data.dimensions) == 2
+
+# def test_build_dataset_bad_example() -> None:
+#     builder = MDIODatasetBuilder("Bad example")
+#     builder.add_dimension("inline", 256)
+#     builder.add_dimension("crossline", 512)
+#     builder.add_dimension("depth", 384)
+#     builder.add_variable(name="image", dimensions=["inline", "crossline", "depth"])
+#     dataset = builder.build()
+
+#     json_str = dataset.model_dump_json()
+#     file_path = os.path.join(os.path.dirname(__file__), "bad_example.json")
+#     with open(file_path, 'w') as f:
+#         f.write(json_str)
+
+def test_build_campos_3d(tmp_path: Path) -> None:
+    """Test building a toy dataset with multiple variables and attributes."""
+    dataset = make_campos_3d_dataset()
+
+    # Verify dataset structure
+    assert dataset.metadata.name == "campos_3d"
+    assert dataset.metadata.api_version == "1.0.0"
+    assert dataset.metadata.attributes["foo"] == "bar"
+    assert len(dataset.metadata.attributes["textHeader"]) == 3
+
+    # Verify variables (including dimension variables)
+    # 3 dimension variables + 4 data variables + 2 coordinate variables
+    assert len(dataset.variables) == 9  # noqa: PLR2004
+
+    # Verify dimension variables
+    inline_var = next(v for v in dataset.variables if v.name == "inline")
+    assert inline_var.data_type == ScalarType.UINT32
+    assert len(inline_var.dimensions) == 1
+    assert inline_var.dimensions[0].name == "inline"
+
+    depth_var = next(v for v in dataset.variables if v.name == "depth")
+    assert depth_var.data_type == ScalarType.UINT32
+    assert depth_var.metadata.units_v1.length == "m"
+
+    # Verify image variable
+    image = next(v for v in dataset.variables if v.name == "image")
+    assert image.data_type == ScalarType.FLOAT32
+    assert isinstance(image.compressor, Blosc)
+    assert image.compressor.algorithm == "zstd"
+    assert image.metadata.stats_v1.count == 100
+
+    # Verify velocity variable
+    velocity = next(v for v in dataset.variables if v.name == "velocity")
+    assert velocity.data_type == ScalarType.FLOAT16
+    assert velocity.compressor is None
+    assert velocity.metadata.units_v1.speed == "m/s"
+
+    # Verify image_inline variable
+    image_inline = next(
+        v for v in dataset.variables if v.name == "image_inline")
+    assert image_inline.long_name == "inline optimized version of 3d_stack"
+    assert isinstance(image_inline.compressor, Blosc)
+    assert image_inline.compressor.algorithm == "zstd"
+
+    # Verify image_headers variable
+    headers = next(v for v in dataset.variables if v.name == "image_headers")
+    assert isinstance(headers.data_type, StructuredType)
+    assert len(headers.data_type.fields) == 4
+    assert headers.data_type.fields[0].name == "cdp-x"
+
+# def test_build_campos_3d_contract(tmp_path: Path) -> None:
+#     '''Test building campos_3d dataset and converting to JSON schema format.'''
+#     dataset = make_campos_3d_dataset()
+#     # json_str = dataset.model_dump_json()
+#     # json_sorted_str = json.dumps(json.loads(json_str), sort_keys=True)
+#     m_dict = dataset.model_dump(mode="json", by_alias=True)
+#     json_sorted_str = json.dumps(m_dict, sort_keys=True)
+
+#     sorted_contract = load_campos_3d_contract()
+
+#     save(json_sorted_str, sorted_contract)
+
+# def save(model: str, contract: str) -> None:
+#     model_file_path = os.path.join(os.path.dirname(__file__), "campos_3d_model.json")
+#     contract_file_path = os.path.join(os.path.dirname(__file__), "campos_3d_contract.json")
+#     with open(model_file_path, 'w') as f:
+#         f.write(model)
+#     with open(contract_file_path, 'w') as f:
+#         f.write(contract)
+
+# def load_campos_3d_contract():
+#     file_path = os.path.join(os.path.dirname(__file__), 'test_data/campos_3d_contract.json')
+#     with open(file_path, 'r') as f:
+#         contract = json.load(f)
+#     assert contract is not None
+#     return json.dumps(contract, sort_keys=True)
+
+def make_campos_3d_dataset() -> Dataset:
+    """Create in-memory campos_3d dataset."""
+
+    ds = MDIODatasetBuilder(
+        "campos_3d",
+        attributes=UserAttributes(attributes={
+            "textHeader": [
+                "C01 .......................... ",
+                "C02 .......................... ",
+                "C03 .......................... ",
+            ],
+            "foo": "bar"
+        }))
+
+    # Add dimensions
+    ds.add_dimension("inline", 256, var_data_type=ScalarType.UINT32)
+    ds.add_dimension("crossline", 512, var_data_type=ScalarType.UINT32)
+    ds.add_dimension("depth", 384, var_data_type=ScalarType.UINT32,
+                     var_metadata_info=[
+                         AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+                     )
+    # Add coordinates
+    ds.add_coordinate(
+        "cdp-x",
+        dimensions=["inline", "crossline"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+    )
+    ds.add_coordinate(
+        "cdp-y",
+        dimensions=["inline", "crossline"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+        # metadata={"unitsV1": {"length": "m"}},
+    )
+    # Add image variable
+    ds.add_variable(
+        name="image",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(
+                        binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+            UserAttributes(
+                attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
+        ])
+    # Add velocity variable
+    ds.add_variable(
+        name="velocity",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT16,
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+            ),
+            AllUnits(units_v1=SpeedUnitModel(
+                speed=SpeedUnitEnum.METER_PER_SECOND)),
+        ],
+    )
+    # Add inline-optimized image variable
+    ds.add_variable(
+        name="image_inline",
+        long_name="inline optimized version of 3d_stack",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512]))
+            )]
+    )
+    # Add headers variable with structured dtype
+    ds.add_variable(
+        name="image_headers",
+        dimensions=["inline", "crossline"],
+        data_type=StructuredType(
+            fields=[
+                {"name": "cdp-x", "format": ScalarType.INT32},
+                {"name": "cdp-y", "format": ScalarType.INT32},
+                {"name": "elevation", "format": ScalarType.FLOAT16},
+                {"name": "some_scalar", "format": ScalarType.FLOAT16},
+            ]
+        ),
+        coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+    )
+    return ds.build()
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index e5078a5ef..e6bfda71f 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -141,7 +141,7 @@ def test_add_dimensions_if_needed() -> None:
     # Assert that the number of dimensions has not increased
     assert len(builder._dimensions) == 3
 
-def test__add_dimensions_if_needed_when_one_already_exists() -> None:
+def test__add_dimensions_if_one_already_exists() -> None:
     """Test adding existing named dimensions to a dataset."""
     builder = MDIODatasetBuilder("Test Dataset Builder")
 

From fe4af2bdab5219e2949d1cc28bec62091a226e24 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Wed, 2 Jul 2025 10:16:01 -0500
Subject: [PATCH 23/56] [v1] Update dependencies to latest (#567)

* Update dependencies to latest versions

* Update linter type-checking code to 'TC' in pyproject.toml

https://astral.sh/blog/ruff-v0.8.0#new-error-codes-for-flake8-type-checking-rules

* Refactor: Move Zarr codec imports to top-level

* disable safety in CI (temporary)

* Refactor: Replace Zarr codec imports with numcodecs equivalents

* Refactor: Remove unused numcodecs imports and related methods

* pin zarr due to zarr 3.0.9 bug
---
 .github/workflows/tests.yml     |    2 +-
 pyproject.toml                  |   52 +-
 src/mdio/schemas/compressors.py |   22 -
 uv.lock                         | 1985 ++++++++++++++-----------------
 4 files changed, 928 insertions(+), 1133 deletions(-)

diff --git a/.github/workflows/tests.yml b/.github/workflows/tests.yml
index 8d7c81fa3..71ad8630e 100644
--- a/.github/workflows/tests.yml
+++ b/.github/workflows/tests.yml
@@ -13,7 +13,7 @@ jobs:
       matrix:
         include:
           - { python: "3.13", os: "ubuntu-latest", session: "pre-commit" }
-          - { python: "3.13", os: "ubuntu-latest", session: "safety" }
+          #          - { python: "3.13", os: "ubuntu-latest", session: "safety" }
           #          - { python: "3.13", os: "ubuntu-latest", session: "mypy" }
           #          - { python: "3.12", os: "ubuntu-latest", session: "mypy" }
           #          - { python: "3.11", os: "ubuntu-latest", session: "mypy" }
diff --git a/pyproject.toml b/pyproject.toml
index 7e01894ec..a9e14605e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,30 +23,30 @@ classifiers = [
 ]
 
 dependencies = [
-    "click (>=8.1.7,<9.0.0)",
+    "click (>=8.2.1,<9.0.0)",
     "click-params (>=0.5.0,<0.6.0)",
-    "dask (>=2024.12.0)",
-    "fsspec (>=2024.10.0)",
-    "pint>=0.24.3,<0.25",
-    "psutil (>=6.1.0,<7.0.0)",
-    "pydantic (>=2.8.2,<3.0.0)",
-    "pydantic-settings (>=2.4.0,<3.0.0)",
-    "rich (>=13.9.4,<14.0.0)",
-    "segy (>=0.4.0,<0.5.0)",
-    "tqdm (>=4.67.0,<5.0.0)",
-    "xarray>=2025.3.1",
-    "zarr (>=3.0.8,<4.0.0)",
+    "dask (>=2025.5.1)",
+    "fsspec (>=2025.5.1)",
+    "pint>=0.24.4,<0.25",
+    "psutil (>=7.0.0,<8.0.0)",
+    "pydantic (>=2.11.7,<3.0.0)",
+    "pydantic-settings (>=2.10.1,<3.0.0)",
+    "rich (>=14.0.0,<15.0.0)",
+    "segy (>=0.4.1.post2,<0.5.0)",
+    "tqdm (>=4.67.1,<5.0.0)",
+    "xarray>=2025.6.1",
+    "zarr (>=3.0.8,<3.0.9)",
 ]
 
 [project.optional-dependencies]
 cloud = [
-    "s3fs == 2024.12.0",
-    "gcsfs (>=2024.10.0)",
-    "adlfs (>=2024.7.0)",
+    "s3fs == 2025.5.1",
+    "gcsfs (>=2025.5.1)",
+    "adlfs (>=2024.12.0)",
 ]
 distributed = [
-    "distributed (>=2024.12.0)",
-    "bokeh (>=3.4.2,<4.0.0)",
+    "distributed (>=2025.5.1)",
+    "bokeh (>=3.7.3,<4.0.0)",
 ]
 lossy = ["zfpy (>=1.0.1,<2.0.0)"]
 
@@ -60,17 +60,17 @@ mdio = "mdio.__main__:main"
 
 [dependency-groups]
 dev = [
-    "ruff (>=0.11.8)",
-    "coverage[toml] (>=7.6.7,<8)",
-    "mypy (>=1.13.0,<2)",
-    "pre-commit (>=4.0.1,<5)",
+    "ruff (>=0.12.1)",
+    "coverage[toml] (>=7.9.1,<8)",
+    "mypy (>=1.16.1,<2)",
+    "pre-commit (>=4.2.0,<5)",
     "pre-commit-hooks (>=5.0.0,<6)",
-    "pytest (>=8.3.3,<9)",
+    "pytest (>=8.4.1,<9)",
     "pytest-dependency (>=0.6.0,<0.7)",
-    "safety (>=3.2.3,<4)",
-    "typeguard (>=4.4.1,<5)",
+#    "safety (>=3.5.2,<4)",  # too tight pydantic and psutil dependency
+    "typeguard (>=4.4.4,<5)",
     "xdoctest[colors] (>=1.2.0,<2)",
-    "Pygments (>=2.18.0,<3)",
+    "Pygments (>=2.19.2,<3)",
 ]
 
 docs = [
@@ -116,7 +116,7 @@ select = [
     "RET", # return
     "SIM", # simplify
     "TID", # tidy-imports
-    "TCH", # type-checking
+    "TC", # type-checking
     "ARG", # unused-arguments
     "PTH", # use-pathlib
     "TD",  # todos
diff --git a/src/mdio/schemas/compressors.py b/src/mdio/schemas/compressors.py
index e17948da2..2eb87f7ad 100644
--- a/src/mdio/schemas/compressors.py
+++ b/src/mdio/schemas/compressors.py
@@ -53,17 +53,6 @@ class Blosc(CamelCaseStrictModel):
         description="The size of the block to be used for compression.",
     )
 
-    def make_instance(self):  # noqa: ANN201
-        """Translate parameters to compressor kwargs.."""
-        from zarr.codecs import Blosc as _Blosc
-
-        return _Blosc(
-            cname=self.algorithm,
-            clevel=self.level,
-            shuffle=self.shuffle,
-            blocksize=self.blocksize,
-        )
-
 
 zfp_mode_map = {
     "fixed_rate": 2,
@@ -139,17 +128,6 @@ def check_requirements(self) -> ZFP:
 
         return self
 
-    def make_instance(self):  # noqa: ANN201
-        """Translate parameters to compressor kwargs.."""
-        from zarr.codecs import ZFPY as _ZFPY
-
-        return _ZFPY(
-            mode=self.mode.int_code,
-            tolerance=self.tolerance,
-            rate=self.rate,
-            precision=self.precision,
-        )
-
 
 class CompressorModel(CamelCaseStrictModel):
     """Model representing compressor configuration."""
diff --git a/uv.lock b/uv.lock
index de95c4e6f..964a1c2d4 100644
--- a/uv.lock
+++ b/uv.lock
@@ -26,7 +26,7 @@ wheels = [
 
 [[package]]
 name = "aiobotocore"
-version = "2.22.0"
+version = "2.23.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
@@ -37,9 +37,9 @@ dependencies = [
     { name = "python-dateutil" },
     { name = "wrapt" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/9c/4c/113c4f5611103bba8e5252805fbee7944f5d9541addba9a96b091c0c4308/aiobotocore-2.22.0.tar.gz", hash = "sha256:11091477266b75c2b5d28421c1f2bc9a87d175d0b8619cb830805e7a113a170b", size = 110322 }
+sdist = { url = "https://files.pythonhosted.org/packages/9d/25/4b06ea1214ddf020a28df27dc7136ac9dfaf87929d51e6f6044dd350ed67/aiobotocore-2.23.0.tar.gz", hash = "sha256:0333931365a6c7053aee292fe6ef50c74690c4ae06bb019afdf706cb6f2f5e32", size = 115825 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/8e/ffa5840cb7de19ada85bda1fae1ae22671a18992e9373f2e2df9db5389b5/aiobotocore-2.22.0-py3-none-any.whl", hash = "sha256:b4e6306f79df9d81daff1f9d63189a2dbee4b77ce3ab937304834e35eaaeeccf", size = 78930 },
+    { url = "https://files.pythonhosted.org/packages/ea/43/ccf9b29669cdb09fd4bfc0a8effeb2973b22a0f3c3be4142d0b485975d11/aiobotocore-2.23.0-py3-none-any.whl", hash = "sha256:8202cebbf147804a083a02bc282fbfda873bfdd0065fd34b64784acb7757b66e", size = 84161 },
 ]
 
 [[package]]
@@ -53,7 +53,7 @@ wheels = [
 
 [[package]]
 name = "aiohttp"
-version = "3.12.2"
+version = "3.12.13"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -64,59 +64,59 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/06/a2/a946c4f5c54233c97788c2278ea50beaadf45211f452f932b36ce322f660/aiohttp-3.12.2.tar.gz", hash = "sha256:0018956472ee535d2cad761a5bb88eb4ad80f94cd86472cee26a244799f7c79f", size = 7780423 }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/08/39/9866f5996a7db870464e1f153b9f6a3412167ee79293f138bad09de783cd/aiohttp-3.12.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:536a37af26ed50bd4f3cf7d989955e5a987e9343f1a55f5393e7950a6ac93fce", size = 701750 },
-    { url = "https://files.pythonhosted.org/packages/81/eb/187fba5f1c210bed03c4e4fe50b6cc64d18c6776e6d17887b527ee2fb806/aiohttp-3.12.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6f8fbb48953238e7ba8ab9dee6757a4f6b72cd6242eb7fe1cb004b24f91effee", size = 474015 },
-    { url = "https://files.pythonhosted.org/packages/c5/e5/8f203120a8a932739face58614f8c93912ccd26c0b18da3f476b7372158b/aiohttp-3.12.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:74190229bd54bc3df7090f634b0b7fe53c45fb41aae5fbfae462093ced35c950", size = 462282 },
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 [[package]]
@@ -3992,9 +3809,9 @@ wheels = [
 
 [[package]]
 name = "zipp"
-version = "3.22.0"
+version = "3.23.0"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/12/b6/7b3d16792fdf94f146bed92be90b4eb4563569eca91513c8609aebf0c167/zipp-3.22.0.tar.gz", hash = "sha256:dd2f28c3ce4bc67507bfd3781d21b7bb2be31103b51a4553ad7d90b84e57ace5", size = 25257 }
+sdist = { url = "https://files.pythonhosted.org/packages/e3/02/0f2892c661036d50ede074e376733dca2ae7c6eb617489437771209d4180/zipp-3.23.0.tar.gz", hash = "sha256:a07157588a12518c9d4034df3fbbee09c814741a33ff63c05fa29d26a2404166", size = 25547 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ad/da/f64669af4cae46f17b90798a827519ce3737d31dbafad65d391e49643dc4/zipp-3.22.0-py3-none-any.whl", hash = "sha256:fe208f65f2aca48b81f9e6fd8cf7b8b32c26375266b009b413d45306b6148343", size = 9796 },
+    { url = "https://files.pythonhosted.org/packages/2e/54/647ade08bf0db230bfea292f893923872fd20be6ac6f53b2b936ba839d75/zipp-3.23.0-py3-none-any.whl", hash = "sha256:071652d6115ed432f5ce1d34c336c0adfd6a884660d1e9712a256d3d3bd4b14e", size = 10276 },
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From 79863ac554a4250f86b0712aee810d1eb5e427fb Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 2 Jul 2025 21:49:22 +0000
Subject: [PATCH 24/56] Dataset Build - pass one

---
 src/mdio/schemas/v1/dataset_builder.py        | 288 ++++++-----------
 .../v1/test_dataset_builder_add_coordinate.py |  27 +-
 .../v1/test_dataset_builder_add_dimension.py  |  60 ++--
 .../v1/test_dataset_builder_add_variable.py   |  29 +-
 tests/unit/v1/test_dataset_builder_build.py   | 143 ++++-----
 tests/unit/v1/test_dataset_builder_helpers.py | 290 ++++--------------
 6 files changed, 297 insertions(+), 540 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 8b1698789..701fdbba3 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -7,8 +7,6 @@
 from typing import Any
 from typing import TypeAlias
 
-import xarray as xr
-
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
 
@@ -19,14 +17,12 @@
 from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset import DatasetInfo
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.variable import Coordinate
-from mdio.schemas.v1.variable import CoordinateMetadata
 from mdio.schemas.v1.variable import Variable
-from mdio.schemas.v1.variable import VariableMetadata
-from mdio.schemas.v1.dataset import Dataset, DatasetInfo
-from mdio.schemas.v1.dataset import DatasetMetadata
 
 AnyMetadataList: TypeAlias = list[AllUnits |
                                   UserAttributes |
@@ -50,24 +46,10 @@ class _BuilderState(Enum):
     HAS_VARIABLES = auto()
 
 
-def contains_dimension(
-    dimensions: list[NamedDimension], name_or_dimension: str | NamedDimension
-) -> bool:
-    """Check if a dimension with the given name exists in the list."""
-    if isinstance(name_or_dimension, str):
-        name = name_or_dimension
-        return get_dimension(dimensions, name) is not None
-    if isinstance(name_or_dimension, NamedDimension):
-        dimension = name_or_dimension
-        return get_dimension(dimensions, dimension.name, dimension.size) is not None
-    msg = f"Expected str or NamedDimension, got {type(name_or_dimension).__name__}"
-    raise TypeError(msg)
-
-
-def get_dimension(
+def _get_dimension(
     dimensions: list[NamedDimension], name: str, size: int | None = None
 ) -> NamedDimension | None:
-    """Get a dimension by name from the list."""
+    """Get a dimension by name and size from the list[NamedDimension] ."""
     if dimensions is None:
         return False
     if not isinstance(name, str):
@@ -83,19 +65,6 @@ def get_dimension(
     return nd
 
 
-def get_dimension_names(dimensions: list[NamedDimension | str]) -> list[str]:
-    """Get a dimension by name from the list."""
-    names = []
-    if dimensions is None:
-        return names
-    for dim in dimensions:
-        if isinstance(dim, NamedDimension):
-            names.append(dim.name)
-        elif isinstance(dim, str):
-            names.append(dim)
-    return names
-
-
 def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList) -> dict[str, Any]:
     """Convert a dictionary, list or pydantic BaseModel to a dictionary."""
     if val is None:
@@ -142,42 +111,18 @@ def __init__(self, name: str, attributes: UserAttributes | None = None):
         self._state = _BuilderState.INITIAL
         self._unnamed_variable_counter = 0
 
-    def _add_dimensions_if_needed(
-        self, dimensions: list[NamedDimension | str] | None
-    ) -> list[NamedDimension]:
-        if dimensions is None:
-            return []
-
-        added_dims = []
-        for dim in dimensions:
-            if isinstance(dim, str):
-                if not contains_dimension(self._dimensions, dim):
-                    msg = f"Pre-existing dimension named {dim!r} is not found"
-                    raise ValueError(msg)
-            else:
-                if not isinstance(dim, NamedDimension):
-                    msg = f"Expected NamedDimension or str, got {type(dim).__name__}"
-                    raise TypeError(msg)
-                if contains_dimension(self._dimensions, dim):
-                    continue
-                # Use value instead of a reference
-                d = NamedDimension(name=dim.name, size=dim.size)
-                self._dimensions.append(d)
-                added_dims.append(d)
-        return added_dims
-
+    
     def add_dimension(  # noqa: PLR0913
         self,
         name: str,
         size: int,
-        var_long_name: str = None,
         var_data_type: ScalarType | StructuredType = ScalarType.INT32,
         var_metadata_info: VariableMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
         """Add a dimension.
 
-        This must be called at least once before adding coordinates or variables.
-        This call will create a variable, if one does not yet exists
+        This function be called at least once before adding coordinates or variables.
+        This call will create a dimension variable, if one does not yet exists
 
         Args:
             name: Name of the dimension
@@ -192,28 +137,31 @@ def add_dimension(  # noqa: PLR0913
         if not name:
             msg = "'name' must be a non-empty string"
             raise ValueError(msg)
+        
+        # Validate that the dimension is not already defined
         old_var = next((e for e in self._dimensions if e.name == name), None)
         if old_var is not None:
             msg = "Adding dimension with the same name twice is not allowed"
             raise ValueError(msg)
 
-        added_dims = self._add_dimensions_if_needed([NamedDimension(name=name, size=size)])
-        if added_dims:
-            meta_dict = _to_dictionary(var_metadata_info)
-            # Create a variable for the dimension
-            dim_var = Variable(
-                name=name,
-                longName=var_long_name,
-                # IMPORTANT: we always use NamedDimension here, not the dimension name
-                # Since the Dataset does not have a dimension list, we need to preserve NamedDimension
-                # somewhere. Namely, in the variable created for the dimension
-                dimensions=added_dims,
-                dataType=var_data_type,
-                compressor=None,
-                coordinates=None,
-                metadata=meta_dict,
-            )
-            self._variables.append(dim_var)
+        dim = NamedDimension(name=name, size=size)
+        self._dimensions.append(dim)
+
+        meta_dict = _to_dictionary(var_metadata_info)
+        # Create a variable for the dimension
+        dim_var = Variable(
+            name=name,
+            longName=f"'{name}' dimension variable",
+            # IMPORTANT: we use NamedDimension here, not the dimension name.
+            # Since the Dataset does not have a dimension list, we need to preserve 
+            # NamedDimension somewhere. Namely, in the variable created for the dimension
+            dimensions=[dim],
+            dataType=var_data_type,
+            compressor=None,
+            coordinates=None,
+            metadata=meta_dict,
+        )
+        self._variables.append(dim_var)
 
         self._state = _BuilderState.HAS_DIMENSIONS
         return self
@@ -223,12 +171,25 @@ def add_coordinate(  # noqa: PLR0913
         name: str,
         *,
         long_name: str = None,
-        #TODO Only allow adding dimensions by name, not by NamedDimension object
-        dimensions: list[NamedDimension | str],
+        dimensions: list[str],
         data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
         metadata_info: CoordinateMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
-        """Add a coordinate after adding at least one dimension."""
+        """Add a coordinate after adding at least one dimension.
+
+        This function must be called after all required dimensions are added via add_dimension().
+        This call will create a coordinate variable.
+
+        Args:
+            name: Name of the coordinate
+            long_name: Optional long name for the coordinate
+            dimensions: List of dimension names that the coordinate is associated with
+            data_type: Data type for the coordinate (defaults to FLOAT32)
+            metadata_info: Optional metadata information for the coordinate
+
+        Returns:
+            self: Returns self for method chaining
+        """
         if self._state == _BuilderState.INITIAL:
             msg = "Must add at least one dimension before adding coordinates"
             raise ValueError(msg)
@@ -239,32 +200,38 @@ def add_coordinate(  # noqa: PLR0913
             msg = "'dimensions' must be a non-empty list"
             raise ValueError(msg)
         old_var = next((e for e in self._coordinates if e.name == name), None)
+
+        # Validate that the coordinate is not already defined
         if old_var is not None:
             msg = "Adding coordinate with the same name twice is not allowed"
             raise ValueError(msg)
+        
+        # Validate that all referenced dimensions are already defined
+        for dim in dimensions:
+            if next((d for d in self._dimensions if d.name == dim), None) is None:
+                msg = f"Pre-existing dimension named {dim!r} is not found"
+                raise ValueError(msg)
 
-        self._add_dimensions_if_needed(dimensions)
-        dim_names = get_dimension_names(dimensions)
         meta_dict = _to_dictionary(metadata_info)
         coord = Coordinate(
             name=name,
             longName=long_name,
             # We ass names: sts, not list[NamedDimension | str]
-            dimensions=dim_names,
+            dimensions=dimensions,
             dataType=data_type,
             metadata=meta_dict
         )
         self._coordinates.append(coord)
 
-        # Add coordinate as variables to the dataset
+        # Add a coordinate variable to the dataset
         var_meta_dict = _to_dictionary(coord.metadata)
         coord_var = Variable(
             name=coord.name,
-            longName=coord.long_name,
+            longName=f"'{coord.name}' coordinate variable",
             dimensions=coord.dimensions,
             dataType=coord.data_type,
             compressor=None,
-            # IMPORTANT: we always use Coordinate here, not the coordinate name
+            # IMPORTANT: we always use the Coordinate here, not the coordinate name
             # Since the Dataset does not have a coordinate list, we need to preserve Coordinate
             # somewhere. Namely, in the variable created for the coordinate
             coordinates=[coord],
@@ -280,15 +247,30 @@ def add_variable(  # noqa: PLR0913
         name: str,
         *,
         long_name: str = None,
-        #TODO Only allow adding dimensions by name, not by NamedDimension object
-        dimensions: list[NamedDimension | str],
+        dimensions: list[str],
         data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
         compressor: Blosc | ZFP | None = None,
-        #TODO Only allow adding coordinates by name, not by Coordinate object
-        coordinates: list[Coordinate | str] | None = None,
+        coordinates: list[str] | None = None,
         metadata_info: VariableMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
-        """Add a variable after adding at least one dimension."""
+        """Add a variable after adding at least one dimension and, optionally, coordinate.
+
+        This function must be called after all required dimensions are added via add_dimension().
+        This function must be called after all required coordinates are added via add_coordinate().
+
+        Args:
+            name: Name of the variable
+            long_name: Optional long name for the variable
+            dimensions: List of dimension names that the variable is associated with
+            data_type: Data type for the variable (defaults to FLOAT32)
+            compressor: Compressor used for the variable (defaults to None)
+            coordinates: List of coordinate names that the variable is associated with
+                         (defaults to None, meaning no coordinates)
+            metadata_info: Optional metadata information for the variable
+
+        Returns:
+            self: Returns self for method chaining.
+        """
         if self._state == _BuilderState.INITIAL:
             msg = "Must add at least one dimension before adding variables"
             raise ValueError(msg)
@@ -298,19 +280,32 @@ def add_variable(  # noqa: PLR0913
         if dimensions is None or not dimensions:
             msg = "'dimensions' must be a non-empty list"
             raise ValueError(msg)
+        
+        # Validate that the variable is not already defined
         old_var = next((e for e in self._variables if e.name == name), None)
         if old_var is not None:
             msg = "Adding variable with the same name twice is not allowed"
             raise ValueError(msg)
 
-        self._add_dimensions_if_needed(dimensions)
-        dim_names = get_dimension_names(dimensions)
+        # Validate that all referenced dimensions are already defined
+        for dim in dimensions:
+            if next((e for e in self._dimensions if e.name == dim), None) is None:
+                msg = f"Pre-existing dimension named {dim!r} is not found"
+                raise ValueError(msg)
+
+        # Validate that all referenced coordinates are already defined
+        if coordinates is not None:
+            for coord in coordinates:
+                if next((c for c in self._coordinates if c.name == coord), None) is None:
+                    msg = f"Pre-existing coordinate named {coord!r} is not found"
+                    raise ValueError(msg)
+
         meta_dict = _to_dictionary(metadata_info)
         self._variables.append(
             Variable(
                 name=name,
                 long_name=long_name,
-                dimensions=dim_names,
+                dimensions=dimensions,
                 data_type=data_type,
                 compressor=compressor,
                 coordinates=coordinates,
@@ -321,100 +316,17 @@ def add_variable(  # noqa: PLR0913
         return self
 
     def build(self) -> Dataset:
-        """Build the final dataset."""
+        """Build the final dataset.
+
+        This function must be called after at least one dimension is added via add_dimension().
+        It will create a Dataset object with all added dimensions, coordinates, and variables.
+
+        Returns:
+            Dataset: The built dataset with all added dimensions, coordinates, and variables.
+        """
         if self._state == _BuilderState.INITIAL:
             msg = "Must add at least one dimension before building"
             raise ValueError(msg)
 
         var_meta_dict = _to_dictionary([self._info, self._attributes])
-        dataset = Dataset(variables=self._variables, metadata=var_meta_dict)
-
-        return dataset
-
-    # def to_mdio(
-    #     self,
-    #     store: str,
-    #     mode: str = "w",
-    #     compute: bool = False,
-    #     **kwargs: Mapping[str, str | int | float | bool],
-    # ) -> Dataset:
-    #     """Write the dataset to a Zarr store and return the constructed mdio.Dataset.
-
-    #     This function constructs an mdio.Dataset from the MDIO dataset and writes its metadata
-    #     to a Zarr store. The actual data is not written, only the metadata structure is created.
-    #     """
-    #     return write_mdio_metadata(self.build(), store, mode, compute, **kwargs)
-
-# def write_mdio_metadata(
-#     mdio_ds: Dataset,
-#     store: str,
-#     mode: str = "w",
-#     compute: bool = False,
-#     **kwargs: Mapping[str, str | int | float | bool],
-# ) -> mdio.Dataset:
-#     """Write MDIO metadata to a Zarr store and return the constructed mdio.Dataset.
-
-#     This function constructs an mdio.Dataset from the MDIO dataset and writes its metadata
-#     to a Zarr store. The actual data is not written, only the metadata structure is created.
-
-#     Args:
-#         mdio_ds: The MDIO dataset to serialize
-#         store: Path to the Zarr or .mdio store
-#         mode: Write mode to pass to to_mdio(), e.g. 'w' or 'a'
-#         compute: Whether to compute (write) array chunks (True) or only metadata (False)
-#         **kwargs: Additional arguments to pass to to_mdio()
-
-#     Returns:
-#         The constructed xarray Dataset with MDIO extensions
-#     """
-#     ds = _construct_mdio_dataset(mdio_ds)
-
-#     def _generate_encodings() -> dict:
-#         """Generate encodings for each variable in the MDIO dataset.
-
-#         Returns:
-#             Dictionary mapping variable names to their encoding configurations.
-#         """
-#         # TODO(Anybody, #10274): Re-enable chunk_key_encoding when supported by xarray
-#         # dimension_separator_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
-
-#         # Collect dimension sizes (same approach as _construct_mdio_dataset)
-#         dims: dict[str, int] = {}
-#         for var in mdio_ds.variables:
-#             for d in var.dimensions:
-#                 if isinstance(d, NamedDimension):
-#                     dims[d.name] = d.size
-
-#         global_encodings = {}
-#         for var in mdio_ds.variables:
-#             fill_value = 0
-#             if isinstance(var.data_type, StructuredType):
-#                 continue
-#             chunks = None
-#             if var.metadata is not None and var.metadata.chunk_grid is not None:
-#                 chunks = var.metadata.chunk_grid.configuration.chunk_shape
-#             else:
-#                 # When no chunk_grid is provided, set chunks to shape to avoid chunking
-#                 dim_names = [d.name if isinstance(d, NamedDimension) else d for d in var.dimensions]
-#                 chunks = tuple(dims[name] for name in dim_names)
-#             global_encodings[var.name] = {
-#                 "chunks": chunks,
-#                 # TODO(Anybody, #10274): Re-enable chunk_key_encoding when supported by xarray
-#                 # "chunk_key_encoding": dimension_separator_encoding,
-#                 "_FillValue": fill_value,
-#                 "dtype": var.data_type,
-#                 "compressors": _convert_compressor(var.compressor),
-#             }
-#         return global_encodings
-
-#     ds.to_mdio(
-#         store,
-#         mode=mode,
-#         zarr_format=2,
-#         consolidated=True,
-#         safe_chunks=False,
-#         compute=compute,
-#         encoding=_generate_encodings(),
-#         **kwargs,
-#     )
-#     return ds
+        return Dataset(variables=self._variables, metadata=var_meta_dict)
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index e6fa4bcf1..0adb9240b 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -27,17 +27,24 @@ def test_add_coordinate() -> None:
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 100)
 
+    # Validate required parameters
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_coordinate(bad_name, dimensions=["speed"])
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_coordinate("", dimensions=["speed"])
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("amplitude", dimensions=None)
+        builder.add_coordinate("cdp-x", dimensions=None)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("amplitude", dimensions=[])
+        builder.add_coordinate("cdp-x", dimensions=[])
 
-    builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+    # Add a variable using non-existent dimensions
+    msg="Pre-existing dimension named 'xline' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate("bad_cdp-x", dimensions=["inline", "xline"])
+
+    # Validate state transition
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
     assert builder._state == _BuilderState.HAS_COORDINATES
     assert len(builder._dimensions) == 2 
     # 2 variables for dimensions, 1 variable for coordinates
@@ -45,16 +52,18 @@ def test_add_coordinate() -> None:
     assert len(builder._coordinates) == 1
     
     # Validate that we created a coordinate variable
-    var_cdp = next(e for e in builder._variables if e.name == "cdp")
+    var_cdp = next(e for e in builder._variables if e.name == "cdp-x")
     assert var_cdp is not None
-    assert len(var_cdp.dimensions) == 2
+    # Validate that dimensions are stored as names
+    assert set(var_cdp.dimensions) == {"inline", "crossline"}
+    # Validate that coordinates are stored as Coordinate
     assert len(var_cdp.coordinates) == 1
-    assert next(e for e in var_cdp.coordinates if e.name == "cdp") is not None
+    assert next((e for e in var_cdp.coordinates if e.name == "cdp-x"), None) is not None
 
     # Adding coordinate with the same name twice
     msg="Adding coordinate with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+        builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
 
 def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
@@ -97,7 +106,7 @@ def test_coordinate_with_units() -> None:
     assert crd0.long_name is None               # Default value
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata.attributes is None
-    assert crd0.metadata.units_v1.length == "ft"
+    assert crd0.metadata.units_v1.length == LengthUnitEnum.FOOT
 
 
 def test_coordinate_with_attributes() -> None:
@@ -151,5 +160,5 @@ def test_coordinate_with_full_metadata() -> None:
     assert crd0.data_type == ScalarType.FLOAT32 # Default value
     assert crd0.metadata.attributes["MGA"] == 51
     assert crd0.metadata.attributes["UnitSystem"] == "Imperial"
-    assert crd0.metadata.units_v1.length == "ft"
+    assert crd0.metadata.units_v1.length == LengthUnitEnum.FOOT
 
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index a6a12e85f..1465a8925 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -8,12 +8,12 @@
 
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
-from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.dataset_builder import _get_dimension
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.stats import SummaryStatistics
@@ -27,6 +27,7 @@ def test_add_dimension() -> None:
     builder = MDIODatasetBuilder("test_dataset")
     assert builder._state == _BuilderState.INITIAL
 
+    # Validate required parameters
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_dimension(bad_name, 200)
@@ -36,14 +37,29 @@ def test_add_dimension() -> None:
     # First dimension should change state to HAS_DIMENSIONS and create a variable
     builder.add_dimension("x", 100)
     assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 1  
-    assert builder._dimensions[0] == NamedDimension(name="x", size=100)
-    assert len(builder._variables) == 1  
+    assert len(builder._dimensions) == 1
+    assert _get_dimension(builder._dimensions, "x", 100) is not None
 
-    # Validate that we created a dimension variable properly
+    # Validate that we have created a dimension variable and 
+    # that variable has the embedded NamedDimension
+    assert len(builder._variables) == 1  
     var_x = next(e for e in builder._variables if e.name == "x")
     assert var_x is not None
     assert len(var_x.dimensions) == 1
+    # Validate that the dimension variable has the NamedDimension
+    assert _get_dimension(var_x.dimensions, "x", 100) is not None
+    assert var_x.long_name == "'x' dimension variable"
+    assert var_x.data_type == ScalarType.INT32
+    assert var_x.compressor is None
+    assert var_x.coordinates is None
+    assert var_x.metadata is None
+
+    # Validate that we can't add a dimension with the same name twice
+    with pytest.raises(
+        ValueError,
+        match="Adding dimension with the same name twice is not allowed",
+    ):
+        builder.add_dimension("x", 200)
 
     # Adding dimension with the same name twice
     msg="Adding dimension with the same name twice is not allowed"
@@ -58,15 +74,16 @@ def test_add_dimension_with_defaults() -> None:
     builder.add_dimension("x", 100)
     assert builder._state == _BuilderState.HAS_DIMENSIONS
     assert len(builder._dimensions) == 1  
-    assert builder._dimensions[0] == NamedDimension(name="x", size=100)
-    assert len(builder._variables) == 1  
-    var0 = builder._variables[0]
-    assert var0.name == "x"
-    assert var0.long_name is None
-    assert var0.data_type == ScalarType.INT32
-    assert var0.compressor is None
-    assert var0.coordinates is None
-    assert var0.metadata is None
+    # Validate that the dimension builder has the NamedDimension
+    assert _get_dimension(builder._dimensions, "x", 100) is not None
+    var_x = next((e for e in builder._variables if e.name == "x"), None)
+    assert var_x is not None
+    assert var_x.name == "x"
+    assert var_x.long_name == "'x' dimension variable"
+    assert var_x.data_type == ScalarType.INT32
+    assert var_x.compressor is None
+    assert var_x.coordinates is None
+    assert var_x.metadata is None
 
 def test_add_dimension_with_units() -> None:
     """Test adding dimensions with units."""
@@ -82,17 +99,16 @@ def test_add_dimension_with_units() -> None:
     assert len(builder._variables) == 1
     var0 = builder._variables[0]
     assert var0.name == "length"
-    assert var0.long_name is None
+    assert var0.long_name == "'length' dimension variable"
     assert var0.data_type == ScalarType.FLOAT64
     assert var0.compressor is None
     assert var0.coordinates is None
-    assert var0.metadata.units_v1.length == "ft"
+    assert var0.metadata.units_v1.length == LengthUnitEnum.FOOT
 
 def test_add_dimension_with_attributes() -> None:
     """Test adding dimensions with attributes."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with strongly-typed attribute list
     builder.add_dimension(
         "length",
         size=100,
@@ -111,7 +127,6 @@ def test_add_dimension_with_chunk_grid() -> None:
     """Test adding dimensions with chunk grid."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with strongly-typed chunk grid
     grid_definition = RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
     builder.add_dimension(
         "length",
@@ -131,7 +146,6 @@ def test_add_dimension_with_stats() -> None:
     """Test adding dimensions with stats."""
     builder = MDIODatasetBuilder("test_dataset")
 
-    # Add dimension with strongly-typed stats
     builder.add_dimension(
         "depth",
         size=100,
@@ -162,8 +176,6 @@ def test_add_dimension_with_full_metadata() -> None:
     """Test adding dimensions with all metadata."""
     builder = MDIODatasetBuilder("test_dataset")
 
-
-    # Add dimension with all strongly-typed metadata
     builder.add_dimension(
         "length",
         size=100,
@@ -191,9 +203,9 @@ def test_add_dimension_with_full_metadata() -> None:
     var0 = builder._variables[0]
     assert var0.name == "length"
     assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.units_v1.length == "ft"
-    assert var0.metadata.attributes["MGA"] == 51  
-    assert var0.metadata.attributes["UnitSystem"] == "Imperial"  
+    assert var0.metadata.units_v1.length == LengthUnitEnum.FOOT
+    assert var0.metadata.attributes["MGA"] == 51
+    assert var0.metadata.attributes["UnitSystem"] == "Imperial"
     assert var0.metadata.chunk_grid.name == "regular"
     assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]  
     assert var0.metadata.stats_v1.count == 100  
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 1181e10d7..ca6d8f955 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -36,15 +36,21 @@ def test_add_variable() -> None:
     builder.add_dimension("crossline", 100)
     builder.add_dimension("depth", 100)
 
+    # Validate required parameters
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_variable(bad_name, dimensions=["speed"])
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_variable("", dimensions=["speed"])
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("amplitude", dimensions=None)
+        builder.add_variable("bad_amplitude", dimensions=None)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("amplitude", dimensions=[])
+        builder.add_variable("bad_amplitude", dimensions=[])
+
+    # Add a variable using non-existent dimensions
+    msg="Pre-existing dimension named 'xline' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable("bad_amplitude", dimensions=["inline", "xline", "depth"])
 
     builder.add_variable("amplitude", dimensions=["inline", "crossline", "depth"])
     assert builder._state == _BuilderState.HAS_VARIABLES
@@ -52,10 +58,21 @@ def test_add_variable() -> None:
     assert len(builder._variables) == 4 
     assert len(builder._coordinates) == 0  
 
+    # Add a variable using non-existent coordinates
+    msg="Pre-existing coordinate named 'cdp-x' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable("bad_amplitude", 
+                             dimensions=["inline", "crossline", "depth"],
+                             coordinates=["cdp-x", "cdp-y"])    
+
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
+
     # Adding variable with the same name twice
     msg="Adding variable with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude", dimensions=["inline", "crossline", "depth"])
+        builder.add_variable("amplitude", 
+                             dimensions=["inline", "crossline", "depth"])
 
 
 def test_add_variable_with_defaults() -> None:
@@ -92,7 +109,7 @@ def test_add_variable_full_parameters() -> None:
         dimensions=["inline", "crossline", "depth"],    
         data_type=ScalarType.FLOAT64, 
         compressor=Blosc(algorithm="zstd"), 
-        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coordinates=["cdp-x", "cdp-y"],
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
             UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
@@ -124,10 +141,10 @@ def test_add_variable_full_parameters() -> None:
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
     # NOTE: add_variable() stores coordinates as names
-    assert set(v.coordinates) == {"inline", "crossline", "depth", "cdp-x", "cdp-y"}
+    assert set(v.coordinates) == {"cdp-x", "cdp-y"}
     assert v.metadata.stats_v1.count == 100 
     assert isinstance(v.metadata, VariableMetadata)
-    assert v.metadata.units_v1.length == "ft"
+    assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
     assert v.metadata.attributes["MGA"] == 51
     assert v.metadata.attributes["UnitSystem"] == "Imperial"  
     assert v.metadata.chunk_grid.name == "regular"
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 64dfead0c..488a9e6d2 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -4,39 +4,28 @@
 # Thus, disable it for this file
 """Tests the schema v1 dataset_builder.add_coordinate() public API."""
 
-from datetime import UTC, datetime
-import json
-import os
-from pathlib import Path
-import pytest
-
-from mdio.schemas import builder
-from mdio.schemas.chunk_grid import RegularChunkGrid, RegularChunkShape
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
-from mdio.schemas.dtype import ScalarType, StructuredType
-from mdio.schemas.metadata import ChunkGridMetadata, UserAttributes
-from mdio.schemas.v1.dataset import Dataset, DatasetInfo, DatasetMetadata
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
-from mdio.schemas.v1.dataset_builder import _BuilderState
-from mdio.schemas.v1.stats import CenteredBinHistogram, StatisticsMetadata, SummaryStatistics
-from mdio.schemas.v1.units import AllUnits, SpeedUnitEnum, SpeedUnitModel
+from mdio.schemas.v1.dataset_builder import _get_dimension
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
-from mdio.schemas.v1.variable import VariableMetadata
+from mdio.schemas.v1.units import SpeedUnitEnum
+from mdio.schemas.v1.units import SpeedUnitModel
 
 
 def test_build() -> None:
-    """Test adding coordinates. Check the state transition and validate required parameters."""
-    builder = MDIODatasetBuilder("test_dataset")
-    assert builder._state == _BuilderState.INITIAL
-
-    builder.add_dimension("x", 100)
-    builder.add_dimension("y", 100)
-
-    builder.build()
-
-
-def test_build_dataset() -> None:
     """Test building a complete dataset."""
     dataset = (
         MDIODatasetBuilder("test_dataset")
@@ -58,21 +47,9 @@ def test_build_dataset() -> None:
     assert var_data.long_name == "Test Data"
     assert len(var_data.dimensions) == 2
 
-# def test_build_dataset_bad_example() -> None:
-#     builder = MDIODatasetBuilder("Bad example")
-#     builder.add_dimension("inline", 256)
-#     builder.add_dimension("crossline", 512)
-#     builder.add_dimension("depth", 384)
-#     builder.add_variable(name="image", dimensions=["inline", "crossline", "depth"])
-#     dataset = builder.build()
-
-#     json_str = dataset.model_dump_json()
-#     file_path = os.path.join(os.path.dirname(__file__), "bad_example.json")
-#     with open(file_path, 'w') as f:
-#         f.write(json_str)
-
-def test_build_campos_3d(tmp_path: Path) -> None:
-    """Test building a toy dataset with multiple variables and attributes."""
+
+def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50)
+    """Test building a Campos 3D dataset with multiple variables and attributes."""
     dataset = make_campos_3d_dataset()
 
     # Verify dataset structure
@@ -83,37 +60,74 @@ def test_build_campos_3d(tmp_path: Path) -> None:
 
     # Verify variables (including dimension variables)
     # 3 dimension variables + 4 data variables + 2 coordinate variables
-    assert len(dataset.variables) == 9  # noqa: PLR2004
+    assert len(dataset.variables) == 9
 
     # Verify dimension variables
     inline_var = next(v for v in dataset.variables if v.name == "inline")
     assert inline_var.data_type == ScalarType.UINT32
-    assert len(inline_var.dimensions) == 1
-    assert inline_var.dimensions[0].name == "inline"
+    # Dimension variables store dimensions as NamedDimension
+    assert _get_dimension(inline_var.dimensions, "inline", 256)
+
+    crossline_var = next(v for v in dataset.variables if v.name == "crossline")
+    assert crossline_var.data_type == ScalarType.UINT32
+    # Dimension variables store dimensions as NamedDimension
+    assert _get_dimension(crossline_var.dimensions, "crossline", 512)
 
     depth_var = next(v for v in dataset.variables if v.name == "depth")
     assert depth_var.data_type == ScalarType.UINT32
-    assert depth_var.metadata.units_v1.length == "m"
+    # Dimension variables store dimensions as NamedDimension
+    assert _get_dimension(depth_var.dimensions, "depth", 384)
+    assert depth_var.metadata.units_v1.length == LengthUnitEnum.METER
+
+    # Verify coordinate variables
+    cdp_x = next(v for v in dataset.variables if v.name == "cdp-x")
+    assert cdp_x.data_type == ScalarType.FLOAT32
+    # Coordinates variables store dimensions as names
+    assert set(cdp_x.dimensions) == {"inline", "crossline"}
+    assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    cdp_y = next(v for v in dataset.variables if v.name == "cdp-y")
+    assert cdp_y.data_type == ScalarType.FLOAT32
+    # Coordinates variables store dimensions as names
+    assert set(cdp_y.dimensions) == {"inline", "crossline"}
+    assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
 
     # Verify image variable
     image = next(v for v in dataset.variables if v.name == "image")
+    assert set(image.dimensions) == {"inline", "crossline", "depth"}
     assert image.data_type == ScalarType.FLOAT32
     assert isinstance(image.compressor, Blosc)
     assert image.compressor.algorithm == "zstd"
+    # Other variables store dimensions as names
+    assert set(image.coordinates) == {"cdp-x", "cdp-y"}
+    assert isinstance(image.metadata.chunk_grid, RegularChunkGrid)
+    assert image.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+    assert isinstance(image.metadata.stats_v1, SummaryStatistics)   
     assert image.metadata.stats_v1.count == 100
 
     # Verify velocity variable
     velocity = next(v for v in dataset.variables if v.name == "velocity")
+    assert set(velocity.dimensions) == {"inline", "crossline", "depth"}
     assert velocity.data_type == ScalarType.FLOAT16
     assert velocity.compressor is None
-    assert velocity.metadata.units_v1.speed == "m/s"
+    # Other variables store dimensions as names
+    assert set(velocity.coordinates) == {"cdp-x", "cdp-y"}
+    assert isinstance(velocity.metadata.chunk_grid, RegularChunkGrid)
+    assert velocity.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+    assert isinstance(velocity.metadata.units_v1, SpeedUnitModel)
+    assert velocity.metadata.units_v1.speed == SpeedUnitEnum.METER_PER_SECOND
 
     # Verify image_inline variable
     image_inline = next(
         v for v in dataset.variables if v.name == "image_inline")
     assert image_inline.long_name == "inline optimized version of 3d_stack"
+    assert set(image_inline.dimensions) == {"inline", "crossline", "depth"}
+    assert image_inline.data_type == ScalarType.FLOAT32
     assert isinstance(image_inline.compressor, Blosc)
     assert image_inline.compressor.algorithm == "zstd"
+    assert set(image_inline.coordinates) == {"cdp-x", "cdp-y"}
+    assert isinstance(image_inline.metadata.chunk_grid, RegularChunkGrid)
+    assert image_inline.metadata.chunk_grid.configuration.chunk_shape == [4, 512, 512]
 
     # Verify image_headers variable
     headers = next(v for v in dataset.variables if v.name == "image_headers")
@@ -121,36 +135,8 @@ def test_build_campos_3d(tmp_path: Path) -> None:
     assert len(headers.data_type.fields) == 4
     assert headers.data_type.fields[0].name == "cdp-x"
 
-# def test_build_campos_3d_contract(tmp_path: Path) -> None:
-#     '''Test building campos_3d dataset and converting to JSON schema format.'''
-#     dataset = make_campos_3d_dataset()
-#     # json_str = dataset.model_dump_json()
-#     # json_sorted_str = json.dumps(json.loads(json_str), sort_keys=True)
-#     m_dict = dataset.model_dump(mode="json", by_alias=True)
-#     json_sorted_str = json.dumps(m_dict, sort_keys=True)
-
-#     sorted_contract = load_campos_3d_contract()
-
-#     save(json_sorted_str, sorted_contract)
-
-# def save(model: str, contract: str) -> None:
-#     model_file_path = os.path.join(os.path.dirname(__file__), "campos_3d_model.json")
-#     contract_file_path = os.path.join(os.path.dirname(__file__), "campos_3d_contract.json")
-#     with open(model_file_path, 'w') as f:
-#         f.write(model)
-#     with open(contract_file_path, 'w') as f:
-#         f.write(contract)
-
-# def load_campos_3d_contract():
-#     file_path = os.path.join(os.path.dirname(__file__), 'test_data/campos_3d_contract.json')
-#     with open(file_path, 'r') as f:
-#         contract = json.load(f)
-#     assert contract is not None
-#     return json.dumps(contract, sort_keys=True)
-
 def make_campos_3d_dataset() -> Dataset:
     """Create in-memory campos_3d dataset."""
-
     ds = MDIODatasetBuilder(
         "campos_3d",
         attributes=UserAttributes(attributes={
@@ -181,7 +167,6 @@ def make_campos_3d_dataset() -> Dataset:
         dimensions=["inline", "crossline"],
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
-        # metadata={"unitsV1": {"length": "m"}},
     )
     # Add image variable
     ds.add_variable(
@@ -189,7 +174,7 @@ def make_campos_3d_dataset() -> Dataset:
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT32,
         compressor=Blosc(algorithm="zstd"),
-        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coordinates=["cdp-x", "cdp-y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -214,7 +199,7 @@ def make_campos_3d_dataset() -> Dataset:
         name="velocity",
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT16,
-        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coordinates=["cdp-x", "cdp-y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -231,7 +216,7 @@ def make_campos_3d_dataset() -> Dataset:
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT32,
         compressor=Blosc(algorithm="zstd"),
-        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coordinates=["cdp-x", "cdp-y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -250,6 +235,6 @@ def make_campos_3d_dataset() -> Dataset:
                 {"name": "some_scalar", "format": ScalarType.FLOAT16},
             ]
         ),
-        coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+        coordinates=["cdp-x", "cdp-y"],
     )
     return ds.build()
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index e6bfda71f..6fbba42a5 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -1,6 +1,6 @@
-# ruff: noqa: PLR2004 
+# ruff: noqa: PLR2004
 # PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert. 
+# The above erroneous warning is generated for every numerical assert.
 # Thus, disable it for this file
 """Tests the schema v1 dataset_builder internal methods."""
 
@@ -10,265 +10,87 @@
 import pytest
 from pydantic import Field
 
-from mdio.schemas.chunk_grid import RegularChunkGrid
-from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.core import StrictModel
 from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.metadata import ChunkGridMetadata
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _get_dimension
 from mdio.schemas.v1.dataset_builder import _to_dictionary
-from mdio.schemas.v1.dataset_builder import contains_dimension
-from mdio.schemas.v1.dataset_builder import get_dimension
-from mdio.schemas.v1.dataset_builder import get_dimension_names
-from mdio.schemas.v1.stats import CenteredBinHistogram
-from mdio.schemas.v1.stats import StatisticsMetadata
-from mdio.schemas.v1.stats import SummaryStatistics
-from mdio.schemas.v1.units import LengthUnitEnum
-from mdio.schemas.v1.units import LengthUnitModel
-from mdio.schemas.v1.variable import AllUnits
-from mdio.schemas.v1.variable import CoordinateMetadata
-from mdio.schemas.v1.variable import UserAttributes
-from mdio.schemas.v1.variable import VariableMetadata
 
 
-def test__get_dimension_by_name() -> None:
+def test__get_dimension() -> None:
     """Test getting a dimension by name from the list of dimensions."""
-    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(
+        name="crossline", size=3)]
 
-    assert get_dimension([], "inline") is None
-    assert get_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
-    assert get_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
-    assert get_dimension(dimensions, "time") is None
+    assert _get_dimension([], "inline") is None
+    assert _get_dimension(dimensions, "inline") == NamedDimension(
+        name="inline", size=2)
+    assert _get_dimension(dimensions, "crossline") == NamedDimension(
+        name="crossline", size=3)
+    assert _get_dimension(dimensions, "time") is None
 
     with pytest.raises(TypeError, match="Expected str, got NoneType"):
-        get_dimension(dimensions, None)
+        _get_dimension(dimensions, None)
     with pytest.raises(TypeError, match="Expected str, got int"):
-        get_dimension(dimensions, 42)
+        _get_dimension(dimensions, 42)
     with pytest.raises(
         ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
     ):
-        get_dimension(dimensions, "inline", size=200)
+        _get_dimension(dimensions, "inline", size=200)
 
 
-def test__contains_dimension() -> None:
-    """Test if a dimension with a given name exists in the list of dimensions."""
-    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
-
-    assert contains_dimension([], "inline") is False
-
-    assert contains_dimension(dimensions, "inline") is True
-    assert contains_dimension(dimensions, "crossline") is True
-    assert contains_dimension(dimensions, "time") is False
-
-    with pytest.raises(TypeError, match="Expected str or NamedDimension, got NoneType"):
-        contains_dimension(dimensions, None)
-    with pytest.raises(TypeError, match="Expected str or NamedDimension, got int"):
-        contains_dimension(dimensions, 42)
-    with pytest.raises(
-        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
-    ):
-        contains_dimension(dimensions, NamedDimension(name="inline", size=200))
-
-
-def test_get_dimension_names() -> None:
-    """Test getting a list of dimension names from list[NamedDimension | str]."""
-    empty_list = get_dimension_names(None)
-    assert empty_list is not None
-    assert isinstance(empty_list, list)
-    assert len(empty_list) == 0
-
-    empty_list = get_dimension_names([])
-    assert empty_list is not None
-    assert isinstance(empty_list, list)
-    assert len(empty_list) == 0
-
-    dim_list = get_dimension_names([
-        NamedDimension(name="inline", size=2), 
-        "amplitude",
-        NamedDimension(name="crossline", size=3)
-    ])
-    assert dim_list is not None
-    assert isinstance(dim_list, list)
-    assert set(dim_list) == {"inline", "amplitude", "crossline"}
-
-
-def test_add_dimensions_if_needed() -> None:
-    """Test adding named dimensions to a dataset."""
-    builder = MDIODatasetBuilder("Test Dataset Builder")
-    #
-    # Validate initial state
-    #
-    assert builder._dimensions is not None
-    assert len(builder._dimensions) == 0
-
-    #
-    # Validate that adding empty dimensions does not change the state
-    #
-    added_dims = builder._add_dimensions_if_needed(None)
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-    added_dims = builder._add_dimensions_if_needed([])
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-    added_dims = builder._add_dimensions_if_needed({})
-    assert len(builder._dimensions) == 0
-    assert len(added_dims) == 0
-
-    #
-    # Add named dimensions
-    #
-    inline_dim = NamedDimension(name="inline", size=2)
-    added_dims = builder._add_dimensions_if_needed([inline_dim])
-    assert len(builder._dimensions) == 1
-    assert len(added_dims) == 1
-    assert contains_dimension(added_dims, inline_dim)
-
-    crossline_dim = NamedDimension(name="crossline", size=3)
-    time_dim = NamedDimension(name="time", size=4)
-    added_dims = builder._add_dimensions_if_needed([crossline_dim, time_dim])
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert contains_dimension(added_dims, crossline_dim)
-    assert contains_dimension(added_dims, time_dim)
-
-    #
-    # Add invalid object type
-    #
-    with pytest.raises(TypeError, match="Expected NamedDimension or str, got int"):
-        builder._add_dimensions_if_needed([42])
-    # Assert that the number of dimensions has not increased
-    assert len(builder._dimensions) == 3
-
-def test__add_dimensions_if_one_already_exists() -> None:
-    """Test adding existing named dimensions to a dataset."""
-    builder = MDIODatasetBuilder("Test Dataset Builder")
-
-    inline_dim = NamedDimension(name="inline", size=2)
-    crossline_dim = NamedDimension(name="crossline", size=3)
-    time_dim = NamedDimension(name="time", size=4)
-    #
-    # Add dimensions with the same names again does nothing
-    # (make sure we are passing different instances)
-    #
-    inline_dim2 = NamedDimension(name=inline_dim.name, size=inline_dim.size)
-    crossline_dim2 = NamedDimension(name=crossline_dim.name, size=crossline_dim.size)
-    time_dim2 = NamedDimension(name=time_dim.name, size=time_dim.size)
-    builder._add_dimensions_if_needed([inline_dim2, crossline_dim2, time_dim2])
-    added_dims = builder._add_dimensions_if_needed([inline_dim2, crossline_dim2, time_dim2])
-    # Validate that the dimensions and variables are not duplicated
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert len(added_dims) == 0
-
-    # Add dimensions with the same name, but different size again
-    with pytest.raises(
-        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
-    ):
-        builder._add_dimensions_if_needed([NamedDimension(name="inline", size=200)])
-    # Assert that the number of dimensions has not increased
-    assert len(builder._dimensions) == 3
-
-    #
-    # Add existing dimension using its name
-    #
-    added_dims = builder._add_dimensions_if_needed(["inline", "crossline"])
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-    assert len(added_dims) == 0
-
-    #
-    # Add non-existing dimension using its name is not allowed
-    #
-    with pytest.raises(ValueError, match="Pre-existing dimension named 'offset' is not found"):
-        builder._add_dimensions_if_needed(["offset"])
-    assert len(builder._dimensions) == 3
-    assert contains_dimension(builder._dimensions, inline_dim)
-    assert contains_dimension(builder._dimensions, crossline_dim)
-    assert contains_dimension(builder._dimensions, time_dim)
-
 def test__to_dictionary() -> None:
-    """Test converting a BaseModel to a dictionary."""
+    """Test converting a dictionary, list or pydantic BaseModel to a dictionary."""
+    # Validate inputs
     with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got datetime"):
-        # This should raise an error because datetime is not a BaseModel
         _to_dictionary(datetime.now(UTC))
 
+    # Convert None to None
+    result = _to_dictionary(None)
+    assert result is None
+
+    # Validate conversion of a Pydantic BaseModel
     class SomeModel(StrictModel):
         count: int = Field(default=None, description="Samples count")
-        samples: list[float] = Field(default_factory=list, description="Samples.")
+        samples: list[float] = Field(
+            default_factory=list, description="Samples.")
         created: datetime = Field(
             default_factory=datetime.now, description="Creation time with TZ info."
         )
-
-    m = SomeModel(count=3, 
-                  samples=[1.0, 2.0, 3.0], 
-                  created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC))
-    result = _to_dictionary(m)
+    md = SomeModel(count=3,
+                   samples=[1.0, 2.0, 3.0],
+                   created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC))
+    result = _to_dictionary(md)
     assert isinstance(result, dict)
-    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
+    assert result == {
+        "count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
 
-    d = {
+    # Validate conversion of a dictionary
+    dct = {
         "count": 3,
         "samples": [1.0, 2.0, 3.0],
         "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)}
-    result = _to_dictionary(m)
+    result = _to_dictionary(dct)
     assert isinstance(result, dict)
-    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
-
-
-# def test__make_coordinate_metadata() -> None:
-#     """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
-#     units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-#     attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
-#     meta_list = [units, attrs]
-
-#     # Assume that multiple attributes are allowed
-#     metadata = _make_coordinate_metadata(meta_list)
-#     assert isinstance(metadata, CoordinateMetadata)
-#     assert metadata.units_v1.length == "ft"
-#     assert metadata.attributes["MGA"] == 51
-#     assert metadata.attributes["UnitSystem"] == "Imperial"
-
-#     meta_list = ["ft"]
-#     with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got str"):
-#         _make_variable_metadata(meta_list)
-
-# def test__make_variable_metadata() -> None:
-#     """Test creating VariableMetadata from a strongly-typed list of AllUnits or UserAttributes."""
-#     units = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
-#     attrs = UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})
-#     chgrd = ChunkGridMetadata(
-#                 chunk_grid=RegularChunkGrid(
-#                     configuration=RegularChunkShape(chunk_shape=[20])))
-#     stats = StatisticsMetadata(
-#                 stats_v1=SummaryStatistics(
-#                     count=100,
-#                     sum=1215.1,
-#                     sumSquares=125.12,
-#                     min=5.61,
-#                     max=10.84,
-#                     histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15])))
-#     metadata_info = [units, attrs, chgrd, stats]
-#     metadata = _make_variable_metadata(metadata_info)
-#     assert isinstance(metadata, VariableMetadata)
-#     assert metadata.units_v1.length == "ft"
-#     assert metadata.attributes["MGA"] == 51  
-#     assert metadata.attributes["UnitSystem"] == "Imperial"  
-#     assert metadata.chunk_grid.name == "regular"
-#     assert metadata.chunk_grid.configuration.chunk_shape == [20]  
-#     assert metadata.stats_v1.count == 100  
-#     assert metadata.stats_v1.sum == 1215.1  
-#     assert metadata.stats_v1.sum_squares == 125.12  
-#     assert metadata.stats_v1.min == 5.61  
-#     assert metadata.stats_v1.max == 10.84  
-#     assert metadata.stats_v1.histogram.bin_centers == [1, 2]  
-#     assert metadata.stats_v1.histogram.counts == [10, 15]  
-
-#     meta_list = ["ft"]
-#     with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got str"):
-#         _make_variable_metadata(meta_list)
+    assert result == {"count": 3,
+                      "samples": [1.0, 2.0, 3.0],
+                      "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC), }
+
+    # Validate conversion of a dictionary
+    lst = [None,
+           SomeModel(count=3,
+                     samples=[1.0, 2.0, 3.0],
+                     created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)),
+           {
+               "count2": 3,
+               "samples2": [1.0, 2.0, 3.0],
+               "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+           }]
+    result = _to_dictionary(lst)
+    assert isinstance(result, dict)
+    assert result == {"count": 3,
+                      "samples": [1.0, 2.0, 3.0],
+                      "created": "2023-10-01T12:00:00Z",
+                      "count2": 3,
+                      "samples2": [1.0, 2.0, 3.0],
+                      "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+                      }

From 4062a770be50a16db4a5c2adc4185eea2454b854 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Mon, 7 Jul 2025 09:12:28 -0500
Subject: [PATCH 25/56] unpin zarr because breaking bug fixed (#569)

---
 pyproject.toml |   2 +-
 uv.lock        | 391 +++++++++++++++++++++++++------------------------
 2 files changed, 202 insertions(+), 191 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index a9e14605e..e2f72190f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -35,7 +35,7 @@ dependencies = [
     "segy (>=0.4.1.post2,<0.5.0)",
     "tqdm (>=4.67.1,<5.0.0)",
     "xarray>=2025.6.1",
-    "zarr (>=3.0.8,<3.0.9)",
+    "zarr (>=3.0.10,<4.0.0)",
 ]
 
 [project.optional-dependencies]
diff --git a/uv.lock b/uv.lock
index 964a1c2d4..6f04c3630 100644
--- a/uv.lock
+++ b/uv.lock
@@ -130,14 +130,15 @@ wheels = [
 
 [[package]]
 name = "aiosignal"
-version = "1.3.2"
+version = "1.4.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "frozenlist" },
+    { name = "typing-extensions", marker = "python_full_version < '3.13'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ba/b5/6d55e80f6d8a08ce22b982eafa278d823b541c925f11ee774b0b9c43473d/aiosignal-1.3.2.tar.gz", hash = "sha256:a8c255c66fafb1e499c9351d0bf32ff2d8a0321595ebac3b93713656d2436f54", size = 19424 }
+sdist = { url = "https://files.pythonhosted.org/packages/61/62/06741b579156360248d1ec624842ad0edf697050bbaf7c3e46394e106ad1/aiosignal-1.4.0.tar.gz", hash = "sha256:f47eecd9468083c2029cc99945502cb7708b082c232f9aca65da147157b251c7", size = 25007 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ec/6a/bc7e17a3e87a2985d3e8f4da4cd0f481060eb78fb08596c42be62c90a4d9/aiosignal-1.3.2-py2.py3-none-any.whl", hash = "sha256:45cde58e409a301715980c2b01d0c28bdde3770d8290b5eb2173759d9acb31a5", size = 7597 },
+    { url = "https://files.pythonhosted.org/packages/fb/76/641ae371508676492379f16e2fa48f4e2c11741bd63c48be4b12a6b09cba/aiosignal-1.4.0-py3-none-any.whl", hash = "sha256:053243f8b92b990551949e63930a839ff0cf0b0ebbe0597b0f3fb19e1a0fe82e", size = 7490 },
 ]
 
 [[package]]
@@ -201,16 +202,16 @@ wheels = [
 
 [[package]]
 name = "azure-core"
-version = "1.34.0"
+version = "1.35.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
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-    { url = "https://files.pythonhosted.org/packages/69/e0/552843e0d356fbb5256d21449fa957fa4eff3bbc135a74a691ee70c7c5da/typing_extensions-4.14.0-py3-none-any.whl", hash = "sha256:a1514509136dd0b477638fc68d6a91497af5076466ad0fa6c338e44e359944af", size = 43839 },
+    { url = "https://files.pythonhosted.org/packages/b5/00/d631e67a838026495268c2f6884f3711a15a9a2a96cd244fdaea53b823fb/typing_extensions-4.14.1-py3-none-any.whl", hash = "sha256:d1e1e3b58374dc93031d6eda2420a48ea44a36c2b4766a4fdeb3710755731d76", size = 43906 },
 ]
 
 [[package]]
@@ -3642,16 +3653,16 @@ wheels = [
 
 [[package]]
 name = "xarray"
-version = "2025.6.1"
+version = "2025.7.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "numpy" },
     { name = "packaging" },
     { name = "pandas" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/19/ec/e50d833518f10b0c24feb184b209bb6856f25b919ba8c1f89678b930b1cd/xarray-2025.6.1.tar.gz", hash = "sha256:a84f3f07544634a130d7dc615ae44175419f4c77957a7255161ed99c69c7c8b0", size = 3003185 }
+sdist = { url = "https://files.pythonhosted.org/packages/75/b5/d2f1fb2f583ae803b86280dcb7a4f81eef9d4c54f1ecde2307d1b6b1a147/xarray-2025.7.0.tar.gz", hash = "sha256:fd83ac8d638e7caef9d7f0c82bcdf380cede29d2ff84575133b2b95164af78ee", size = 3005754 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/82/8a/6b50c1dd2260d407c1a499d47cf829f59f07007e0dcebafdabb24d1d26a5/xarray-2025.6.1-py3-none-any.whl", hash = "sha256:8b988b47f67a383bdc3b04c5db475cd165e580134c1f1943d52aee4a9c97651b", size = 1314739 },
+    { url = "https://files.pythonhosted.org/packages/6e/40/c9127ffdcceb865044267eb8cccfd8973ee5f8174677d2a67f50df626674/xarray-2025.7.0-py3-none-any.whl", hash = "sha256:7b5d7267bd554ae119c7a0062f62b50517b4dd1968efc11f2553826b7d99297f", size = 1316539 },
 ]
 
 [[package]]
@@ -3762,7 +3773,7 @@ wheels = [
 
 [[package]]
 name = "zarr"
-version = "3.0.8"
+version = "3.0.10"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "donfig" },
@@ -3771,9 +3782,9 @@ dependencies = [
     { name = "packaging" },
     { name = "typing-extensions" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/52/60/9652fd0536fbaca8d08cbc1a5572c52e0ce01773297df75da8bb47e45907/zarr-3.0.8.tar.gz", hash = "sha256:88505d095af899a88ae8ac4db02f4650ef0801d2ff6f65b6d1f0a45dcf760a6d", size = 256825 }
+sdist = { url = "https://files.pythonhosted.org/packages/07/10/a1b6eabeb5a8681916568a7c6a7a1849c952131be127ccbd57e05d47d43e/zarr-3.0.10.tar.gz", hash = "sha256:1fd1318ade646f692d8f604be0e0ad125675a061196e612e3f7a2cfa9e957d1c", size = 263594 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/00/3b/e20bdf84088c11f2c396d034506cbffadd53e024111c1aa4585c2aba1523/zarr-3.0.8-py3-none-any.whl", hash = "sha256:7f81e7aec086437d98882aa432209107114bd7f3a9f4958b2af9c6b5928a70a7", size = 205364 },
+    { url = "https://files.pythonhosted.org/packages/45/57/3329346940f78de49047ddcb03fdbca9e16450c3a942688bf24201a322e5/zarr-3.0.10-py3-none-any.whl", hash = "sha256:110724c045fbe4ff5509a8a2a6b6098cb244a6af43da85eaeecef9821473163f", size = 209508 },
 ]
 
 [[package]]

From 4b2b1638189bf96299c22c5d1fcbd16322d17aec Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 7 Jul 2025 19:18:45 +0000
Subject: [PATCH 26/56] Revert .container changes

---
 .devcontainer/Dockerfile.cli    | 47 -------------------------
 .devcontainer/Dockerfile.dev    | 61 ---------------------------------
 .devcontainer/Dockerfile.nox    | 49 --------------------------
 .devcontainer/devcontainer.json | 20 +++++------
 4 files changed, 9 insertions(+), 168 deletions(-)
 delete mode 100644 .devcontainer/Dockerfile.cli
 delete mode 100644 .devcontainer/Dockerfile.dev
 delete mode 100644 .devcontainer/Dockerfile.nox

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
deleted file mode 100644
index 92720e34e..000000000
--- a/.devcontainer/Dockerfile.cli
+++ /dev/null
@@ -1,47 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# * Clone mdio-python and build a Docker image:
-#      git clone https://github.com/TGSAI/mdio-python.git
-#      cd mdio-python
-#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
-# * Run /bin/bash in the Docker container:
-#
-#
-# USAGE:
-#  docker run -it --rm --name mdio-cli mdio-cli --version
-#  docker run -it --rm --name mdio-cli mdio-cli --help
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy import \
-#     /DATA/segy_file.segy \
-#     /DATA/mdio_file.mdio \
-#     -loc 181,185 \
-#     -names inline,crossline
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy export \
-#     /DATA/mdio_file.mdio \
-#     /DATA/segy_file_copy.segy
-#
-FROM python:3.13-bookworm
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
-
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install .
-
-ENTRYPOINT ["mdio"]
-CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
deleted file mode 100644
index 05f135799..000000000
--- a/.devcontainer/Dockerfile.dev
+++ /dev/null
@@ -1,61 +0,0 @@
-# USAGE: 
-#   This file will be used by the VS Code DevContainer extension 
-#   to create a development environment for the mdio-python project.
-# HOW TO RUN TESTS
-#    1. Open the project in VS Code.
-#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
-#    3. Once the container is running, open a terminal in VS Code.
-#    4. Run the tests using the command: `nox -s test`.
-# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
-#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
-#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
-# NOTES: 
-#  1. The container will be run as the non-root user 'vscode' with UID 1000.
-#  2. The virtual environment will be setup at /home/vscode/venv 
-#  3. The project source code will be mounted at /workspaces/mdio-python
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
-
-# Install git for nox pre-commit
-RUN apt-get update \
-  && apt-get install -y --no-install-recommends \
-    git \
-  && rm -rf /var/lib/apt/lists/*
-
-ENV USERNAME="vscode"
-USER $USERNAME
-
-# # Add path to the user-installed packages
-# ENV PYTHONUSERBASE=/home/$USERNAME/.local
-# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
-
-WORKDIR /workspaces/mdio-python
-
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-# Initialize virtual environement in the container
-ENV VIRTUAL_ENV="/home/$USERNAME/venv"
-RUN python3 -m venv $VIRTUAL_ENV
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-
-# installing pytest is required for VS Code Python Testing
-RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
-
-# Install the project in editable mode
-# This allows for live reloading of the code during development
-RUN pip install -e .
-
-# RUN uv pip install snakeviz
-
-
-
-
-
-
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
deleted file mode 100644
index 103673fd2..000000000
--- a/.devcontainer/Dockerfile.nox
+++ /dev/null
@@ -1,49 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# 1. Make sure you have Docker installed and running.
-# 2. Clone mdio-python and build the Docker image:
-#    git clone https://github.com/TGSAI/mdio-python.git
-#    cd mdio-python
-#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
-# 3. Run /bin/bash in the Docker container :
-#    LOCAL_DATA_DIR=$(pwd); \
-#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
-#
-# USAGE:
-#   docker run -it --rm mdio-nox --list
-#   docker run -it --rm mdio-nox -s tests-3.13
-#   docker run -it --rm mdio-nox --no-stop-on-first-error
-#
-# NOTE: nox will fail if run in the directory mounted from the host machine
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
-ARG PYTHON_VERSION
-ARG LINUX_DISTRO
-RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install .
-
-# Install UV dependency manager and Nox test automator
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-ENTRYPOINT ["nox"]
-CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index dc80446c6..b618a5260 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile.dev",
+    "dockerfile": "Dockerfile",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    // "post_create_script": "bash ./.devcontainer/post-install.sh"
+    "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,9 +16,8 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-      "python.testing.pytestArgs": ["tests"], 
-          "python.testing.unittestEnabled": false,
-          "python.testing.pytestEnabled": true
+        "python.terminal.activateEnvInCurrentTerminal": true,
+        "python.defaultInterpreterPath": "/opt/venv/bin/python"
       },
       "extensions": [
         "ms-python.python",
@@ -28,18 +27,17 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker",
-        "eamodio.gitlens",
-        "visualstudioexptteam.vscodeintellicode"
+        "streetsidesoftware.code-spell-checker"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
-  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
-  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
+    // Re-use local Git configuration
+    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
   ]
 }

From c532c3b9e914b11f09c550f968c0c7ae350e6147 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 7 Jul 2025 19:24:03 +0000
Subject: [PATCH 27/56] PR review: remove DEVELOPER_NOTES.md

---
 DEVELOPER_NOTES.md | 136 ---------------------------------------------
 1 file changed, 136 deletions(-)
 delete mode 100644 DEVELOPER_NOTES.md

diff --git a/DEVELOPER_NOTES.md b/DEVELOPER_NOTES.md
deleted file mode 100644
index dec21dfe2..000000000
--- a/DEVELOPER_NOTES.md
+++ /dev/null
@@ -1,136 +0,0 @@
-# Developer Notes
-
-## MDIO v1 scope of work
-
-### TASK 1: Creation an empty MDIO v1 dataset with metadata defined using the v1 schema   
-#### DESCRIPTION
-In the v0, the following code was used to create an empty dataset:  
-
-```Python
-grid = Grid([Dimension("inline",...), Dimension("crossline", ...), Dimension("depth", ...)])
-variable = MDIOVariableConfig("stack_amplitude", ...)
-create_conf = MDIOCreateConfig(path="demo.mdio", grid=grid, variables=[variable])
-create_empty(config=create_conf)
-```
-
-In the v1 it is replaced with the following API, which uses v1 schema:
-
-```Python
-builder = MDIODatasetBuilder(...)
-builder.add_dimension("inline", ...)
-builder.add_dimension("crossline",...)
-builder.add_dimension("depth", ...)
-builder.add_coordinate("cdp_x",...)
-builder.add_coordinate("cdp_y",...)
-builder.add_variable("stack_amplitude",...)
-builder.to_mdio(store="demo.mdio")
-```
-
-#### DEFINITION OF DONE
-* The resulting v1 MDIO control `demo.mdio` file structure must be identical between Python and C++
-* Code coverage 90%
-* Code documentation will be updated:
-    * API doc strings are reviewed
-    * docs/tutorials/creation.ipynb - current version describes v0 API. Should be updated with v1 API
-    * docs/api_reference.md - will be updated with new API
-
-#### ASSUMPTIONS
-We expect that the following v0 workflows to keep working with this change
-* Populating MDIOs
-* Updating File and Checking with MDIOReader
-* Write to SEG-Y
-
-## Overall API design and implementation
-We will have only a strongly-typed (see pydantic) API. For example:
-
-```Python
-VariableMetadataList: TypeAlias = list[AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata]
-def add_dimension(
-    self,
-    name: str,
-    size: int,
-    long_name: str = None,
-    data_type: ScalarType | StructuredType = ScalarType.INT32,
-    metadata_info: VariableMetadataList | None = None,
-) -> "MDIODatasetBuilder":
-```
-
-Which will be used as following:
-
-```Python
-builder.add_dimension(
-    "length",
-    size=100,
-    data_type=ScalarType.FLOAT32,
-    metadata_info=[
-        AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
-        UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
-        ChunkGridMetadata(
-            chunk_grid=RegularChunkGrid(
-                configuration=RegularChunkShape(
-                    chunk_shape=[20]))),
-        StatisticsMetadata(stats_v1=SummaryStatistics(
-            count=100,
-            sum=1215.1,
-            sumSquares=125.12,
-            min=5.61,
-            max=10.84,
-            histogram=CenteredBinHistogram(
-                binCenters=[1, 2], 
-                counts=[10, 15])))
-    ]
-)
-```
-### Notes
-* When a coordinate or a variable is created, their schema allows to store their dimensions either as
-    * list of dimensions name `list[str]`, where the names refer to the dimensions defined in the builder._dimensions 
-    * list of named dimensions `list[NamedDimension]`, which duplicate the dimensions defined in the builder._dimensions
-    * Mixture of the two above `list[NamedDimension | str]` 
-
-    which approach should be used?  
-    
-    `RESOLUTION: We will be using the first approach.`
-
-    **IMPORTANT: For binary compatibility, We need to ensure that the C++ code follows the same logic**
-
-* Metadata population from a dictionary in add_coordinate() and add_variable() will not be supported to ensure that the API is strongly-typed. If it is needed, such conversion should be done as a separate step:
-    ```Python
-    def make_variable_metadata_list_from_dict(metadata: dict[str, Any]) -> VariableMetadataList:
-        # Implementation goes here
-    def make_coordinate_metadata_list_from_dict(metadata: dict[str, Any]) -> CoordinateMetadataList:
-        # Implementation goes here
-    ```
-    `RESOLUTION: The approach confirmed.`
-
-## Schema V1 questions
-
-* add_dimension(): Can a dimension with the same name be added multiple times. Options:
-   * Allowed: the second request is ignored (current implementation)
-   * Not Allowed: should it raise an error?
-
-    `RESOLUTION: The dimensions with the same name are not allowed`
-* The pydantic attribute names are different from the v1 schema attributes names.  What are the repercussions?
-    ```
-    'statsV1' <-> 'stats_v1'
-    'unitsV1' <-> 'units_v1'
-    'chunkGrid' <-> 'chunk_grid'
-    ```
-    `Under investigation`
-* Should histogram (e.g., SummaryStatistics) have a `histogram_type` attribute?
-
-  `Under investigation`
-* Units
-  * Why 'ftUS' is not supported by the schema? U.S. survey foot vs the International Foot:  
-    *"The U.S. survey foot is defined as 1200/3937 meters, while the international foot is defined as exactly 0.3048 meters.
-    https://www.axiomint.com/survey-foot-versus-international-foot-whats-the-difference/ 
-    "The REAL issue is when ... applied to State Plane coordinates in the N2,000,000 and E6,000,000 range! 
-    This ... moves a State Plane coordinate position 4 feet by 12 feet."*
-  * Why there are no dimensionless unis (for seismic amplitudes, inlines, etc.)
-
-  `Under investigation`
-
-## Design suggestions
-* Should we rename add_dimension to add_dimension_variable (or similar) to indicate that we not just providing the dimension name, but also creating the dimension variable
-
-    `RESOLUTION: Shorter names are preferable for public API. The function behavior will be described in the docs`
-

From 08798cd7323bb48653503f6de557619dd7cdb1c5 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 7 Jul 2025 19:36:04 +0000
Subject: [PATCH 28/56] PR Review: add_coordinate() should accept only
 data_type: ScalarType

---
 src/mdio/schemas/v1/dataset_builder.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 701fdbba3..89711e0c3 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -172,7 +172,7 @@ def add_coordinate(  # noqa: PLR0913
         *,
         long_name: str = None,
         dimensions: list[str],
-        data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
+        data_type: ScalarType = ScalarType.FLOAT32,
         metadata_info: CoordinateMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
         """Add a coordinate after adding at least one dimension.

From e8febe4f9749f15da8ae3f063d78898cfde3412b Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 7 Jul 2025 19:50:49 +0000
Subject: [PATCH 29/56] PR review: add_variable() data_type remove default

---
 src/mdio/schemas/v1/dataset_builder.py        |  2 +-
 .../v1/test_dataset_builder_add_variable.py   | 26 ++++++++++++-------
 tests/unit/v1/test_dataset_builder_build.py   |  4 ++-
 3 files changed, 21 insertions(+), 11 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 89711e0c3..dbedd3d6d 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -248,7 +248,7 @@ def add_variable(  # noqa: PLR0913
         *,
         long_name: str = None,
         dimensions: list[str],
-        data_type: ScalarType | StructuredType = ScalarType.FLOAT32,
+        data_type: ScalarType | StructuredType,
         compressor: Blosc | ZFP | None = None,
         coordinates: list[str] | None = None,
         metadata_info: VariableMetadataList | None = None,
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index ca6d8f955..5484ea92b 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -30,7 +30,7 @@ def test_add_variable() -> None:
     
     msg = "Must add at least one dimension before adding variables"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude", dimensions=["speed"])
+        builder.add_variable("amplitude", dimensions=["speed"], data_type = ScalarType.FLOAT32)
 
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 100)
@@ -39,20 +39,24 @@ def test_add_variable() -> None:
     # Validate required parameters
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable(bad_name, dimensions=["speed"])
+        builder.add_variable(bad_name, dimensions=["speed"], data_type = ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable("", dimensions=["speed"])
+        builder.add_variable("", dimensions=["speed"], data_type = ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=None)
+        builder.add_variable("bad_amplitude", dimensions=None, data_type = ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=[])
+        builder.add_variable("bad_amplitude", dimensions=[], data_type = ScalarType.FLOAT32)
 
     # Add a variable using non-existent dimensions
     msg="Pre-existing dimension named 'xline' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("bad_amplitude", dimensions=["inline", "xline", "depth"])
+        builder.add_variable("bad_amplitude", 
+                             dimensions=["inline", "xline", "depth"], 
+                             data_type = ScalarType.FLOAT32)
 
-    builder.add_variable("amplitude", dimensions=["inline", "crossline", "depth"])
+    builder.add_variable("amplitude", 
+                         dimensions=["inline", "crossline", "depth"], 
+                         data_type = ScalarType.FLOAT32)
     assert builder._state == _BuilderState.HAS_VARIABLES
     assert len(builder._dimensions) == 3 
     assert len(builder._variables) == 4 
@@ -63,6 +67,7 @@ def test_add_variable() -> None:
     with pytest.raises(ValueError, match=msg):
         builder.add_variable("bad_amplitude", 
                              dimensions=["inline", "crossline", "depth"],
+                             data_type = ScalarType.FLOAT32,
                              coordinates=["cdp-x", "cdp-y"])    
 
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
@@ -72,7 +77,8 @@ def test_add_variable() -> None:
     msg="Adding variable with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
         builder.add_variable("amplitude", 
-                             dimensions=["inline", "crossline", "depth"])
+                             dimensions=["inline", "crossline", "depth"],
+                             data_type = ScalarType.FLOAT32)
 
 
 def test_add_variable_with_defaults() -> None:
@@ -82,7 +88,9 @@ def test_add_variable_with_defaults() -> None:
     builder.add_dimension("crossline", 100)
     builder.add_dimension("depth", 100)
     # Add variable using defaults
-    builder.add_variable("seismic_amplitude", dimensions=["inline", "crossline", "depth"])
+    builder.add_variable("seismic_amplitude", 
+                         dimensions=["inline", "crossline", "depth"],
+                         data_type=ScalarType.FLOAT32)
     assert len(builder._dimensions) == 3 
     assert len(builder._variables) == 4 
     assert len(builder._coordinates) == 0 
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 488a9e6d2..2af86cdfc 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -33,7 +33,9 @@ def test_build() -> None:
         .add_dimension("y", 200)
         .add_coordinate("x_coord", dimensions=["x"])
         .add_coordinate("y_coord", dimensions=["y"])
-        .add_variable("data", dimensions=["x", "y"], long_name="Test Data")
+        .add_variable("data", dimensions=["x", "y"], 
+                      long_name="Test Data", 
+                      data_type=ScalarType.FLOAT32)
         .build()
     )
     assert isinstance(dataset, Dataset)

From 0a4be3f34dbb10ad5aac6716673fd479d816549c Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Tue, 8 Jul 2025 18:24:51 +0000
Subject: [PATCH 30/56] RE review: do not add dimension variable

---
 src/mdio/schemas/v1/dataset_builder.py        | 152 ++++----
 .../v1/test_dataset_builder_add_coordinate.py | 143 ++++---
 .../v1/test_dataset_builder_add_dimension.py  | 167 +--------
 .../v1/test_dataset_builder_add_variable.py   | 349 +++++++++++++-----
 tests/unit/v1/test_dataset_builder_build.py   | 105 ++++--
 tests/unit/v1/test_dataset_builder_helpers.py |  18 +-
 6 files changed, 495 insertions(+), 439 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index dbedd3d6d..f0621de30 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -46,10 +46,10 @@ class _BuilderState(Enum):
     HAS_VARIABLES = auto()
 
 
-def _get_dimension(
+def _get_named_dimension(
     dimensions: list[NamedDimension], name: str, size: int | None = None
 ) -> NamedDimension | None:
-    """Get a dimension by name and size from the list[NamedDimension] ."""
+    """Get a dimension by name and optional size from the list[NamedDimension]."""
     if dimensions is None:
         return False
     if not isinstance(name, str):
@@ -111,25 +111,18 @@ def __init__(self, name: str, attributes: UserAttributes | None = None):
         self._state = _BuilderState.INITIAL
         self._unnamed_variable_counter = 0
 
-    
     def add_dimension(  # noqa: PLR0913
         self,
         name: str,
-        size: int,
-        var_data_type: ScalarType | StructuredType = ScalarType.INT32,
-        var_metadata_info: VariableMetadataList | None = None,
+        size: int
     ) -> "MDIODatasetBuilder":
         """Add a dimension.
 
         This function be called at least once before adding coordinates or variables.
-        This call will create a dimension variable, if one does not yet exists
 
         Args:
             name: Name of the dimension
             size: Size of the dimension
-            var_long_name: Optional long name for the dimension variable
-            var_data_type: Data type for the dimension variable (defaults to INT32)
-            var_metadata_info: Optional metadata information for the dimension variable
 
         Returns:
             self: Returns self for method chaining
@@ -137,7 +130,7 @@ def add_dimension(  # noqa: PLR0913
         if not name:
             msg = "'name' must be a non-empty string"
             raise ValueError(msg)
-        
+
         # Validate that the dimension is not already defined
         old_var = next((e for e in self._dimensions if e.name == name), None)
         if old_var is not None:
@@ -146,26 +139,34 @@ def add_dimension(  # noqa: PLR0913
 
         dim = NamedDimension(name=name, size=size)
         self._dimensions.append(dim)
-
-        meta_dict = _to_dictionary(var_metadata_info)
-        # Create a variable for the dimension
-        dim_var = Variable(
-            name=name,
-            longName=f"'{name}' dimension variable",
-            # IMPORTANT: we use NamedDimension here, not the dimension name.
-            # Since the Dataset does not have a dimension list, we need to preserve 
-            # NamedDimension somewhere. Namely, in the variable created for the dimension
-            dimensions=[dim],
-            dataType=var_data_type,
-            compressor=None,
-            coordinates=None,
-            metadata=meta_dict,
-        )
-        self._variables.append(dim_var)
-
         self._state = _BuilderState.HAS_DIMENSIONS
         return self
 
+    def _get_coordinate(
+        self,
+        coordinates: list[Coordinate] | list[str],
+        name: str, size: int | None = None
+    ) -> Coordinate | None:
+        """Get a coordinate by name from the list[Coordinate] | list[str]."""
+        if coordinates is None:
+            return None
+
+        for c in coordinates:
+            if isinstance(c, str) and c == name:
+                # The coordinate is stored by name (str). 
+                # Find it in the builder global list and return it.
+                cc = next((v for v in self._coordinates if v.name == name), None)
+                if cc is None:
+                    msg = f"Pre-existing coordinate named {name!r} is not found"
+                    raise ValueError(msg)
+                return cc
+            if isinstance(c, Coordinate) and c.name == name:
+                # The coordinate is stored as an embedded Coordinate object.
+                # Return it.
+                return c
+
+        return None
+
     def add_coordinate(  # noqa: PLR0913
         self,
         name: str,
@@ -173,6 +174,7 @@ def add_coordinate(  # noqa: PLR0913
         long_name: str = None,
         dimensions: list[str],
         data_type: ScalarType = ScalarType.FLOAT32,
+        compressor: Blosc | ZFP | None = None,
         metadata_info: CoordinateMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
         """Add a coordinate after adding at least one dimension.
@@ -200,48 +202,66 @@ def add_coordinate(  # noqa: PLR0913
             msg = "'dimensions' must be a non-empty list"
             raise ValueError(msg)
         old_var = next((e for e in self._coordinates if e.name == name), None)
-
         # Validate that the coordinate is not already defined
         if old_var is not None:
             msg = "Adding coordinate with the same name twice is not allowed"
             raise ValueError(msg)
-        
+
         # Validate that all referenced dimensions are already defined
-        for dim in dimensions:
-            if next((d for d in self._dimensions if d.name == dim), None) is None:
-                msg = f"Pre-existing dimension named {dim!r} is not found"
+        named_dimensions = []
+        for dim_name in dimensions:
+            nd = _get_named_dimension(self._dimensions, dim_name)
+            if nd is None:
+                msg = f"Pre-existing dimension named {dim_name!r} is not found"
                 raise ValueError(msg)
+            named_dimensions.append(nd)    
 
         meta_dict = _to_dictionary(metadata_info)
         coord = Coordinate(
             name=name,
             longName=long_name,
-            # We ass names: sts, not list[NamedDimension | str]
-            dimensions=dimensions,
+            dimensions=named_dimensions,
+            compressor=compressor,
             dataType=data_type,
             metadata=meta_dict
         )
         self._coordinates.append(coord)
 
         # Add a coordinate variable to the dataset
-        var_meta_dict = _to_dictionary(coord.metadata)
-        coord_var = Variable(
+        self.add_variable(
             name=coord.name,
-            longName=f"'{coord.name}' coordinate variable",
-            dimensions=coord.dimensions,
-            dataType=coord.data_type,
-            compressor=None,
-            # IMPORTANT: we always use the Coordinate here, not the coordinate name
-            # Since the Dataset does not have a coordinate list, we need to preserve Coordinate
-            # somewhere. Namely, in the variable created for the coordinate
-            coordinates=[coord],
-            metadata=var_meta_dict
+            long_name=f"'{coord.name}' coordinate variable",
+            dimensions=dimensions,  # dimension names (list[str])
+            data_type=coord.data_type,
+            compressor=compressor,
+            coordinates=[name],  # Use the coordinate name as a reference
+            metadata_info=coord.metadata
         )
-        self._variables.append(coord_var)
 
         self._state = _BuilderState.HAS_COORDINATES
         return self
 
+    def add_dimension_coordinate(
+        self,
+        dimension_name: str,
+        *,
+        data_type: ScalarType,
+        compressor: Blosc | ZFP | None = None,
+        metadata_info: VariableMetadataList | None = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a dimension coordinate variable for a pre-existing dimension.
+        This is a convenience method to create a coordinate variable
+        that represents sampling along a dimension.
+        """
+        self.add_coordinate(dimension_name,
+                            long_name=dimension_name,
+                            dimensions=[dimension_name],
+                            data_type=data_type,
+                            compressor=compressor,
+                            metadata_info=_to_dictionary(metadata_info))
+
+        return self
+
     def add_variable(  # noqa: PLR0913
         self,
         name: str,
@@ -255,9 +275,13 @@ def add_variable(  # noqa: PLR0913
     ) -> "MDIODatasetBuilder":
         """Add a variable after adding at least one dimension and, optionally, coordinate.
 
-        This function must be called after all required dimensions are added via add_dimension().
+        This function must be called after all required dimensions are added via add_dimension()
         This function must be called after all required coordinates are added via add_coordinate().
 
+        If this function is called with a single dimension name that matches the variable name,
+        it will create a dimension variable. Dimension variables are special variables that
+        represent sampling along a dimension.
+
         Args:
             name: Name of the variable
             long_name: Optional long name for the variable
@@ -280,7 +304,7 @@ def add_variable(  # noqa: PLR0913
         if dimensions is None or not dimensions:
             msg = "'dimensions' must be a non-empty list"
             raise ValueError(msg)
-        
+
         # Validate that the variable is not already defined
         old_var = next((e for e in self._variables if e.name == name), None)
         if old_var is not None:
@@ -288,10 +312,13 @@ def add_variable(  # noqa: PLR0913
             raise ValueError(msg)
 
         # Validate that all referenced dimensions are already defined
-        for dim in dimensions:
-            if next((e for e in self._dimensions if e.name == dim), None) is None:
-                msg = f"Pre-existing dimension named {dim!r} is not found"
+        named_dimensions = []
+        for dim_name in dimensions:
+            nd = _get_named_dimension(self._dimensions, dim_name)
+            if nd is None:
+                msg = f"Pre-existing dimension named {dim_name!r} is not found"
                 raise ValueError(msg)
+            named_dimensions.append(nd)
 
         # Validate that all referenced coordinates are already defined
         if coordinates is not None:
@@ -301,17 +328,16 @@ def add_variable(  # noqa: PLR0913
                     raise ValueError(msg)
 
         meta_dict = _to_dictionary(metadata_info)
-        self._variables.append(
-            Variable(
-                name=name,
-                long_name=long_name,
-                dimensions=dimensions,
-                data_type=data_type,
-                compressor=compressor,
-                coordinates=coordinates,
-                metadata=meta_dict,
-            )
-        )
+        var = Variable(
+            name=name,
+            long_name=long_name,
+            dimensions=named_dimensions,
+            data_type=data_type,
+            compressor=compressor,
+            coordinates=coordinates,
+            metadata=meta_dict)
+        self._variables.append(var)
+
         self._state = _BuilderState.HAS_VARIABLES
         return self
 
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 0adb9240b..cae46834f 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -6,13 +6,15 @@
 
 import pytest
 
+from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _get_named_dimension
 from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.variable import VariableMetadata
 
 
 def test_add_coordinate() -> None:
@@ -25,7 +27,7 @@ def test_add_coordinate() -> None:
         builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
 
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
+    builder.add_dimension("crossline", 200)
 
     # Validate required parameters
     bad_name = None
@@ -47,18 +49,21 @@ def test_add_coordinate() -> None:
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
     assert builder._state == _BuilderState.HAS_COORDINATES
     assert len(builder._dimensions) == 2 
-    # 2 variables for dimensions, 1 variable for coordinates
-    assert len(builder._variables) == 3 
+    # 1 variable for coordinates
+    assert len(builder._variables) == 1 
     assert len(builder._coordinates) == 1
     
     # Validate that we created a coordinate variable
     var_cdp = next(e for e in builder._variables if e.name == "cdp-x")
     assert var_cdp is not None
-    # Validate that dimensions are stored as names
-    assert set(var_cdp.dimensions) == {"inline", "crossline"}
+    assert len(var_cdp.dimensions) == 2
+    assert _get_named_dimension(var_cdp.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(var_cdp.dimensions, "crossline", 200) is not None
     # Validate that coordinates are stored as Coordinate
     assert len(var_cdp.coordinates) == 1
-    assert next((e for e in var_cdp.coordinates if e.name == "cdp-x"), None) is not None
+    # No dimensions are stored in coordinates
+    # Validate that non-dimension coordinates
+    assert builder._get_coordinate(var_cdp.coordinates, "cdp-x") is not None
 
     # Adding coordinate with the same name twice
     msg="Adding coordinate with the same name twice is not allowed"
@@ -69,96 +74,76 @@ def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
     builder = MDIODatasetBuilder("test_dataset")
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
+    builder.add_dimension("crossline", 200)
     # Add coordinate using defaults
     builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
     assert len(builder._dimensions) == 2 
-    # 2 variables for dimensions, 1 variable for coordinates
-    assert len(builder._variables) == 3
+    # 1 variable for coordinates
+    assert len(builder._variables) == 1
     assert len(builder._coordinates) == 1
-    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert crd0 is not None
-    # NOTE: add_variable() stores dimensions as names
-    assert set(crd0.dimensions) == {"inline", "crossline"}
-    assert crd0.long_name is None               # Default value
-    assert crd0.data_type == ScalarType.FLOAT32 # Default value
-    assert crd0.metadata is None                # Default value
- 
-def test_coordinate_with_units() -> None:
-    """Test adding coordinates with units."""
-    builder = MDIODatasetBuilder("test_dataset")
-    builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
-    # Add coordinate with units
-    builder.add_coordinate(
-        "cdp", 
-        dimensions=["inline", "crossline"],
-        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
-    )
-    assert len(builder._dimensions) == 2 
-    # 2 variables for dimensions, 1 variable for coordinates
-    assert len(builder._variables) == 3  
-    assert len(builder._coordinates) == 1 
-    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert crd0 is not None
-    # NOTE: add_coordinate() stores dimensions as names
-    assert set(crd0.dimensions) == {"inline", "crossline"}
-    assert crd0.long_name is None               # Default value
-    assert crd0.data_type == ScalarType.FLOAT32 # Default value
-    assert crd0.metadata.attributes is None
-    assert crd0.metadata.units_v1.length == LengthUnitEnum.FOOT
-
 
-def test_coordinate_with_attributes() -> None:
-    """Test adding coordinates with attributes."""
-    builder = MDIODatasetBuilder("test_dataset")
-    builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
-    # Add coordinate with attributes
-    builder.add_coordinate(
-        "cdp", 
-        dimensions=["inline", "crossline"], 
-        metadata_info=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})],
-    )
-    assert len(builder._dimensions) == 2 
-    # 2 variables for dimensions, 1 variable for coordinates
-    assert len(builder._variables) == 3  
-    assert len(builder._coordinates) == 1 
-    # NOTE: add_coordinate() stores dimensions as names
-    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert crd0 is not None
-    assert set(crd0.dimensions) == {"inline", "crossline"}
-    assert crd0.long_name is None               # Default value
-    assert crd0.data_type == ScalarType.FLOAT32 # Default value
-    assert crd0.metadata.attributes["MGA"] == 51
-    assert crd0.metadata.attributes["UnitSystem"] == "Imperial"
-    assert crd0.metadata.units_v1 is None
+    # Validate: the structure of the coordinate
+    coord_cdp = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert coord_cdp is not None
+    assert len(coord_cdp.dimensions) == 2
+    assert _get_named_dimension(coord_cdp.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(coord_cdp.dimensions, "crossline", 200) is not None
+    assert coord_cdp.long_name is None               # Default value
+    assert coord_cdp.data_type == ScalarType.FLOAT32 # Default value
+    assert coord_cdp.compressor is None              # Default value
+    assert coord_cdp.metadata is None                # Default value
 
 
-def test_coordinate_with_full_metadata() -> None:
+def test_coordinate_with_full_parameters() -> None:
     """Test adding coordinates with all metadata."""
     builder = MDIODatasetBuilder("test_dataset")
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
+    builder.add_dimension("crossline", 200)
     # Add coordinate with all metadata
     builder.add_coordinate(
         "cdp",
+        long_name = "Common Depth Point",
         dimensions=["inline", "crossline"],
+        data_type = ScalarType.FLOAT16,
+        compressor = Blosc(algorithm="zstd"),
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
             UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
     )
+    # Validate: the state of the builder
+    assert builder._state == _BuilderState.HAS_COORDINATES
     assert len(builder._dimensions) == 2 
-    # 2 variables for dimensions, 1 variable for coordinates
-    assert len(builder._variables) == 3  
+    # 1 variable for coordinates
+    assert len(builder._variables) == 1 
     assert len(builder._coordinates) == 1 
-    # NOTE: add_coordinate() stores dimensions as names
-    crd0 = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert crd0 is not None
-    assert set(crd0.dimensions) == {"inline", "crossline"}
-    assert crd0.long_name is None               # Default value
-    assert crd0.data_type == ScalarType.FLOAT32 # Default value
-    assert crd0.metadata.attributes["MGA"] == 51
-    assert crd0.metadata.attributes["UnitSystem"] == "Imperial"
-    assert crd0.metadata.units_v1.length == LengthUnitEnum.FOOT
 
+    # Validate: the structure of the coordinate
+    coord_cdp = next((e for e in builder._coordinates if e.name == "cdp"), None)
+    assert coord_cdp is not None
+    assert len(coord_cdp.dimensions) == 2
+    assert _get_named_dimension(coord_cdp.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(coord_cdp.dimensions, "crossline", 200) is not None
+    assert coord_cdp.long_name == "Common Depth Point"
+    assert coord_cdp.data_type == ScalarType.FLOAT16 
+    assert isinstance(coord_cdp.compressor, Blosc)
+    assert coord_cdp.compressor.algorithm == "zstd"
+    assert coord_cdp.metadata.attributes["MGA"] == 51
+    assert coord_cdp.metadata.attributes["UnitSystem"] == "Imperial"
+    assert coord_cdp.metadata.units_v1.length == LengthUnitEnum.FOOT
+
+     # Validate: the structure of the created variable
+    v = next((v for v in builder._variables if v.name == "cdp"), None)
+    assert v is not None
+    assert v.long_name == "'cdp' coordinate variable"
+    assert len(v.dimensions) == 2
+    assert _get_named_dimension(v.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(v.dimensions, "crossline", 200) is not None
+    assert v.data_type == ScalarType.FLOAT16
+    assert isinstance(v.compressor, Blosc)
+    assert v.compressor.algorithm == "zstd"
+    assert len(v.coordinates) == 1
+    assert builder._get_coordinate(v.coordinates, "cdp") is not None
+    assert isinstance(v.metadata, VariableMetadata)
+    assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
+    assert v.metadata.attributes["MGA"] == 51
+    assert v.metadata.attributes["UnitSystem"] == "Imperial"
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index 1465a8925..b701380fb 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -13,7 +13,7 @@
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
-from mdio.schemas.v1.dataset_builder import _get_dimension
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.stats import SummaryStatistics
@@ -38,21 +38,7 @@ def test_add_dimension() -> None:
     builder.add_dimension("x", 100)
     assert builder._state == _BuilderState.HAS_DIMENSIONS
     assert len(builder._dimensions) == 1
-    assert _get_dimension(builder._dimensions, "x", 100) is not None
-
-    # Validate that we have created a dimension variable and 
-    # that variable has the embedded NamedDimension
-    assert len(builder._variables) == 1  
-    var_x = next(e for e in builder._variables if e.name == "x")
-    assert var_x is not None
-    assert len(var_x.dimensions) == 1
-    # Validate that the dimension variable has the NamedDimension
-    assert _get_dimension(var_x.dimensions, "x", 100) is not None
-    assert var_x.long_name == "'x' dimension variable"
-    assert var_x.data_type == ScalarType.INT32
-    assert var_x.compressor is None
-    assert var_x.coordinates is None
-    assert var_x.metadata is None
+    assert _get_named_dimension(builder._dimensions, "x", 100) is not None
 
     # Validate that we can't add a dimension with the same name twice
     with pytest.raises(
@@ -66,152 +52,3 @@ def test_add_dimension() -> None:
     with pytest.raises(ValueError, match=msg):
         builder.add_dimension("x", 200)
 
-def test_add_dimension_with_defaults() -> None:
-    """Test dimension builder state transitions and functionality."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    # First dimension should change state to HAS_DIMENSIONS and create a variable
-    builder.add_dimension("x", 100)
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 1  
-    # Validate that the dimension builder has the NamedDimension
-    assert _get_dimension(builder._dimensions, "x", 100) is not None
-    var_x = next((e for e in builder._variables if e.name == "x"), None)
-    assert var_x is not None
-    assert var_x.name == "x"
-    assert var_x.long_name == "'x' dimension variable"
-    assert var_x.data_type == ScalarType.INT32
-    assert var_x.compressor is None
-    assert var_x.coordinates is None
-    assert var_x.metadata is None
-
-def test_add_dimension_with_units() -> None:
-    """Test adding dimensions with units."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    # Add dimension with strongly-typed unit list of single-item
-    builder.add_dimension(
-        "length",
-        size=100,
-        var_data_type=ScalarType.FLOAT64,
-        var_metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
-    )
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "length"
-    assert var0.long_name == "'length' dimension variable"
-    assert var0.data_type == ScalarType.FLOAT64
-    assert var0.compressor is None
-    assert var0.coordinates is None
-    assert var0.metadata.units_v1.length == LengthUnitEnum.FOOT
-
-def test_add_dimension_with_attributes() -> None:
-    """Test adding dimensions with attributes."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    builder.add_dimension(
-        "length",
-        size=100,
-        var_data_type=ScalarType.FLOAT32,
-        var_metadata_info=[UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})],
-    )
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "length"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.attributes["MGA"] == 51
-    assert var0.metadata.attributes["UnitSystem"] == "Imperial"
-
-
-def test_add_dimension_with_chunk_grid() -> None:
-    """Test adding dimensions with chunk grid."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    grid_definition = RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
-    builder.add_dimension(
-        "length",
-        size=100,
-        var_data_type=ScalarType.FLOAT32,
-        var_metadata_info=[ChunkGridMetadata(chunk_grid=grid_definition)],
-    )
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "length"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.chunk_grid.name == "regular"
-    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]
-
-
-def test_add_dimension_with_stats() -> None:
-    """Test adding dimensions with stats."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    builder.add_dimension(
-        "depth",
-        size=100,
-        var_data_type=ScalarType.FLOAT32,
-        var_metadata_info=[
-            StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    # TODO(DmitriyRepin, #0): Also test EdgeDefinedHistogram
-                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
-                )
-            )
-        ],
-    )
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "depth"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.stats_v1.count == 100  
-    assert var0.metadata.stats_v1.sum == 1215.1  
-
-
-def test_add_dimension_with_full_metadata() -> None:
-    """Test adding dimensions with all metadata."""
-    builder = MDIODatasetBuilder("test_dataset")
-
-    builder.add_dimension(
-        "length",
-        size=100,
-        var_data_type=ScalarType.FLOAT32,
-        var_metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
-            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
-            ),
-            StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
-                )
-            ),
-        ],
-    )
-
-    assert len(builder._variables) == 1
-    var0 = builder._variables[0]
-    assert var0.name == "length"
-    assert var0.data_type == ScalarType.FLOAT32
-    assert var0.metadata.units_v1.length == LengthUnitEnum.FOOT
-    assert var0.metadata.attributes["MGA"] == 51
-    assert var0.metadata.attributes["UnitSystem"] == "Imperial"
-    assert var0.metadata.chunk_grid.name == "regular"
-    assert var0.metadata.chunk_grid.configuration.chunk_shape == [20]  
-    assert var0.metadata.stats_v1.count == 100  
-    assert var0.metadata.stats_v1.sum == 1215.1  
-    assert var0.metadata.stats_v1.sum_squares == 125.12  
-    assert var0.metadata.stats_v1.min == 5.61  
-    assert var0.metadata.stats_v1.max == 10.84  
-    assert var0.metadata.stats_v1.histogram.bin_centers == [1, 2]  
-    assert var0.metadata.stats_v1.histogram.counts == [10, 15]  
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 5484ea92b..ad24b9de4 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -6,13 +6,14 @@
 
 import pytest
 
+from mdio.schemas import builder
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _get_named_dimension
 from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
@@ -23,145 +24,299 @@
 from mdio.schemas.v1.variable import VariableMetadata
 
 
-def test_add_variable() -> None:
+def test_add_variable_no_coords() -> None:
     """Test adding variable. Check the state transition and validate required parameters.."""
     builder = MDIODatasetBuilder("test_dataset")
     assert builder._state == _BuilderState.INITIAL
-    
+
+    # Validate: Must add at least one dimension before adding variables
     msg = "Must add at least one dimension before adding variables"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude", dimensions=["speed"], data_type = ScalarType.FLOAT32)
+        builder.add_variable("amplitude", dimensions=[
+                             "speed"], data_type=ScalarType.FLOAT32)
 
+   # Add dimension before we can add a data variable
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
-    builder.add_dimension("depth", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
 
-    # Validate required parameters
+    # Validate: required parameters must be preset
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable(bad_name, dimensions=["speed"], data_type = ScalarType.FLOAT32)
+        builder.add_variable(bad_name, dimensions=[
+                             "speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable("", dimensions=["speed"], data_type = ScalarType.FLOAT32)
+        builder.add_variable(
+            "", dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=None, data_type = ScalarType.FLOAT32)
+        builder.add_variable("bad_amplitude", dimensions=None,
+                             data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=[], data_type = ScalarType.FLOAT32)
+        builder.add_variable("bad_amplitude", dimensions=[],
+                             data_type=ScalarType.FLOAT32)
 
-    # Add a variable using non-existent dimensions
-    msg="Pre-existing dimension named 'xline' is not found"
+    # Validate: Add a variable using non-existent dimensions is not allowed
+    msg = "Pre-existing dimension named 'il' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("bad_amplitude", 
-                             dimensions=["inline", "xline", "depth"], 
-                             data_type = ScalarType.FLOAT32)
+        builder.add_variable("bad_amplitude",
+                             dimensions=["il", "xl", "depth"],
+                             data_type=ScalarType.FLOAT32)
 
-    builder.add_variable("amplitude", 
-                         dimensions=["inline", "crossline", "depth"], 
-                         data_type = ScalarType.FLOAT32)
+    # Add a variable without coordinates
+    builder.add_variable("amplitude",
+                         dimensions=["inline", "crossline", "depth"],
+                         data_type=ScalarType.FLOAT32)
     assert builder._state == _BuilderState.HAS_VARIABLES
-    assert len(builder._dimensions) == 3 
-    assert len(builder._variables) == 4 
-    assert len(builder._coordinates) == 0  
+    assert len(builder._dimensions) == 3
+    assert len(builder._variables) == 1
+    assert len(builder._coordinates) == 0
+
+    # Validate the structure of the created variable
+    var_ampl = next((e for e in builder._variables if e.name == "amplitude"), None)
+    assert var_ampl is not None
+    # Validate that dimensions are stored as NamedDimensions
+    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
+    # Validate that no coordinates are set
+    assert var_ampl.coordinates is None
 
-    # Add a variable using non-existent coordinates
-    msg="Pre-existing coordinate named 'cdp-x' is not found"
+    # Validate: adding a variable with the same name twice is not allowed
+    msg = "Adding variable with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("bad_amplitude", 
+        builder.add_variable("amplitude",
                              dimensions=["inline", "crossline", "depth"],
-                             data_type = ScalarType.FLOAT32,
-                             coordinates=["cdp-x", "cdp-y"])    
+                             data_type=ScalarType.FLOAT32)
 
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
-    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
 
-    # Adding variable with the same name twice
-    msg="Adding variable with the same name twice is not allowed"
+def test_add_variable_with_coords() -> None:
+    """Test adding variable. Check the state transition and validate required parameters.."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+
+    # Add dimension coordinates before we can add a data variable
+    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
+    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
+
+    # Validate: adding a variable with a coordinate that has not been pre-created is not allowed
+    msg = "Pre-existing coordinate named 'depth' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude", 
+        builder.add_variable("ampl",
                              dimensions=["inline", "crossline", "depth"],
-                             data_type = ScalarType.FLOAT32)
+                             coordinates=["inline", "crossline", "depth"],
+                             data_type=ScalarType.FLOAT32)
+
+    # Add a variable with pre-defined dimension coordinates
+    builder.add_variable("ampl",
+                         dimensions=["inline", "crossline", "depth"],
+                         coordinates=["inline", "crossline"],
+                         data_type=ScalarType.FLOAT32)
+
+    assert builder._state == _BuilderState.HAS_VARIABLES
+    assert len(builder._dimensions) == 3
+    # 2 dim coordinate variables + 1 data variables
+    assert len(builder._variables) == 3
+    assert len(builder._coordinates) == 2
+
+    # Validate: the structure of the created variable
+    var_ampl = next((e for e in builder._variables if e.name == "ampl"), None)
+    assert var_ampl is not None
+    # Validate: that dimensions are stored as NamedDimensions
+    assert len(var_ampl.dimensions) == 3
+    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
+    assert len(var_ampl.coordinates) == 2
+    # Validate that dim coordinates "inline" and "crossline" are set
+    assert builder._get_coordinate(var_ampl.coordinates, "inline") is not None
+    assert builder._get_coordinate(var_ampl.coordinates, "crossline") is not None
+    # "depth" coordinate is not set
+
+    # Add non-dim coordinates (e.g., 2D coordinates)
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
+
+    # Add a variable with pre-defined dimension and non-dimension coordinates
+    builder.add_variable("ampl2",
+                         dimensions=["inline", "crossline", "depth"],
+                         coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+                         data_type=ScalarType.FLOAT32)
+
+    assert builder._state == _BuilderState.HAS_VARIABLES
+    assert len(builder._dimensions) == 3
+    # 2 dim coordinate variables + 2 non-dim coordinate variables + 1 data variables
+    assert len(builder._variables) == 6
+    assert len(builder._coordinates) == 4
+
+    # Validate: the structure of the created variable
+    var_ampl2 = next((e for e in builder._variables if e.name == "ampl2"), None)
+    assert var_ampl2 is not None
+    # Validate: that dimensions are stored as NamedDimensions
+    assert len(var_ampl2.dimensions) == 3
+    assert _get_named_dimension(var_ampl2.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(var_ampl2.dimensions, "crossline", 200) is not None
+    assert _get_named_dimension(var_ampl2.dimensions, "depth", 300) is not None
+    assert len(var_ampl2.coordinates) == 4
+    # Validate that dim coordinates "inline" and "crossline" are set
+    assert builder._get_coordinate(var_ampl2.coordinates, "inline") is not None
+    assert builder._get_coordinate(var_ampl2.coordinates, "crossline") is not None
+    # "depth" coordinate is not set
+    # Validate that non-dimension coordinates "cdp-x" and "cdp-y"
+    assert builder._get_coordinate(var_ampl2.coordinates, "cdp-x") is not None
+    assert builder._get_coordinate(var_ampl2.coordinates, "cdp-y") is not None
+
+
+def test_add_dimension_coordinate() -> None:
+    """Test adding dimension variable."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+
+    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
+
+    # Validate: that coordinate is stored in the builder global list
+    coord_il = builder._get_coordinate(builder._coordinates, "inline")
+    # Validate: that dimensions are stored as NamedDimensions in the coordinate
+    assert _get_named_dimension(coord_il.dimensions, "inline", 100) is not None
+    # Validate: a dim variable has been created
+    var_il = next((e for e in builder._variables if e.name == "inline"), None)
+    assert var_il is not None
+    # Validate: the variable has the expected properties
+    assert var_il.name == "inline"
+    assert var_il.long_name == "'inline' coordinate variable"
+    assert len(var_il.dimensions) == 1
+    assert _get_named_dimension(var_il.dimensions, "inline", 100) is not None
+    assert var_il.data_type == ScalarType.INT32
+    assert var_il.compressor is None  # Default value
+    assert len(var_il.coordinates) == 1
+    assert builder._get_coordinate(var_il.coordinates, "inline") is not None
+    assert var_il.metadata is None  # Default value
 
 
 def test_add_variable_with_defaults() -> None:
     """Test adding variable with default arguments."""
     builder = MDIODatasetBuilder("test_dataset")
+    # Add dimensions before we can add a data variables
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
-    builder.add_dimension("depth", 100)
-    # Add variable using defaults
-    builder.add_variable("seismic_amplitude", 
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+    # Add dimension coordinates
+    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
+    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
+    builder.add_dimension_coordinate("depth",
+                                     data_type=ScalarType.FLOAT32,
+                                     metadata_info=[
+                                         AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))])
+
+    # Add data variable using defaults
+    builder.add_variable("ampl",
                          dimensions=["inline", "crossline", "depth"],
                          data_type=ScalarType.FLOAT32)
-    assert len(builder._dimensions) == 3 
-    assert len(builder._variables) == 4 
-    assert len(builder._coordinates) == 0 
-    var0 = next((e for e in builder._variables if e.name == "seismic_amplitude"), None)
-    assert var0 is not None
-    # NOTE: add_variable() stores dimensions as names
-    assert set(var0.dimensions) == {"inline", "crossline", "depth"}
-    assert var0.long_name is None               # Default value
-    assert var0.data_type == ScalarType.FLOAT32 # Default value
-    assert var0.compressor is None              # Default value
-    assert var0.coordinates is None             # Default value
-    assert var0.metadata is None                # Default value
+    assert len(builder._dimensions) == 3
+    # 3 dim coordinate variables + 1 data variable = 4
+    assert len(builder._variables) == 4
+    assert len(builder._coordinates) == 3
+
+    # Validate: the structure of the created variable
+    var_ampl = next((e for e in builder._variables if e.name == "ampl"), None)
+    assert var_ampl is not None
+    assert var_ampl.name == "ampl"
+    assert var_ampl.long_name is None  # Default value
+    # Validate: that dimensions are stored as NamedDimensions
+    assert len(var_ampl.dimensions) == 3
+    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
+    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
+    assert var_ampl.data_type == ScalarType.FLOAT32
+    assert var_ampl.compressor is None  # Default value
+    assert var_ampl.coordinates is None  # Default value
+    # Validate: the variable has the expected properties
+    assert var_ampl.metadata is None  # Default value
+
 
 def test_add_variable_full_parameters() -> None:
     """Test adding variable with full parameters."""
     builder = MDIODatasetBuilder("test_dataset")
+    # Add dimensions before we can add a data variables
     builder.add_dimension("inline", 100)
-    builder.add_dimension("crossline", 100)
-    builder.add_dimension("depth", 100)
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
-    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
-    builder.add_variable("seismic_amplitude", 
-        long_name="Amplitude (dimensionless)",
-        dimensions=["inline", "crossline", "depth"],    
-        data_type=ScalarType.FLOAT64, 
-        compressor=Blosc(algorithm="zstd"), 
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
-            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
-            ),
-            StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
-                )
-            ),
-        ])
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+
+    # Add dimension coordinates
+    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
+    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
+    builder.add_dimension_coordinate("depth", data_type=ScalarType.INT32)
+    
+    # Add coordinates before we can add a data variable
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+
+    # Add data variable with full parameters
+    builder.add_variable("ampl",
+                         long_name="Amplitude (dimensionless)",
+                         dimensions=["inline", "crossline", "depth"],
+                         data_type=ScalarType.FLOAT32,
+                         compressor=Blosc(algorithm="zstd"),
+                         coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+                         metadata_info=[
+                             AllUnits(units_v1=LengthUnitModel(
+                                 length=LengthUnitEnum.FOOT)),
+                             UserAttributes(
+                                 attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+                             ChunkGridMetadata(
+                                 chunk_grid=RegularChunkGrid(
+                                     configuration=RegularChunkShape(chunk_shape=[20]))
+                             ),
+                             StatisticsMetadata(
+                                 stats_v1=SummaryStatistics(
+                                     count=100,
+                                     sum=1215.1,
+                                     sumSquares=125.12,
+                                     min=5.61,
+                                     max=10.84,
+                                     histogram=CenteredBinHistogram(
+                                         binCenters=[1, 2], counts=[10, 15]),
+                                 )
+                             ),
+                         ])
+    # Validate: the state of the builder
+    assert builder._state == _BuilderState.HAS_VARIABLES
     assert len(builder._dimensions) == 3
-    assert len(builder._coordinates) == 2  
-    # We expect 6 variables:
-    # 3 variables for dimensions, 2 variables for coordinates, and 1 variable for seismic_amplitude
-    assert len(builder._variables) == 6 
-    v = next((v for v in builder._variables if v.name == "seismic_amplitude"), None)
+    # 3 dim coords + 2 non-dim coords = 5
+    assert len(builder._coordinates) == 5
+    # 3 dim coord + 2 non-dim coords, and 1 data variable
+    assert len(builder._variables) == 6
+
+     # Validate: the structure of the created variable
+    v = next((v for v in builder._variables if v.name == "ampl"), None)
     assert v is not None
+    assert v.name == "ampl"
     assert v.long_name == "Amplitude (dimensionless)"
-    # NOTE: add_variable() stores dimensions as names
-    assert set(v.dimensions) == {"inline", "crossline", "depth"}
-    assert v.data_type == ScalarType.FLOAT64
+    assert len(v.dimensions) == 3
+    assert _get_named_dimension(v.dimensions, "inline", 100) is not None
+    assert _get_named_dimension(v.dimensions, "crossline", 200) is not None
+    assert _get_named_dimension(v.dimensions, "depth", 300) is not None
+    assert v.data_type == ScalarType.FLOAT32
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
-    # NOTE: add_variable() stores coordinates as names
-    assert set(v.coordinates) == {"cdp-x", "cdp-y"}
-    assert v.metadata.stats_v1.count == 100 
+    assert len(v.coordinates) == 5
+    assert builder._get_coordinate(v.coordinates, "inline") is not None
+    assert builder._get_coordinate(v.coordinates, "crossline") is not None
+    assert builder._get_coordinate(v.coordinates, "depth") is not None
+    assert builder._get_coordinate(v.coordinates, "cdp-x") is not None
+    assert builder._get_coordinate(v.coordinates, "cdp-y") is not None
+    assert v.metadata.stats_v1.count == 100
     assert isinstance(v.metadata, VariableMetadata)
     assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
     assert v.metadata.attributes["MGA"] == 51
-    assert v.metadata.attributes["UnitSystem"] == "Imperial"  
+    assert v.metadata.attributes["UnitSystem"] == "Imperial"
     assert v.metadata.chunk_grid.name == "regular"
-    assert v.metadata.chunk_grid.configuration.chunk_shape == [20]  
-    assert v.metadata.stats_v1.count == 100  
-    assert v.metadata.stats_v1.sum == 1215.1  
-    assert v.metadata.stats_v1.sum_squares == 125.12  
-    assert v.metadata.stats_v1.min == 5.61  
-    assert v.metadata.stats_v1.max == 10.84  
-    assert v.metadata.stats_v1.histogram.bin_centers == [1, 2]  
-    assert v.metadata.stats_v1.histogram.counts == [10, 15]  
-
+    assert v.metadata.chunk_grid.configuration.chunk_shape == [20]
+    assert v.metadata.stats_v1.count == 100
+    assert v.metadata.stats_v1.sum == 1215.1
+    assert v.metadata.stats_v1.sum_squares == 125.12
+    assert v.metadata.stats_v1.min == 5.61
+    assert v.metadata.stats_v1.max == 10.84
+    assert v.metadata.stats_v1.histogram.bin_centers == [1, 2]
+    assert v.metadata.stats_v1.histogram.counts == [10, 15]
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 2af86cdfc..8e06f08dd 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -14,7 +14,7 @@
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
-from mdio.schemas.v1.dataset_builder import _get_dimension
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.stats import SummaryStatistics
@@ -29,21 +29,32 @@ def test_build() -> None:
     """Test building a complete dataset."""
     dataset = (
         MDIODatasetBuilder("test_dataset")
-        .add_dimension("x", 100)
-        .add_dimension("y", 200)
-        .add_coordinate("x_coord", dimensions=["x"])
-        .add_coordinate("y_coord", dimensions=["y"])
-        .add_variable("data", dimensions=["x", "y"], 
+        .add_dimension("inline", 100)
+        .add_dimension("crossline", 200)
+        # Add a dimension coordinate explicitly using add_coordinate()
+        .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64) 
+        # Add a dimension coordinate using .add_dimension_coordinate() shortcut
+        .add_dimension_coordinate("crossline", data_type=ScalarType.FLOAT64)
+        .add_coordinate("x_coord", dimensions=["inline", "crossline"])
+        .add_coordinate("y_coord", dimensions=["inline", "crossline"])
+        .add_variable("data", 
                       long_name="Test Data", 
+                      dimensions=["inline", "crossline"], 
+                      coordinates=["inline", "crossline", "x_coord", "y_coord"],
                       data_type=ScalarType.FLOAT32)
         .build()
     )
+
+    # TODO: Expand this
     assert isinstance(dataset, Dataset)
     assert dataset.metadata.name == "test_dataset"
-    # 2 dimension variables + 1 data variable + 2 coordinate variables
+    # 2 dim coord var + 2 non-dim coord var + 1 data variables = 5 variables
     assert len(dataset.variables) == 5
-    assert next(v for v in dataset.variables if v.name == "x") is not None
-    assert next(v for v in dataset.variables if v.name == "y") is not None
+    assert next(v for v in dataset.variables if v.name == "inline") is not None
+    assert next(v for v in dataset.variables if v.name == "crossline") is not None
+    assert next(v for v in dataset.variables if v.name == "x_coord") is not None
+    assert next(v for v in dataset.variables if v.name == "y_coord") is not None
+    assert next(v for v in dataset.variables if v.name == "data") is not None
     var_data = next(v for v in dataset.variables if v.name == "data")
     assert var_data is not None
     assert var_data.long_name == "Test Data"
@@ -68,35 +79,40 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
     inline_var = next(v for v in dataset.variables if v.name == "inline")
     assert inline_var.data_type == ScalarType.UINT32
     # Dimension variables store dimensions as NamedDimension
-    assert _get_dimension(inline_var.dimensions, "inline", 256)
+    assert _get_named_dimension(inline_var.dimensions, "inline", 256)
 
     crossline_var = next(v for v in dataset.variables if v.name == "crossline")
     assert crossline_var.data_type == ScalarType.UINT32
     # Dimension variables store dimensions as NamedDimension
-    assert _get_dimension(crossline_var.dimensions, "crossline", 512)
+    assert _get_named_dimension(crossline_var.dimensions, "crossline", 512)
 
     depth_var = next(v for v in dataset.variables if v.name == "depth")
-    assert depth_var.data_type == ScalarType.UINT32
+    assert depth_var.data_type == ScalarType.FLOAT64
     # Dimension variables store dimensions as NamedDimension
-    assert _get_dimension(depth_var.dimensions, "depth", 384)
+    assert _get_named_dimension(depth_var.dimensions, "depth", 384)
     assert depth_var.metadata.units_v1.length == LengthUnitEnum.METER
 
     # Verify coordinate variables
     cdp_x = next(v for v in dataset.variables if v.name == "cdp-x")
     assert cdp_x.data_type == ScalarType.FLOAT32
-    # Coordinates variables store dimensions as names
-    assert set(cdp_x.dimensions) == {"inline", "crossline"}
+    assert len(cdp_x.dimensions) == 2
+    assert _get_named_dimension(cdp_x.dimensions, "inline", 256)
+    assert _get_named_dimension(cdp_x.dimensions, "crossline", 512)
     assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
 
     cdp_y = next(v for v in dataset.variables if v.name == "cdp-y")
     assert cdp_y.data_type == ScalarType.FLOAT32
-    # Coordinates variables store dimensions as names
-    assert set(cdp_y.dimensions) == {"inline", "crossline"}
+    assert len(cdp_y.dimensions) == 2
+    assert _get_named_dimension(cdp_y.dimensions, "inline", 256)
+    assert _get_named_dimension(cdp_y.dimensions, "crossline", 512)
     assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
 
     # Verify image variable
     image = next(v for v in dataset.variables if v.name == "image")
-    assert set(image.dimensions) == {"inline", "crossline", "depth"}
+    assert len(image.dimensions) == 3
+    assert _get_named_dimension(image.dimensions, "inline", 256)
+    assert _get_named_dimension(image.dimensions, "crossline", 512)
+    assert _get_named_dimension(image.dimensions, "depth", 384)
     assert image.data_type == ScalarType.FLOAT32
     assert isinstance(image.compressor, Blosc)
     assert image.compressor.algorithm == "zstd"
@@ -109,7 +125,10 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
 
     # Verify velocity variable
     velocity = next(v for v in dataset.variables if v.name == "velocity")
-    assert set(velocity.dimensions) == {"inline", "crossline", "depth"}
+    assert len(velocity.dimensions) == 3
+    assert _get_named_dimension(velocity.dimensions, "inline", 256)
+    assert _get_named_dimension(velocity.dimensions, "crossline", 512)
+    assert _get_named_dimension(velocity.dimensions, "depth", 384)
     assert velocity.data_type == ScalarType.FLOAT16
     assert velocity.compressor is None
     # Other variables store dimensions as names
@@ -123,7 +142,10 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
     image_inline = next(
         v for v in dataset.variables if v.name == "image_inline")
     assert image_inline.long_name == "inline optimized version of 3d_stack"
-    assert set(image_inline.dimensions) == {"inline", "crossline", "depth"}
+    assert len(image_inline.dimensions) == 3
+    assert _get_named_dimension(image_inline.dimensions, "inline", 256)
+    assert _get_named_dimension(image_inline.dimensions, "crossline", 512)
+    assert _get_named_dimension(image_inline.dimensions, "depth", 384)
     assert image_inline.data_type == ScalarType.FLOAT32
     assert isinstance(image_inline.compressor, Blosc)
     assert image_inline.compressor.algorithm == "zstd"
@@ -151,12 +173,15 @@ def make_campos_3d_dataset() -> Dataset:
         }))
 
     # Add dimensions
-    ds.add_dimension("inline", 256, var_data_type=ScalarType.UINT32)
-    ds.add_dimension("crossline", 512, var_data_type=ScalarType.UINT32)
-    ds.add_dimension("depth", 384, var_data_type=ScalarType.UINT32,
-                     var_metadata_info=[
-                         AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
-                     )
+    ds.add_dimension("inline", 256)
+    ds.add_dimension("crossline", 512)
+    ds.add_dimension("depth", 384)
+    ds.add_dimension_coordinate("inline", data_type=ScalarType.UINT32)
+    ds.add_dimension_coordinate("crossline", data_type=ScalarType.UINT32)
+    ds.add_dimension_coordinate("depth", data_type=ScalarType.FLOAT64,
+                                metadata_info=[
+                                    AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+                                    ])
     # Add coordinates
     ds.add_coordinate(
         "cdp-x",
@@ -170,6 +195,7 @@ def make_campos_3d_dataset() -> Dataset:
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
     )
+
     # Add image variable
     ds.add_variable(
         name="image",
@@ -240,3 +266,30 @@ def make_campos_3d_dataset() -> Dataset:
         coordinates=["cdp-x", "cdp-y"],
     )
     return ds.build()
+
+# def test_edge_case_not_used_dimension():
+#     builder = MDIODatasetBuilder("test_dataset")
+
+#     builder.add_dimension("inline", 100)
+#     builder.add_dimension("xline", 200)
+#     builder.add_dimension("depth", 300)
+#     builder.add_dimension("time", 600)
+
+#     # Add 'dimension Coordinate' or 'index Coordinates', 
+#     # the coordinates with the same name as a dimension, marked by *) on objects used in binary operations.
+#     builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT32)
+#     builder.add_coordinate("xline", dimensions=["xline"], data_type=ScalarType.FLOAT32)
+#     # No 'depth' dimension coordinate is provided
+
+#     # Add 'non-dimension coordinates' before we can add a data variable
+#     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+#     builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
+
+#     # Add data variable with full parameters
+#     builder.add_variable("seismic", 
+#                          dimensions=["inline", "crossline", "depth"],
+#                          data_type=ScalarType.FLOAT64,
+#                          coordinates=["cdp-x", "cdp-y"])   
+    
+#     # NOTE: The model has separate list list[Coordinate] | list[str] 
+#     # It does not allow mixing names and NamedDimensions
\ No newline at end of file
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index 6fbba42a5..aecd5ff6d 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -12,30 +12,30 @@
 
 from mdio.schemas.core import StrictModel
 from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.v1.dataset_builder import _get_dimension
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
 from mdio.schemas.v1.dataset_builder import _to_dictionary
 
 
-def test__get_dimension() -> None:
+def test__get_named_dimension() -> None:
     """Test getting a dimension by name from the list of dimensions."""
     dimensions = [NamedDimension(name="inline", size=2), NamedDimension(
         name="crossline", size=3)]
 
-    assert _get_dimension([], "inline") is None
-    assert _get_dimension(dimensions, "inline") == NamedDimension(
+    assert _get_named_dimension([], "inline") is None
+    assert _get_named_dimension(dimensions, "inline") == NamedDimension(
         name="inline", size=2)
-    assert _get_dimension(dimensions, "crossline") == NamedDimension(
+    assert _get_named_dimension(dimensions, "crossline") == NamedDimension(
         name="crossline", size=3)
-    assert _get_dimension(dimensions, "time") is None
+    assert _get_named_dimension(dimensions, "time") is None
 
     with pytest.raises(TypeError, match="Expected str, got NoneType"):
-        _get_dimension(dimensions, None)
+        _get_named_dimension(dimensions, None)
     with pytest.raises(TypeError, match="Expected str, got int"):
-        _get_dimension(dimensions, 42)
+        _get_named_dimension(dimensions, 42)
     with pytest.raises(
         ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
     ):
-        _get_dimension(dimensions, "inline", size=200)
+        _get_named_dimension(dimensions, "inline", size=200)
 
 
 def test__to_dictionary() -> None:

From 7b25d6bdf041dc6abe69002bdc45838213747eac Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Tue, 8 Jul 2025 19:06:12 +0000
Subject: [PATCH 31/56] PR Review: get api version from the package version

---
 src/mdio/schemas/v1/dataset_builder.py      | 17 ++++++++++++-----
 tests/unit/v1/test_dataset_builder_build.py |  2 +-
 2 files changed, 13 insertions(+), 6 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index f0621de30..4b12375e7 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -6,6 +6,7 @@
 from enum import auto
 from typing import Any
 from typing import TypeAlias
+from importlib import metadata
 
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
@@ -17,7 +18,7 @@
 from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset import Dataset, DatasetMetadata
 from mdio.schemas.v1.dataset import DatasetInfo
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.units import AllUnits
@@ -97,13 +98,16 @@ class MDIODatasetBuilder:
 
     def __init__(self, name: str, attributes: UserAttributes | None = None):
 
-        info = DatasetInfo(
+        try:
+            api_version = metadata.version("multidimio")
+        except metadata.PackageNotFoundError:
+            api_version = "unknown"
+
+        self._info = DatasetInfo(
             name=name,
-            api_version="1.0.0",
+            api_version=api_version,
             created_on=datetime.now(UTC)
         )
-        # TODO(BrianMichell, #0): Pull from package metadata
-        self._info = info
         self._attributes = attributes
         self._dimensions: list[NamedDimension] = []
         self._coordinates: list[Coordinate] = []
@@ -252,6 +256,9 @@ def add_dimension_coordinate(
         """Add a dimension coordinate variable for a pre-existing dimension.
         This is a convenience method to create a coordinate variable
         that represents sampling along a dimension.
+
+        The dimension coordinate is a coordinate that has a single dimension and
+        the name of the coordinate is the same as the name of the dimension
         """
         self.add_coordinate(dimension_name,
                             long_name=dimension_name,
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 8e06f08dd..048f640d3 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -67,7 +67,7 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
 
     # Verify dataset structure
     assert dataset.metadata.name == "campos_3d"
-    assert dataset.metadata.api_version == "1.0.0"
+    assert dataset.metadata.api_version == "1.0.0a1"
     assert dataset.metadata.attributes["foo"] == "bar"
     assert len(dataset.metadata.attributes["textHeader"]) == 3
 

From 7ca3ed8fbc1b6f47cbf10e01737d4c8a51f6f7ba Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 9 Jul 2025 14:46:20 +0000
Subject: [PATCH 32/56] PR Review: remove add_dimension_coordinate

---
 .devcontainer/Dockerfile.cli                  | 47 ++++++++++++++
 .devcontainer/Dockerfile.dev                  | 61 +++++++++++++++++++
 .devcontainer/Dockerfile.nox                  | 49 +++++++++++++++
 .devcontainer/devcontainer.json               | 20 +++---
 src/mdio/schemas/v1/dataset_builder.py        | 24 --------
 .../v1/test_dataset_builder_add_variable.py   | 50 ++++-----------
 tests/unit/v1/test_dataset_builder_build.py   | 16 +++--
 7 files changed, 187 insertions(+), 80 deletions(-)
 create mode 100644 .devcontainer/Dockerfile.cli
 create mode 100644 .devcontainer/Dockerfile.dev
 create mode 100644 .devcontainer/Dockerfile.nox

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
new file mode 100644
index 000000000..92720e34e
--- /dev/null
+++ b/.devcontainer/Dockerfile.cli
@@ -0,0 +1,47 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# * Clone mdio-python and build a Docker image:
+#      git clone https://github.com/TGSAI/mdio-python.git
+#      cd mdio-python
+#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
+# * Run /bin/bash in the Docker container:
+#
+#
+# USAGE:
+#  docker run -it --rm --name mdio-cli mdio-cli --version
+#  docker run -it --rm --name mdio-cli mdio-cli --help
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy import \
+#     /DATA/segy_file.segy \
+#     /DATA/mdio_file.mdio \
+#     -loc 181,185 \
+#     -names inline,crossline
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy export \
+#     /DATA/mdio_file.mdio \
+#     /DATA/segy_file_copy.segy
+#
+FROM python:3.13-bookworm
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
+
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install .
+
+ENTRYPOINT ["mdio"]
+CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
new file mode 100644
index 000000000..05f135799
--- /dev/null
+++ b/.devcontainer/Dockerfile.dev
@@ -0,0 +1,61 @@
+# USAGE: 
+#   This file will be used by the VS Code DevContainer extension 
+#   to create a development environment for the mdio-python project.
+# HOW TO RUN TESTS
+#    1. Open the project in VS Code.
+#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
+#    3. Once the container is running, open a terminal in VS Code.
+#    4. Run the tests using the command: `nox -s test`.
+# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
+#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
+#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
+# NOTES: 
+#  1. The container will be run as the non-root user 'vscode' with UID 1000.
+#  2. The virtual environment will be setup at /home/vscode/venv 
+#  3. The project source code will be mounted at /workspaces/mdio-python
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
+
+# Install git for nox pre-commit
+RUN apt-get update \
+  && apt-get install -y --no-install-recommends \
+    git \
+  && rm -rf /var/lib/apt/lists/*
+
+ENV USERNAME="vscode"
+USER $USERNAME
+
+# # Add path to the user-installed packages
+# ENV PYTHONUSERBASE=/home/$USERNAME/.local
+# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
+
+WORKDIR /workspaces/mdio-python
+
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+# Initialize virtual environement in the container
+ENV VIRTUAL_ENV="/home/$USERNAME/venv"
+RUN python3 -m venv $VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+
+# installing pytest is required for VS Code Python Testing
+RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
+
+# Install the project in editable mode
+# This allows for live reloading of the code during development
+RUN pip install -e .
+
+# RUN uv pip install snakeviz
+
+
+
+
+
+
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
new file mode 100644
index 000000000..103673fd2
--- /dev/null
+++ b/.devcontainer/Dockerfile.nox
@@ -0,0 +1,49 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# 1. Make sure you have Docker installed and running.
+# 2. Clone mdio-python and build the Docker image:
+#    git clone https://github.com/TGSAI/mdio-python.git
+#    cd mdio-python
+#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
+# 3. Run /bin/bash in the Docker container :
+#    LOCAL_DATA_DIR=$(pwd); \
+#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
+#
+# USAGE:
+#   docker run -it --rm mdio-nox --list
+#   docker run -it --rm mdio-nox -s tests-3.13
+#   docker run -it --rm mdio-nox --no-stop-on-first-error
+#
+# NOTE: nox will fail if run in the directory mounted from the host machine
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
+ARG PYTHON_VERSION
+ARG LINUX_DISTRO
+RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install .
+
+# Install UV dependency manager and Nox test automator
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+ENTRYPOINT ["nox"]
+CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index b618a5260..dc80446c6 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile",
+    "dockerfile": "Dockerfile.dev",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    "post_create_script": "bash ./.devcontainer/post-install.sh"
+    // "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,8 +16,9 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-        "python.terminal.activateEnvInCurrentTerminal": true,
-        "python.defaultInterpreterPath": "/opt/venv/bin/python"
+      "python.testing.pytestArgs": ["tests"], 
+          "python.testing.unittestEnabled": false,
+          "python.testing.pytestEnabled": true
       },
       "extensions": [
         "ms-python.python",
@@ -27,17 +28,18 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker"
+        "streetsidesoftware.code-spell-checker",
+        "eamodio.gitlens",
+        "visualstudioexptteam.vscodeintellicode"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
+  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
+  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // Re-use local Git configuration
-    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
+    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
   ]
 }
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 4b12375e7..2750e82f2 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -245,30 +245,6 @@ def add_coordinate(  # noqa: PLR0913
         self._state = _BuilderState.HAS_COORDINATES
         return self
 
-    def add_dimension_coordinate(
-        self,
-        dimension_name: str,
-        *,
-        data_type: ScalarType,
-        compressor: Blosc | ZFP | None = None,
-        metadata_info: VariableMetadataList | None = None,
-    ) -> "MDIODatasetBuilder":
-        """Add a dimension coordinate variable for a pre-existing dimension.
-        This is a convenience method to create a coordinate variable
-        that represents sampling along a dimension.
-
-        The dimension coordinate is a coordinate that has a single dimension and
-        the name of the coordinate is the same as the name of the dimension
-        """
-        self.add_coordinate(dimension_name,
-                            long_name=dimension_name,
-                            dimensions=[dimension_name],
-                            data_type=data_type,
-                            compressor=compressor,
-                            metadata_info=_to_dictionary(metadata_info))
-
-        return self
-
     def add_variable(  # noqa: PLR0913
         self,
         name: str,
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index ad24b9de4..3db688098 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -97,8 +97,8 @@ def test_add_variable_with_coords() -> None:
     builder.add_dimension("depth", 300)
 
     # Add dimension coordinates before we can add a data variable
-    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
-    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
 
     # Validate: adding a variable with a coordinate that has not been pre-created is not allowed
     msg = "Pre-existing coordinate named 'depth' is not found"
@@ -168,32 +168,6 @@ def test_add_variable_with_coords() -> None:
     assert builder._get_coordinate(var_ampl2.coordinates, "cdp-y") is not None
 
 
-def test_add_dimension_coordinate() -> None:
-    """Test adding dimension variable."""
-    builder = MDIODatasetBuilder("test_dataset")
-    builder.add_dimension("inline", 100)
-
-    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
-
-    # Validate: that coordinate is stored in the builder global list
-    coord_il = builder._get_coordinate(builder._coordinates, "inline")
-    # Validate: that dimensions are stored as NamedDimensions in the coordinate
-    assert _get_named_dimension(coord_il.dimensions, "inline", 100) is not None
-    # Validate: a dim variable has been created
-    var_il = next((e for e in builder._variables if e.name == "inline"), None)
-    assert var_il is not None
-    # Validate: the variable has the expected properties
-    assert var_il.name == "inline"
-    assert var_il.long_name == "'inline' coordinate variable"
-    assert len(var_il.dimensions) == 1
-    assert _get_named_dimension(var_il.dimensions, "inline", 100) is not None
-    assert var_il.data_type == ScalarType.INT32
-    assert var_il.compressor is None  # Default value
-    assert len(var_il.coordinates) == 1
-    assert builder._get_coordinate(var_il.coordinates, "inline") is not None
-    assert var_il.metadata is None  # Default value
-
-
 def test_add_variable_with_defaults() -> None:
     """Test adding variable with default arguments."""
     builder = MDIODatasetBuilder("test_dataset")
@@ -202,12 +176,12 @@ def test_add_variable_with_defaults() -> None:
     builder.add_dimension("crossline", 200)
     builder.add_dimension("depth", 300)
     # Add dimension coordinates
-    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
-    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
-    builder.add_dimension_coordinate("depth",
-                                     data_type=ScalarType.FLOAT32,
-                                     metadata_info=[
-                                         AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))])
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32,
+                           metadata_info=[
+                               AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+                           ]) 
 
     # Add data variable using defaults
     builder.add_variable("ampl",
@@ -244,10 +218,10 @@ def test_add_variable_full_parameters() -> None:
     builder.add_dimension("depth", 300)
 
     # Add dimension coordinates
-    builder.add_dimension_coordinate("inline", data_type=ScalarType.INT32)
-    builder.add_dimension_coordinate("crossline", data_type=ScalarType.INT32)
-    builder.add_dimension_coordinate("depth", data_type=ScalarType.INT32)
-    
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
+
     # Add coordinates before we can add a data variable
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
     builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 048f640d3..322855856 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -31,10 +31,8 @@ def test_build() -> None:
         MDIODatasetBuilder("test_dataset")
         .add_dimension("inline", 100)
         .add_dimension("crossline", 200)
-        # Add a dimension coordinate explicitly using add_coordinate()
         .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64) 
-        # Add a dimension coordinate using .add_dimension_coordinate() shortcut
-        .add_dimension_coordinate("crossline", data_type=ScalarType.FLOAT64)
+        .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64) 
         .add_coordinate("x_coord", dimensions=["inline", "crossline"])
         .add_coordinate("y_coord", dimensions=["inline", "crossline"])
         .add_variable("data", 
@@ -176,12 +174,12 @@ def make_campos_3d_dataset() -> Dataset:
     ds.add_dimension("inline", 256)
     ds.add_dimension("crossline", 512)
     ds.add_dimension("depth", 384)
-    ds.add_dimension_coordinate("inline", data_type=ScalarType.UINT32)
-    ds.add_dimension_coordinate("crossline", data_type=ScalarType.UINT32)
-    ds.add_dimension_coordinate("depth", data_type=ScalarType.FLOAT64,
-                                metadata_info=[
-                                    AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
-                                    ])
+    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32) 
+    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32) 
+    ds.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.FLOAT64, 
+                      metadata_info=[
+                          AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+                      ])
     # Add coordinates
     ds.add_coordinate(
         "cdp-x",

From 4d1ec9cc4307d5febfee299ab7cdfeddb3c83725 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 9 Jul 2025 15:27:00 +0000
Subject: [PATCH 33/56] PR Review: add_coordinate() remove data_type default
 value

---
 src/mdio/schemas/v1/dataset_builder.py        |  2 +-
 .../v1/test_dataset_builder_add_coordinate.py | 18 +++++-----
 .../v1/test_dataset_builder_add_variable.py   |  4 +--
 tests/unit/v1/test_dataset_builder_build.py   | 34 +++----------------
 4 files changed, 16 insertions(+), 42 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 2750e82f2..80d4b8761 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -177,7 +177,7 @@ def add_coordinate(  # noqa: PLR0913
         *,
         long_name: str = None,
         dimensions: list[str],
-        data_type: ScalarType = ScalarType.FLOAT32,
+        data_type: ScalarType,
         compressor: Blosc | ZFP | None = None,
         metadata_info: CoordinateMetadataList | None = None,
     ) -> "MDIODatasetBuilder":
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index cae46834f..0d4fdc6eb 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -24,7 +24,7 @@ def test_add_coordinate() -> None:
     
     msg = "Must add at least one dimension before adding coordinates"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+        builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
@@ -32,21 +32,21 @@ def test_add_coordinate() -> None:
     # Validate required parameters
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_coordinate(bad_name, dimensions=["speed"])
+        builder.add_coordinate(bad_name, dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_coordinate("", dimensions=["speed"])
+        builder.add_coordinate("", dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("cdp-x", dimensions=None)
+        builder.add_coordinate("cdp-x", dimensions=None, data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("cdp-x", dimensions=[])
+        builder.add_coordinate("cdp-x", dimensions=[], data_type=ScalarType.FLOAT32)
 
     # Add a variable using non-existent dimensions
     msg="Pre-existing dimension named 'xline' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("bad_cdp-x", dimensions=["inline", "xline"])
+        builder.add_coordinate("bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32)
 
     # Validate state transition
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
     assert builder._state == _BuilderState.HAS_COORDINATES
     assert len(builder._dimensions) == 2 
     # 1 variable for coordinates
@@ -68,7 +68,7 @@ def test_add_coordinate() -> None:
     # Adding coordinate with the same name twice
     msg="Adding coordinate with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
+        builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
 def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
@@ -76,7 +76,7 @@ def test_add_coordinate_with_defaults() -> None:
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
     # Add coordinate using defaults
-    builder.add_coordinate("cdp", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
     assert len(builder._dimensions) == 2 
     # 1 variable for coordinates
     assert len(builder._variables) == 1
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 3db688098..99f2f994b 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -135,8 +135,8 @@ def test_add_variable_with_coords() -> None:
     # "depth" coordinate is not set
 
     # Add non-dim coordinates (e.g., 2D coordinates)
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
-    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
+    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
     # Add a variable with pre-defined dimension and non-dimension coordinates
     builder.add_variable("ampl2",
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 322855856..b008e062f 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -33,8 +33,8 @@ def test_build() -> None:
         .add_dimension("crossline", 200)
         .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64) 
         .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64) 
-        .add_coordinate("x_coord", dimensions=["inline", "crossline"])
-        .add_coordinate("y_coord", dimensions=["inline", "crossline"])
+        .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
         .add_variable("data", 
                       long_name="Test Data", 
                       dimensions=["inline", "crossline"], 
@@ -43,7 +43,6 @@ def test_build() -> None:
         .build()
     )
 
-    # TODO: Expand this
     assert isinstance(dataset, Dataset)
     assert dataset.metadata.name == "test_dataset"
     # 2 dim coord var + 2 non-dim coord var + 1 data variables = 5 variables
@@ -184,12 +183,14 @@ def make_campos_3d_dataset() -> Dataset:
     ds.add_coordinate(
         "cdp-x",
         dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
     )
     ds.add_coordinate(
         "cdp-y",
         dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
     )
@@ -264,30 +265,3 @@ def make_campos_3d_dataset() -> Dataset:
         coordinates=["cdp-x", "cdp-y"],
     )
     return ds.build()
-
-# def test_edge_case_not_used_dimension():
-#     builder = MDIODatasetBuilder("test_dataset")
-
-#     builder.add_dimension("inline", 100)
-#     builder.add_dimension("xline", 200)
-#     builder.add_dimension("depth", 300)
-#     builder.add_dimension("time", 600)
-
-#     # Add 'dimension Coordinate' or 'index Coordinates', 
-#     # the coordinates with the same name as a dimension, marked by *) on objects used in binary operations.
-#     builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT32)
-#     builder.add_coordinate("xline", dimensions=["xline"], data_type=ScalarType.FLOAT32)
-#     # No 'depth' dimension coordinate is provided
-
-#     # Add 'non-dimension coordinates' before we can add a data variable
-#     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"])
-#     builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"])
-
-#     # Add data variable with full parameters
-#     builder.add_variable("seismic", 
-#                          dimensions=["inline", "crossline", "depth"],
-#                          data_type=ScalarType.FLOAT64,
-#                          coordinates=["cdp-x", "cdp-y"])   
-    
-#     # NOTE: The model has separate list list[Coordinate] | list[str] 
-#     # It does not allow mixing names and NamedDimensions
\ No newline at end of file

From 99fcf4385e5ce6147b37832b498f7d6d5ee3cca3 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 9 Jul 2025 19:10:44 +0000
Subject: [PATCH 34/56] PR Review: improve unit tests by extracting common
 functionality in validate* functions

---
 src/mdio/schemas/v1/dataset_builder.py        |  35 +--
 tests/unit/v1/helpers.py                      | 243 +++++++++++++++++
 .../v1/test_dataset_builder_add_coordinate.py | 113 ++++----
 .../v1/test_dataset_builder_add_dimension.py  |   4 +-
 .../v1/test_dataset_builder_add_variable.py   | 137 +++-------
 tests/unit/v1/test_dataset_builder_build.py   | 244 ++++++------------
 6 files changed, 412 insertions(+), 364 deletions(-)
 create mode 100644 tests/unit/v1/helpers.py

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 80d4b8761..3bfd914ea 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -146,30 +146,6 @@ def add_dimension(  # noqa: PLR0913
         self._state = _BuilderState.HAS_DIMENSIONS
         return self
 
-    def _get_coordinate(
-        self,
-        coordinates: list[Coordinate] | list[str],
-        name: str, size: int | None = None
-    ) -> Coordinate | None:
-        """Get a coordinate by name from the list[Coordinate] | list[str]."""
-        if coordinates is None:
-            return None
-
-        for c in coordinates:
-            if isinstance(c, str) and c == name:
-                # The coordinate is stored by name (str). 
-                # Find it in the builder global list and return it.
-                cc = next((v for v in self._coordinates if v.name == name), None)
-                if cc is None:
-                    msg = f"Pre-existing coordinate named {name!r} is not found"
-                    raise ValueError(msg)
-                return cc
-            if isinstance(c, Coordinate) and c.name == name:
-                # The coordinate is stored as an embedded Coordinate object.
-                # Return it.
-                return c
-
-        return None
 
     def add_coordinate(  # noqa: PLR0913
         self,
@@ -303,13 +279,22 @@ def add_variable(  # noqa: PLR0913
                 raise ValueError(msg)
             named_dimensions.append(nd)
 
+        coordinate_objs: list[Coordinate] = []
         # Validate that all referenced coordinates are already defined
         if coordinates is not None:
             for coord in coordinates:
-                if next((c for c in self._coordinates if c.name == coord), None) is None:
+                c: Coordinate = next((c for c in self._coordinates if c.name == coord), None)
+                if c is not None:
+                    coordinate_objs.append(c)
+                else:
                     msg = f"Pre-existing coordinate named {coord!r} is not found"
                     raise ValueError(msg)
 
+        if coordinates is not None:
+            # If this is a dimension coordinate variable, embed the Coordinate into it
+            if len(coordinates) == 1 and coordinates[0] == name:
+                coordinates = coordinate_objs
+
         meta_dict = _to_dictionary(metadata_info)
         var = Variable(
             name=name,
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
new file mode 100644
index 000000000..814357b42
--- /dev/null
+++ b/tests/unit/v1/helpers.py
@@ -0,0 +1,243 @@
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType, StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import SpeedUnitEnum
+from mdio.schemas.v1.units import SpeedUnitModel
+from mdio.schemas.v1.variable import Coordinate, Variable
+
+
+def validate_builder(builder: MDIODatasetBuilder,
+                     state: _BuilderState,
+                     n_dims: int,
+                     n_coords: int,
+                     n_var: int) -> None:
+    """Validate the state of the builder and the number of dimensions, coordinates, and variables."""
+    assert builder._state == state
+    assert len(builder._dimensions) == n_dims
+    assert len(builder._coordinates) == n_coords
+    assert len(builder._variables) == n_var
+
+
+def validate_coordinate(builder: MDIODatasetBuilder,
+                        name: str,
+                        dims: list[tuple[str, int]],
+                        dtype: ScalarType) -> Coordinate:
+    """Validate existence and the structure of the created coordinate."""
+    # Validate that coordinate exists
+    c = next((c for c in builder._coordinates if c.name == name), None)
+    assert c is not None
+    assert isinstance(c, Coordinate)
+
+    # Validate that dimensions are stored as NamedDimensions
+    for d in dims:
+        name = d[0]
+        size = d[1]
+        assert _get_named_dimension(c.dimensions, name, size) is not None
+
+    assert c.data_type == dtype
+    return c
+
+
+def validate_variable(container: MDIODatasetBuilder | Dataset,
+                      name: str,
+                      dims: list[tuple[str, int]],
+                      coords: list[str],
+                      dtype: ScalarType) -> Variable:
+    """Validate existence and the structure of the created variable."""
+
+    if isinstance(container, MDIODatasetBuilder):
+        var_list = container._variables
+        global_coord_list = container._coordinates
+    elif isinstance(container, Dataset):
+        var_list = container.variables
+        global_coord_list = _get_all_coordinates(container)
+    else:
+        raise TypeError("container must be MDIODatasetBuilder or Dataset")
+
+    # Validate that the variable exists
+    v = next((e for e in var_list if e.name == name), None)
+    assert v is not None
+    assert isinstance(v, Variable)
+
+    # Validate that dimensions are stored as NamedDimensions within the variable
+    assert len(v.dimensions) == len(dims)
+    for d in dims:
+        name = d[0]
+        size = d[1]
+        assert _get_named_dimension(v.dimensions, name, size) is not None
+
+    # Validate that coordinates are either embedded or can be resolved from names to Coordinate
+    if coords is None:
+        assert v.coordinates is None
+    else:
+        assert len(v.coordinates) == len(coords)
+        for coord_name in coords:
+            assert _get_coordinate(global_coord_list, v.coordinates, coord_name) is not None
+            
+    assert v.data_type == dtype
+    return v
+
+
+def _get_coordinate(
+    global_coord_list: list[Coordinate],
+    coordinates_or_references: list[Coordinate] | list[str],
+    name: str, size: int | None = None
+) -> Coordinate | None:
+    """Get a coordinate by name from the list[Coordinate] | list[str].
+    Validates that the coordinate referenced by the name can be found in the global coordinate list
+    """
+    if coordinates_or_references is None:
+        return None
+
+    for c in coordinates_or_references:
+        if isinstance(c, str) and c == name:
+            # The coordinate is stored by name (str). 
+            cc = None
+            # Find the Coordinate in the global list and return it.
+            if global_coord_list is not None:
+                cc = next((cc for cc in global_coord_list if cc.name == name), None)
+            if cc is None:
+                msg = f"Pre-existing coordinate named {name!r} is not found"
+                raise ValueError(msg)
+            return cc
+        if isinstance(c, Coordinate) and c.name == name:
+            # The coordinate is stored as an embedded Coordinate object.
+            # Return it.
+            return c
+
+    return None
+
+
+def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
+    all_coords: dict[str, Coordinate] = {}
+    for v in dataset.variables:
+        if v.coordinates is not None:
+            for c in v.coordinates:
+                if isinstance(c, Coordinate) and c.name not in all_coords:
+                    all_coords[c.name] = c
+    return list(all_coords.values())
+
+
+def make_campos_3d_dataset() -> Dataset:
+    """Create in-memory campos_3d dataset."""
+    ds = MDIODatasetBuilder(
+        "campos_3d",
+        attributes=UserAttributes(attributes={
+            "textHeader": [
+                "C01 .......................... ",
+                "C02 .......................... ",
+                "C03 .......................... ",
+            ],
+            "foo": "bar"
+        }))
+
+    # Add dimensions
+    ds.add_dimension("inline", 256)
+    ds.add_dimension("crossline", 512)
+    ds.add_dimension("depth", 384)
+    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32) 
+    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32) 
+    ds.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.FLOAT64, 
+                      metadata_info=[
+                          AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+                      ])
+    # Add coordinates
+    ds.add_coordinate(
+        "cdp-x",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+    )
+    ds.add_coordinate(
+        "cdp-y",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+    )
+
+    # Add image variable
+    ds.add_variable(
+        name="image",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(
+                        binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+            UserAttributes(
+                attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
+        ])
+    # Add velocity variable
+    ds.add_variable(
+        name="velocity",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT16,
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+            ),
+            AllUnits(units_v1=SpeedUnitModel(
+                speed=SpeedUnitEnum.METER_PER_SECOND)),
+        ],
+    )
+    # Add inline-optimized image variable
+    ds.add_variable(
+        name="image_inline",
+        long_name="inline optimized version of 3d_stack",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512]))
+            )]
+    )
+    # Add headers variable with structured dtype
+    ds.add_variable(
+        name="image_headers",
+        dimensions=["inline", "crossline"],
+        data_type=StructuredType(
+            fields=[
+                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
+                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
+                StructuredField(name="inline", format=ScalarType.UINT32),       
+                StructuredField(name="crossline", format=ScalarType.UINT32),
+            ]
+        ),
+        coordinates=["cdp-x", "cdp-y"],
+    )
+    return ds.build()
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 0d4fdc6eb..232c525d8 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -6,6 +6,7 @@
 
 import pytest
 
+from mdio.schemas import builder
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import UserAttributes
@@ -15,7 +16,7 @@
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.variable import VariableMetadata
-
+from .helpers import validate_builder, validate_coordinate, validate_variable
 
 def test_add_coordinate() -> None:
     """Test adding coordinates. Check the state transition and validate required parameters."""
@@ -47,23 +48,14 @@ def test_add_coordinate() -> None:
 
     # Validate state transition
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-    assert builder._state == _BuilderState.HAS_COORDINATES
-    assert len(builder._dimensions) == 2 
-    # 1 variable for coordinates
-    assert len(builder._variables) == 1 
-    assert len(builder._coordinates) == 1
-    
-    # Validate that we created a coordinate variable
-    var_cdp = next(e for e in builder._variables if e.name == "cdp-x")
-    assert var_cdp is not None
-    assert len(var_cdp.dimensions) == 2
-    assert _get_named_dimension(var_cdp.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(var_cdp.dimensions, "crossline", 200) is not None
-    # Validate that coordinates are stored as Coordinate
-    assert len(var_cdp.coordinates) == 1
-    # No dimensions are stored in coordinates
-    # Validate that non-dimension coordinates
-    assert builder._get_coordinate(var_cdp.coordinates, "cdp-x") is not None
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    validate_variable(
+        builder,
+        name="cdp-x",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp-x"],
+        dtype=ScalarType.FLOAT32
+    )
 
     # Adding coordinate with the same name twice
     msg="Adding coordinate with the same name twice is not allowed"
@@ -75,23 +67,26 @@ def test_add_coordinate_with_defaults() -> None:
     builder = MDIODatasetBuilder("test_dataset")
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
+
     # Add coordinate using defaults
     builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-    assert len(builder._dimensions) == 2 
-    # 1 variable for coordinates
-    assert len(builder._variables) == 1
-    assert len(builder._coordinates) == 1
-
-    # Validate: the structure of the coordinate
-    coord_cdp = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert coord_cdp is not None
-    assert len(coord_cdp.dimensions) == 2
-    assert _get_named_dimension(coord_cdp.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(coord_cdp.dimensions, "crossline", 200) is not None
-    assert coord_cdp.long_name is None               # Default value
-    assert coord_cdp.data_type == ScalarType.FLOAT32 # Default value
-    assert coord_cdp.compressor is None              # Default value
-    assert coord_cdp.metadata is None                # Default value
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    validate_coordinate(
+        builder,    
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        dtype=ScalarType.FLOAT32
+    )
+    v = validate_variable(
+        builder,
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp"],
+        dtype=ScalarType.FLOAT32
+    )
+    assert v.long_name == "'cdp' coordinate variable"  # Default value
+    assert v.compressor is None                        # Default value
+    assert v.metadata is None                          # Default value
 
 
 def test_coordinate_with_full_parameters() -> None:
@@ -99,6 +94,7 @@ def test_coordinate_with_full_parameters() -> None:
     builder = MDIODatasetBuilder("test_dataset")
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
+
     # Add coordinate with all metadata
     builder.add_coordinate(
         "cdp",
@@ -110,39 +106,28 @@ def test_coordinate_with_full_parameters() -> None:
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
             UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
     )
-    # Validate: the state of the builder
-    assert builder._state == _BuilderState.HAS_COORDINATES
-    assert len(builder._dimensions) == 2 
-    # 1 variable for coordinates
-    assert len(builder._variables) == 1 
-    assert len(builder._coordinates) == 1 
-
-    # Validate: the structure of the coordinate
-    coord_cdp = next((e for e in builder._coordinates if e.name == "cdp"), None)
-    assert coord_cdp is not None
-    assert len(coord_cdp.dimensions) == 2
-    assert _get_named_dimension(coord_cdp.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(coord_cdp.dimensions, "crossline", 200) is not None
-    assert coord_cdp.long_name == "Common Depth Point"
-    assert coord_cdp.data_type == ScalarType.FLOAT16 
-    assert isinstance(coord_cdp.compressor, Blosc)
-    assert coord_cdp.compressor.algorithm == "zstd"
-    assert coord_cdp.metadata.attributes["MGA"] == 51
-    assert coord_cdp.metadata.attributes["UnitSystem"] == "Imperial"
-    assert coord_cdp.metadata.units_v1.length == LengthUnitEnum.FOOT
-
-     # Validate: the structure of the created variable
-    v = next((v for v in builder._variables if v.name == "cdp"), None)
-    assert v is not None
-    assert v.long_name == "'cdp' coordinate variable"
-    assert len(v.dimensions) == 2
-    assert _get_named_dimension(v.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(v.dimensions, "crossline", 200) is not None
-    assert v.data_type == ScalarType.FLOAT16
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    c = validate_coordinate(
+        builder,    
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        dtype=ScalarType.FLOAT16
+    )
+    assert c.long_name == "Common Depth Point"
+    assert isinstance(c.compressor, Blosc)
+    assert c.compressor.algorithm == "zstd"
+    assert c.metadata.attributes["MGA"] == 51
+    assert c.metadata.attributes["UnitSystem"] == "Imperial"
+    assert c.metadata.units_v1.length == LengthUnitEnum.FOOT
+    v = validate_variable(
+        builder,
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp"],
+        dtype=ScalarType.FLOAT16
+    )
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
-    assert len(v.coordinates) == 1
-    assert builder._get_coordinate(v.coordinates, "cdp") is not None
     assert isinstance(v.metadata, VariableMetadata)
     assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
     assert v.metadata.attributes["MGA"] == 51
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index b701380fb..5fd70a016 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -20,6 +20,7 @@
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
+from .helpers import validate_builder
 
 
 def test_add_dimension() -> None:
@@ -36,8 +37,7 @@ def test_add_dimension() -> None:
 
     # First dimension should change state to HAS_DIMENSIONS and create a variable
     builder.add_dimension("x", 100)
-    assert builder._state == _BuilderState.HAS_DIMENSIONS
-    assert len(builder._dimensions) == 1
+    validate_builder(builder, _BuilderState.HAS_DIMENSIONS, n_dims=1, n_coords=0, n_var=0)
     assert _get_named_dimension(builder._dimensions, "x", 100) is not None
 
     # Validate that we can't add a dimension with the same name twice
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 99f2f994b..3bd5ef370 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -21,13 +21,14 @@
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
-from mdio.schemas.v1.variable import VariableMetadata
-
+from mdio.schemas.v1.variable import VariableMetadata, Variable
+from .helpers import validate_builder
+from .helpers import validate_variable
 
 def test_add_variable_no_coords() -> None:
     """Test adding variable. Check the state transition and validate required parameters.."""
     builder = MDIODatasetBuilder("test_dataset")
-    assert builder._state == _BuilderState.INITIAL
+    validate_builder(builder, _BuilderState.INITIAL, n_dims=0, n_coords=0, n_var=0)
 
     # Validate: Must add at least one dimension before adding variables
     msg = "Must add at least one dimension before adding variables"
@@ -66,20 +67,11 @@ def test_add_variable_no_coords() -> None:
     builder.add_variable("amplitude",
                          dimensions=["inline", "crossline", "depth"],
                          data_type=ScalarType.FLOAT32)
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    assert len(builder._dimensions) == 3
-    assert len(builder._variables) == 1
-    assert len(builder._coordinates) == 0
-
-    # Validate the structure of the created variable
-    var_ampl = next((e for e in builder._variables if e.name == "amplitude"), None)
-    assert var_ampl is not None
-    # Validate that dimensions are stored as NamedDimensions
-    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
-    # Validate that no coordinates are set
-    assert var_ampl.coordinates is None
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=0, n_var=1)
+    validate_variable(builder, "amplitude",
+                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+                       coords=None,
+                       dtype=ScalarType.FLOAT32)
 
     # Validate: adding a variable with the same name twice is not allowed
     msg = "Adding variable with the same name twice is not allowed"
@@ -113,26 +105,11 @@ def test_add_variable_with_coords() -> None:
                          dimensions=["inline", "crossline", "depth"],
                          coordinates=["inline", "crossline"],
                          data_type=ScalarType.FLOAT32)
-
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    assert len(builder._dimensions) == 3
-    # 2 dim coordinate variables + 1 data variables
-    assert len(builder._variables) == 3
-    assert len(builder._coordinates) == 2
-
-    # Validate: the structure of the created variable
-    var_ampl = next((e for e in builder._variables if e.name == "ampl"), None)
-    assert var_ampl is not None
-    # Validate: that dimensions are stored as NamedDimensions
-    assert len(var_ampl.dimensions) == 3
-    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
-    assert len(var_ampl.coordinates) == 2
-    # Validate that dim coordinates "inline" and "crossline" are set
-    assert builder._get_coordinate(var_ampl.coordinates, "inline") is not None
-    assert builder._get_coordinate(var_ampl.coordinates, "crossline") is not None
-    # "depth" coordinate is not set
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=2, n_var=3)
+    validate_variable(builder, "ampl",
+                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+                       coords=["inline", "crossline"],
+                       dtype=ScalarType.FLOAT32)
 
     # Add non-dim coordinates (e.g., 2D coordinates)
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
@@ -143,29 +120,11 @@ def test_add_variable_with_coords() -> None:
                          dimensions=["inline", "crossline", "depth"],
                          coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
                          data_type=ScalarType.FLOAT32)
-
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    assert len(builder._dimensions) == 3
-    # 2 dim coordinate variables + 2 non-dim coordinate variables + 1 data variables
-    assert len(builder._variables) == 6
-    assert len(builder._coordinates) == 4
-
-    # Validate: the structure of the created variable
-    var_ampl2 = next((e for e in builder._variables if e.name == "ampl2"), None)
-    assert var_ampl2 is not None
-    # Validate: that dimensions are stored as NamedDimensions
-    assert len(var_ampl2.dimensions) == 3
-    assert _get_named_dimension(var_ampl2.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(var_ampl2.dimensions, "crossline", 200) is not None
-    assert _get_named_dimension(var_ampl2.dimensions, "depth", 300) is not None
-    assert len(var_ampl2.coordinates) == 4
-    # Validate that dim coordinates "inline" and "crossline" are set
-    assert builder._get_coordinate(var_ampl2.coordinates, "inline") is not None
-    assert builder._get_coordinate(var_ampl2.coordinates, "crossline") is not None
-    # "depth" coordinate is not set
-    # Validate that non-dimension coordinates "cdp-x" and "cdp-y"
-    assert builder._get_coordinate(var_ampl2.coordinates, "cdp-x") is not None
-    assert builder._get_coordinate(var_ampl2.coordinates, "cdp-y") is not None
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=4, n_var=6)
+    validate_variable(builder, "ampl2",
+                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+                       coords=["inline", "crossline", "cdp-x", "cdp-y"],
+                       dtype=ScalarType.FLOAT32)
 
 
 def test_add_variable_with_defaults() -> None:
@@ -187,26 +146,15 @@ def test_add_variable_with_defaults() -> None:
     builder.add_variable("ampl",
                          dimensions=["inline", "crossline", "depth"],
                          data_type=ScalarType.FLOAT32)
-    assert len(builder._dimensions) == 3
-    # 3 dim coordinate variables + 1 data variable = 4
-    assert len(builder._variables) == 4
-    assert len(builder._coordinates) == 3
-
-    # Validate: the structure of the created variable
-    var_ampl = next((e for e in builder._variables if e.name == "ampl"), None)
-    assert var_ampl is not None
-    assert var_ampl.name == "ampl"
-    assert var_ampl.long_name is None  # Default value
-    # Validate: that dimensions are stored as NamedDimensions
-    assert len(var_ampl.dimensions) == 3
-    assert _get_named_dimension(var_ampl.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "crossline", 200) is not None
-    assert _get_named_dimension(var_ampl.dimensions, "depth", 300) is not None
-    assert var_ampl.data_type == ScalarType.FLOAT32
-    assert var_ampl.compressor is None  # Default value
-    assert var_ampl.coordinates is None  # Default value
-    # Validate: the variable has the expected properties
-    assert var_ampl.metadata is None  # Default value
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=3, n_var=4)
+    v = validate_variable(builder, "ampl",
+                                   dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+                                   coords=None,
+                                   dtype=ScalarType.FLOAT32)
+    assert v.long_name is None  # Default value
+    assert v.compressor is None  # Default value
+    assert v.coordinates is None  # Default value
+    assert v.metadata is None  # Default value
 
 
 def test_add_variable_full_parameters() -> None:
@@ -216,12 +164,10 @@ def test_add_variable_full_parameters() -> None:
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
     builder.add_dimension("depth", 300)
-
     # Add dimension coordinates
     builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
     builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
     builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
-
     # Add coordinates before we can add a data variable
     builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
     builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
@@ -254,32 +200,15 @@ def test_add_variable_full_parameters() -> None:
                                  )
                              ),
                          ])
-    # Validate: the state of the builder
-    assert builder._state == _BuilderState.HAS_VARIABLES
-    assert len(builder._dimensions) == 3
-    # 3 dim coords + 2 non-dim coords = 5
-    assert len(builder._coordinates) == 5
-    # 3 dim coord + 2 non-dim coords, and 1 data variable
-    assert len(builder._variables) == 6
-
-     # Validate: the structure of the created variable
-    v = next((v for v in builder._variables if v.name == "ampl"), None)
-    assert v is not None
-    assert v.name == "ampl"
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=5, n_var=6)
+    v = validate_variable(builder, "ampl",
+                           dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+                           coords=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+                           dtype=ScalarType.FLOAT32)
     assert v.long_name == "Amplitude (dimensionless)"
-    assert len(v.dimensions) == 3
-    assert _get_named_dimension(v.dimensions, "inline", 100) is not None
-    assert _get_named_dimension(v.dimensions, "crossline", 200) is not None
-    assert _get_named_dimension(v.dimensions, "depth", 300) is not None
-    assert v.data_type == ScalarType.FLOAT32
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
     assert len(v.coordinates) == 5
-    assert builder._get_coordinate(v.coordinates, "inline") is not None
-    assert builder._get_coordinate(v.coordinates, "crossline") is not None
-    assert builder._get_coordinate(v.coordinates, "depth") is not None
-    assert builder._get_coordinate(v.coordinates, "cdp-x") is not None
-    assert builder._get_coordinate(v.coordinates, "cdp-y") is not None
     assert v.metadata.stats_v1.count == 100
     assert isinstance(v.metadata, VariableMetadata)
     assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index b008e062f..f2bda0e5d 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -8,7 +8,7 @@
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
-from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import ScalarType, StructuredField
 from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
@@ -23,7 +23,9 @@
 from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.units import SpeedUnitEnum
 from mdio.schemas.v1.units import SpeedUnitModel
+from .helpers import make_campos_3d_dataset
 
+from .helpers import validate_builder, validate_coordinate, validate_variable
 
 def test_build() -> None:
     """Test building a complete dataset."""
@@ -52,11 +54,6 @@ def test_build() -> None:
     assert next(v for v in dataset.variables if v.name == "x_coord") is not None
     assert next(v for v in dataset.variables if v.name == "y_coord") is not None
     assert next(v for v in dataset.variables if v.name == "data") is not None
-    var_data = next(v for v in dataset.variables if v.name == "data")
-    assert var_data is not None
-    assert var_data.long_name == "Test Data"
-    assert len(var_data.dimensions) == 2
-
 
 def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50)
     """Test building a Campos 3D dataset with multiple variables and attributes."""
@@ -72,82 +69,84 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
     # 3 dimension variables + 4 data variables + 2 coordinate variables
     assert len(dataset.variables) == 9
 
-    # Verify dimension variables
-    inline_var = next(v for v in dataset.variables if v.name == "inline")
-    assert inline_var.data_type == ScalarType.UINT32
-    # Dimension variables store dimensions as NamedDimension
-    assert _get_named_dimension(inline_var.dimensions, "inline", 256)
+    # Verify dimension coordinate variables
+    validate_variable(
+        dataset,
+        name="inline",
+        dims=[("inline", 256)],
+        coords=["inline"],
+        dtype=ScalarType.UINT32
+    )
 
-    crossline_var = next(v for v in dataset.variables if v.name == "crossline")
-    assert crossline_var.data_type == ScalarType.UINT32
-    # Dimension variables store dimensions as NamedDimension
-    assert _get_named_dimension(crossline_var.dimensions, "crossline", 512)
+    validate_variable(
+        dataset,
+        name="crossline",
+        dims=[("crossline", 512)],
+        coords=["crossline"],
+        dtype=ScalarType.UINT32
+    )
 
-    depth_var = next(v for v in dataset.variables if v.name == "depth")
-    assert depth_var.data_type == ScalarType.FLOAT64
-    # Dimension variables store dimensions as NamedDimension
-    assert _get_named_dimension(depth_var.dimensions, "depth", 384)
-    assert depth_var.metadata.units_v1.length == LengthUnitEnum.METER
+    depth = validate_variable(
+        dataset,
+        name="depth",
+        dims=[("depth", 384)],
+        coords=["depth"],
+        dtype=ScalarType.FLOAT64
+    )
+    assert depth.metadata.units_v1.length == LengthUnitEnum.METER
 
     # Verify coordinate variables
-    cdp_x = next(v for v in dataset.variables if v.name == "cdp-x")
-    assert cdp_x.data_type == ScalarType.FLOAT32
-    assert len(cdp_x.dimensions) == 2
-    assert _get_named_dimension(cdp_x.dimensions, "inline", 256)
-    assert _get_named_dimension(cdp_x.dimensions, "crossline", 512)
+    cdp_x = validate_variable(
+        dataset,
+        name="cdp-x",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-x"],
+        dtype=ScalarType.FLOAT32
+    )
     assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
 
-    cdp_y = next(v for v in dataset.variables if v.name == "cdp-y")
-    assert cdp_y.data_type == ScalarType.FLOAT32
-    assert len(cdp_y.dimensions) == 2
-    assert _get_named_dimension(cdp_y.dimensions, "inline", 256)
-    assert _get_named_dimension(cdp_y.dimensions, "crossline", 512)
+    cdp_y = validate_variable(
+        dataset,
+        name="cdp-y",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-y"],
+        dtype=ScalarType.FLOAT32
+    )
     assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
 
-    # Verify image variable
-    image = next(v for v in dataset.variables if v.name == "image")
-    assert len(image.dimensions) == 3
-    assert _get_named_dimension(image.dimensions, "inline", 256)
-    assert _get_named_dimension(image.dimensions, "crossline", 512)
-    assert _get_named_dimension(image.dimensions, "depth", 384)
-    assert image.data_type == ScalarType.FLOAT32
-    assert isinstance(image.compressor, Blosc)
+    # Verify data variables
+    image = validate_variable(
+        dataset,    
+        name="image",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32
+    )
+    assert image.metadata.units_v1 is None  # No units defined for image
     assert image.compressor.algorithm == "zstd"
-    # Other variables store dimensions as names
-    assert set(image.coordinates) == {"cdp-x", "cdp-y"}
-    assert isinstance(image.metadata.chunk_grid, RegularChunkGrid)
     assert image.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
-    assert isinstance(image.metadata.stats_v1, SummaryStatistics)   
     assert image.metadata.stats_v1.count == 100
 
-    # Verify velocity variable
-    velocity = next(v for v in dataset.variables if v.name == "velocity")
-    assert len(velocity.dimensions) == 3
-    assert _get_named_dimension(velocity.dimensions, "inline", 256)
-    assert _get_named_dimension(velocity.dimensions, "crossline", 512)
-    assert _get_named_dimension(velocity.dimensions, "depth", 384)
-    assert velocity.data_type == ScalarType.FLOAT16
+    velocity = validate_variable(
+        dataset,
+        name="velocity",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT16
+    )
     assert velocity.compressor is None
-    # Other variables store dimensions as names
-    assert set(velocity.coordinates) == {"cdp-x", "cdp-y"}
-    assert isinstance(velocity.metadata.chunk_grid, RegularChunkGrid)
     assert velocity.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
-    assert isinstance(velocity.metadata.units_v1, SpeedUnitModel)
     assert velocity.metadata.units_v1.speed == SpeedUnitEnum.METER_PER_SECOND
 
-    # Verify image_inline variable
-    image_inline = next(
-        v for v in dataset.variables if v.name == "image_inline")
+    image_inline = validate_variable(
+        dataset,
+        name="image_inline",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32
+    )
     assert image_inline.long_name == "inline optimized version of 3d_stack"
-    assert len(image_inline.dimensions) == 3
-    assert _get_named_dimension(image_inline.dimensions, "inline", 256)
-    assert _get_named_dimension(image_inline.dimensions, "crossline", 512)
-    assert _get_named_dimension(image_inline.dimensions, "depth", 384)
-    assert image_inline.data_type == ScalarType.FLOAT32
-    assert isinstance(image_inline.compressor, Blosc)
     assert image_inline.compressor.algorithm == "zstd"
-    assert set(image_inline.coordinates) == {"cdp-x", "cdp-y"}
-    assert isinstance(image_inline.metadata.chunk_grid, RegularChunkGrid)
     assert image_inline.metadata.chunk_grid.configuration.chunk_shape == [4, 512, 512]
 
     # Verify image_headers variable
@@ -156,112 +155,19 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
     assert len(headers.data_type.fields) == 4
     assert headers.data_type.fields[0].name == "cdp-x"
 
-def make_campos_3d_dataset() -> Dataset:
-    """Create in-memory campos_3d dataset."""
-    ds = MDIODatasetBuilder(
-        "campos_3d",
-        attributes=UserAttributes(attributes={
-            "textHeader": [
-                "C01 .......................... ",
-                "C02 .......................... ",
-                "C03 .......................... ",
-            ],
-            "foo": "bar"
-        }))
-
-    # Add dimensions
-    ds.add_dimension("inline", 256)
-    ds.add_dimension("crossline", 512)
-    ds.add_dimension("depth", 384)
-    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32) 
-    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32) 
-    ds.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.FLOAT64, 
-                      metadata_info=[
-                          AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
-                      ])
-    # Add coordinates
-    ds.add_coordinate(
-        "cdp-x",
-        dimensions=["inline", "crossline"],
-        data_type=ScalarType.FLOAT32,
-        metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
-    )
-    ds.add_coordinate(
-        "cdp-y",
-        dimensions=["inline", "crossline"],
-        data_type=ScalarType.FLOAT32,
-        metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
-    )
-
-    # Add image variable
-    ds.add_variable(
-        name="image",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT32,
-        compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
-            ),
-            StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    histogram=CenteredBinHistogram(
-                        binCenters=[1, 2], counts=[10, 15]),
-                )
-            ),
-            UserAttributes(
-                attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
-        ])
-    # Add velocity variable
-    ds.add_variable(
-        name="velocity",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT16,
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
-            ),
-            AllUnits(units_v1=SpeedUnitModel(
-                speed=SpeedUnitEnum.METER_PER_SECOND)),
-        ],
-    )
-    # Add inline-optimized image variable
-    ds.add_variable(
-        name="image_inline",
-        long_name="inline optimized version of 3d_stack",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT32,
-        compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512]))
-            )]
-    )
-    # Add headers variable with structured dtype
-    ds.add_variable(
+    headers = validate_variable(
+        dataset,
         name="image_headers",
-        dimensions=["inline", "crossline"],
-        data_type=StructuredType(
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=StructuredType(
             fields=[
-                {"name": "cdp-x", "format": ScalarType.INT32},
-                {"name": "cdp-y", "format": ScalarType.INT32},
-                {"name": "elevation", "format": ScalarType.FLOAT16},
-                {"name": "some_scalar", "format": ScalarType.FLOAT16},
+                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
+                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
+                StructuredField(name="inline", format=ScalarType.UINT32),       
+                StructuredField(name="crossline", format=ScalarType.UINT32),
             ]
-        ),
-        coordinates=["cdp-x", "cdp-y"],
+        )
     )
-    return ds.build()
+
+

From 0778fdd251bba96595149f19ed675dcf92fa0c55 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 9 Jul 2025 19:17:18 +0000
Subject: [PATCH 35/56] Remove the Dockerfile changes. They are not supposed to
 be a part of this PR

---
 .devcontainer/Dockerfile.cli    | 47 -------------------------
 .devcontainer/Dockerfile.dev    | 61 ---------------------------------
 .devcontainer/Dockerfile.nox    | 49 --------------------------
 .devcontainer/devcontainer.json | 20 +++++------
 4 files changed, 9 insertions(+), 168 deletions(-)
 delete mode 100644 .devcontainer/Dockerfile.cli
 delete mode 100644 .devcontainer/Dockerfile.dev
 delete mode 100644 .devcontainer/Dockerfile.nox

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
deleted file mode 100644
index 92720e34e..000000000
--- a/.devcontainer/Dockerfile.cli
+++ /dev/null
@@ -1,47 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# * Clone mdio-python and build a Docker image:
-#      git clone https://github.com/TGSAI/mdio-python.git
-#      cd mdio-python
-#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
-# * Run /bin/bash in the Docker container:
-#
-#
-# USAGE:
-#  docker run -it --rm --name mdio-cli mdio-cli --version
-#  docker run -it --rm --name mdio-cli mdio-cli --help
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy import \
-#     /DATA/segy_file.segy \
-#     /DATA/mdio_file.mdio \
-#     -loc 181,185 \
-#     -names inline,crossline
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy export \
-#     /DATA/mdio_file.mdio \
-#     /DATA/segy_file_copy.segy
-#
-FROM python:3.13-bookworm
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
-
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install .
-
-ENTRYPOINT ["mdio"]
-CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
deleted file mode 100644
index 05f135799..000000000
--- a/.devcontainer/Dockerfile.dev
+++ /dev/null
@@ -1,61 +0,0 @@
-# USAGE: 
-#   This file will be used by the VS Code DevContainer extension 
-#   to create a development environment for the mdio-python project.
-# HOW TO RUN TESTS
-#    1. Open the project in VS Code.
-#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
-#    3. Once the container is running, open a terminal in VS Code.
-#    4. Run the tests using the command: `nox -s test`.
-# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
-#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
-#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
-# NOTES: 
-#  1. The container will be run as the non-root user 'vscode' with UID 1000.
-#  2. The virtual environment will be setup at /home/vscode/venv 
-#  3. The project source code will be mounted at /workspaces/mdio-python
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
-
-# Install git for nox pre-commit
-RUN apt-get update \
-  && apt-get install -y --no-install-recommends \
-    git \
-  && rm -rf /var/lib/apt/lists/*
-
-ENV USERNAME="vscode"
-USER $USERNAME
-
-# # Add path to the user-installed packages
-# ENV PYTHONUSERBASE=/home/$USERNAME/.local
-# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
-
-WORKDIR /workspaces/mdio-python
-
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-# Initialize virtual environement in the container
-ENV VIRTUAL_ENV="/home/$USERNAME/venv"
-RUN python3 -m venv $VIRTUAL_ENV
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-
-# installing pytest is required for VS Code Python Testing
-RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
-
-# Install the project in editable mode
-# This allows for live reloading of the code during development
-RUN pip install -e .
-
-# RUN uv pip install snakeviz
-
-
-
-
-
-
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
deleted file mode 100644
index 103673fd2..000000000
--- a/.devcontainer/Dockerfile.nox
+++ /dev/null
@@ -1,49 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# 1. Make sure you have Docker installed and running.
-# 2. Clone mdio-python and build the Docker image:
-#    git clone https://github.com/TGSAI/mdio-python.git
-#    cd mdio-python
-#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
-# 3. Run /bin/bash in the Docker container :
-#    LOCAL_DATA_DIR=$(pwd); \
-#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
-#
-# USAGE:
-#   docker run -it --rm mdio-nox --list
-#   docker run -it --rm mdio-nox -s tests-3.13
-#   docker run -it --rm mdio-nox --no-stop-on-first-error
-#
-# NOTE: nox will fail if run in the directory mounted from the host machine
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
-ARG PYTHON_VERSION
-ARG LINUX_DISTRO
-RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install .
-
-# Install UV dependency manager and Nox test automator
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-ENTRYPOINT ["nox"]
-CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index dc80446c6..b618a5260 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile.dev",
+    "dockerfile": "Dockerfile",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    // "post_create_script": "bash ./.devcontainer/post-install.sh"
+    "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,9 +16,8 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-      "python.testing.pytestArgs": ["tests"], 
-          "python.testing.unittestEnabled": false,
-          "python.testing.pytestEnabled": true
+        "python.terminal.activateEnvInCurrentTerminal": true,
+        "python.defaultInterpreterPath": "/opt/venv/bin/python"
       },
       "extensions": [
         "ms-python.python",
@@ -28,18 +27,17 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker",
-        "eamodio.gitlens",
-        "visualstudioexptteam.vscodeintellicode"
+        "streetsidesoftware.code-spell-checker"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
-  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
-  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
+    // Re-use local Git configuration
+    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
   ]
 }

From 7e74567ec615d0982b2239b0e916dbfdf2a5db48 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 9 Jul 2025 19:38:26 +0000
Subject: [PATCH 36/56] PR Review: run ruff

---
 src/mdio/schemas/v1/dataset_builder.py        | 10 +++---
 tests/unit/v1/helpers.py                      | 34 +++++++++++--------
 .../v1/test_dataset_builder_add_coordinate.py | 25 +++++++++-----
 .../v1/test_dataset_builder_add_dimension.py  | 12 +------
 .../v1/test_dataset_builder_add_variable.py   | 19 +++++++----
 tests/unit/v1/test_dataset_builder_build.py   | 18 +++-------
 6 files changed, 58 insertions(+), 60 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 3bfd914ea..5b102ddd2 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -4,9 +4,9 @@
 from datetime import datetime
 from enum import Enum
 from enum import auto
+from importlib import metadata
 from typing import Any
 from typing import TypeAlias
-from importlib import metadata
 
 from pydantic import BaseModel
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
@@ -18,7 +18,7 @@
 from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset import Dataset, DatasetMetadata
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset import DatasetInfo
 from mdio.schemas.v1.stats import StatisticsMetadata
 from mdio.schemas.v1.units import AllUnits
@@ -167,6 +167,7 @@ def add_coordinate(  # noqa: PLR0913
             long_name: Optional long name for the coordinate
             dimensions: List of dimension names that the coordinate is associated with
             data_type: Data type for the coordinate (defaults to FLOAT32)
+            compressor: Compressor used for the variable (defaults to None)
             metadata_info: Optional metadata information for the coordinate
 
         Returns:
@@ -290,9 +291,8 @@ def add_variable(  # noqa: PLR0913
                     msg = f"Pre-existing coordinate named {coord!r} is not found"
                     raise ValueError(msg)
 
-        if coordinates is not None:
-            # If this is a dimension coordinate variable, embed the Coordinate into it
-            if len(coordinates) == 1 and coordinates[0] == name:
+        # If this is a dimension coordinate variable, embed the Coordinate into it
+        if coordinates is not None and len(coordinates) == 1 and coordinates[0] == name:
                 coordinates = coordinate_objs
 
         meta_dict = _to_dictionary(metadata_info)
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index 814357b42..699425c19 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -1,13 +1,15 @@
-
+"""Helper methods used in unit tests."""
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
-from mdio.schemas.dtype import ScalarType, StructuredField
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
 from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset import Dataset
-from mdio.schemas.v1.dataset_builder import _BuilderState, MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.dataset_builder import _get_named_dimension
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
@@ -17,7 +19,8 @@
 from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.units import SpeedUnitEnum
 from mdio.schemas.v1.units import SpeedUnitModel
-from mdio.schemas.v1.variable import Coordinate, Variable
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import Variable
 
 
 def validate_builder(builder: MDIODatasetBuilder,
@@ -25,7 +28,7 @@ def validate_builder(builder: MDIODatasetBuilder,
                      n_dims: int,
                      n_coords: int,
                      n_var: int) -> None:
-    """Validate the state of the builder and the number of dimensions, coordinates, and variables."""
+    """Validate the state of the builder, the number of dimensions, coordinates, and variables."""
     assert builder._state == state
     assert len(builder._dimensions) == n_dims
     assert len(builder._coordinates) == n_coords
@@ -58,7 +61,6 @@ def validate_variable(container: MDIODatasetBuilder | Dataset,
                       coords: list[str],
                       dtype: ScalarType) -> Variable:
     """Validate existence and the structure of the created variable."""
-
     if isinstance(container, MDIODatasetBuilder):
         var_list = container._variables
         global_coord_list = container._coordinates
@@ -66,7 +68,8 @@ def validate_variable(container: MDIODatasetBuilder | Dataset,
         var_list = container.variables
         global_coord_list = _get_all_coordinates(container)
     else:
-        raise TypeError("container must be MDIODatasetBuilder or Dataset")
+        err_msg = f"Expected MDIODatasetBuilder or Dataset, got {type(container)}"
+        raise TypeError(err_msg)
 
     # Validate that the variable exists
     v = next((e for e in var_list if e.name == name), None)
@@ -93,23 +96,26 @@ def validate_variable(container: MDIODatasetBuilder | Dataset,
 
 
 def _get_coordinate(
-    global_coord_list: list[Coordinate],
-    coordinates_or_references: list[Coordinate] | list[str],
-    name: str, size: int | None = None
-) -> Coordinate | None:
+        global_coord_list: list[Coordinate],
+        coordinates_or_references: list[Coordinate] | list[str],
+        name: str) -> Coordinate | None:     
     """Get a coordinate by name from the list[Coordinate] | list[str].
-    Validates that the coordinate referenced by the name can be found in the global coordinate list
+
+    The function validates that the coordinate referenced by the name can be found 
+    in the global coordinate list.   
+    If the coordinate is stored as a Coordinate object, it is returned directly.
     """
     if coordinates_or_references is None:
         return None
 
     for c in coordinates_or_references:
         if isinstance(c, str) and c == name:
-            # The coordinate is stored by name (str). 
+            # The coordinate is stored by name (str).
             cc = None
             # Find the Coordinate in the global list and return it.
             if global_coord_list is not None:
-                cc = next((cc for cc in global_coord_list if cc.name == name), None)
+                cc = next(
+                    (cc for cc in global_coord_list if cc.name == name), None)
             if cc is None:
                 msg = f"Pre-existing coordinate named {name!r} is not found"
                 raise ValueError(msg)
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 232c525d8..334c27b89 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -6,17 +6,20 @@
 
 import pytest
 
-from mdio.schemas import builder
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _get_named_dimension
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.variable import VariableMetadata
-from .helpers import validate_builder, validate_coordinate, validate_variable
+
+from .helpers import validate_builder
+from .helpers import validate_coordinate
+from .helpers import validate_variable
+
 
 def test_add_coordinate() -> None:
     """Test adding coordinates. Check the state transition and validate required parameters."""
@@ -25,7 +28,8 @@ def test_add_coordinate() -> None:
     
     msg = "Must add at least one dimension before adding coordinates"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        builder.add_coordinate(
+            "cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
@@ -42,12 +46,14 @@ def test_add_coordinate() -> None:
         builder.add_coordinate("cdp-x", dimensions=[], data_type=ScalarType.FLOAT32)
 
     # Add a variable using non-existent dimensions
-    msg="Pre-existing dimension named 'xline' is not found"
+    msg = "Pre-existing dimension named 'xline' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32)
+        builder.add_coordinate(
+            "bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32)
 
     # Validate state transition
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
     validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
     validate_variable(
         builder,
@@ -58,9 +64,10 @@ def test_add_coordinate() -> None:
     )
 
     # Adding coordinate with the same name twice
-    msg="Adding coordinate with the same name twice is not allowed"
+    msg = "Adding coordinate with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        builder.add_coordinate(
+            "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
 def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index 5fd70a016..e11a788de 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -6,20 +6,10 @@
 
 import pytest
 
-from mdio.schemas.chunk_grid import RegularChunkGrid
-from mdio.schemas.chunk_grid import RegularChunkShape
-from mdio.schemas.dtype import ScalarType
-from mdio.schemas.metadata import ChunkGridMetadata
-from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.dataset_builder import _get_named_dimension
-from mdio.schemas.v1.stats import CenteredBinHistogram
-from mdio.schemas.v1.stats import StatisticsMetadata
-from mdio.schemas.v1.stats import SummaryStatistics
-from mdio.schemas.v1.units import AllUnits
-from mdio.schemas.v1.units import LengthUnitEnum
-from mdio.schemas.v1.units import LengthUnitModel
+
 from .helpers import validate_builder
 
 
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 3bd5ef370..8227be473 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -6,14 +6,13 @@
 
 import pytest
 
-from mdio.schemas import builder
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
-from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder, _get_named_dimension
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_builder import _BuilderState
 from mdio.schemas.v1.stats import CenteredBinHistogram
 from mdio.schemas.v1.stats import StatisticsMetadata
@@ -21,10 +20,12 @@
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import LengthUnitModel
-from mdio.schemas.v1.variable import VariableMetadata, Variable
+from mdio.schemas.v1.variable import VariableMetadata
+
 from .helpers import validate_builder
 from .helpers import validate_variable
 
+
 def test_add_variable_no_coords() -> None:
     """Test adding variable. Check the state transition and validate required parameters.."""
     builder = MDIODatasetBuilder("test_dataset")
@@ -112,8 +113,10 @@ def test_add_variable_with_coords() -> None:
                        dtype=ScalarType.FLOAT32)
 
     # Add non-dim coordinates (e.g., 2D coordinates)
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+    builder.add_coordinate(
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
 
     # Add a variable with pre-defined dimension and non-dimension coordinates
     builder.add_variable("ampl2",
@@ -169,8 +172,10 @@ def test_add_variable_full_parameters() -> None:
     builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
     builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
     # Add coordinates before we can add a data variable
-    builder.add_coordinate("cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
-    builder.add_coordinate("cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+    builder.add_coordinate(
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
 
     # Add data variable with full parameters
     builder.add_variable("ampl",
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index f2bda0e5d..d42f29a7a 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -5,27 +5,17 @@
 """Tests the schema v1 dataset_builder.add_coordinate() public API."""
 
 
-from mdio.schemas.chunk_grid import RegularChunkGrid
-from mdio.schemas.chunk_grid import RegularChunkShape
-from mdio.schemas.compressors import Blosc
-from mdio.schemas.dtype import ScalarType, StructuredField
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
 from mdio.schemas.dtype import StructuredType
-from mdio.schemas.metadata import ChunkGridMetadata
-from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
-from mdio.schemas.v1.dataset_builder import _get_named_dimension
-from mdio.schemas.v1.stats import CenteredBinHistogram
-from mdio.schemas.v1.stats import StatisticsMetadata
-from mdio.schemas.v1.stats import SummaryStatistics
-from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
-from mdio.schemas.v1.units import LengthUnitModel
 from mdio.schemas.v1.units import SpeedUnitEnum
-from mdio.schemas.v1.units import SpeedUnitModel
+
 from .helpers import make_campos_3d_dataset
+from .helpers import validate_variable
 
-from .helpers import validate_builder, validate_coordinate, validate_variable
 
 def test_build() -> None:
     """Test building a complete dataset."""

From 0aaa5f6110eb7afd59a5cb901a747da5fc60cbde Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Thu, 10 Jul 2025 15:10:07 +0000
Subject: [PATCH 37/56] PR Review: fix pre-commit errors

---
 src/mdio/schemas/v1/dataset_builder.py        |  60 +++---
 tests/unit/v1/helpers.py                      | 109 +++++-----
 .../v1/test_dataset_builder_add_coordinate.py |  44 ++--
 .../v1/test_dataset_builder_add_dimension.py  |   3 +-
 .../v1/test_dataset_builder_add_variable.py   | 200 ++++++++++--------
 tests/unit/v1/test_dataset_builder_build.py   |  52 ++---
 tests/unit/v1/test_dataset_builder_helpers.py |  68 +++---
 7 files changed, 283 insertions(+), 253 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 5b102ddd2..85bae21fe 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -25,16 +25,13 @@
 from mdio.schemas.v1.variable import Coordinate
 from mdio.schemas.v1.variable import Variable
 
-AnyMetadataList: TypeAlias = list[AllUnits |
-                                  UserAttributes |
-                                  ChunkGridMetadata |
-                                  StatisticsMetadata |
-                                  DatasetInfo]
+AnyMetadataList: TypeAlias = list[
+    AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata | DatasetInfo
+]
 CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
-VariableMetadataList: TypeAlias = list[AllUnits |
-                                       UserAttributes |
-                                       ChunkGridMetadata |
-                                       StatisticsMetadata]
+VariableMetadataList: TypeAlias = list[
+    AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata
+]
 DatasetMetadataList: TypeAlias = list[DatasetInfo | UserAttributes]
 
 
@@ -97,17 +94,12 @@ class MDIODatasetBuilder:
     """
 
     def __init__(self, name: str, attributes: UserAttributes | None = None):
-
         try:
             api_version = metadata.version("multidimio")
         except metadata.PackageNotFoundError:
             api_version = "unknown"
 
-        self._info = DatasetInfo(
-            name=name,
-            api_version=api_version,
-            created_on=datetime.now(UTC)
-        )
+        self._info = DatasetInfo(name=name, api_version=api_version, created_on=datetime.now(UTC))
         self._attributes = attributes
         self._dimensions: list[NamedDimension] = []
         self._coordinates: list[Coordinate] = []
@@ -116,9 +108,7 @@ def __init__(self, name: str, attributes: UserAttributes | None = None):
         self._unnamed_variable_counter = 0
 
     def add_dimension(  # noqa: PLR0913
-        self,
-        name: str,
-        size: int
+        self, name: str, size: int
     ) -> "MDIODatasetBuilder":
         """Add a dimension.
 
@@ -128,6 +118,10 @@ def add_dimension(  # noqa: PLR0913
             name: Name of the dimension
             size: Size of the dimension
 
+        Raises:
+            ValueError: If 'name' is not a non-empty string.
+                        if the dimension is already defined.
+
         Returns:
             self: Returns self for method chaining
         """
@@ -146,7 +140,6 @@ def add_dimension(  # noqa: PLR0913
         self._state = _BuilderState.HAS_DIMENSIONS
         return self
 
-
     def add_coordinate(  # noqa: PLR0913
         self,
         name: str,
@@ -170,6 +163,13 @@ def add_coordinate(  # noqa: PLR0913
             compressor: Compressor used for the variable (defaults to None)
             metadata_info: Optional metadata information for the coordinate
 
+        Raises:
+            ValueError: If no dimensions have been added yet.
+                        If 'name' is not a non-empty string.
+                        If 'dimensions' is not a non-empty list.
+                        If the coordinate is already defined.
+                        If any referenced dimension is not already defined.
+
         Returns:
             self: Returns self for method chaining
         """
@@ -195,7 +195,7 @@ def add_coordinate(  # noqa: PLR0913
             if nd is None:
                 msg = f"Pre-existing dimension named {dim_name!r} is not found"
                 raise ValueError(msg)
-            named_dimensions.append(nd)    
+            named_dimensions.append(nd)
 
         meta_dict = _to_dictionary(metadata_info)
         coord = Coordinate(
@@ -204,7 +204,7 @@ def add_coordinate(  # noqa: PLR0913
             dimensions=named_dimensions,
             compressor=compressor,
             dataType=data_type,
-            metadata=meta_dict
+            metadata=meta_dict,
         )
         self._coordinates.append(coord)
 
@@ -216,7 +216,7 @@ def add_coordinate(  # noqa: PLR0913
             data_type=coord.data_type,
             compressor=compressor,
             coordinates=[name],  # Use the coordinate name as a reference
-            metadata_info=coord.metadata
+            metadata_info=coord.metadata,
         )
 
         self._state = _BuilderState.HAS_COORDINATES
@@ -252,6 +252,14 @@ def add_variable(  # noqa: PLR0913
                          (defaults to None, meaning no coordinates)
             metadata_info: Optional metadata information for the variable
 
+        Raises:
+            ValueError: If no dimensions have been added yet.
+                        If 'name' is not a non-empty string.
+                        If 'dimensions' is not a non-empty list.
+                        If the variable is already defined.
+                        If any referenced dimension is not already defined.
+                        If any referenced coordinate is not already defined.
+
         Returns:
             self: Returns self for method chaining.
         """
@@ -293,7 +301,7 @@ def add_variable(  # noqa: PLR0913
 
         # If this is a dimension coordinate variable, embed the Coordinate into it
         if coordinates is not None and len(coordinates) == 1 and coordinates[0] == name:
-                coordinates = coordinate_objs
+            coordinates = coordinate_objs
 
         meta_dict = _to_dictionary(metadata_info)
         var = Variable(
@@ -303,7 +311,8 @@ def add_variable(  # noqa: PLR0913
             data_type=data_type,
             compressor=compressor,
             coordinates=coordinates,
-            metadata=meta_dict)
+            metadata=meta_dict,
+        )
         self._variables.append(var)
 
         self._state = _BuilderState.HAS_VARIABLES
@@ -315,6 +324,9 @@ def build(self) -> Dataset:
         This function must be called after at least one dimension is added via add_dimension().
         It will create a Dataset object with all added dimensions, coordinates, and variables.
 
+        Raises:
+            ValueError: If no dimensions have been added yet.
+
         Returns:
             Dataset: The built dataset with all added dimensions, coordinates, and variables.
         """
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index 699425c19..2058bdd54 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -1,4 +1,5 @@
 """Helper methods used in unit tests."""
+
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.compressors import Blosc
@@ -23,11 +24,9 @@
 from mdio.schemas.v1.variable import Variable
 
 
-def validate_builder(builder: MDIODatasetBuilder,
-                     state: _BuilderState,
-                     n_dims: int,
-                     n_coords: int,
-                     n_var: int) -> None:
+def validate_builder(
+    builder: MDIODatasetBuilder, state: _BuilderState, n_dims: int, n_coords: int, n_var: int
+) -> None:
     """Validate the state of the builder, the number of dimensions, coordinates, and variables."""
     assert builder._state == state
     assert len(builder._dimensions) == n_dims
@@ -35,10 +34,9 @@ def validate_builder(builder: MDIODatasetBuilder,
     assert len(builder._variables) == n_var
 
 
-def validate_coordinate(builder: MDIODatasetBuilder,
-                        name: str,
-                        dims: list[tuple[str, int]],
-                        dtype: ScalarType) -> Coordinate:
+def validate_coordinate(
+    builder: MDIODatasetBuilder, name: str, dims: list[tuple[str, int]], dtype: ScalarType
+) -> Coordinate:
     """Validate existence and the structure of the created coordinate."""
     # Validate that coordinate exists
     c = next((c for c in builder._coordinates if c.name == name), None)
@@ -55,11 +53,13 @@ def validate_coordinate(builder: MDIODatasetBuilder,
     return c
 
 
-def validate_variable(container: MDIODatasetBuilder | Dataset,
-                      name: str,
-                      dims: list[tuple[str, int]],
-                      coords: list[str],
-                      dtype: ScalarType) -> Variable:
+def validate_variable(
+    container: MDIODatasetBuilder | Dataset,
+    name: str,
+    dims: list[tuple[str, int]],
+    coords: list[str],
+    dtype: ScalarType,
+) -> Variable:
     """Validate existence and the structure of the created variable."""
     if isinstance(container, MDIODatasetBuilder):
         var_list = container._variables
@@ -90,19 +90,20 @@ def validate_variable(container: MDIODatasetBuilder | Dataset,
         assert len(v.coordinates) == len(coords)
         for coord_name in coords:
             assert _get_coordinate(global_coord_list, v.coordinates, coord_name) is not None
-            
+
     assert v.data_type == dtype
     return v
 
 
 def _get_coordinate(
-        global_coord_list: list[Coordinate],
-        coordinates_or_references: list[Coordinate] | list[str],
-        name: str) -> Coordinate | None:     
+    global_coord_list: list[Coordinate],
+    coordinates_or_references: list[Coordinate] | list[str],
+    name: str,
+) -> Coordinate | None:
     """Get a coordinate by name from the list[Coordinate] | list[str].
 
-    The function validates that the coordinate referenced by the name can be found 
-    in the global coordinate list.   
+    The function validates that the coordinate referenced by the name can be found
+    in the global coordinate list.
     If the coordinate is stored as a Coordinate object, it is returned directly.
     """
     if coordinates_or_references is None:
@@ -114,8 +115,7 @@ def _get_coordinate(
             cc = None
             # Find the Coordinate in the global list and return it.
             if global_coord_list is not None:
-                cc = next(
-                    (cc for cc in global_coord_list if cc.name == name), None)
+                cc = next((cc for cc in global_coord_list if cc.name == name), None)
             if cc is None:
                 msg = f"Pre-existing coordinate named {name!r} is not found"
                 raise ValueError(msg)
@@ -142,39 +142,42 @@ def make_campos_3d_dataset() -> Dataset:
     """Create in-memory campos_3d dataset."""
     ds = MDIODatasetBuilder(
         "campos_3d",
-        attributes=UserAttributes(attributes={
-            "textHeader": [
-                "C01 .......................... ",
-                "C02 .......................... ",
-                "C03 .......................... ",
-            ],
-            "foo": "bar"
-        }))
+        attributes=UserAttributes(
+            attributes={
+                "textHeader": [
+                    "C01 .......................... ",
+                    "C02 .......................... ",
+                    "C03 .......................... ",
+                ],
+                "foo": "bar",
+            }
+        ),
+    )
 
     # Add dimensions
     ds.add_dimension("inline", 256)
     ds.add_dimension("crossline", 512)
     ds.add_dimension("depth", 384)
-    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32) 
-    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32) 
-    ds.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.FLOAT64, 
-                      metadata_info=[
-                          AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
-                      ])
+    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate(
+        "depth",
+        dimensions=["depth"],
+        data_type=ScalarType.FLOAT64,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
     # Add coordinates
     ds.add_coordinate(
         "cdp-x",
         dimensions=["inline", "crossline"],
         data_type=ScalarType.FLOAT32,
-        metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
     )
     ds.add_coordinate(
         "cdp-y",
         dimensions=["inline", "crossline"],
         data_type=ScalarType.FLOAT32,
-        metadata_info=[
-            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))]
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
     )
 
     # Add image variable
@@ -187,7 +190,8 @@ def make_campos_3d_dataset() -> Dataset:
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
             ),
             StatisticsMetadata(
                 stats_v1=SummaryStatistics(
@@ -196,13 +200,12 @@ def make_campos_3d_dataset() -> Dataset:
                     sumSquares=125.12,
                     min=5.61,
                     max=10.84,
-                    histogram=CenteredBinHistogram(
-                        binCenters=[1, 2], counts=[10, 15]),
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
                 )
             ),
-            UserAttributes(
-                attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
-        ])
+            UserAttributes(attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
+        ],
+    )
     # Add velocity variable
     ds.add_variable(
         name="velocity",
@@ -212,10 +215,10 @@ def make_campos_3d_dataset() -> Dataset:
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128]))
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
             ),
-            AllUnits(units_v1=SpeedUnitModel(
-                speed=SpeedUnitEnum.METER_PER_SECOND)),
+            AllUnits(units_v1=SpeedUnitModel(speed=SpeedUnitEnum.METER_PER_SECOND)),
         ],
     )
     # Add inline-optimized image variable
@@ -229,8 +232,10 @@ def make_campos_3d_dataset() -> Dataset:
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512]))
-            )]
+                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512])
+                )
+            )
+        ],
     )
     # Add headers variable with structured dtype
     ds.add_variable(
@@ -240,7 +245,7 @@ def make_campos_3d_dataset() -> Dataset:
             fields=[
                 StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
                 StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
-                StructuredField(name="inline", format=ScalarType.UINT32),       
+                StructuredField(name="inline", format=ScalarType.UINT32),
                 StructuredField(name="crossline", format=ScalarType.UINT32),
             ]
         ),
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 334c27b89..46cb27cd1 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -25,11 +25,12 @@ def test_add_coordinate() -> None:
     """Test adding coordinates. Check the state transition and validate required parameters."""
     builder = MDIODatasetBuilder("test_dataset")
     assert builder._state == _BuilderState.INITIAL
-    
+
     msg = "Must add at least one dimension before adding coordinates"
     with pytest.raises(ValueError, match=msg):
         builder.add_coordinate(
-            "cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+            "cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        )
 
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
@@ -49,25 +50,29 @@ def test_add_coordinate() -> None:
     msg = "Pre-existing dimension named 'xline' is not found"
     with pytest.raises(ValueError, match=msg):
         builder.add_coordinate(
-            "bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32)
+            "bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32
+        )
 
     # Validate state transition
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
     validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
     validate_variable(
         builder,
         name="cdp-x",
         dims=[("inline", 100), ("crossline", 200)],
         coords=["cdp-x"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
 
     # Adding coordinate with the same name twice
     msg = "Adding coordinate with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
         builder.add_coordinate(
-            "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+            "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        )
+
 
 def test_add_coordinate_with_defaults() -> None:
     """Test adding coordinates with default arguments."""
@@ -79,21 +84,18 @@ def test_add_coordinate_with_defaults() -> None:
     builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
     validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
     validate_coordinate(
-        builder,    
-        name="cdp",
-        dims=[("inline", 100), ("crossline", 200)],
-        dtype=ScalarType.FLOAT32
+        builder, name="cdp", dims=[("inline", 100), ("crossline", 200)], dtype=ScalarType.FLOAT32
     )
     v = validate_variable(
         builder,
         name="cdp",
         dims=[("inline", 100), ("crossline", 200)],
         coords=["cdp"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
     assert v.long_name == "'cdp' coordinate variable"  # Default value
-    assert v.compressor is None                        # Default value
-    assert v.metadata is None                          # Default value
+    assert v.compressor is None  # Default value
+    assert v.metadata is None  # Default value
 
 
 def test_coordinate_with_full_parameters() -> None:
@@ -105,20 +107,18 @@ def test_coordinate_with_full_parameters() -> None:
     # Add coordinate with all metadata
     builder.add_coordinate(
         "cdp",
-        long_name = "Common Depth Point",
+        long_name="Common Depth Point",
         dimensions=["inline", "crossline"],
-        data_type = ScalarType.FLOAT16,
-        compressor = Blosc(algorithm="zstd"),
+        data_type=ScalarType.FLOAT16,
+        compressor=Blosc(algorithm="zstd"),
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
-            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"})]
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+        ],
     )
     validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
     c = validate_coordinate(
-        builder,    
-        name="cdp",
-        dims=[("inline", 100), ("crossline", 200)],
-        dtype=ScalarType.FLOAT16
+        builder, name="cdp", dims=[("inline", 100), ("crossline", 200)], dtype=ScalarType.FLOAT16
     )
     assert c.long_name == "Common Depth Point"
     assert isinstance(c.compressor, Blosc)
@@ -131,7 +131,7 @@ def test_coordinate_with_full_parameters() -> None:
         name="cdp",
         dims=[("inline", 100), ("crossline", 200)],
         coords=["cdp"],
-        dtype=ScalarType.FLOAT16
+        dtype=ScalarType.FLOAT16,
     )
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index e11a788de..ddcbd745c 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -38,7 +38,6 @@ def test_add_dimension() -> None:
         builder.add_dimension("x", 200)
 
     # Adding dimension with the same name twice
-    msg="Adding dimension with the same name twice is not allowed"
+    msg = "Adding dimension with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
         builder.add_dimension("x", 200)
-
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 8227be473..84abfe3ad 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -34,10 +34,9 @@ def test_add_variable_no_coords() -> None:
     # Validate: Must add at least one dimension before adding variables
     msg = "Must add at least one dimension before adding variables"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude", dimensions=[
-                             "speed"], data_type=ScalarType.FLOAT32)
+        builder.add_variable("amplitude", dimensions=["speed"], data_type=ScalarType.FLOAT32)
 
-   # Add dimension before we can add a data variable
+    # Add dimension before we can add a data variable
     builder.add_dimension("inline", 100)
     builder.add_dimension("crossline", 200)
     builder.add_dimension("depth", 300)
@@ -45,41 +44,40 @@ def test_add_variable_no_coords() -> None:
     # Validate: required parameters must be preset
     bad_name = None
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable(bad_name, dimensions=[
-                             "speed"], data_type=ScalarType.FLOAT32)
+        builder.add_variable(bad_name, dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
-        builder.add_variable(
-            "", dimensions=["speed"], data_type=ScalarType.FLOAT32)
+        builder.add_variable("", dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=None,
-                             data_type=ScalarType.FLOAT32)
+        builder.add_variable("bad_amplitude", dimensions=None, data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_variable("bad_amplitude", dimensions=[],
-                             data_type=ScalarType.FLOAT32)
+        builder.add_variable("bad_amplitude", dimensions=[], data_type=ScalarType.FLOAT32)
 
     # Validate: Add a variable using non-existent dimensions is not allowed
     msg = "Pre-existing dimension named 'il' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("bad_amplitude",
-                             dimensions=["il", "xl", "depth"],
-                             data_type=ScalarType.FLOAT32)
+        builder.add_variable(
+            "bad_amplitude", dimensions=["il", "xl", "depth"], data_type=ScalarType.FLOAT32
+        )
 
     # Add a variable without coordinates
-    builder.add_variable("amplitude",
-                         dimensions=["inline", "crossline", "depth"],
-                         data_type=ScalarType.FLOAT32)
+    builder.add_variable(
+        "amplitude", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+    )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=0, n_var=1)
-    validate_variable(builder, "amplitude",
-                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-                       coords=None,
-                       dtype=ScalarType.FLOAT32)
+    validate_variable(
+        builder,
+        "amplitude",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=None,
+        dtype=ScalarType.FLOAT32,
+    )
 
     # Validate: adding a variable with the same name twice is not allowed
     msg = "Adding variable with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("amplitude",
-                             dimensions=["inline", "crossline", "depth"],
-                             data_type=ScalarType.FLOAT32)
+        builder.add_variable(
+            "amplitude", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+        )
 
 
 def test_add_variable_with_coords() -> None:
@@ -96,38 +94,52 @@ def test_add_variable_with_coords() -> None:
     # Validate: adding a variable with a coordinate that has not been pre-created is not allowed
     msg = "Pre-existing coordinate named 'depth' is not found"
     with pytest.raises(ValueError, match=msg):
-        builder.add_variable("ampl",
-                             dimensions=["inline", "crossline", "depth"],
-                             coordinates=["inline", "crossline", "depth"],
-                             data_type=ScalarType.FLOAT32)
+        builder.add_variable(
+            "ampl",
+            dimensions=["inline", "crossline", "depth"],
+            coordinates=["inline", "crossline", "depth"],
+            data_type=ScalarType.FLOAT32,
+        )
 
     # Add a variable with pre-defined dimension coordinates
-    builder.add_variable("ampl",
-                         dimensions=["inline", "crossline", "depth"],
-                         coordinates=["inline", "crossline"],
-                         data_type=ScalarType.FLOAT32)
+    builder.add_variable(
+        "ampl",
+        dimensions=["inline", "crossline", "depth"],
+        coordinates=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+    )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=2, n_var=3)
-    validate_variable(builder, "ampl",
-                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-                       coords=["inline", "crossline"],
-                       dtype=ScalarType.FLOAT32)
+    validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline"],
+        dtype=ScalarType.FLOAT32,
+    )
 
     # Add non-dim coordinates (e.g., 2D coordinates)
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
     builder.add_coordinate(
-        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
 
     # Add a variable with pre-defined dimension and non-dimension coordinates
-    builder.add_variable("ampl2",
-                         dimensions=["inline", "crossline", "depth"],
-                         coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
-                         data_type=ScalarType.FLOAT32)
+    builder.add_variable(
+        "ampl2",
+        dimensions=["inline", "crossline", "depth"],
+        coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+        data_type=ScalarType.FLOAT32,
+    )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=4, n_var=6)
-    validate_variable(builder, "ampl2",
-                       dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-                       coords=["inline", "crossline", "cdp-x", "cdp-y"],
-                       dtype=ScalarType.FLOAT32)
+    validate_variable(
+        builder,
+        "ampl2",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline", "cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
 
 
 def test_add_variable_with_defaults() -> None:
@@ -140,20 +152,25 @@ def test_add_variable_with_defaults() -> None:
     # Add dimension coordinates
     builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
     builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
-    builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32,
-                           metadata_info=[
-                               AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
-                           ]) 
+    builder.add_coordinate(
+        "depth",
+        dimensions=["depth"],
+        data_type=ScalarType.UINT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
 
     # Add data variable using defaults
-    builder.add_variable("ampl",
-                         dimensions=["inline", "crossline", "depth"],
-                         data_type=ScalarType.FLOAT32)
+    builder.add_variable(
+        "ampl", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+    )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=3, n_var=4)
-    v = validate_variable(builder, "ampl",
-                                   dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-                                   coords=None,
-                                   dtype=ScalarType.FLOAT32)
+    v = validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=None,
+        dtype=ScalarType.FLOAT32,
+    )
     assert v.long_name is None  # Default value
     assert v.compressor is None  # Default value
     assert v.coordinates is None  # Default value
@@ -173,43 +190,46 @@ def test_add_variable_full_parameters() -> None:
     builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
     # Add coordinates before we can add a data variable
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+    )
     builder.add_coordinate(
-        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64)
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+    )
 
     # Add data variable with full parameters
-    builder.add_variable("ampl",
-                         long_name="Amplitude (dimensionless)",
-                         dimensions=["inline", "crossline", "depth"],
-                         data_type=ScalarType.FLOAT32,
-                         compressor=Blosc(algorithm="zstd"),
-                         coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
-                         metadata_info=[
-                             AllUnits(units_v1=LengthUnitModel(
-                                 length=LengthUnitEnum.FOOT)),
-                             UserAttributes(
-                                 attributes={"MGA": 51, "UnitSystem": "Imperial"}),
-                             ChunkGridMetadata(
-                                 chunk_grid=RegularChunkGrid(
-                                     configuration=RegularChunkShape(chunk_shape=[20]))
-                             ),
-                             StatisticsMetadata(
-                                 stats_v1=SummaryStatistics(
-                                     count=100,
-                                     sum=1215.1,
-                                     sumSquares=125.12,
-                                     min=5.61,
-                                     max=10.84,
-                                     histogram=CenteredBinHistogram(
-                                         binCenters=[1, 2], counts=[10, 15]),
-                                 )
-                             ),
-                         ])
+    builder.add_variable(
+        "ampl",
+        long_name="Amplitude (dimensionless)",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+        ],
+    )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=5, n_var=6)
-    v = validate_variable(builder, "ampl",
-                           dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-                           coords=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
-                           dtype=ScalarType.FLOAT32)
+    v = validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
     assert v.long_name == "Amplitude (dimensionless)"
     assert isinstance(v.compressor, Blosc)
     assert v.compressor.algorithm == "zstd"
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index d42f29a7a..aa5fad552 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -4,7 +4,6 @@
 # Thus, disable it for this file
 """Tests the schema v1 dataset_builder.add_coordinate() public API."""
 
-
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.dtype import StructuredField
 from mdio.schemas.dtype import StructuredType
@@ -23,15 +22,17 @@ def test_build() -> None:
         MDIODatasetBuilder("test_dataset")
         .add_dimension("inline", 100)
         .add_dimension("crossline", 200)
-        .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64) 
-        .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64) 
+        .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64)
+        .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64)
         .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
         .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-        .add_variable("data", 
-                      long_name="Test Data", 
-                      dimensions=["inline", "crossline"], 
-                      coordinates=["inline", "crossline", "x_coord", "y_coord"],
-                      data_type=ScalarType.FLOAT32)
+        .add_variable(
+            "data",
+            long_name="Test Data",
+            dimensions=["inline", "crossline"],
+            coordinates=["inline", "crossline", "x_coord", "y_coord"],
+            data_type=ScalarType.FLOAT32,
+        )
         .build()
     )
 
@@ -45,7 +46,8 @@ def test_build() -> None:
     assert next(v for v in dataset.variables if v.name == "y_coord") is not None
     assert next(v for v in dataset.variables if v.name == "data") is not None
 
-def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50)
+
+def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
     """Test building a Campos 3D dataset with multiple variables and attributes."""
     dataset = make_campos_3d_dataset()
 
@@ -61,11 +63,7 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
 
     # Verify dimension coordinate variables
     validate_variable(
-        dataset,
-        name="inline",
-        dims=[("inline", 256)],
-        coords=["inline"],
-        dtype=ScalarType.UINT32
+        dataset, name="inline", dims=[("inline", 256)], coords=["inline"], dtype=ScalarType.UINT32
     )
 
     validate_variable(
@@ -73,15 +71,11 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
         name="crossline",
         dims=[("crossline", 512)],
         coords=["crossline"],
-        dtype=ScalarType.UINT32
+        dtype=ScalarType.UINT32,
     )
 
     depth = validate_variable(
-        dataset,
-        name="depth",
-        dims=[("depth", 384)],
-        coords=["depth"],
-        dtype=ScalarType.FLOAT64
+        dataset, name="depth", dims=[("depth", 384)], coords=["depth"], dtype=ScalarType.FLOAT64
     )
     assert depth.metadata.units_v1.length == LengthUnitEnum.METER
 
@@ -91,7 +85,7 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
         name="cdp-x",
         dims=[("inline", 256), ("crossline", 512)],
         coords=["cdp-x"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
     assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
 
@@ -100,17 +94,17 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
         name="cdp-y",
         dims=[("inline", 256), ("crossline", 512)],
         coords=["cdp-y"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
     assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
 
     # Verify data variables
     image = validate_variable(
-        dataset,    
+        dataset,
         name="image",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
         coords=["cdp-x", "cdp-y"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
     assert image.metadata.units_v1 is None  # No units defined for image
     assert image.compressor.algorithm == "zstd"
@@ -122,7 +116,7 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
         name="velocity",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
         coords=["cdp-x", "cdp-y"],
-        dtype=ScalarType.FLOAT16
+        dtype=ScalarType.FLOAT16,
     )
     assert velocity.compressor is None
     assert velocity.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
@@ -133,7 +127,7 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
         name="image_inline",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
         coords=["cdp-x", "cdp-y"],
-        dtype=ScalarType.FLOAT32
+        dtype=ScalarType.FLOAT32,
     )
     assert image_inline.long_name == "inline optimized version of 3d_stack"
     assert image_inline.compressor.algorithm == "zstd"
@@ -154,10 +148,8 @@ def test_build_campos_3d() -> None: # noqa: PLR0915 Too many statements (57 > 50
             fields=[
                 StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
                 StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
-                StructuredField(name="inline", format=ScalarType.UINT32),       
+                StructuredField(name="inline", format=ScalarType.UINT32),
                 StructuredField(name="crossline", format=ScalarType.UINT32),
             ]
-        )
+        ),
     )
-
-
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index aecd5ff6d..b1ab99647 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -18,14 +18,11 @@
 
 def test__get_named_dimension() -> None:
     """Test getting a dimension by name from the list of dimensions."""
-    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(
-        name="crossline", size=3)]
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
 
     assert _get_named_dimension([], "inline") is None
-    assert _get_named_dimension(dimensions, "inline") == NamedDimension(
-        name="inline", size=2)
-    assert _get_named_dimension(dimensions, "crossline") == NamedDimension(
-        name="crossline", size=3)
+    assert _get_named_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
+    assert _get_named_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
     assert _get_named_dimension(dimensions, "time") is None
 
     with pytest.raises(TypeError, match="Expected str, got NoneType"):
@@ -51,46 +48,51 @@ def test__to_dictionary() -> None:
     # Validate conversion of a Pydantic BaseModel
     class SomeModel(StrictModel):
         count: int = Field(default=None, description="Samples count")
-        samples: list[float] = Field(
-            default_factory=list, description="Samples.")
+        samples: list[float] = Field(default_factory=list, description="Samples.")
         created: datetime = Field(
             default_factory=datetime.now, description="Creation time with TZ info."
         )
-    md = SomeModel(count=3,
-                   samples=[1.0, 2.0, 3.0],
-                   created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC))
+
+    md = SomeModel(
+        count=3, samples=[1.0, 2.0, 3.0], created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+    )
     result = _to_dictionary(md)
     assert isinstance(result, dict)
-    assert result == {
-        "count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
+    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
 
     # Validate conversion of a dictionary
     dct = {
         "count": 3,
         "samples": [1.0, 2.0, 3.0],
-        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)}
+        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }
     result = _to_dictionary(dct)
     assert isinstance(result, dict)
-    assert result == {"count": 3,
-                      "samples": [1.0, 2.0, 3.0],
-                      "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC), }
+    assert result == {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }
 
     # Validate conversion of a dictionary
-    lst = [None,
-           SomeModel(count=3,
-                     samples=[1.0, 2.0, 3.0],
-                     created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)),
-           {
-               "count2": 3,
-               "samples2": [1.0, 2.0, 3.0],
-               "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
-           }]
+    lst = [
+        None,
+        SomeModel(
+            count=3, samples=[1.0, 2.0, 3.0], created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+        ),
+        {
+            "count2": 3,
+            "samples2": [1.0, 2.0, 3.0],
+            "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+        },
+    ]
     result = _to_dictionary(lst)
     assert isinstance(result, dict)
-    assert result == {"count": 3,
-                      "samples": [1.0, 2.0, 3.0],
-                      "created": "2023-10-01T12:00:00Z",
-                      "count2": 3,
-                      "samples2": [1.0, 2.0, 3.0],
-                      "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
-                      }
+    assert result == {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": "2023-10-01T12:00:00Z",
+        "count2": 3,
+        "samples2": [1.0, 2.0, 3.0],
+        "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }

From 1904deefe7dd58f3d4cb24cbbc682d93f0064926 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Thu, 10 Jul 2025 10:45:04 -0500
Subject: [PATCH 38/56] remove some noqa overrides

---
 src/mdio/schemas/v1/dataset_builder.py | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index 85bae21fe..facd0dc8d 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -9,7 +9,6 @@
 from typing import TypeAlias
 
 from pydantic import BaseModel
-from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding  # noqa: F401
 
 from mdio.schemas.compressors import ZFP
 from mdio.schemas.compressors import Blosc
@@ -107,9 +106,7 @@ def __init__(self, name: str, attributes: UserAttributes | None = None):
         self._state = _BuilderState.INITIAL
         self._unnamed_variable_counter = 0
 
-    def add_dimension(  # noqa: PLR0913
-        self, name: str, size: int
-    ) -> "MDIODatasetBuilder":
+    def add_dimension(self, name: str, size: int) -> "MDIODatasetBuilder":
         """Add a dimension.
 
         This function be called at least once before adding coordinates or variables.

From 90d31a1cd76724d2cb9ad64ede2a615533c80ca6 Mon Sep 17 00:00:00 2001
From: Dima From Texas <34629861+dmitriyrepin@users.noreply.github.com>
Date: Thu, 10 Jul 2025 10:55:47 -0500
Subject: [PATCH 39/56] Implement MDIO Dataset builder to create in-memory
 instance of schemas.v1.dataset.Dataset (#568)

* schema_v1-dataset_builder-add_dimension

* First take on add_dimension(), add_coordinate(), add_variable()

* Finished add_dimension, add_coordinate, add_variable

* Work on build

* Generalize _to_dictionary()

* build

* Dataset Build - pass one

* Revert .container changes

* PR review: remove DEVELOPER_NOTES.md

* PR Review: add_coordinate() should accept only data_type: ScalarType

* PR review: add_variable() data_type remove default

* RE review: do not add dimension variable

* PR Review: get api version from the package version

* PR Review: remove add_dimension_coordinate

* PR Review: add_coordinate() remove data_type default value

* PR Review: improve unit tests by extracting common functionality in validate* functions

* Remove the Dockerfile changes. They are not supposed to be a part of this PR

* PR Review: run ruff

* PR Review: fix pre-commit errors

* remove some noqa overrides

---------

Co-authored-by: Altay Sansal <tasansal@users.noreply.github.com>
---
 src/mdio/schemas/v1/dataset_builder.py        | 335 ++++++++++++++++++
 tests/unit/v1/__init__.py                     |   1 +
 tests/unit/v1/helpers.py                      | 254 +++++++++++++
 .../v1/test_dataset_builder_add_coordinate.py | 141 ++++++++
 .../v1/test_dataset_builder_add_dimension.py  |  43 +++
 .../v1/test_dataset_builder_add_variable.py   | 250 +++++++++++++
 tests/unit/v1/test_dataset_builder_build.py   | 155 ++++++++
 tests/unit/v1/test_dataset_builder_helpers.py |  98 +++++
 8 files changed, 1277 insertions(+)
 create mode 100644 src/mdio/schemas/v1/dataset_builder.py
 create mode 100644 tests/unit/v1/__init__.py
 create mode 100644 tests/unit/v1/helpers.py
 create mode 100644 tests/unit/v1/test_dataset_builder_add_coordinate.py
 create mode 100644 tests/unit/v1/test_dataset_builder_add_dimension.py
 create mode 100644 tests/unit/v1/test_dataset_builder_add_variable.py
 create mode 100644 tests/unit/v1/test_dataset_builder_build.py
 create mode 100644 tests/unit/v1/test_dataset_builder_helpers.py

diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
new file mode 100644
index 000000000..facd0dc8d
--- /dev/null
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -0,0 +1,335 @@
+"""Builder pattern implementation for MDIO v1 schema models."""
+
+from datetime import UTC
+from datetime import datetime
+from enum import Enum
+from enum import auto
+from importlib import metadata
+from typing import Any
+from typing import TypeAlias
+
+from pydantic import BaseModel
+
+from mdio.schemas.compressors import ZFP
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset import DatasetInfo
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import Variable
+
+AnyMetadataList: TypeAlias = list[
+    AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata | DatasetInfo
+]
+CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes]
+VariableMetadataList: TypeAlias = list[
+    AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata
+]
+DatasetMetadataList: TypeAlias = list[DatasetInfo | UserAttributes]
+
+
+class _BuilderState(Enum):
+    """States for the template builder."""
+
+    INITIAL = auto()
+    HAS_DIMENSIONS = auto()
+    HAS_COORDINATES = auto()
+    HAS_VARIABLES = auto()
+
+
+def _get_named_dimension(
+    dimensions: list[NamedDimension], name: str, size: int | None = None
+) -> NamedDimension | None:
+    """Get a dimension by name and optional size from the list[NamedDimension]."""
+    if dimensions is None:
+        return False
+    if not isinstance(name, str):
+        msg = f"Expected str, got {type(name).__name__}"
+        raise TypeError(msg)
+
+    nd = next((dim for dim in dimensions if dim.name == name), None)
+    if nd is None:
+        return None
+    if size is not None and nd.size != size:
+        msg = f"Dimension {name!r} found but size {nd.size} does not match expected size {size}"
+        raise ValueError(msg)
+    return nd
+
+
+def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList) -> dict[str, Any]:
+    """Convert a dictionary, list or pydantic BaseModel to a dictionary."""
+    if val is None:
+        return None
+    if isinstance(val, BaseModel):
+        return val.model_dump(mode="json", by_alias=True)
+    if isinstance(val, dict):
+        return val
+    if isinstance(val, list):
+        metadata_dict = {}
+        for md in val:
+            if md is None:
+                continue
+            metadata_dict.update(_to_dictionary(md))
+        return metadata_dict
+    msg = f"Expected BaseModel, dict or list, got {type(val).__name__}"
+    raise TypeError(msg)
+
+
+class MDIODatasetBuilder:
+    """Builder for creating MDIO datasets with enforced build order.
+
+    This builder implements the builder pattern to create MDIO datasets with a v1 schema.
+    It enforces a specific build order to ensure valid dataset construction:
+    1. Must add dimensions first via add_dimension()
+    2. Can optionally add coordinates via add_coordinate()
+    3. Must add variables via add_variable()
+    4. Must call build() to create the dataset.
+    """
+
+    def __init__(self, name: str, attributes: UserAttributes | None = None):
+        try:
+            api_version = metadata.version("multidimio")
+        except metadata.PackageNotFoundError:
+            api_version = "unknown"
+
+        self._info = DatasetInfo(name=name, api_version=api_version, created_on=datetime.now(UTC))
+        self._attributes = attributes
+        self._dimensions: list[NamedDimension] = []
+        self._coordinates: list[Coordinate] = []
+        self._variables: list[Variable] = []
+        self._state = _BuilderState.INITIAL
+        self._unnamed_variable_counter = 0
+
+    def add_dimension(self, name: str, size: int) -> "MDIODatasetBuilder":
+        """Add a dimension.
+
+        This function be called at least once before adding coordinates or variables.
+
+        Args:
+            name: Name of the dimension
+            size: Size of the dimension
+
+        Raises:
+            ValueError: If 'name' is not a non-empty string.
+                        if the dimension is already defined.
+
+        Returns:
+            self: Returns self for method chaining
+        """
+        if not name:
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
+
+        # Validate that the dimension is not already defined
+        old_var = next((e for e in self._dimensions if e.name == name), None)
+        if old_var is not None:
+            msg = "Adding dimension with the same name twice is not allowed"
+            raise ValueError(msg)
+
+        dim = NamedDimension(name=name, size=size)
+        self._dimensions.append(dim)
+        self._state = _BuilderState.HAS_DIMENSIONS
+        return self
+
+    def add_coordinate(  # noqa: PLR0913
+        self,
+        name: str,
+        *,
+        long_name: str = None,
+        dimensions: list[str],
+        data_type: ScalarType,
+        compressor: Blosc | ZFP | None = None,
+        metadata_info: CoordinateMetadataList | None = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a coordinate after adding at least one dimension.
+
+        This function must be called after all required dimensions are added via add_dimension().
+        This call will create a coordinate variable.
+
+        Args:
+            name: Name of the coordinate
+            long_name: Optional long name for the coordinate
+            dimensions: List of dimension names that the coordinate is associated with
+            data_type: Data type for the coordinate (defaults to FLOAT32)
+            compressor: Compressor used for the variable (defaults to None)
+            metadata_info: Optional metadata information for the coordinate
+
+        Raises:
+            ValueError: If no dimensions have been added yet.
+                        If 'name' is not a non-empty string.
+                        If 'dimensions' is not a non-empty list.
+                        If the coordinate is already defined.
+                        If any referenced dimension is not already defined.
+
+        Returns:
+            self: Returns self for method chaining
+        """
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before adding coordinates"
+            raise ValueError(msg)
+        if not name:
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
+        if dimensions is None or not dimensions:
+            msg = "'dimensions' must be a non-empty list"
+            raise ValueError(msg)
+        old_var = next((e for e in self._coordinates if e.name == name), None)
+        # Validate that the coordinate is not already defined
+        if old_var is not None:
+            msg = "Adding coordinate with the same name twice is not allowed"
+            raise ValueError(msg)
+
+        # Validate that all referenced dimensions are already defined
+        named_dimensions = []
+        for dim_name in dimensions:
+            nd = _get_named_dimension(self._dimensions, dim_name)
+            if nd is None:
+                msg = f"Pre-existing dimension named {dim_name!r} is not found"
+                raise ValueError(msg)
+            named_dimensions.append(nd)
+
+        meta_dict = _to_dictionary(metadata_info)
+        coord = Coordinate(
+            name=name,
+            longName=long_name,
+            dimensions=named_dimensions,
+            compressor=compressor,
+            dataType=data_type,
+            metadata=meta_dict,
+        )
+        self._coordinates.append(coord)
+
+        # Add a coordinate variable to the dataset
+        self.add_variable(
+            name=coord.name,
+            long_name=f"'{coord.name}' coordinate variable",
+            dimensions=dimensions,  # dimension names (list[str])
+            data_type=coord.data_type,
+            compressor=compressor,
+            coordinates=[name],  # Use the coordinate name as a reference
+            metadata_info=coord.metadata,
+        )
+
+        self._state = _BuilderState.HAS_COORDINATES
+        return self
+
+    def add_variable(  # noqa: PLR0913
+        self,
+        name: str,
+        *,
+        long_name: str = None,
+        dimensions: list[str],
+        data_type: ScalarType | StructuredType,
+        compressor: Blosc | ZFP | None = None,
+        coordinates: list[str] | None = None,
+        metadata_info: VariableMetadataList | None = None,
+    ) -> "MDIODatasetBuilder":
+        """Add a variable after adding at least one dimension and, optionally, coordinate.
+
+        This function must be called after all required dimensions are added via add_dimension()
+        This function must be called after all required coordinates are added via add_coordinate().
+
+        If this function is called with a single dimension name that matches the variable name,
+        it will create a dimension variable. Dimension variables are special variables that
+        represent sampling along a dimension.
+
+        Args:
+            name: Name of the variable
+            long_name: Optional long name for the variable
+            dimensions: List of dimension names that the variable is associated with
+            data_type: Data type for the variable (defaults to FLOAT32)
+            compressor: Compressor used for the variable (defaults to None)
+            coordinates: List of coordinate names that the variable is associated with
+                         (defaults to None, meaning no coordinates)
+            metadata_info: Optional metadata information for the variable
+
+        Raises:
+            ValueError: If no dimensions have been added yet.
+                        If 'name' is not a non-empty string.
+                        If 'dimensions' is not a non-empty list.
+                        If the variable is already defined.
+                        If any referenced dimension is not already defined.
+                        If any referenced coordinate is not already defined.
+
+        Returns:
+            self: Returns self for method chaining.
+        """
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before adding variables"
+            raise ValueError(msg)
+        if not name:
+            msg = "'name' must be a non-empty string"
+            raise ValueError(msg)
+        if dimensions is None or not dimensions:
+            msg = "'dimensions' must be a non-empty list"
+            raise ValueError(msg)
+
+        # Validate that the variable is not already defined
+        old_var = next((e for e in self._variables if e.name == name), None)
+        if old_var is not None:
+            msg = "Adding variable with the same name twice is not allowed"
+            raise ValueError(msg)
+
+        # Validate that all referenced dimensions are already defined
+        named_dimensions = []
+        for dim_name in dimensions:
+            nd = _get_named_dimension(self._dimensions, dim_name)
+            if nd is None:
+                msg = f"Pre-existing dimension named {dim_name!r} is not found"
+                raise ValueError(msg)
+            named_dimensions.append(nd)
+
+        coordinate_objs: list[Coordinate] = []
+        # Validate that all referenced coordinates are already defined
+        if coordinates is not None:
+            for coord in coordinates:
+                c: Coordinate = next((c for c in self._coordinates if c.name == coord), None)
+                if c is not None:
+                    coordinate_objs.append(c)
+                else:
+                    msg = f"Pre-existing coordinate named {coord!r} is not found"
+                    raise ValueError(msg)
+
+        # If this is a dimension coordinate variable, embed the Coordinate into it
+        if coordinates is not None and len(coordinates) == 1 and coordinates[0] == name:
+            coordinates = coordinate_objs
+
+        meta_dict = _to_dictionary(metadata_info)
+        var = Variable(
+            name=name,
+            long_name=long_name,
+            dimensions=named_dimensions,
+            data_type=data_type,
+            compressor=compressor,
+            coordinates=coordinates,
+            metadata=meta_dict,
+        )
+        self._variables.append(var)
+
+        self._state = _BuilderState.HAS_VARIABLES
+        return self
+
+    def build(self) -> Dataset:
+        """Build the final dataset.
+
+        This function must be called after at least one dimension is added via add_dimension().
+        It will create a Dataset object with all added dimensions, coordinates, and variables.
+
+        Raises:
+            ValueError: If no dimensions have been added yet.
+
+        Returns:
+            Dataset: The built dataset with all added dimensions, coordinates, and variables.
+        """
+        if self._state == _BuilderState.INITIAL:
+            msg = "Must add at least one dimension before building"
+            raise ValueError(msg)
+
+        var_meta_dict = _to_dictionary([self._info, self._attributes])
+        return Dataset(variables=self._variables, metadata=var_meta_dict)
diff --git a/tests/unit/v1/__init__.py b/tests/unit/v1/__init__.py
new file mode 100644
index 000000000..fa2ea633b
--- /dev/null
+++ b/tests/unit/v1/__init__.py
@@ -0,0 +1 @@
+"""Unit tests for parts of the MDIO package related to the v1 schema."""
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
new file mode 100644
index 000000000..2058bdd54
--- /dev/null
+++ b/tests/unit/v1/helpers.py
@@ -0,0 +1,254 @@
+"""Helper methods used in unit tests."""
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import SpeedUnitEnum
+from mdio.schemas.v1.units import SpeedUnitModel
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import Variable
+
+
+def validate_builder(
+    builder: MDIODatasetBuilder, state: _BuilderState, n_dims: int, n_coords: int, n_var: int
+) -> None:
+    """Validate the state of the builder, the number of dimensions, coordinates, and variables."""
+    assert builder._state == state
+    assert len(builder._dimensions) == n_dims
+    assert len(builder._coordinates) == n_coords
+    assert len(builder._variables) == n_var
+
+
+def validate_coordinate(
+    builder: MDIODatasetBuilder, name: str, dims: list[tuple[str, int]], dtype: ScalarType
+) -> Coordinate:
+    """Validate existence and the structure of the created coordinate."""
+    # Validate that coordinate exists
+    c = next((c for c in builder._coordinates if c.name == name), None)
+    assert c is not None
+    assert isinstance(c, Coordinate)
+
+    # Validate that dimensions are stored as NamedDimensions
+    for d in dims:
+        name = d[0]
+        size = d[1]
+        assert _get_named_dimension(c.dimensions, name, size) is not None
+
+    assert c.data_type == dtype
+    return c
+
+
+def validate_variable(
+    container: MDIODatasetBuilder | Dataset,
+    name: str,
+    dims: list[tuple[str, int]],
+    coords: list[str],
+    dtype: ScalarType,
+) -> Variable:
+    """Validate existence and the structure of the created variable."""
+    if isinstance(container, MDIODatasetBuilder):
+        var_list = container._variables
+        global_coord_list = container._coordinates
+    elif isinstance(container, Dataset):
+        var_list = container.variables
+        global_coord_list = _get_all_coordinates(container)
+    else:
+        err_msg = f"Expected MDIODatasetBuilder or Dataset, got {type(container)}"
+        raise TypeError(err_msg)
+
+    # Validate that the variable exists
+    v = next((e for e in var_list if e.name == name), None)
+    assert v is not None
+    assert isinstance(v, Variable)
+
+    # Validate that dimensions are stored as NamedDimensions within the variable
+    assert len(v.dimensions) == len(dims)
+    for d in dims:
+        name = d[0]
+        size = d[1]
+        assert _get_named_dimension(v.dimensions, name, size) is not None
+
+    # Validate that coordinates are either embedded or can be resolved from names to Coordinate
+    if coords is None:
+        assert v.coordinates is None
+    else:
+        assert len(v.coordinates) == len(coords)
+        for coord_name in coords:
+            assert _get_coordinate(global_coord_list, v.coordinates, coord_name) is not None
+
+    assert v.data_type == dtype
+    return v
+
+
+def _get_coordinate(
+    global_coord_list: list[Coordinate],
+    coordinates_or_references: list[Coordinate] | list[str],
+    name: str,
+) -> Coordinate | None:
+    """Get a coordinate by name from the list[Coordinate] | list[str].
+
+    The function validates that the coordinate referenced by the name can be found
+    in the global coordinate list.
+    If the coordinate is stored as a Coordinate object, it is returned directly.
+    """
+    if coordinates_or_references is None:
+        return None
+
+    for c in coordinates_or_references:
+        if isinstance(c, str) and c == name:
+            # The coordinate is stored by name (str).
+            cc = None
+            # Find the Coordinate in the global list and return it.
+            if global_coord_list is not None:
+                cc = next((cc for cc in global_coord_list if cc.name == name), None)
+            if cc is None:
+                msg = f"Pre-existing coordinate named {name!r} is not found"
+                raise ValueError(msg)
+            return cc
+        if isinstance(c, Coordinate) and c.name == name:
+            # The coordinate is stored as an embedded Coordinate object.
+            # Return it.
+            return c
+
+    return None
+
+
+def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
+    all_coords: dict[str, Coordinate] = {}
+    for v in dataset.variables:
+        if v.coordinates is not None:
+            for c in v.coordinates:
+                if isinstance(c, Coordinate) and c.name not in all_coords:
+                    all_coords[c.name] = c
+    return list(all_coords.values())
+
+
+def make_campos_3d_dataset() -> Dataset:
+    """Create in-memory campos_3d dataset."""
+    ds = MDIODatasetBuilder(
+        "campos_3d",
+        attributes=UserAttributes(
+            attributes={
+                "textHeader": [
+                    "C01 .......................... ",
+                    "C02 .......................... ",
+                    "C03 .......................... ",
+                ],
+                "foo": "bar",
+            }
+        ),
+    )
+
+    # Add dimensions
+    ds.add_dimension("inline", 256)
+    ds.add_dimension("crossline", 512)
+    ds.add_dimension("depth", 384)
+    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate(
+        "depth",
+        dimensions=["depth"],
+        data_type=ScalarType.FLOAT64,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+    # Add coordinates
+    ds.add_coordinate(
+        "cdp-x",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+    ds.add_coordinate(
+        "cdp-y",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+
+    # Add image variable
+    ds.add_variable(
+        name="image",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+            UserAttributes(attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
+        ],
+    )
+    # Add velocity variable
+    ds.add_variable(
+        name="velocity",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT16,
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
+            ),
+            AllUnits(units_v1=SpeedUnitModel(speed=SpeedUnitEnum.METER_PER_SECOND)),
+        ],
+    )
+    # Add inline-optimized image variable
+    ds.add_variable(
+        name="image_inline",
+        long_name="inline optimized version of 3d_stack",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512])
+                )
+            )
+        ],
+    )
+    # Add headers variable with structured dtype
+    ds.add_variable(
+        name="image_headers",
+        dimensions=["inline", "crossline"],
+        data_type=StructuredType(
+            fields=[
+                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
+                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
+                StructuredField(name="inline", format=ScalarType.UINT32),
+                StructuredField(name="crossline", format=ScalarType.UINT32),
+            ]
+        ),
+        coordinates=["cdp-x", "cdp-y"],
+    )
+    return ds.build()
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
new file mode 100644
index 000000000..46cb27cd1
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -0,0 +1,141 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_coordinate() public API."""
+
+import pytest
+
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.variable import VariableMetadata
+
+from .helpers import validate_builder
+from .helpers import validate_coordinate
+from .helpers import validate_variable
+
+
+def test_add_coordinate() -> None:
+    """Test adding coordinates. Check the state transition and validate required parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+
+    msg = "Must add at least one dimension before adding coordinates"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate(
+            "cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        )
+
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+
+    # Validate required parameters
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_coordinate(bad_name, dimensions=["speed"], data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_coordinate("", dimensions=["speed"], data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_coordinate("cdp-x", dimensions=None, data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_coordinate("cdp-x", dimensions=[], data_type=ScalarType.FLOAT32)
+
+    # Add a variable using non-existent dimensions
+    msg = "Pre-existing dimension named 'xline' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate(
+            "bad_cdp-x", dimensions=["inline", "xline"], data_type=ScalarType.FLOAT32
+        )
+
+    # Validate state transition
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    validate_variable(
+        builder,
+        name="cdp-x",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp-x"],
+        dtype=ScalarType.FLOAT32,
+    )
+
+    # Adding coordinate with the same name twice
+    msg = "Adding coordinate with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_coordinate(
+            "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        )
+
+
+def test_add_coordinate_with_defaults() -> None:
+    """Test adding coordinates with default arguments."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+
+    # Add coordinate using defaults
+    builder.add_coordinate("cdp", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    validate_coordinate(
+        builder, name="cdp", dims=[("inline", 100), ("crossline", 200)], dtype=ScalarType.FLOAT32
+    )
+    v = validate_variable(
+        builder,
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert v.long_name == "'cdp' coordinate variable"  # Default value
+    assert v.compressor is None  # Default value
+    assert v.metadata is None  # Default value
+
+
+def test_coordinate_with_full_parameters() -> None:
+    """Test adding coordinates with all metadata."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+
+    # Add coordinate with all metadata
+    builder.add_coordinate(
+        "cdp",
+        long_name="Common Depth Point",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT16,
+        compressor=Blosc(algorithm="zstd"),
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+        ],
+    )
+    validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
+    c = validate_coordinate(
+        builder, name="cdp", dims=[("inline", 100), ("crossline", 200)], dtype=ScalarType.FLOAT16
+    )
+    assert c.long_name == "Common Depth Point"
+    assert isinstance(c.compressor, Blosc)
+    assert c.compressor.algorithm == "zstd"
+    assert c.metadata.attributes["MGA"] == 51
+    assert c.metadata.attributes["UnitSystem"] == "Imperial"
+    assert c.metadata.units_v1.length == LengthUnitEnum.FOOT
+    v = validate_variable(
+        builder,
+        name="cdp",
+        dims=[("inline", 100), ("crossline", 200)],
+        coords=["cdp"],
+        dtype=ScalarType.FLOAT16,
+    )
+    assert isinstance(v.compressor, Blosc)
+    assert v.compressor.algorithm == "zstd"
+    assert isinstance(v.metadata, VariableMetadata)
+    assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
+    assert v.metadata.attributes["MGA"] == 51
+    assert v.metadata.attributes["UnitSystem"] == "Imperial"
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
new file mode 100644
index 000000000..ddcbd745c
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -0,0 +1,43 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_dimension() public API."""
+
+import pytest
+
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
+
+from .helpers import validate_builder
+
+
+def test_add_dimension() -> None:
+    """Test adding dimension. Check the state transition and validate required parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    assert builder._state == _BuilderState.INITIAL
+
+    # Validate required parameters
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_dimension(bad_name, 200)
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_dimension("", 200)
+
+    # First dimension should change state to HAS_DIMENSIONS and create a variable
+    builder.add_dimension("x", 100)
+    validate_builder(builder, _BuilderState.HAS_DIMENSIONS, n_dims=1, n_coords=0, n_var=0)
+    assert _get_named_dimension(builder._dimensions, "x", 100) is not None
+
+    # Validate that we can't add a dimension with the same name twice
+    with pytest.raises(
+        ValueError,
+        match="Adding dimension with the same name twice is not allowed",
+    ):
+        builder.add_dimension("x", 200)
+
+    # Adding dimension with the same name twice
+    msg = "Adding dimension with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_dimension("x", 200)
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
new file mode 100644
index 000000000..84abfe3ad
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -0,0 +1,250 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 Variable public API."""
+
+import pytest
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _BuilderState
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import StatisticsMetadata
+from mdio.schemas.v1.stats import SummaryStatistics
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.variable import VariableMetadata
+
+from .helpers import validate_builder
+from .helpers import validate_variable
+
+
+def test_add_variable_no_coords() -> None:
+    """Test adding variable. Check the state transition and validate required parameters.."""
+    builder = MDIODatasetBuilder("test_dataset")
+    validate_builder(builder, _BuilderState.INITIAL, n_dims=0, n_coords=0, n_var=0)
+
+    # Validate: Must add at least one dimension before adding variables
+    msg = "Must add at least one dimension before adding variables"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable("amplitude", dimensions=["speed"], data_type=ScalarType.FLOAT32)
+
+    # Add dimension before we can add a data variable
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+
+    # Validate: required parameters must be preset
+    bad_name = None
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_variable(bad_name, dimensions=["speed"], data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'name' must be a non-empty string"):
+        builder.add_variable("", dimensions=["speed"], data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_variable("bad_amplitude", dimensions=None, data_type=ScalarType.FLOAT32)
+    with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
+        builder.add_variable("bad_amplitude", dimensions=[], data_type=ScalarType.FLOAT32)
+
+    # Validate: Add a variable using non-existent dimensions is not allowed
+    msg = "Pre-existing dimension named 'il' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable(
+            "bad_amplitude", dimensions=["il", "xl", "depth"], data_type=ScalarType.FLOAT32
+        )
+
+    # Add a variable without coordinates
+    builder.add_variable(
+        "amplitude", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+    )
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=0, n_var=1)
+    validate_variable(
+        builder,
+        "amplitude",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=None,
+        dtype=ScalarType.FLOAT32,
+    )
+
+    # Validate: adding a variable with the same name twice is not allowed
+    msg = "Adding variable with the same name twice is not allowed"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable(
+            "amplitude", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+        )
+
+
+def test_add_variable_with_coords() -> None:
+    """Test adding variable. Check the state transition and validate required parameters.."""
+    builder = MDIODatasetBuilder("test_dataset")
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+
+    # Add dimension coordinates before we can add a data variable
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+
+    # Validate: adding a variable with a coordinate that has not been pre-created is not allowed
+    msg = "Pre-existing coordinate named 'depth' is not found"
+    with pytest.raises(ValueError, match=msg):
+        builder.add_variable(
+            "ampl",
+            dimensions=["inline", "crossline", "depth"],
+            coordinates=["inline", "crossline", "depth"],
+            data_type=ScalarType.FLOAT32,
+        )
+
+    # Add a variable with pre-defined dimension coordinates
+    builder.add_variable(
+        "ampl",
+        dimensions=["inline", "crossline", "depth"],
+        coordinates=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+    )
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=2, n_var=3)
+    validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline"],
+        dtype=ScalarType.FLOAT32,
+    )
+
+    # Add non-dim coordinates (e.g., 2D coordinates)
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
+    builder.add_coordinate(
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+    )
+
+    # Add a variable with pre-defined dimension and non-dimension coordinates
+    builder.add_variable(
+        "ampl2",
+        dimensions=["inline", "crossline", "depth"],
+        coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+        data_type=ScalarType.FLOAT32,
+    )
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=4, n_var=6)
+    validate_variable(
+        builder,
+        "ampl2",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline", "cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
+
+
+def test_add_variable_with_defaults() -> None:
+    """Test adding variable with default arguments."""
+    builder = MDIODatasetBuilder("test_dataset")
+    # Add dimensions before we can add a data variables
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+    # Add dimension coordinates
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate(
+        "depth",
+        dimensions=["depth"],
+        data_type=ScalarType.UINT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+
+    # Add data variable using defaults
+    builder.add_variable(
+        "ampl", dimensions=["inline", "crossline", "depth"], data_type=ScalarType.FLOAT32
+    )
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=3, n_var=4)
+    v = validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=None,
+        dtype=ScalarType.FLOAT32,
+    )
+    assert v.long_name is None  # Default value
+    assert v.compressor is None  # Default value
+    assert v.coordinates is None  # Default value
+    assert v.metadata is None  # Default value
+
+
+def test_add_variable_full_parameters() -> None:
+    """Test adding variable with full parameters."""
+    builder = MDIODatasetBuilder("test_dataset")
+    # Add dimensions before we can add a data variables
+    builder.add_dimension("inline", 100)
+    builder.add_dimension("crossline", 200)
+    builder.add_dimension("depth", 300)
+    # Add dimension coordinates
+    builder.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
+    # Add coordinates before we can add a data variable
+    builder.add_coordinate(
+        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+    )
+    builder.add_coordinate(
+        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+    )
+
+    # Add data variable with full parameters
+    builder.add_variable(
+        "ampl",
+        long_name="Amplitude (dimensionless)",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        metadata_info=[
+            AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
+            UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[20]))
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+        ],
+    )
+    validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=5, n_var=6)
+    v = validate_variable(
+        builder,
+        "ampl",
+        dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
+        coords=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert v.long_name == "Amplitude (dimensionless)"
+    assert isinstance(v.compressor, Blosc)
+    assert v.compressor.algorithm == "zstd"
+    assert len(v.coordinates) == 5
+    assert v.metadata.stats_v1.count == 100
+    assert isinstance(v.metadata, VariableMetadata)
+    assert v.metadata.units_v1.length == LengthUnitEnum.FOOT
+    assert v.metadata.attributes["MGA"] == 51
+    assert v.metadata.attributes["UnitSystem"] == "Imperial"
+    assert v.metadata.chunk_grid.name == "regular"
+    assert v.metadata.chunk_grid.configuration.chunk_shape == [20]
+    assert v.metadata.stats_v1.count == 100
+    assert v.metadata.stats_v1.sum == 1215.1
+    assert v.metadata.stats_v1.sum_squares == 125.12
+    assert v.metadata.stats_v1.min == 5.61
+    assert v.metadata.stats_v1.max == 10.84
+    assert v.metadata.stats_v1.histogram.bin_centers == [1, 2]
+    assert v.metadata.stats_v1.histogram.counts == [10, 15]
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
new file mode 100644
index 000000000..aa5fad552
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -0,0 +1,155 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder.add_coordinate() public API."""
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import SpeedUnitEnum
+
+from .helpers import make_campos_3d_dataset
+from .helpers import validate_variable
+
+
+def test_build() -> None:
+    """Test building a complete dataset."""
+    dataset = (
+        MDIODatasetBuilder("test_dataset")
+        .add_dimension("inline", 100)
+        .add_dimension("crossline", 200)
+        .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64)
+        .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64)
+        .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        .add_variable(
+            "data",
+            long_name="Test Data",
+            dimensions=["inline", "crossline"],
+            coordinates=["inline", "crossline", "x_coord", "y_coord"],
+            data_type=ScalarType.FLOAT32,
+        )
+        .build()
+    )
+
+    assert isinstance(dataset, Dataset)
+    assert dataset.metadata.name == "test_dataset"
+    # 2 dim coord var + 2 non-dim coord var + 1 data variables = 5 variables
+    assert len(dataset.variables) == 5
+    assert next(v for v in dataset.variables if v.name == "inline") is not None
+    assert next(v for v in dataset.variables if v.name == "crossline") is not None
+    assert next(v for v in dataset.variables if v.name == "x_coord") is not None
+    assert next(v for v in dataset.variables if v.name == "y_coord") is not None
+    assert next(v for v in dataset.variables if v.name == "data") is not None
+
+
+def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
+    """Test building a Campos 3D dataset with multiple variables and attributes."""
+    dataset = make_campos_3d_dataset()
+
+    # Verify dataset structure
+    assert dataset.metadata.name == "campos_3d"
+    assert dataset.metadata.api_version == "1.0.0a1"
+    assert dataset.metadata.attributes["foo"] == "bar"
+    assert len(dataset.metadata.attributes["textHeader"]) == 3
+
+    # Verify variables (including dimension variables)
+    # 3 dimension variables + 4 data variables + 2 coordinate variables
+    assert len(dataset.variables) == 9
+
+    # Verify dimension coordinate variables
+    validate_variable(
+        dataset, name="inline", dims=[("inline", 256)], coords=["inline"], dtype=ScalarType.UINT32
+    )
+
+    validate_variable(
+        dataset,
+        name="crossline",
+        dims=[("crossline", 512)],
+        coords=["crossline"],
+        dtype=ScalarType.UINT32,
+    )
+
+    depth = validate_variable(
+        dataset, name="depth", dims=[("depth", 384)], coords=["depth"], dtype=ScalarType.FLOAT64
+    )
+    assert depth.metadata.units_v1.length == LengthUnitEnum.METER
+
+    # Verify coordinate variables
+    cdp_x = validate_variable(
+        dataset,
+        name="cdp-x",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-x"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    cdp_y = validate_variable(
+        dataset,
+        name="cdp-y",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+    # Verify data variables
+    image = validate_variable(
+        dataset,
+        name="image",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert image.metadata.units_v1 is None  # No units defined for image
+    assert image.compressor.algorithm == "zstd"
+    assert image.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+    assert image.metadata.stats_v1.count == 100
+
+    velocity = validate_variable(
+        dataset,
+        name="velocity",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT16,
+    )
+    assert velocity.compressor is None
+    assert velocity.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+    assert velocity.metadata.units_v1.speed == SpeedUnitEnum.METER_PER_SECOND
+
+    image_inline = validate_variable(
+        dataset,
+        name="image_inline",
+        dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=ScalarType.FLOAT32,
+    )
+    assert image_inline.long_name == "inline optimized version of 3d_stack"
+    assert image_inline.compressor.algorithm == "zstd"
+    assert image_inline.metadata.chunk_grid.configuration.chunk_shape == [4, 512, 512]
+
+    # Verify image_headers variable
+    headers = next(v for v in dataset.variables if v.name == "image_headers")
+    assert isinstance(headers.data_type, StructuredType)
+    assert len(headers.data_type.fields) == 4
+    assert headers.data_type.fields[0].name == "cdp-x"
+
+    headers = validate_variable(
+        dataset,
+        name="image_headers",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp-x", "cdp-y"],
+        dtype=StructuredType(
+            fields=[
+                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
+                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
+                StructuredField(name="inline", format=ScalarType.UINT32),
+                StructuredField(name="crossline", format=ScalarType.UINT32),
+            ]
+        ),
+    )
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
new file mode 100644
index 000000000..b1ab99647
--- /dev/null
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -0,0 +1,98 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_builder internal methods."""
+
+from datetime import UTC
+from datetime import datetime
+
+import pytest
+from pydantic import Field
+
+from mdio.schemas.core import StrictModel
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.v1.dataset_builder import _get_named_dimension
+from mdio.schemas.v1.dataset_builder import _to_dictionary
+
+
+def test__get_named_dimension() -> None:
+    """Test getting a dimension by name from the list of dimensions."""
+    dimensions = [NamedDimension(name="inline", size=2), NamedDimension(name="crossline", size=3)]
+
+    assert _get_named_dimension([], "inline") is None
+    assert _get_named_dimension(dimensions, "inline") == NamedDimension(name="inline", size=2)
+    assert _get_named_dimension(dimensions, "crossline") == NamedDimension(name="crossline", size=3)
+    assert _get_named_dimension(dimensions, "time") is None
+
+    with pytest.raises(TypeError, match="Expected str, got NoneType"):
+        _get_named_dimension(dimensions, None)
+    with pytest.raises(TypeError, match="Expected str, got int"):
+        _get_named_dimension(dimensions, 42)
+    with pytest.raises(
+        ValueError, match="Dimension 'inline' found but size 2 does not match expected size 200"
+    ):
+        _get_named_dimension(dimensions, "inline", size=200)
+
+
+def test__to_dictionary() -> None:
+    """Test converting a dictionary, list or pydantic BaseModel to a dictionary."""
+    # Validate inputs
+    with pytest.raises(TypeError, match="Expected BaseModel, dict or list, got datetime"):
+        _to_dictionary(datetime.now(UTC))
+
+    # Convert None to None
+    result = _to_dictionary(None)
+    assert result is None
+
+    # Validate conversion of a Pydantic BaseModel
+    class SomeModel(StrictModel):
+        count: int = Field(default=None, description="Samples count")
+        samples: list[float] = Field(default_factory=list, description="Samples.")
+        created: datetime = Field(
+            default_factory=datetime.now, description="Creation time with TZ info."
+        )
+
+    md = SomeModel(
+        count=3, samples=[1.0, 2.0, 3.0], created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+    )
+    result = _to_dictionary(md)
+    assert isinstance(result, dict)
+    assert result == {"count": 3, "created": "2023-10-01T12:00:00Z", "samples": [1.0, 2.0, 3.0]}
+
+    # Validate conversion of a dictionary
+    dct = {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }
+    result = _to_dictionary(dct)
+    assert isinstance(result, dict)
+    assert result == {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }
+
+    # Validate conversion of a dictionary
+    lst = [
+        None,
+        SomeModel(
+            count=3, samples=[1.0, 2.0, 3.0], created=datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC)
+        ),
+        {
+            "count2": 3,
+            "samples2": [1.0, 2.0, 3.0],
+            "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+        },
+    ]
+    result = _to_dictionary(lst)
+    assert isinstance(result, dict)
+    assert result == {
+        "count": 3,
+        "samples": [1.0, 2.0, 3.0],
+        "created": "2023-10-01T12:00:00Z",
+        "count2": 3,
+        "samples2": [1.0, 2.0, 3.0],
+        "created2": datetime(2023, 10, 1, 12, 0, 0, tzinfo=UTC),
+    }

From 4c7c8337f16d3d1ee5602f54df66a3fcc0dc1581 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Thu, 10 Jul 2025 23:34:39 +0000
Subject: [PATCH 40/56] Writing XArray / Zarr

---
 _dev/DEVELOPERS_NOTES.md                      |  10 +
 _dev/zmetadata.cpp.json                       | 294 ++++++++++++++++++
 _dev/zmetadata.python.json                    | 282 +++++++++++++++++
 src/mdio/schemas/v1/dataset_builder.py        |   2 +-
 src/mdio/schemas/v1/dataset_serializer.py     | 224 +++++++++++++
 tests/unit/v1/helpers.py                      | 122 ++++++++
 .../v1/test_dataset_builder_add_coordinate.py |   2 +-
 .../v1/test_dataset_builder_add_variable.py   |   2 +-
 tests/unit/v1/test_dataset_builder_build.py   |   2 +-
 tests/unit/v1/test_dataset_serializer.py      |  60 ++++
 10 files changed, 996 insertions(+), 4 deletions(-)
 create mode 100644 _dev/DEVELOPERS_NOTES.md
 create mode 100644 _dev/zmetadata.cpp.json
 create mode 100644 _dev/zmetadata.python.json
 create mode 100644 src/mdio/schemas/v1/dataset_serializer.py
 create mode 100644 tests/unit/v1/test_dataset_serializer.py

diff --git a/_dev/DEVELOPERS_NOTES.md b/_dev/DEVELOPERS_NOTES.md
new file mode 100644
index 000000000..2e4718a4b
--- /dev/null
+++ b/_dev/DEVELOPERS_NOTES.md
@@ -0,0 +1,10 @@
+# Wring empty XArray / Zarr to a local storage
+
+src/mdio/schemas/v1/dataset_serializer.py
+
+## Issues encountered
+
+1. Non-zero size of the serialized data files
+2. Not clear how to properly set `compressor`, `dimension_separator`, and `fill_value`
+    * Should `fill_value` be a part f the model?
+3. For image_inline chunks[2] are somehow different?
\ No newline at end of file
diff --git a/_dev/zmetadata.cpp.json b/_dev/zmetadata.cpp.json
new file mode 100644
index 000000000..40a12d6de
--- /dev/null
+++ b/_dev/zmetadata.cpp.json
@@ -0,0 +1,294 @@
+{
+    "metadata": {
+        ".zattrs": {
+            "apiVersion": "1.0.0",
+            "attributes": {
+                "foo": "bar",
+                "textHeader": [
+                    "C01 .......................... ",
+                    "C02 .......................... ",
+                    "C03 .......................... "
+                ]
+            },
+            "createdOn": "2023-12-12T15:02:06.413469-06:00",
+            "name": "campos_3d"
+        },
+        ".zgroup": {
+            "zarr_format": 2
+        },
+        "cdp-x/.zarray": {
+            "chunks": [
+                256,
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "cdp-x/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "cdp-y/.zarray": {
+            "chunks": [
+                256,
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "cdp-y/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "crossline/.zarray": {
+            "chunks": [
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                512
+            ],
+            "zarr_format": 2
+        },
+        "crossline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "crossline"
+            ]
+        },
+        "depth/.zarray": {
+            "chunks": [
+                384
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                384
+            ],
+            "zarr_format": 2
+        },
+        "depth/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "depth"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "image/.zarray": {
+            "chunks": [
+                128,
+                128,
+                128
+            ],
+            "compressor": {
+                "blocksize": 0,
+                "clevel": 5,
+                "cname": "zstd",
+                "id": "blosc",
+                "shuffle": 1
+            },
+            "dimension_separator": "/",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "image/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "attributes": {
+                "fizz": "buzz"
+            },
+            "coordinates": "cdp-x cdp-y",
+            "statsV1": {
+                "count": 100,
+                "histogram": {
+                    "binCenters": [
+                        1,
+                        2
+                    ],
+                    "counts": [
+                        10,
+                        15
+                    ]
+                },
+                "max": 10.84,
+                "min": 5.61,
+                "sum": 1215.1,
+                "sumSquares": 125.12
+            }
+        },
+        "image_headers/.zarray": {
+            "chunks": [
+                128,
+                128
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": [
+                [
+                    "cdp-x",
+                    "<i4"
+                ],
+                [
+                    "cdp-y",
+                    "<i4"
+                ],
+                [
+                    "elevation",
+                    "<f2"
+                ],
+                [
+                    "some_scalar",
+                    "<f2"
+                ]
+            ],
+            "fill_value": "AAAAAAAAAAAAAAAA",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "image_headers/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "coordinates": "cdp-x cdp-y"
+        },
+        "image_inline/.zarray": {
+            "chunks": [
+                4,
+                512,
+                512
+            ],
+            "compressor": {
+                "blocksize": 0,
+                "clevel": 5,
+                "cname": "zstd",
+                "id": "blosc",
+                "shuffle": 1
+            },
+            "dimension_separator": "/",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "image_inline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "coordinates": "cdp-x cdp-y",
+            "long_name": "inline optimized version of 3d_stack"
+        },
+        "inline/.zarray": {
+            "chunks": [
+                256
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256
+            ],
+            "zarr_format": 2
+        },
+        "inline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline"
+            ]
+        },
+        "velocity/.zarray": {
+            "chunks": [
+                128,
+                128,
+                128
+            ],
+            "compressor": null,
+            "dimension_separator": "/",
+            "dtype": "<f2",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "velocity/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "coordinates": "cdp-x cdp-y",
+            "unitsV1": {
+                "speed": "m/s"
+            }
+        }
+    },
+    "zarr_consolidated_format": 1
+}
diff --git a/_dev/zmetadata.python.json b/_dev/zmetadata.python.json
new file mode 100644
index 000000000..ce52cec38
--- /dev/null
+++ b/_dev/zmetadata.python.json
@@ -0,0 +1,282 @@
+{
+    "metadata": {
+        ".zattrs": {
+            "apiVersion": "1.0.0a1",
+            "attributes": {
+                "foo": "bar",
+                "textHeader": [
+                    "C01 .......................... ",
+                    "C02 .......................... ",
+                    "C03 .......................... "
+                ]
+            },
+            "createdOn": "2025-07-10 23:17:20.653097+00:00",
+            "name": "campos_3d"
+        },
+        ".zgroup": {
+            "zarr_format": 2
+        },
+        "cdp-x/.zarray": {
+            "chunks": [
+                256,
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "cdp-x/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "cdp-y/.zarray": {
+            "chunks": [
+                256,
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "cdp-y/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "crossline/.zarray": {
+            "chunks": [
+                512
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                512
+            ],
+            "zarr_format": 2
+        },
+        "crossline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "crossline"
+            ]
+        },
+        "depth/.zarray": {
+            "chunks": [
+                384
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                384
+            ],
+            "zarr_format": 2
+        },
+        "depth/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "depth"
+            ],
+            "unitsV1": {
+                "length": "m"
+            }
+        },
+        "image/.zarray": {
+            "chunks": [
+                128,
+                128,
+                128
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "image/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "attributes": {
+                "fizz": "buzz"
+            },
+            "coordinates": "cdp-x cdp-y",
+            "statsV1": {
+                "count": 100,
+                "histogram": {
+                    "binCenters": [
+                        1,
+                        2
+                    ],
+                    "counts": [
+                        10,
+                        15
+                    ]
+                },
+                "max": 10.84,
+                "min": 5.61,
+                "sum": 1215.1,
+                "sumSquares": 125.12
+            }
+        },
+        "image_headers/.zarray": {
+            "chunks": [
+                128,
+                128
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": [
+                [
+                    "cdp-x",
+                    "<i4"
+                ],
+                [
+                    "cdp-y",
+                    "<i4"
+                ],
+                [
+                    "elevation",
+                    "<f2"
+                ],
+                [
+                    "some_scalar",
+                    "<f2"
+                ]
+            ],
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512
+            ],
+            "zarr_format": 2
+        },
+        "image_headers/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline"
+            ],
+            "coordinates": "cdp-x cdp-y"
+        },
+        "image_inline/.zarray": {
+            "chunks": [
+                4,
+                512,
+                384
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<f4",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "image_inline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "coordinates": "cdp-x cdp-y",
+            "long_name": "inline optimized version of 3d_stack"
+        },
+        "inline/.zarray": {
+            "chunks": [
+                256
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<u4",
+            "fill_value": null,
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256
+            ],
+            "zarr_format": 2
+        },
+        "inline/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline"
+            ]
+        },
+        "velocity/.zarray": {
+            "chunks": [
+                128,
+                128,
+                128
+            ],
+            "compressor": null,
+            "dimension_separator": ".",
+            "dtype": "<f2",
+            "fill_value": "NaN",
+            "filters": null,
+            "order": "C",
+            "shape": [
+                256,
+                512,
+                384
+            ],
+            "zarr_format": 2
+        },
+        "velocity/.zattrs": {
+            "_ARRAY_DIMENSIONS": [
+                "inline",
+                "crossline",
+                "depth"
+            ],
+            "coordinates": "cdp-x cdp-y",
+            "unitsV1": {
+                "speed": "m/s"
+            }
+        }
+    },
+    "zarr_consolidated_format": 1
+}
\ No newline at end of file
diff --git a/src/mdio/schemas/v1/dataset_builder.py b/src/mdio/schemas/v1/dataset_builder.py
index facd0dc8d..698b18740 100644
--- a/src/mdio/schemas/v1/dataset_builder.py
+++ b/src/mdio/schemas/v1/dataset_builder.py
@@ -208,7 +208,7 @@ def add_coordinate(  # noqa: PLR0913
         # Add a coordinate variable to the dataset
         self.add_variable(
             name=coord.name,
-            long_name=f"'{coord.name}' coordinate variable",
+            long_name=coord.long_name,
             dimensions=dimensions,  # dimension names (list[str])
             data_type=coord.data_type,
             compressor=compressor,
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
new file mode 100644
index 000000000..1b3fbabd6
--- /dev/null
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -0,0 +1,224 @@
+from typing import Mapping
+import warnings
+
+import dask
+import xarray as xr
+import numpy as np
+import zarr
+
+from mdio.schemas.dimension import NamedDimension
+from mdio.schemas.dtype import ScalarType, StructuredType
+from mdio.schemas.v1 import dataset
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import _to_dictionary
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import Variable
+
+
+def _get_all_named_dimensions(dataset: Dataset) -> dict[str, NamedDimension]:
+    all_named_dims: dict[str, NamedDimension] = {}
+    for v in dataset.variables:
+        if v.dimensions is not None:
+            for d in v.dimensions:
+                if isinstance(d, NamedDimension):
+                    all_named_dims[d.name] = d
+                else:
+                    # Skip, if this is a named reference
+                    # This should not be ever a case for the dataset generated with the dataset builder
+                    warnings.warn(
+                        f"Unsupported dimension type: {type(d)} in variable {v.name}. "
+                        "Expected NamedDimension."
+                    )
+                    pass
+    return all_named_dims
+
+def _get_all_coordinates(dataset: Dataset) -> dict[str, Coordinate]:
+    all_coords: dict[str, Coordinate] = {}
+    for v in dataset.variables:
+        if v.coordinates is not None:
+            for c in v.coordinates:
+                if isinstance(c, Coordinate) and c.name not in all_coords:
+                    all_coords[c.name] = c
+    return all_coords
+
+def _get_dimension_names(var: Variable) -> list[str]:
+    dim_names: list[str] = []
+    if var.dimensions is not None:
+        for d in var.dimensions:
+            if isinstance(d, NamedDimension):
+                dim_names.append(d.name)
+            elif isinstance(d, str):
+                # This should not be ever a case for the dataset generated with the dataset builder
+                warnings.warn(f"Unsupported dimension type: 'str' in variable {var.name}. "
+                        "Expected NamedDimension."
+                    )
+                dim_names.append(d)
+            else:
+                err = f"Unsupported dimension type: {type(d)} in variable {var.name}"
+                raise TypeError(err)
+    return dim_names
+ 
+def _get_coord_names(var: Variable) -> list[str]:
+    coord_names: list[str] = []
+    if var.coordinates is not None:
+        for c in var.coordinates:
+            if isinstance(c, Coordinate):
+                coord_names.append(c.name)
+            elif isinstance(c, str):
+                coord_names.append(c)
+            else:
+                err = f"Unsupported coordinate type: {type(c)} in variable {var.name}"
+                raise TypeError(err)
+    return coord_names
+
+def _get_np_datatype(var: Variable) -> np.dtype:
+    data_type = var.data_type
+    if isinstance(data_type, ScalarType):
+        return np.dtype(data_type.value)
+    elif isinstance(data_type, StructuredType):
+        return np.dtype([(f.name, f.format.value) for f in data_type.fields])
+    else:
+        raise TypeError(f"Unsupported data_type: {data_type}")
+
+def _get_zarr_shape(var: Variable) -> tuple[int, ...]:
+    # NOTE: This assumes that the variable dimensions are all NamedDimension
+    return tuple(dim.size for dim in var.dimensions)
+
+def _get_zarr_chunks(var: Variable) -> tuple[int, ...]:
+    """Get the chunk shape for a variable, defaulting to its shape if no chunk grid is defined."""
+    if var.metadata is not None and var.metadata.chunk_grid is not None:
+        return var.metadata.chunk_grid.configuration.chunk_shape
+    else:
+        # Default to full shape if no chunk grid is defined
+        return _get_zarr_shape(var)
+
+def to_xarray_dataset(ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
+    """Build an MDIO dataset with correct dimensions and dtypes.
+
+    This internal function constructs the underlying data structure for an MDIO dataset,
+    handling dimension mapping, data types, and metadata organization.
+
+    Args:
+        mdio_ds: The source MDIO dataset to construct from.
+
+    Returns:
+        The constructed dataset with proper MDIO structure and metadata.
+
+    Raises:
+        TypeError: If an unsupported data type is encountered.
+    """
+
+    # See the xarray tutorial for more details on how to create datasets:
+    # https://tutorial.xarray.dev/fundamentals/01.1_creating_data_structures.html   
+
+    # all_dims = _get_all_named_dimensions(ds)
+    # all_coords = _get_all_coordinates(ds)
+
+    # Build all variables
+    data_arrays: dict[str, xr.DataArray] = {}
+    for v in ds.variables:
+
+        # Use dask array instead of numpy array for lazy evaluation
+        shape = _get_zarr_shape(v)
+        dtype = _get_np_datatype(v)
+        chunks = _get_zarr_chunks(v)
+        arr = dask.array.zeros(shape, dtype=dtype, chunks=chunks)
+
+        # Create a DataArray for the variable. We will set coords in the second pass
+        dim_names = _get_dimension_names(v)
+        data_array = xr.DataArray(arr, dims=dim_names) 
+
+        # https://docs.xarray.dev/en/stable/internals/zarr-encoding-spec.html#zarr-encoding
+        # If you don't explicitly specify a compressor when creating a Zarr array, Z
+        # arr will use a default compressor based on the Zarr format version and the data type of your array. 
+        # Zarr V2 (Default is Blosc)
+        # data_array.encoding.compressor = None
+        #TODO: beging the par that does not work
+        data_array.encoding["fill_value"] = 0.0
+        data_array.encoding["dimension_separator"] = "/" # Does not work
+        if v.compressor is not None:
+            compressor = _to_dictionary(v.compressor)
+            data_array.encoding["compressor"] = compressor
+        else:
+            data_array.encoding["compressor"] = None
+        #TODO: end the part that does not work
+
+        # Add array attributes
+        if v.metadata is not None:
+            meta_dict = _to_dictionary(v.metadata)
+            # Exclude chunk_grid
+            del meta_dict["chunkGrid"]  
+            # Remove empty attributes
+            meta_dict = {k: v for k, v in meta_dict.items() if v is not None}
+            # Add metadata to the data array attributes
+            data_array.attrs.update(meta_dict)
+            pass
+        if v.long_name:
+            data_array.attrs["long_name"] = v.long_name
+
+        # Let's store the data array for the second pass
+        data_arrays[v.name] = data_array
+
+    # Add non-dimension coordinates to the data arrays
+    for v in ds.variables:
+        da = data_arrays[v.name]
+        non_dim_coords_names = set(_get_coord_names(v)) - set(_get_dimension_names(v)) - {v.name}
+        # Create a populate a dictionary {coord_name: DataArray for the coordinate}
+        non_dim_coords_dict : dict[str, xr.DataArray] = {} 
+        for name in non_dim_coords_names:
+            non_dim_coords_dict[name] = data_arrays[name]
+        if non_dim_coords_dict:
+            # NOTE: here is a gotcha: assign_coords() does not update in-place, 
+            # but returns an updated instance!
+            data_arrays[v.name] = da.assign_coords(non_dim_coords_dict)
+            pass
+
+    # Now let's create a dataset with all data arrays
+    xr_ds = xr.Dataset(data_arrays)
+    # Attach dataset metadata
+    if ds.metadata is not None:
+        xr_ds.attrs["apiVersion"] = ds.metadata.api_version
+        xr_ds.attrs["createdOn"] = str(ds.metadata.created_on)
+        xr_ds.attrs["name"] = ds.metadata.name
+        if ds.metadata.attributes:
+            xr_ds.attrs["attributes"] = ds.metadata.attributes
+
+    return xr_ds
+
+
+def to_zarr(dataset: xr.Dataset,
+    store: str | None = None,
+    *args: str | int | float | bool,
+    **kwargs: Mapping[str, str | int | float | bool],
+) -> None:
+    """Alias for `.to_zarr()`."""
+    # Ensure zarr_format=2 by default unless explicitly overridden
+    zarr_format = kwargs.get("zarr_format", 2)
+    if zarr_format != 2:  # noqa: PLR2004
+        msg = "MDIO only supports zarr_format=2"
+        raise ValueError(msg)
+
+    # ds.to_zarr("foo.zarr", consolidated=False, encoding={"foo": {"compressors": [compressor]}})
+    # Define compressor
+    # compressor = zarr.Blosc(cname="zstd", clevel=5, shuffle=2)
+    # # Define encoding
+    # encoding = {
+    #     "foo": {"compressor": compressor},
+    #     "bar": {"compressor": compressor},
+    # }
+    # kwargs["encoding"] = encoding
+    encoding = {}
+    for key in dataset.data_vars.keys():
+        c = dataset[key].encoding.get("compressors", None)
+        encoding[key] = {"compressors": c}
+    kwargs["encoding"] = encoding
+
+    kwargs["zarr_format"] = zarr_format
+
+
+
+
+    return dataset.to_zarr(*args, store=store, **kwargs)
+
+# https://docs.xarray.dev/en/stable/user-guide/io.html
+# ds.to_zarr("path/to/directory.zarr", zarr_format=2, consolidated=False)
\ No newline at end of file
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index 2058bdd54..8a01a9663 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -138,6 +138,128 @@ def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
     return list(all_coords.values())
 
 
+def make_campos_3d_acceptance_dataset() -> Dataset:
+    """Create in-memory campos_3d dataset."""
+    ds = MDIODatasetBuilder(
+        "campos_3d",
+        attributes=UserAttributes(
+            attributes={
+                "textHeader": [
+                    "C01 .......................... ",
+                    "C02 .......................... ",
+                    "C03 .......................... ",
+                ],
+                "foo": "bar",
+            }
+        ),
+    )
+
+    # Add dimensions
+    ds.add_dimension("inline", 256)
+    ds.add_dimension("crossline", 512)
+    ds.add_dimension("depth", 384) # data_type=ScalarType.UINT32, LengthUnitEnum.METER
+    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
+    ds.add_coordinate(
+        "depth",
+        dimensions=["depth"],
+        data_type=ScalarType.UINT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+    # Add coordinates
+    ds.add_coordinate(
+        "cdp-x",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+    ds.add_coordinate(
+        "cdp-y",
+        dimensions=["inline", "crossline"],
+        data_type=ScalarType.FLOAT32,
+        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
+    )
+
+    # Add image variable
+    ds.add_variable(
+        name="image",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
+            ),
+            StatisticsMetadata(
+                stats_v1=SummaryStatistics(
+                    count=100,
+                    sum=1215.1,
+                    sumSquares=125.12,
+                    min=5.61,
+                    max=10.84,
+                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
+                )
+            ),
+            UserAttributes(attributes={"fizz": "buzz"}),
+        ],
+    )
+    # Add velocity variable
+    ds.add_variable(
+        name="velocity",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT16,
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
+                )
+            ),
+            AllUnits(units_v1=SpeedUnitModel(speed=SpeedUnitEnum.METER_PER_SECOND)),
+        ],
+    )
+    # Add inline-optimized image variable
+    ds.add_variable(
+        name="image_inline",
+        long_name="inline optimized version of 3d_stack",
+        dimensions=["inline", "crossline", "depth"],
+        data_type=ScalarType.FLOAT32,
+        compressor=Blosc(algorithm="zstd"),
+        coordinates=["cdp-x", "cdp-y"],
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512])
+                )
+            )
+        ],
+    )
+    # Add headers variable with structured dtype
+    ds.add_variable(
+        name="image_headers",
+        dimensions=["inline", "crossline"],
+        data_type=StructuredType(
+            fields=[
+                StructuredField(name="cdp-x", format=ScalarType.INT32),
+                StructuredField(name="cdp-y", format=ScalarType.INT32),
+                StructuredField(name="elevation", format=ScalarType.FLOAT16),
+                StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
+            ]
+        ),
+        metadata_info=[
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[128, 128])
+                )
+            )
+        ],
+        coordinates=["cdp-x", "cdp-y"],
+    )
+    return ds.build()
+
 def make_campos_3d_dataset() -> Dataset:
     """Create in-memory campos_3d dataset."""
     ds = MDIODatasetBuilder(
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 46cb27cd1..20f686024 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -93,7 +93,7 @@ def test_add_coordinate_with_defaults() -> None:
         coords=["cdp"],
         dtype=ScalarType.FLOAT32,
     )
-    assert v.long_name == "'cdp' coordinate variable"  # Default value
+    assert v.long_name is None  # Default value
     assert v.compressor is None  # Default value
     assert v.metadata is None  # Default value
 
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 84abfe3ad..6f46db501 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -2,7 +2,7 @@
 # PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
 # The above erroneous warning is generated for every numerical assert.
 # Thus, disable it for this file
-"""Tests the schema v1 Variable public API."""
+"""Tests the schema v1 dataset_builder.add_variable() public API."""
 
 import pytest
 
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index aa5fad552..832f624c1 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -2,7 +2,7 @@
 # PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
 # The above erroneous warning is generated for every numerical assert.
 # Thus, disable it for this file
-"""Tests the schema v1 dataset_builder.add_coordinate() public API."""
+"""Tests the schema v1 dataset_builder.build() public API."""
 
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.dtype import StructuredField
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
new file mode 100644
index 000000000..ddd43563a
--- /dev/null
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -0,0 +1,60 @@
+# ruff: noqa: PLR2004
+# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
+# The above erroneous warning is generated for every numerical assert.
+# Thus, disable it for this file
+"""Tests the schema v1 dataset_serializer public API."""
+
+import dask
+import xarray as xr
+import numpy as np
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_serializer import to_xarray_dataset, to_zarr
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import SpeedUnitEnum
+
+from .helpers import make_campos_3d_acceptance_dataset, make_campos_3d_dataset
+from .helpers import validate_variable
+
+
+# def test_to_xarray_dataset(capsys) -> None:
+#     """Test building a complete dataset."""
+#     dataset = (
+#         MDIODatasetBuilder("test_dataset")
+#         .add_dimension("inline", 100)
+#         .add_dimension("crossline", 200)
+#         .add_dimension("depth", 300)
+#         .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64)
+#         .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64)
+#         .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+#         .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+#         .add_variable(
+#             "data",
+#             long_name="Test Data",
+#             dimensions=["inline", "crossline", "depth"],
+#             coordinates=["inline", "crossline", "x_coord", "y_coord"],
+#             data_type=ScalarType.FLOAT32,
+#         )
+#         .build()
+#     )
+
+#     # with capsys.disabled():
+#     xds : xr.Dataset = to_xarray_dataset(dataset)
+
+#     to_zarr(xds, f"test-dataset-{xds.attrs["name"]}.zarr", mode="w")
+
+
+def test_campos_3d_acceptance_to_xarray_dataset(capsys) -> None:
+    """Test building a complete dataset."""
+    dataset = make_campos_3d_acceptance_dataset()
+
+
+    xds : xr.Dataset = to_xarray_dataset(dataset)
+
+    # file_name = "XYZ"
+    file_name = f"{xds.attrs['name']}"
+    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")
\ No newline at end of file

From 4b39ffa844367df72e6f9ef2facb4dcd5ea701f0 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Thu, 10 Jul 2025 23:37:17 +0000
Subject: [PATCH 41/56] gitignore

---
 .gitignore | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/.gitignore b/.gitignore
index bfdc38f28..643394a40 100644
--- a/.gitignore
+++ b/.gitignore
@@ -153,3 +153,5 @@ mdio1/*
 pytest-of-*
 tmp
 debugging/*
+
+test-data/*

From cea73086ec1754dfc2a87fc0b768f42767e306b8 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Fri, 11 Jul 2025 20:13:09 +0000
Subject: [PATCH 42/56] to_zarr() fix compression

---
 _dev/DEVELOPERS_NOTES.md                  |  13 +-
 _dev/zmetadata.cpp.json                   | 483 +++++++++-------------
 _dev/zmetadata.python.json                | 473 +++++++++------------
 src/mdio/schemas/v1/dataset_serializer.py | 248 +++++++----
 tests/unit/v1/helpers.py                  |   7 +-
 tests/unit/v1/test_dataset_serializer.py  |  75 ++--
 6 files changed, 592 insertions(+), 707 deletions(-)

diff --git a/_dev/DEVELOPERS_NOTES.md b/_dev/DEVELOPERS_NOTES.md
index 2e4718a4b..8c575025a 100644
--- a/_dev/DEVELOPERS_NOTES.md
+++ b/_dev/DEVELOPERS_NOTES.md
@@ -4,7 +4,12 @@ src/mdio/schemas/v1/dataset_serializer.py
 
 ## Issues encountered
 
-1. Non-zero size of the serialized data files
-2. Not clear how to properly set `compressor`, `dimension_separator`, and `fill_value`
-    * Should `fill_value` be a part f the model?
-3. For image_inline chunks[2] are somehow different?
\ No newline at end of file
+1. FIXED: Non-zero size of the serialized data files
+2. FIXED: Not clear how to properly set `compressor`, `dimension_separator`, and `fill_value`
+3. FIXED: For image_inline chunks[2] are somehow different?
+
+4. `fill_value` for StructuredType is set to null, but "AAAAAAAAAAAAAAAA" is expected
+
+## TO DO:
+* Add more unit tests for internal functions
+* Add a trest comparing expected and actual .zmetadata for the serialized dataset 
diff --git a/_dev/zmetadata.cpp.json b/_dev/zmetadata.cpp.json
index 40a12d6de..394de1a8f 100644
--- a/_dev/zmetadata.cpp.json
+++ b/_dev/zmetadata.cpp.json
@@ -1,294 +1,195 @@
 {
-    "metadata": {
-        ".zattrs": {
-            "apiVersion": "1.0.0",
-            "attributes": {
-                "foo": "bar",
-                "textHeader": [
-                    "C01 .......................... ",
-                    "C02 .......................... ",
-                    "C03 .......................... "
-                ]
-            },
-            "createdOn": "2023-12-12T15:02:06.413469-06:00",
-            "name": "campos_3d"
-        },
-        ".zgroup": {
-            "zarr_format": 2
-        },
-        "cdp-x/.zarray": {
-            "chunks": [
-                256,
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "cdp-x/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "cdp-y/.zarray": {
-            "chunks": [
-                256,
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "cdp-y/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "crossline/.zarray": {
-            "chunks": [
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                512
-            ],
-            "zarr_format": 2
-        },
-        "crossline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "crossline"
-            ]
-        },
-        "depth/.zarray": {
-            "chunks": [
-                384
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                384
-            ],
-            "zarr_format": 2
-        },
-        "depth/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "depth"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "image/.zarray": {
-            "chunks": [
-                128,
-                128,
-                128
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "zstd",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dimension_separator": "/",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "image/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "attributes": {
-                "fizz": "buzz"
-            },
-            "coordinates": "cdp-x cdp-y",
-            "statsV1": {
-                "count": 100,
-                "histogram": {
-                    "binCenters": [
-                        1,
-                        2
-                    ],
-                    "counts": [
-                        10,
-                        15
-                    ]
-                },
-                "max": 10.84,
-                "min": 5.61,
-                "sum": 1215.1,
-                "sumSquares": 125.12
-            }
-        },
-        "image_headers/.zarray": {
-            "chunks": [
-                128,
-                128
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": [
-                [
-                    "cdp-x",
-                    "<i4"
-                ],
-                [
-                    "cdp-y",
-                    "<i4"
-                ],
-                [
-                    "elevation",
-                    "<f2"
-                ],
-                [
-                    "some_scalar",
-                    "<f2"
-                ]
-            ],
-            "fill_value": "AAAAAAAAAAAAAAAA",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "image_headers/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "coordinates": "cdp-x cdp-y"
-        },
-        "image_inline/.zarray": {
-            "chunks": [
-                4,
-                512,
-                512
-            ],
-            "compressor": {
-                "blocksize": 0,
-                "clevel": 5,
-                "cname": "zstd",
-                "id": "blosc",
-                "shuffle": 1
-            },
-            "dimension_separator": "/",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "image_inline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "coordinates": "cdp-x cdp-y",
-            "long_name": "inline optimized version of 3d_stack"
-        },
-        "inline/.zarray": {
-            "chunks": [
-                256
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256
-            ],
-            "zarr_format": 2
-        },
-        "inline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline"
-            ]
-        },
-        "velocity/.zarray": {
-            "chunks": [
-                128,
-                128,
-                128
-            ],
-            "compressor": null,
-            "dimension_separator": "/",
-            "dtype": "<f2",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "velocity/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "coordinates": "cdp-x cdp-y",
-            "unitsV1": {
-                "speed": "m/s"
-            }
-        }
+  "metadata": {
+    ".zattrs": {
+      "apiVersion": "1.0.0",
+      "attributes": {
+        "foo": "bar",
+        "textHeader": [
+          "C01 .......................... ",
+          "C02 .......................... ",
+          "C03 .......................... "
+        ]
+      },
+      "createdOn": "2023-12-12T15:02:06.413469-06:00",
+      "name": "campos_3d"
+    },
+    ".zgroup": {
+      "zarr_format": 2
+    },
+    "cdp-x/.zarray": {
+      "chunks": [256, 512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "cdp-x/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "cdp-y/.zarray": {
+      "chunks": [256, 512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "cdp-y/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "crossline/.zarray": {
+      "chunks": [512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [512],
+      "zarr_format": 2
+    },
+    "crossline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["crossline"]
+    },
+    "depth/.zarray": {
+      "chunks": [384],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [384],
+      "zarr_format": 2
+    },
+    "depth/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["depth"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "image/.zarray": {
+      "chunks": [128, 128, 128],
+      "compressor": {
+        "blocksize": 0,
+        "clevel": 5,
+        "cname": "zstd",
+        "id": "blosc",
+        "shuffle": 1
+      },
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
+    },
+    "image/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "attributes": {
+        "fizz": "buzz"
+      },
+      "coordinates": "cdp-x cdp-y",
+      "statsV1": {
+        "count": 100,
+        "histogram": {
+          "binCenters": [1, 2],
+          "counts": [10, 15]
+        },
+        "max": 10.84,
+        "min": 5.61,
+        "sum": 1215.1,
+        "sumSquares": 125.12
+      }
+    },
+    "image_headers/.zarray": {
+      "chunks": [128, 128],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": [
+        ["cdp-x", "<i4"],
+        ["cdp-y", "<i4"],
+        ["elevation", "<f2"],
+        ["some_scalar", "<f2"]
+      ],
+      "fill_value": "AAAAAAAAAAAAAAAA",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "image_headers/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "coordinates": "cdp-x cdp-y"
+    },
+    "image_inline/.zarray": {
+      "chunks": [4, 512, 512],
+      "compressor": {
+        "blocksize": 0,
+        "clevel": 5,
+        "cname": "zstd",
+        "id": "blosc",
+        "shuffle": 1
+      },
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
+    },
+    "image_inline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "coordinates": "cdp-x cdp-y",
+      "long_name": "inline optimized version of 3d_stack"
+    },
+    "inline/.zarray": {
+      "chunks": [256],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [256],
+      "zarr_format": 2
+    },
+    "inline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline"]
+    },
+    "velocity/.zarray": {
+      "chunks": [128, 128, 128],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f2",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
     },
-    "zarr_consolidated_format": 1
+    "velocity/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "coordinates": "cdp-x cdp-y",
+      "unitsV1": {
+        "speed": "m/s"
+      }
+    }
+  },
+  "zarr_consolidated_format": 1
 }
diff --git a/_dev/zmetadata.python.json b/_dev/zmetadata.python.json
index ce52cec38..56cea2ac5 100644
--- a/_dev/zmetadata.python.json
+++ b/_dev/zmetadata.python.json
@@ -1,282 +1,195 @@
 {
-    "metadata": {
-        ".zattrs": {
-            "apiVersion": "1.0.0a1",
-            "attributes": {
-                "foo": "bar",
-                "textHeader": [
-                    "C01 .......................... ",
-                    "C02 .......................... ",
-                    "C03 .......................... "
-                ]
-            },
-            "createdOn": "2025-07-10 23:17:20.653097+00:00",
-            "name": "campos_3d"
-        },
-        ".zgroup": {
-            "zarr_format": 2
-        },
-        "cdp-x/.zarray": {
-            "chunks": [
-                256,
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "cdp-x/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "cdp-y/.zarray": {
-            "chunks": [
-                256,
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "cdp-y/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "crossline/.zarray": {
-            "chunks": [
-                512
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                512
-            ],
-            "zarr_format": 2
-        },
-        "crossline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "crossline"
-            ]
-        },
-        "depth/.zarray": {
-            "chunks": [
-                384
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                384
-            ],
-            "zarr_format": 2
-        },
-        "depth/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "depth"
-            ],
-            "unitsV1": {
-                "length": "m"
-            }
-        },
-        "image/.zarray": {
-            "chunks": [
-                128,
-                128,
-                128
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "image/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "attributes": {
-                "fizz": "buzz"
-            },
-            "coordinates": "cdp-x cdp-y",
-            "statsV1": {
-                "count": 100,
-                "histogram": {
-                    "binCenters": [
-                        1,
-                        2
-                    ],
-                    "counts": [
-                        10,
-                        15
-                    ]
-                },
-                "max": 10.84,
-                "min": 5.61,
-                "sum": 1215.1,
-                "sumSquares": 125.12
-            }
-        },
-        "image_headers/.zarray": {
-            "chunks": [
-                128,
-                128
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": [
-                [
-                    "cdp-x",
-                    "<i4"
-                ],
-                [
-                    "cdp-y",
-                    "<i4"
-                ],
-                [
-                    "elevation",
-                    "<f2"
-                ],
-                [
-                    "some_scalar",
-                    "<f2"
-                ]
-            ],
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512
-            ],
-            "zarr_format": 2
-        },
-        "image_headers/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline"
-            ],
-            "coordinates": "cdp-x cdp-y"
-        },
-        "image_inline/.zarray": {
-            "chunks": [
-                4,
-                512,
-                384
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<f4",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "image_inline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "coordinates": "cdp-x cdp-y",
-            "long_name": "inline optimized version of 3d_stack"
-        },
-        "inline/.zarray": {
-            "chunks": [
-                256
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<u4",
-            "fill_value": null,
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256
-            ],
-            "zarr_format": 2
-        },
-        "inline/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline"
-            ]
-        },
-        "velocity/.zarray": {
-            "chunks": [
-                128,
-                128,
-                128
-            ],
-            "compressor": null,
-            "dimension_separator": ".",
-            "dtype": "<f2",
-            "fill_value": "NaN",
-            "filters": null,
-            "order": "C",
-            "shape": [
-                256,
-                512,
-                384
-            ],
-            "zarr_format": 2
-        },
-        "velocity/.zattrs": {
-            "_ARRAY_DIMENSIONS": [
-                "inline",
-                "crossline",
-                "depth"
-            ],
-            "coordinates": "cdp-x cdp-y",
-            "unitsV1": {
-                "speed": "m/s"
-            }
-        }
+  "metadata": {
+    ".zattrs": {
+      "apiVersion": "1.0.0a1",
+      "attributes": {
+        "foo": "bar",
+        "textHeader": [
+          "C01 .......................... ",
+          "C02 .......................... ",
+          "C03 .......................... "
+        ]
+      },
+      "createdOn": "2025-07-11 19:53:51.363436+00:00",
+      "name": "campos_3d"
+    },
+    ".zgroup": {
+      "zarr_format": 2
+    },
+    "cdp-x/.zarray": {
+      "chunks": [256, 512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "cdp-x/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "cdp-y/.zarray": {
+      "chunks": [256, 512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "cdp-y/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "crossline/.zarray": {
+      "chunks": [512],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [512],
+      "zarr_format": 2
+    },
+    "crossline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["crossline"]
+    },
+    "depth/.zarray": {
+      "chunks": [384],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [384],
+      "zarr_format": 2
+    },
+    "depth/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["depth"],
+      "unitsV1": {
+        "length": "m"
+      }
+    },
+    "image/.zarray": {
+      "chunks": [128, 128, 128],
+      "compressor": {
+        "blocksize": 0,
+        "clevel": 5,
+        "cname": "zstd",
+        "id": "blosc",
+        "shuffle": 1
+      },
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
+    },
+    "image/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "attributes": {
+        "fizz": "buzz"
+      },
+      "coordinates": "cdp-x cdp-y",
+      "statsV1": {
+        "count": 100,
+        "histogram": {
+          "binCenters": [1, 2],
+          "counts": [10, 15]
+        },
+        "max": 10.84,
+        "min": 5.61,
+        "sum": 1215.1,
+        "sumSquares": 125.12
+      }
+    },
+    "image_headers/.zarray": {
+      "chunks": [128, 128],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": [
+        ["cdp-x", "<i4"],
+        ["cdp-y", "<i4"],
+        ["elevation", "<f2"],
+        ["some_scalar", "<f2"]
+      ],
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512],
+      "zarr_format": 2
+    },
+    "image_headers/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
+      "coordinates": "cdp-x cdp-y"
+    },
+    "image_inline/.zarray": {
+      "chunks": [4, 512, 512],
+      "compressor": {
+        "blocksize": 0,
+        "clevel": 5,
+        "cname": "zstd",
+        "id": "blosc",
+        "shuffle": 1
+      },
+      "dimension_separator": "/",
+      "dtype": "<f4",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
+    },
+    "image_inline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "coordinates": "cdp-x cdp-y",
+      "long_name": "inline optimized version of 3d_stack"
+    },
+    "inline/.zarray": {
+      "chunks": [256],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<u4",
+      "fill_value": null,
+      "filters": null,
+      "order": "C",
+      "shape": [256],
+      "zarr_format": 2
+    },
+    "inline/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline"]
+    },
+    "velocity/.zarray": {
+      "chunks": [128, 128, 128],
+      "compressor": null,
+      "dimension_separator": "/",
+      "dtype": "<f2",
+      "fill_value": "NaN",
+      "filters": null,
+      "order": "C",
+      "shape": [256, 512, 384],
+      "zarr_format": 2
     },
-    "zarr_consolidated_format": 1
-}
\ No newline at end of file
+    "velocity/.zattrs": {
+      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
+      "coordinates": "cdp-x cdp-y",
+      "unitsV1": {
+        "speed": "m/s"
+      }
+    }
+  },
+  "zarr_consolidated_format": 1
+}
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index 1b3fbabd6..1592e93ba 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -1,14 +1,26 @@
-from typing import Mapping
 import warnings
+from collections.abc import Mapping
 
-import dask
-import xarray as xr
+import dask as dask
+import numcodecs as numcodecs
 import numpy as np
-import zarr
-
+import xarray as xr
+import zarr as zarr
+
+try:
+    # zfpy is an optional dependency for ZFP compression
+    # It is not installed by default, so we check for its presence and import it only if available.
+    import zfpy as zfpy
+    from zfpy import ZFPY as zfpy_ZFPY
+except ImportError:
+    zfpy = None
+    zfpy_ZFPY = None
+
+from mdio.schemas.compressors import ZFP as mdio_ZFP
+from mdio.schemas.compressors import Blosc as mdio_Blosc
 from mdio.schemas.dimension import NamedDimension
-from mdio.schemas.dtype import ScalarType, StructuredType
-from mdio.schemas.v1 import dataset
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
 from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset_builder import _to_dictionary
 from mdio.schemas.v1.variable import Coordinate
@@ -29,9 +41,9 @@ def _get_all_named_dimensions(dataset: Dataset) -> dict[str, NamedDimension]:
                         f"Unsupported dimension type: {type(d)} in variable {v.name}. "
                         "Expected NamedDimension."
                     )
-                    pass
     return all_named_dims
 
+
 def _get_all_coordinates(dataset: Dataset) -> dict[str, Coordinate]:
     all_coords: dict[str, Coordinate] = {}
     for v in dataset.variables:
@@ -41,6 +53,7 @@ def _get_all_coordinates(dataset: Dataset) -> dict[str, Coordinate]:
                     all_coords[c.name] = c
     return all_coords
 
+
 def _get_dimension_names(var: Variable) -> list[str]:
     dim_names: list[str] = []
     if var.dimensions is not None:
@@ -49,15 +62,17 @@ def _get_dimension_names(var: Variable) -> list[str]:
                 dim_names.append(d.name)
             elif isinstance(d, str):
                 # This should not be ever a case for the dataset generated with the dataset builder
-                warnings.warn(f"Unsupported dimension type: 'str' in variable {var.name}. "
-                        "Expected NamedDimension."
-                    )
+                warnings.warn(
+                    f"Unsupported dimension type: 'str' in variable {var.name}. "
+                    "Expected NamedDimension."
+                )
                 dim_names.append(d)
             else:
                 err = f"Unsupported dimension type: {type(d)} in variable {var.name}"
                 raise TypeError(err)
     return dim_names
- 
+
+
 def _get_coord_names(var: Variable) -> list[str]:
     coord_names: list[str] = []
     if var.coordinates is not None:
@@ -71,31 +86,99 @@ def _get_coord_names(var: Variable) -> list[str]:
                 raise TypeError(err)
     return coord_names
 
+
 def _get_np_datatype(var: Variable) -> np.dtype:
     data_type = var.data_type
     if isinstance(data_type, ScalarType):
         return np.dtype(data_type.value)
-    elif isinstance(data_type, StructuredType):
+    if isinstance(data_type, StructuredType):
         return np.dtype([(f.name, f.format.value) for f in data_type.fields])
-    else:
-        raise TypeError(f"Unsupported data_type: {data_type}")
+    raise TypeError(f"Unsupported data_type: {data_type}")
+
 
 def _get_zarr_shape(var: Variable) -> tuple[int, ...]:
     # NOTE: This assumes that the variable dimensions are all NamedDimension
     return tuple(dim.size for dim in var.dimensions)
 
+
 def _get_zarr_chunks(var: Variable) -> tuple[int, ...]:
     """Get the chunk shape for a variable, defaulting to its shape if no chunk grid is defined."""
     if var.metadata is not None and var.metadata.chunk_grid is not None:
         return var.metadata.chunk_grid.configuration.chunk_shape
-    else:
-        # Default to full shape if no chunk grid is defined
-        return _get_zarr_shape(var)
+    # Default to full shape if no chunk grid is defined
+    return _get_zarr_shape(var)
+
+
+def _convert_compressor(
+    compressor: mdio_Blosc | mdio_ZFP | None,
+) -> numcodecs.Blosc | zfpy_ZFPY | None:
+    """Convert a compressor to a numcodecs compatible format."""
+    if compressor is None:
+        return None
+
+    if isinstance(compressor, mdio_Blosc):
+        return numcodecs.Blosc(
+            cname=compressor.algorithm.value,
+            clevel=compressor.level,
+            shuffle=compressor.shuffle.value,
+            blocksize=compressor.blocksize if compressor.blocksize > 0 else 0,
+        )
+
+    if isinstance(compressor, mdio_ZFP):
+        if zfpy_ZFPY is None:
+            msg = "zfpy and numcodecs are required to use ZFP compression"
+            raise ImportError(msg)
+        return zfpy_ZFPY(
+            mode=compressor.mode.value,
+            tolerance=compressor.tolerance,
+            rate=compressor.rate,
+            precision=compressor.precision,
+        )
+
+    msg = f"Unsupported compressor model: {type(compressor)}"
+    raise TypeError(msg)
+
+
+# Do we already have it somewhere in the codebase? I could not find it.
+fill_value_map = {
+    ScalarType.BOOL: None,
+    ScalarType.FLOAT16: np.nan,
+    ScalarType.FLOAT32: np.nan,
+    ScalarType.FLOAT64: np.nan,
+    ScalarType.UINT8: 2**8 - 1,  # Max value for uint8
+    ScalarType.UINT16: 2**16 - 1,  # Max value for uint16
+    ScalarType.UINT32: 2**32 - 1,  # Max value for uint32
+    ScalarType.UINT64: 2**64 - 1,  # Max value for uint64
+    ScalarType.INT8: 2**7 - 1,  # Max value for int8
+    ScalarType.INT16: 2**15 - 1,  # Max value for int16
+    ScalarType.INT32: 2**31 - 1,  # Max value for int32
+    ScalarType.INT64: 2**63 - 1,  # Max value for int64
+    ScalarType.COMPLEX64: complex(np.nan, np.nan),
+    ScalarType.COMPLEX128: complex(np.nan, np.nan),
+    ScalarType.COMPLEX256: complex(np.nan, np.nan),
+}
+
+
+def get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
+    """Get the fill value for a given data type.
+    The Zarr fill_value is a scalar value providing the default value to use for
+    uninitialized portions of the array, or null if no fill_value is to be used
+    https://zarr-specs.readthedocs.io/en/latest/v2/v2.0.html
+    """
+    if isinstance(data_type, ScalarType):
+        return fill_value_map.get(data_type)
+    if isinstance(data_type, StructuredType):
+        return "AAAAAAAAAAAAAAAA"  # BUG: this does not work!!!
+    if isinstance(data_type, str):
+        return ""
+    # If we do not have a fill value for this type, use None
+    return None
+
 
-def to_xarray_dataset(ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
-    """Build an MDIO dataset with correct dimensions and dtypes.
+def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
+    """Build an XArray dataset with correct dimensions and dtypes.
 
-    This internal function constructs the underlying data structure for an MDIO dataset,
+    This function constructs the underlying data structure for an XArray dataset,
     handling dimension mapping, data types, and metadata organization.
 
     Args:
@@ -107,17 +190,15 @@ def to_xarray_dataset(ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
     Raises:
         TypeError: If an unsupported data type is encountered.
     """
-
     # See the xarray tutorial for more details on how to create datasets:
-    # https://tutorial.xarray.dev/fundamentals/01.1_creating_data_structures.html   
+    # https://tutorial.xarray.dev/fundamentals/01.1_creating_data_structures.html
 
     # all_dims = _get_all_named_dimensions(ds)
     # all_coords = _get_all_coordinates(ds)
 
-    # Build all variables
+    # First pass: Build all variables
     data_arrays: dict[str, xr.DataArray] = {}
-    for v in ds.variables:
-
+    for v in mdio_ds.variables:
         # Use dask array instead of numpy array for lazy evaluation
         shape = _get_zarr_shape(v)
         dtype = _get_np_datatype(v)
@@ -126,99 +207,92 @@ def to_xarray_dataset(ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
 
         # Create a DataArray for the variable. We will set coords in the second pass
         dim_names = _get_dimension_names(v)
-        data_array = xr.DataArray(arr, dims=dim_names) 
-
-        # https://docs.xarray.dev/en/stable/internals/zarr-encoding-spec.html#zarr-encoding
-        # If you don't explicitly specify a compressor when creating a Zarr array, Z
-        # arr will use a default compressor based on the Zarr format version and the data type of your array. 
-        # Zarr V2 (Default is Blosc)
-        # data_array.encoding.compressor = None
-        #TODO: beging the par that does not work
-        data_array.encoding["fill_value"] = 0.0
-        data_array.encoding["dimension_separator"] = "/" # Does not work
-        if v.compressor is not None:
-            compressor = _to_dictionary(v.compressor)
-            data_array.encoding["compressor"] = compressor
-        else:
-            data_array.encoding["compressor"] = None
-        #TODO: end the part that does not work
+        data_array = xr.DataArray(arr, dims=dim_names)
 
         # Add array attributes
         if v.metadata is not None:
             meta_dict = _to_dictionary(v.metadata)
             # Exclude chunk_grid
-            del meta_dict["chunkGrid"]  
+            del meta_dict["chunkGrid"]
             # Remove empty attributes
             meta_dict = {k: v for k, v in meta_dict.items() if v is not None}
             # Add metadata to the data array attributes
             data_array.attrs.update(meta_dict)
-            pass
         if v.long_name:
             data_array.attrs["long_name"] = v.long_name
 
+        # Compression:
+        # https://docs.xarray.dev/en/stable/internals/zarr-encoding-spec.html#zarr-encoding
+        # If you don't explicitly specify a compressor when creating a Zarr array, Z
+        # arr will use a default compressor based on the Zarr format version and the data type of your array.
+        # Zarr V2 (Default is Blosc).
+        # Thus, if there is no compressor, we will explicitly set "compressor" to None.
+        #
+        # Create a custom chunk key encoding with "/" as separator
+        from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
+        chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
+        encoding = {
+            "fill_value": get_fill_value(v.data_type),
+            "chunks": chunks,
+            "chunk_key_encoding": chunk_key_encoding,
+            # I was hoping the following would work, but it does not.
+            # I see:
+            #    >_compressor = parse_compressor(compressor[0])
+            #    > return numcodecs.get_codec(data)
+            #    E - numcodecs.errors.UnknownCodecError: codec not available: 'None'"
+            # Example: https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#compressors
+            # from zarr.codecs import BloscCodec
+            # compressor = BloscCodec(cname="zstd", clevel=3, shuffle="shuffle")
+            #
+            # "compressor": _to_dictionary(v.compressor)
+            # Thus, we will call the conversion function:
+            "compressor": _convert_compressor(v.compressor),
+        }
+        data_array.encoding = encoding
+
         # Let's store the data array for the second pass
         data_arrays[v.name] = data_array
 
-    # Add non-dimension coordinates to the data arrays
-    for v in ds.variables:
+    # Second pass: Add non-dimension coordinates to the data arrays
+    for v in mdio_ds.variables:
         da = data_arrays[v.name]
         non_dim_coords_names = set(_get_coord_names(v)) - set(_get_dimension_names(v)) - {v.name}
-        # Create a populate a dictionary {coord_name: DataArray for the coordinate}
-        non_dim_coords_dict : dict[str, xr.DataArray] = {} 
+        # Create and populate a dictionary {coord_name: DataArray for the coordinate}
+        non_dim_coords_dict: dict[str, xr.DataArray] = {}
         for name in non_dim_coords_names:
             non_dim_coords_dict[name] = data_arrays[name]
         if non_dim_coords_dict:
-            # NOTE: here is a gotcha: assign_coords() does not update in-place, 
+            # NOTE: here is a gotcha: assign_coords() does not update in-place,
             # but returns an updated instance!
             data_arrays[v.name] = da.assign_coords(non_dim_coords_dict)
-            pass
 
     # Now let's create a dataset with all data arrays
     xr_ds = xr.Dataset(data_arrays)
     # Attach dataset metadata
-    if ds.metadata is not None:
-        xr_ds.attrs["apiVersion"] = ds.metadata.api_version
-        xr_ds.attrs["createdOn"] = str(ds.metadata.created_on)
-        xr_ds.attrs["name"] = ds.metadata.name
-        if ds.metadata.attributes:
-            xr_ds.attrs["attributes"] = ds.metadata.attributes
+    if mdio_ds.metadata is not None:
+        xr_ds.attrs["apiVersion"] = mdio_ds.metadata.api_version
+        xr_ds.attrs["createdOn"] = str(mdio_ds.metadata.created_on)
+        xr_ds.attrs["name"] = mdio_ds.metadata.name
+        if mdio_ds.metadata.attributes:
+            xr_ds.attrs["attributes"] = mdio_ds.metadata.attributes
 
     return xr_ds
 
 
-def to_zarr(dataset: xr.Dataset,
+def to_zarr(
+    dataset: xr.Dataset,
     store: str | None = None,
     *args: str | int | float | bool,
     **kwargs: Mapping[str, str | int | float | bool],
 ) -> None:
-    """Alias for `.to_zarr()`."""
-    # Ensure zarr_format=2 by default unless explicitly overridden
-    zarr_format = kwargs.get("zarr_format", 2)
-    if zarr_format != 2:  # noqa: PLR2004
-        msg = "MDIO only supports zarr_format=2"
-        raise ValueError(msg)
-
-    # ds.to_zarr("foo.zarr", consolidated=False, encoding={"foo": {"compressors": [compressor]}})
-    # Define compressor
-    # compressor = zarr.Blosc(cname="zstd", clevel=5, shuffle=2)
-    # # Define encoding
-    # encoding = {
-    #     "foo": {"compressor": compressor},
-    #     "bar": {"compressor": compressor},
-    # }
-    # kwargs["encoding"] = encoding
-    encoding = {}
-    for key in dataset.data_vars.keys():
-        c = dataset[key].encoding.get("compressors", None)
-        encoding[key] = {"compressors": c}
-    kwargs["encoding"] = encoding
-
-    kwargs["zarr_format"] = zarr_format
-
-
-
-
+    """Write an XArray dataset to Zarr format."""
+    # MDIO only supports zarr_format=2
+    kwargs["zarr_format"] = 2
+    # compute: default: True) – If True write array data immediately,
+    # otherwise return a dask.delayed.Delayed object that can be computed
+    # to write array data later.
+    # *** Metadata is always updated eagerly. ***
+    kwargs["compute"] = False
+    # https://docs.xarray.dev/en/stable/user-guide/io.html
+    # https://docs.xarray.dev/en/latest/generated/xarray.DataArray.to_zarr.html
     return dataset.to_zarr(*args, store=store, **kwargs)
-
-# https://docs.xarray.dev/en/stable/user-guide/io.html
-# ds.to_zarr("path/to/directory.zarr", zarr_format=2, consolidated=False)
\ No newline at end of file
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index 8a01a9663..336f2f0d6 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -157,7 +157,7 @@ def make_campos_3d_acceptance_dataset() -> Dataset:
     # Add dimensions
     ds.add_dimension("inline", 256)
     ds.add_dimension("crossline", 512)
-    ds.add_dimension("depth", 384) # data_type=ScalarType.UINT32, LengthUnitEnum.METER
+    ds.add_dimension("depth", 384)
     ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
     ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
     ds.add_coordinate(
@@ -251,15 +251,14 @@ def make_campos_3d_acceptance_dataset() -> Dataset:
         ),
         metadata_info=[
             ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128])
-                )
+                chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[128, 128]))
             )
         ],
         coordinates=["cdp-x", "cdp-y"],
     )
     return ds.build()
 
+
 def make_campos_3d_dataset() -> Dataset:
     """Create in-memory campos_3d dataset."""
     ds = MDIODatasetBuilder(
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index ddd43563a..1bee02e3c 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -4,57 +4,50 @@
 # Thus, disable it for this file
 """Tests the schema v1 dataset_serializer public API."""
 
-import dask
 import xarray as xr
-import numpy as np
 
 from mdio.schemas.dtype import ScalarType
-from mdio.schemas.dtype import StructuredField
-from mdio.schemas.dtype import StructuredType
-from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
-from mdio.schemas.v1.dataset_serializer import to_xarray_dataset, to_zarr
-from mdio.schemas.v1.units import LengthUnitEnum
-from mdio.schemas.v1.units import SpeedUnitEnum
-
-from .helpers import make_campos_3d_acceptance_dataset, make_campos_3d_dataset
-from .helpers import validate_variable
-
-
-# def test_to_xarray_dataset(capsys) -> None:
-#     """Test building a complete dataset."""
-#     dataset = (
-#         MDIODatasetBuilder("test_dataset")
-#         .add_dimension("inline", 100)
-#         .add_dimension("crossline", 200)
-#         .add_dimension("depth", 300)
-#         .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64)
-#         .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64)
-#         .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-#         .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
-#         .add_variable(
-#             "data",
-#             long_name="Test Data",
-#             dimensions=["inline", "crossline", "depth"],
-#             coordinates=["inline", "crossline", "x_coord", "y_coord"],
-#             data_type=ScalarType.FLOAT32,
-#         )
-#         .build()
-#     )
-
-#     # with capsys.disabled():
-#     xds : xr.Dataset = to_xarray_dataset(dataset)
-
-#     to_zarr(xds, f"test-dataset-{xds.attrs["name"]}.zarr", mode="w")
+from mdio.schemas.v1.dataset_serializer import to_xarray_dataset
+from mdio.schemas.v1.dataset_serializer import to_zarr
+
+from .helpers import make_campos_3d_acceptance_dataset
+
+
+def test_to_xarray_dataset(capsys) -> None:
+    """Test building a complete dataset."""
+    dataset = (
+        MDIODatasetBuilder("test_dataset")
+        .add_dimension("inline", 100)
+        .add_dimension("crossline", 200)
+        .add_dimension("depth", 300)
+        .add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.FLOAT64)
+        .add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.FLOAT64)
+        .add_coordinate("x_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        .add_coordinate("y_coord", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32)
+        .add_variable(
+            "data",
+            long_name="Test Data",
+            dimensions=["inline", "crossline", "depth"],
+            coordinates=["inline", "crossline", "x_coord", "y_coord"],
+            data_type=ScalarType.FLOAT32,
+        )
+        .build()
+    )
+
+    # with capsys.disabled():
+    xds: xr.Dataset = to_xarray_dataset(dataset)
+
+    file_name = "sample_dataset"
+    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")
 
 
 def test_campos_3d_acceptance_to_xarray_dataset(capsys) -> None:
     """Test building a complete dataset."""
     dataset = make_campos_3d_acceptance_dataset()
 
-
-    xds : xr.Dataset = to_xarray_dataset(dataset)
+    xds: xr.Dataset = to_xarray_dataset(dataset)
 
     # file_name = "XYZ"
     file_name = f"{xds.attrs['name']}"
-    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")
\ No newline at end of file
+    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")

From 850135ea3d0f21f9a04b4ede6d7888c46e2e36a1 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Fri, 11 Jul 2025 20:55:45 +0000
Subject: [PATCH 43/56] Fix precommit issues

---
 _dev/DEVELOPERS_NOTES.md                  |  5 +-
 src/mdio/schemas/v1/dataset_serializer.py | 89 ++++++++++-------------
 tests/unit/v1/test_dataset_serializer.py  | 17 ++---
 3 files changed, 50 insertions(+), 61 deletions(-)

diff --git a/_dev/DEVELOPERS_NOTES.md b/_dev/DEVELOPERS_NOTES.md
index 8c575025a..a9df833e0 100644
--- a/_dev/DEVELOPERS_NOTES.md
+++ b/_dev/DEVELOPERS_NOTES.md
@@ -11,5 +11,6 @@ src/mdio/schemas/v1/dataset_serializer.py
 4. `fill_value` for StructuredType is set to null, but "AAAAAAAAAAAAAAAA" is expected
 
 ## TO DO:
-* Add more unit tests for internal functions
-* Add a trest comparing expected and actual .zmetadata for the serialized dataset 
+
+- Add more unit tests for internal functions
+- Add a trest comparing expected and actual .zmetadata for the serialized dataset
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index 1592e93ba..10e9f4628 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -1,22 +1,23 @@
-import warnings
+"""Convert MDIO v1 schema Dataset to Xarray DataSet and write it in Zarr."""
+
 from collections.abc import Mapping
 
-import dask as dask
-import numcodecs as numcodecs
-import numpy as np
-import xarray as xr
-import zarr as zarr
+from dask import array as dask_array
+from numcodecs import Blosc as nc_Blosc
+from numpy import dtype as np_dtype
+from numpy import nan as np_nan
+from xarray import DataArray as xr_DataArray
+from xarray import Dataset as xr_Dataset
+from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
 
 try:
     # zfpy is an optional dependency for ZFP compression
     # It is not installed by default, so we check for its presence and import it only if available.
-    import zfpy as zfpy
-    from zfpy import ZFPY as zfpy_ZFPY
+    from zfpy import ZFPY as zfpy_ZFPY  # noqa: N811
 except ImportError:
-    zfpy = None
-    zfpy_ZFPY = None
+    zfpy_ZFPY = None  # noqa: N816
 
-from mdio.schemas.compressors import ZFP as mdio_ZFP
+from mdio.schemas.compressors import ZFP as mdio_ZFP  # noqa: N811
 from mdio.schemas.compressors import Blosc as mdio_Blosc
 from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import ScalarType
@@ -35,12 +36,8 @@ def _get_all_named_dimensions(dataset: Dataset) -> dict[str, NamedDimension]:
                 if isinstance(d, NamedDimension):
                     all_named_dims[d.name] = d
                 else:
-                    # Skip, if this is a named reference
-                    # This should not be ever a case for the dataset generated with the dataset builder
-                    warnings.warn(
-                        f"Unsupported dimension type: {type(d)} in variable {v.name}. "
-                        "Expected NamedDimension."
-                    )
+                    # Never happens for the dataset generated with the dataset builder
+                    pass
     return all_named_dims
 
 
@@ -61,11 +58,7 @@ def _get_dimension_names(var: Variable) -> list[str]:
             if isinstance(d, NamedDimension):
                 dim_names.append(d.name)
             elif isinstance(d, str):
-                # This should not be ever a case for the dataset generated with the dataset builder
-                warnings.warn(
-                    f"Unsupported dimension type: 'str' in variable {var.name}. "
-                    "Expected NamedDimension."
-                )
+                # Never happens for the dataset generated with the dataset builder
                 dim_names.append(d)
             else:
                 err = f"Unsupported dimension type: {type(d)} in variable {var.name}"
@@ -87,13 +80,14 @@ def _get_coord_names(var: Variable) -> list[str]:
     return coord_names
 
 
-def _get_np_datatype(var: Variable) -> np.dtype:
+def _get_np_datatype(var: Variable) -> np_dtype:
     data_type = var.data_type
     if isinstance(data_type, ScalarType):
-        return np.dtype(data_type.value)
+        return np_dtype(data_type.value)
     if isinstance(data_type, StructuredType):
-        return np.dtype([(f.name, f.format.value) for f in data_type.fields])
-    raise TypeError(f"Unsupported data_type: {data_type}")
+        return np_dtype([(f.name, f.format.value) for f in data_type.fields])
+    err = f"Unsupported data type: {type(data_type)} in variable {var.name}"
+    raise TypeError(err)
 
 
 def _get_zarr_shape(var: Variable) -> tuple[int, ...]:
@@ -111,13 +105,13 @@ def _get_zarr_chunks(var: Variable) -> tuple[int, ...]:
 
 def _convert_compressor(
     compressor: mdio_Blosc | mdio_ZFP | None,
-) -> numcodecs.Blosc | zfpy_ZFPY | None:
+) -> nc_Blosc | zfpy_ZFPY | None:
     """Convert a compressor to a numcodecs compatible format."""
     if compressor is None:
         return None
 
     if isinstance(compressor, mdio_Blosc):
-        return numcodecs.Blosc(
+        return nc_Blosc(
             cname=compressor.algorithm.value,
             clevel=compressor.level,
             shuffle=compressor.shuffle.value,
@@ -142,9 +136,9 @@ def _convert_compressor(
 # Do we already have it somewhere in the codebase? I could not find it.
 fill_value_map = {
     ScalarType.BOOL: None,
-    ScalarType.FLOAT16: np.nan,
-    ScalarType.FLOAT32: np.nan,
-    ScalarType.FLOAT64: np.nan,
+    ScalarType.FLOAT16: np_nan,
+    ScalarType.FLOAT32: np_nan,
+    ScalarType.FLOAT64: np_nan,
     ScalarType.UINT8: 2**8 - 1,  # Max value for uint8
     ScalarType.UINT16: 2**16 - 1,  # Max value for uint16
     ScalarType.UINT32: 2**32 - 1,  # Max value for uint32
@@ -153,14 +147,15 @@ def _convert_compressor(
     ScalarType.INT16: 2**15 - 1,  # Max value for int16
     ScalarType.INT32: 2**31 - 1,  # Max value for int32
     ScalarType.INT64: 2**63 - 1,  # Max value for int64
-    ScalarType.COMPLEX64: complex(np.nan, np.nan),
-    ScalarType.COMPLEX128: complex(np.nan, np.nan),
-    ScalarType.COMPLEX256: complex(np.nan, np.nan),
+    ScalarType.COMPLEX64: complex(np_nan, np_nan),
+    ScalarType.COMPLEX128: complex(np_nan, np_nan),
+    ScalarType.COMPLEX256: complex(np_nan, np_nan),
 }
 
 
-def get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
+def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     """Get the fill value for a given data type.
+
     The Zarr fill_value is a scalar value providing the default value to use for
     uninitialized portions of the array, or null if no fill_value is to be used
     https://zarr-specs.readthedocs.io/en/latest/v2/v2.0.html
@@ -175,7 +170,7 @@ def get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     return None
 
 
-def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
+def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
     """Build an XArray dataset with correct dimensions and dtypes.
 
     This function constructs the underlying data structure for an XArray dataset,
@@ -186,9 +181,6 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
 
     Returns:
         The constructed dataset with proper MDIO structure and metadata.
-
-    Raises:
-        TypeError: If an unsupported data type is encountered.
     """
     # See the xarray tutorial for more details on how to create datasets:
     # https://tutorial.xarray.dev/fundamentals/01.1_creating_data_structures.html
@@ -197,17 +189,17 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
     # all_coords = _get_all_coordinates(ds)
 
     # First pass: Build all variables
-    data_arrays: dict[str, xr.DataArray] = {}
+    data_arrays: dict[str, xr_DataArray] = {}
     for v in mdio_ds.variables:
         # Use dask array instead of numpy array for lazy evaluation
         shape = _get_zarr_shape(v)
         dtype = _get_np_datatype(v)
         chunks = _get_zarr_chunks(v)
-        arr = dask.array.zeros(shape, dtype=dtype, chunks=chunks)
+        arr = dask_array.zeros(shape, dtype=dtype, chunks=chunks)
 
         # Create a DataArray for the variable. We will set coords in the second pass
         dim_names = _get_dimension_names(v)
-        data_array = xr.DataArray(arr, dims=dim_names)
+        data_array = xr_DataArray(arr, dims=dim_names)
 
         # Add array attributes
         if v.metadata is not None:
@@ -224,15 +216,14 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
         # Compression:
         # https://docs.xarray.dev/en/stable/internals/zarr-encoding-spec.html#zarr-encoding
         # If you don't explicitly specify a compressor when creating a Zarr array, Z
-        # arr will use a default compressor based on the Zarr format version and the data type of your array.
-        # Zarr V2 (Default is Blosc).
+        # arr will use a default compressor based on the Zarr format version and the data
+        # type of your array. Zarr V2 (Default is Blosc).
         # Thus, if there is no compressor, we will explicitly set "compressor" to None.
         #
         # Create a custom chunk key encoding with "/" as separator
-        from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
         chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
         encoding = {
-            "fill_value": get_fill_value(v.data_type),
+            "fill_value": _get_fill_value(v.data_type),
             "chunks": chunks,
             "chunk_key_encoding": chunk_key_encoding,
             # I was hoping the following would work, but it does not.
@@ -258,7 +249,7 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
         da = data_arrays[v.name]
         non_dim_coords_names = set(_get_coord_names(v)) - set(_get_dimension_names(v)) - {v.name}
         # Create and populate a dictionary {coord_name: DataArray for the coordinate}
-        non_dim_coords_dict: dict[str, xr.DataArray] = {}
+        non_dim_coords_dict: dict[str, xr_DataArray] = {}
         for name in non_dim_coords_names:
             non_dim_coords_dict[name] = data_arrays[name]
         if non_dim_coords_dict:
@@ -267,7 +258,7 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
             data_arrays[v.name] = da.assign_coords(non_dim_coords_dict)
 
     # Now let's create a dataset with all data arrays
-    xr_ds = xr.Dataset(data_arrays)
+    xr_ds = xr_Dataset(data_arrays)
     # Attach dataset metadata
     if mdio_ds.metadata is not None:
         xr_ds.attrs["apiVersion"] = mdio_ds.metadata.api_version
@@ -280,7 +271,7 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr.DataArray:  # noqa: PLR0912
 
 
 def to_zarr(
-    dataset: xr.Dataset,
+    dataset: xr_Dataset,
     store: str | None = None,
     *args: str | int | float | bool,
     **kwargs: Mapping[str, str | int | float | bool],
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index 1bee02e3c..d1ec69a35 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -4,8 +4,6 @@
 # Thus, disable it for this file
 """Tests the schema v1 dataset_serializer public API."""
 
-import xarray as xr
-
 from mdio.schemas.dtype import ScalarType
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
 from mdio.schemas.v1.dataset_serializer import to_xarray_dataset
@@ -14,7 +12,7 @@
 from .helpers import make_campos_3d_acceptance_dataset
 
 
-def test_to_xarray_dataset(capsys) -> None:
+def test_to_xarray_dataset() -> None:
     """Test building a complete dataset."""
     dataset = (
         MDIODatasetBuilder("test_dataset")
@@ -35,19 +33,18 @@ def test_to_xarray_dataset(capsys) -> None:
         .build()
     )
 
-    # with capsys.disabled():
-    xds: xr.Dataset = to_xarray_dataset(dataset)
+    xr_ds = to_xarray_dataset(dataset)
 
     file_name = "sample_dataset"
-    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")
+    to_zarr(xr_ds, f"test-data/{file_name}.zarr", mode="w")
 
 
-def test_campos_3d_acceptance_to_xarray_dataset(capsys) -> None:
+def test_campos_3d_acceptance_to_xarray_dataset() -> None:
     """Test building a complete dataset."""
     dataset = make_campos_3d_acceptance_dataset()
 
-    xds: xr.Dataset = to_xarray_dataset(dataset)
+    xr_ds = to_xarray_dataset(dataset)
 
     # file_name = "XYZ"
-    file_name = f"{xds.attrs['name']}"
-    to_zarr(xds, f"test-data/{file_name}.zarr", mode="w")
+    file_name = f"{xr_ds.attrs['name']}"
+    to_zarr(xr_ds, f"test-data/{file_name}.zarr", mode="w")

From 82f1960da9939222c2d44077624a6ae126812ee4 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Fri, 11 Jul 2025 22:26:34 +0000
Subject: [PATCH 44/56] Use only make_campos_3d_acceptance_dataset

---
 tests/unit/v1/helpers.py                    | 117 +-------------------
 tests/unit/v1/test_dataset_builder_build.py |  15 +--
 2 files changed, 9 insertions(+), 123 deletions(-)

diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index 336f2f0d6..ccd212895 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -241,6 +241,7 @@ def make_campos_3d_acceptance_dataset() -> Dataset:
     ds.add_variable(
         name="image_headers",
         dimensions=["inline", "crossline"],
+        coordinates=["cdp-x", "cdp-y"],
         data_type=StructuredType(
             fields=[
                 StructuredField(name="cdp-x", format=ScalarType.INT32),
@@ -254,122 +255,6 @@ def make_campos_3d_acceptance_dataset() -> Dataset:
                 chunk_grid=RegularChunkGrid(configuration=RegularChunkShape(chunk_shape=[128, 128]))
             )
         ],
-        coordinates=["cdp-x", "cdp-y"],
     )
     return ds.build()
 
-
-def make_campos_3d_dataset() -> Dataset:
-    """Create in-memory campos_3d dataset."""
-    ds = MDIODatasetBuilder(
-        "campos_3d",
-        attributes=UserAttributes(
-            attributes={
-                "textHeader": [
-                    "C01 .......................... ",
-                    "C02 .......................... ",
-                    "C03 .......................... ",
-                ],
-                "foo": "bar",
-            }
-        ),
-    )
-
-    # Add dimensions
-    ds.add_dimension("inline", 256)
-    ds.add_dimension("crossline", 512)
-    ds.add_dimension("depth", 384)
-    ds.add_coordinate("inline", dimensions=["inline"], data_type=ScalarType.UINT32)
-    ds.add_coordinate("crossline", dimensions=["crossline"], data_type=ScalarType.UINT32)
-    ds.add_coordinate(
-        "depth",
-        dimensions=["depth"],
-        data_type=ScalarType.FLOAT64,
-        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
-    )
-    # Add coordinates
-    ds.add_coordinate(
-        "cdp-x",
-        dimensions=["inline", "crossline"],
-        data_type=ScalarType.FLOAT32,
-        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
-    )
-    ds.add_coordinate(
-        "cdp-y",
-        dimensions=["inline", "crossline"],
-        data_type=ScalarType.FLOAT32,
-        metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
-    )
-
-    # Add image variable
-    ds.add_variable(
-        name="image",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT32,
-        compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
-                )
-            ),
-            StatisticsMetadata(
-                stats_v1=SummaryStatistics(
-                    count=100,
-                    sum=1215.1,
-                    sumSquares=125.12,
-                    min=5.61,
-                    max=10.84,
-                    histogram=CenteredBinHistogram(binCenters=[1, 2], counts=[10, 15]),
-                )
-            ),
-            UserAttributes(attributes={"fizz": "buzz", "UnitSystem": "Canonical"}),
-        ],
-    )
-    # Add velocity variable
-    ds.add_variable(
-        name="velocity",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT16,
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[128, 128, 128])
-                )
-            ),
-            AllUnits(units_v1=SpeedUnitModel(speed=SpeedUnitEnum.METER_PER_SECOND)),
-        ],
-    )
-    # Add inline-optimized image variable
-    ds.add_variable(
-        name="image_inline",
-        long_name="inline optimized version of 3d_stack",
-        dimensions=["inline", "crossline", "depth"],
-        data_type=ScalarType.FLOAT32,
-        compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
-        metadata_info=[
-            ChunkGridMetadata(
-                chunk_grid=RegularChunkGrid(
-                    configuration=RegularChunkShape(chunk_shape=[4, 512, 512])
-                )
-            )
-        ],
-    )
-    # Add headers variable with structured dtype
-    ds.add_variable(
-        name="image_headers",
-        dimensions=["inline", "crossline"],
-        data_type=StructuredType(
-            fields=[
-                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
-                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
-                StructuredField(name="inline", format=ScalarType.UINT32),
-                StructuredField(name="crossline", format=ScalarType.UINT32),
-            ]
-        ),
-        coordinates=["cdp-x", "cdp-y"],
-    )
-    return ds.build()
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 832f624c1..d726c32d4 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -12,7 +12,7 @@
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import SpeedUnitEnum
 
-from .helpers import make_campos_3d_dataset
+from .helpers import make_campos_3d_acceptance_dataset
 from .helpers import validate_variable
 
 
@@ -49,7 +49,7 @@ def test_build() -> None:
 
 def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
     """Test building a Campos 3D dataset with multiple variables and attributes."""
-    dataset = make_campos_3d_dataset()
+    dataset = make_campos_3d_acceptance_dataset()
 
     # Verify dataset structure
     assert dataset.metadata.name == "campos_3d"
@@ -75,7 +75,7 @@ def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 5
     )
 
     depth = validate_variable(
-        dataset, name="depth", dims=[("depth", 384)], coords=["depth"], dtype=ScalarType.FLOAT64
+        dataset, name="depth", dims=[("depth", 384)], coords=["depth"], dtype=ScalarType.UINT32
     )
     assert depth.metadata.units_v1.length == LengthUnitEnum.METER
 
@@ -146,10 +146,11 @@ def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 5
         coords=["cdp-x", "cdp-y"],
         dtype=StructuredType(
             fields=[
-                StructuredField(name="cdp-x", format=ScalarType.FLOAT32),
-                StructuredField(name="cdp-y", format=ScalarType.FLOAT32),
-                StructuredField(name="inline", format=ScalarType.UINT32),
-                StructuredField(name="crossline", format=ScalarType.UINT32),
+                StructuredField(name="cdp-x", format=ScalarType.INT32),
+                StructuredField(name="cdp-y", format=ScalarType.INT32),
+                StructuredField(name="elevation", format=ScalarType.FLOAT16),
+                StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
             ]
         ),
     )
+    assert headers.metadata.chunk_grid.configuration.chunk_shape == [128, 128]

From b5ee31e90e366395df26674a4f8407c0343ae580 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 14 Jul 2025 21:51:54 +0000
Subject: [PATCH 45/56] PR Review: address the review comments

---
 .gitignore                                  |   2 -
 _dev/DEVELOPERS_NOTES.md                    |  16 -
 _dev/zmetadata.cpp.json                     | 195 -----------
 _dev/zmetadata.python.json                  | 195 -----------
 src/mdio/constants.py                       |  61 ++--
 src/mdio/schemas/v1/dataset_serializer.py   | 153 ++++-----
 tests/unit/v1/helpers.py                    |  22 +-
 tests/unit/v1/test_dataset_builder_build.py |   8 +-
 tests/unit/v1/test_dataset_serializer.py    | 350 +++++++++++++++++++-
 9 files changed, 483 insertions(+), 519 deletions(-)
 delete mode 100644 _dev/DEVELOPERS_NOTES.md
 delete mode 100644 _dev/zmetadata.cpp.json
 delete mode 100644 _dev/zmetadata.python.json

diff --git a/.gitignore b/.gitignore
index 643394a40..bfdc38f28 100644
--- a/.gitignore
+++ b/.gitignore
@@ -153,5 +153,3 @@ mdio1/*
 pytest-of-*
 tmp
 debugging/*
-
-test-data/*
diff --git a/_dev/DEVELOPERS_NOTES.md b/_dev/DEVELOPERS_NOTES.md
deleted file mode 100644
index a9df833e0..000000000
--- a/_dev/DEVELOPERS_NOTES.md
+++ /dev/null
@@ -1,16 +0,0 @@
-# Wring empty XArray / Zarr to a local storage
-
-src/mdio/schemas/v1/dataset_serializer.py
-
-## Issues encountered
-
-1. FIXED: Non-zero size of the serialized data files
-2. FIXED: Not clear how to properly set `compressor`, `dimension_separator`, and `fill_value`
-3. FIXED: For image_inline chunks[2] are somehow different?
-
-4. `fill_value` for StructuredType is set to null, but "AAAAAAAAAAAAAAAA" is expected
-
-## TO DO:
-
-- Add more unit tests for internal functions
-- Add a trest comparing expected and actual .zmetadata for the serialized dataset
diff --git a/_dev/zmetadata.cpp.json b/_dev/zmetadata.cpp.json
deleted file mode 100644
index 394de1a8f..000000000
--- a/_dev/zmetadata.cpp.json
+++ /dev/null
@@ -1,195 +0,0 @@
-{
-  "metadata": {
-    ".zattrs": {
-      "apiVersion": "1.0.0",
-      "attributes": {
-        "foo": "bar",
-        "textHeader": [
-          "C01 .......................... ",
-          "C02 .......................... ",
-          "C03 .......................... "
-        ]
-      },
-      "createdOn": "2023-12-12T15:02:06.413469-06:00",
-      "name": "campos_3d"
-    },
-    ".zgroup": {
-      "zarr_format": 2
-    },
-    "cdp-x/.zarray": {
-      "chunks": [256, 512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "cdp-x/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "cdp-y/.zarray": {
-      "chunks": [256, 512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "cdp-y/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "crossline/.zarray": {
-      "chunks": [512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [512],
-      "zarr_format": 2
-    },
-    "crossline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["crossline"]
-    },
-    "depth/.zarray": {
-      "chunks": [384],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [384],
-      "zarr_format": 2
-    },
-    "depth/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["depth"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "image/.zarray": {
-      "chunks": [128, 128, 128],
-      "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "zstd",
-        "id": "blosc",
-        "shuffle": 1
-      },
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "image/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "attributes": {
-        "fizz": "buzz"
-      },
-      "coordinates": "cdp-x cdp-y",
-      "statsV1": {
-        "count": 100,
-        "histogram": {
-          "binCenters": [1, 2],
-          "counts": [10, 15]
-        },
-        "max": 10.84,
-        "min": 5.61,
-        "sum": 1215.1,
-        "sumSquares": 125.12
-      }
-    },
-    "image_headers/.zarray": {
-      "chunks": [128, 128],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": [
-        ["cdp-x", "<i4"],
-        ["cdp-y", "<i4"],
-        ["elevation", "<f2"],
-        ["some_scalar", "<f2"]
-      ],
-      "fill_value": "AAAAAAAAAAAAAAAA",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "image_headers/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "coordinates": "cdp-x cdp-y"
-    },
-    "image_inline/.zarray": {
-      "chunks": [4, 512, 512],
-      "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "zstd",
-        "id": "blosc",
-        "shuffle": 1
-      },
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "image_inline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "coordinates": "cdp-x cdp-y",
-      "long_name": "inline optimized version of 3d_stack"
-    },
-    "inline/.zarray": {
-      "chunks": [256],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [256],
-      "zarr_format": 2
-    },
-    "inline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline"]
-    },
-    "velocity/.zarray": {
-      "chunks": [128, 128, 128],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f2",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "velocity/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "coordinates": "cdp-x cdp-y",
-      "unitsV1": {
-        "speed": "m/s"
-      }
-    }
-  },
-  "zarr_consolidated_format": 1
-}
diff --git a/_dev/zmetadata.python.json b/_dev/zmetadata.python.json
deleted file mode 100644
index 56cea2ac5..000000000
--- a/_dev/zmetadata.python.json
+++ /dev/null
@@ -1,195 +0,0 @@
-{
-  "metadata": {
-    ".zattrs": {
-      "apiVersion": "1.0.0a1",
-      "attributes": {
-        "foo": "bar",
-        "textHeader": [
-          "C01 .......................... ",
-          "C02 .......................... ",
-          "C03 .......................... "
-        ]
-      },
-      "createdOn": "2025-07-11 19:53:51.363436+00:00",
-      "name": "campos_3d"
-    },
-    ".zgroup": {
-      "zarr_format": 2
-    },
-    "cdp-x/.zarray": {
-      "chunks": [256, 512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "cdp-x/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "cdp-y/.zarray": {
-      "chunks": [256, 512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "cdp-y/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "crossline/.zarray": {
-      "chunks": [512],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [512],
-      "zarr_format": 2
-    },
-    "crossline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["crossline"]
-    },
-    "depth/.zarray": {
-      "chunks": [384],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [384],
-      "zarr_format": 2
-    },
-    "depth/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["depth"],
-      "unitsV1": {
-        "length": "m"
-      }
-    },
-    "image/.zarray": {
-      "chunks": [128, 128, 128],
-      "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "zstd",
-        "id": "blosc",
-        "shuffle": 1
-      },
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "image/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "attributes": {
-        "fizz": "buzz"
-      },
-      "coordinates": "cdp-x cdp-y",
-      "statsV1": {
-        "count": 100,
-        "histogram": {
-          "binCenters": [1, 2],
-          "counts": [10, 15]
-        },
-        "max": 10.84,
-        "min": 5.61,
-        "sum": 1215.1,
-        "sumSquares": 125.12
-      }
-    },
-    "image_headers/.zarray": {
-      "chunks": [128, 128],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": [
-        ["cdp-x", "<i4"],
-        ["cdp-y", "<i4"],
-        ["elevation", "<f2"],
-        ["some_scalar", "<f2"]
-      ],
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512],
-      "zarr_format": 2
-    },
-    "image_headers/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline"],
-      "coordinates": "cdp-x cdp-y"
-    },
-    "image_inline/.zarray": {
-      "chunks": [4, 512, 512],
-      "compressor": {
-        "blocksize": 0,
-        "clevel": 5,
-        "cname": "zstd",
-        "id": "blosc",
-        "shuffle": 1
-      },
-      "dimension_separator": "/",
-      "dtype": "<f4",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "image_inline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "coordinates": "cdp-x cdp-y",
-      "long_name": "inline optimized version of 3d_stack"
-    },
-    "inline/.zarray": {
-      "chunks": [256],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<u4",
-      "fill_value": null,
-      "filters": null,
-      "order": "C",
-      "shape": [256],
-      "zarr_format": 2
-    },
-    "inline/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline"]
-    },
-    "velocity/.zarray": {
-      "chunks": [128, 128, 128],
-      "compressor": null,
-      "dimension_separator": "/",
-      "dtype": "<f2",
-      "fill_value": "NaN",
-      "filters": null,
-      "order": "C",
-      "shape": [256, 512, 384],
-      "zarr_format": 2
-    },
-    "velocity/.zattrs": {
-      "_ARRAY_DIMENSIONS": ["inline", "crossline", "depth"],
-      "coordinates": "cdp-x cdp-y",
-      "unitsV1": {
-        "speed": "m/s"
-      }
-    }
-  },
-  "zarr_consolidated_format": 1
-}
diff --git a/src/mdio/constants.py b/src/mdio/constants.py
index bff765314..b6fff807c 100644
--- a/src/mdio/constants.py
+++ b/src/mdio/constants.py
@@ -1,36 +1,59 @@
 """Constant values used across MDIO."""
 
-import numpy as np
+from numpy import finfo as np_finfo
+from numpy import iinfo as np_iinfo
+from numpy import nan as np_nan
 
-FLOAT16_MAX = np.finfo("float16").max
-FLOAT16_MIN = np.finfo("float16").min
+from mdio.schemas.dtype import ScalarType
 
-FLOAT32_MAX = np.finfo("float32").max
-FLOAT32_MIN = np.finfo("float32").min
+FLOAT16_MAX = np_finfo("float16").max
+FLOAT16_MIN = np_finfo("float16").min
 
-FLOAT64_MIN = np.finfo("float64").min
-FLOAT64_MAX = np.finfo("float64").max
+FLOAT32_MAX = np_finfo("float32").max
+FLOAT32_MIN = np_finfo("float32").min
 
-INT8_MIN = np.iinfo("int8").min
-INT8_MAX = np.iinfo("int8").max
+FLOAT64_MIN = np_finfo("float64").min
+FLOAT64_MAX = np_finfo("float64").max
 
-INT16_MIN = np.iinfo("int16").min
-INT16_MAX = np.iinfo("int16").max
+INT8_MIN = np_iinfo("int8").min
+INT8_MAX = np_iinfo("int8").max
 
-INT32_MIN = np.iinfo("int32").min
-INT32_MAX = np.iinfo("int32").max
+INT16_MIN = np_iinfo("int16").min
+INT16_MAX = np_iinfo("int16").max
 
-INT64_MIN = np.iinfo("int64").min
-INT64_MAX = np.iinfo("int64").max
+INT32_MIN = np_iinfo("int32").min
+INT32_MAX = np_iinfo("int32").max
+
+INT64_MIN = np_iinfo("int64").min
+INT64_MAX = np_iinfo("int64").max
 
 UINT8_MIN = 0
-UINT8_MAX = np.iinfo("uint8").max
+UINT8_MAX = np_iinfo("uint8").max
 
 UINT16_MIN = 0
-UINT16_MAX = np.iinfo("uint16").max
+UINT16_MAX = np_iinfo("uint16").max
 
 UINT32_MIN = 0
-UINT32_MAX = np.iinfo("uint32").max
+UINT32_MAX = np_iinfo("uint32").max
 
 UINT64_MIN = 0
-UINT64_MAX = np.iinfo("uint64").max
+UINT64_MAX = np_iinfo("uint64").max
+
+# Zarr fill values for different scalar types
+fill_value_map = {
+    ScalarType.BOOL: None,
+    ScalarType.FLOAT16: np_nan,
+    ScalarType.FLOAT32: np_nan,
+    ScalarType.FLOAT64: np_nan,
+    ScalarType.UINT8: 2**8 - 1,  # Max value for uint8
+    ScalarType.UINT16: 2**16 - 1,  # Max value for uint16
+    ScalarType.UINT32: 2**32 - 1,  # Max value for uint32
+    ScalarType.UINT64: 2**64 - 1,  # Max value for uint64
+    ScalarType.INT8: 2**7 - 1,  # Max value for int8
+    ScalarType.INT16: 2**15 - 1,  # Max value for int16
+    ScalarType.INT32: 2**31 - 1,  # Max value for int32
+    ScalarType.INT64: 2**63 - 1,  # Max value for int64
+    ScalarType.COMPLEX64: complex(np_nan, np_nan),
+    ScalarType.COMPLEX128: complex(np_nan, np_nan),
+    ScalarType.COMPLEX256: complex(np_nan, np_nan),
+}
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index 10e9f4628..a8c871ac4 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -5,7 +5,6 @@
 from dask import array as dask_array
 from numcodecs import Blosc as nc_Blosc
 from numpy import dtype as np_dtype
-from numpy import nan as np_nan
 from xarray import DataArray as xr_DataArray
 from xarray import Dataset as xr_Dataset
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
@@ -17,6 +16,7 @@
 except ImportError:
     zfpy_ZFPY = None  # noqa: N816
 
+from mdio.constants import fill_value_map
 from mdio.schemas.compressors import ZFP as mdio_ZFP  # noqa: N811
 from mdio.schemas.compressors import Blosc as mdio_Blosc
 from mdio.schemas.dimension import NamedDimension
@@ -29,6 +29,26 @@
 
 
 def _get_all_named_dimensions(dataset: Dataset) -> dict[str, NamedDimension]:
+    """Get all NamedDimensions from the dataset variables.
+
+    This function returns a dictionary of NamedDimensions, but if some dimensions
+    are not resolvable, they will not be included in the result.
+
+    Args:
+        dataset: The MDIO Dataset to extract NamedDimensions from.
+
+    Note:
+        The Dataset Builder ensures that all dimensions are resolvable by always embedding
+        dimensions as NamedDimension and never as str.
+        If the dataset is created in a different way, some dimensions may be specified as
+        dimension names (str) instead of NamedDimension. In this case, we will try to resolve
+        them to NamedDimension, but if the dimension is not found, it will be skipped.
+        It is the responsibility of the Dataset creator to ensure that all dimensions are
+        resolvable at the Dataset level.
+
+    Returns:
+        A dictionary mapping dimension names to NamedDimension instances.
+    """
     all_named_dims: dict[str, NamedDimension] = {}
     for v in dataset.variables:
         if v.dimensions is not None:
@@ -36,37 +56,30 @@ def _get_all_named_dimensions(dataset: Dataset) -> dict[str, NamedDimension]:
                 if isinstance(d, NamedDimension):
                     all_named_dims[d.name] = d
                 else:
-                    # Never happens for the dataset generated with the dataset builder
                     pass
     return all_named_dims
 
 
-def _get_all_coordinates(dataset: Dataset) -> dict[str, Coordinate]:
-    all_coords: dict[str, Coordinate] = {}
-    for v in dataset.variables:
-        if v.coordinates is not None:
-            for c in v.coordinates:
-                if isinstance(c, Coordinate) and c.name not in all_coords:
-                    all_coords[c.name] = c
-    return all_coords
-
-
 def _get_dimension_names(var: Variable) -> list[str]:
+    """Get the names of dimensions for a variable.
+
+    Note:
+        We expect that Datasets produced by DatasetBuilder has all dimensions
+        embedded as NamedDimension, but we also support dimension name strings for
+        compatibility with Dataset produced in a different way.
+    """
     dim_names: list[str] = []
     if var.dimensions is not None:
         for d in var.dimensions:
             if isinstance(d, NamedDimension):
                 dim_names.append(d.name)
             elif isinstance(d, str):
-                # Never happens for the dataset generated with the dataset builder
                 dim_names.append(d)
-            else:
-                err = f"Unsupported dimension type: {type(d)} in variable {var.name}"
-                raise TypeError(err)
     return dim_names
 
 
 def _get_coord_names(var: Variable) -> list[str]:
+    """Get the names of coordinates for a variable."""
     coord_names: list[str] = []
     if var.coordinates is not None:
         for c in var.coordinates:
@@ -74,13 +87,11 @@ def _get_coord_names(var: Variable) -> list[str]:
                 coord_names.append(c.name)
             elif isinstance(c, str):
                 coord_names.append(c)
-            else:
-                err = f"Unsupported coordinate type: {type(c)} in variable {var.name}"
-                raise TypeError(err)
     return coord_names
 
 
 def _get_np_datatype(var: Variable) -> np_dtype:
+    """Get the numpy dtype for a variable."""
     data_type = var.data_type
     if isinstance(data_type, ScalarType):
         return np_dtype(data_type.value)
@@ -90,17 +101,33 @@ def _get_np_datatype(var: Variable) -> np_dtype:
     raise TypeError(err)
 
 
-def _get_zarr_shape(var: Variable) -> tuple[int, ...]:
-    # NOTE: This assumes that the variable dimensions are all NamedDimension
-    return tuple(dim.size for dim in var.dimensions)
+def _get_zarr_shape(var: Variable, all_named_dims: dict[str, NamedDimension]) -> tuple[int, ...]:
+    """Get the shape of a variable for Zarr storage.
 
-
-def _get_zarr_chunks(var: Variable) -> tuple[int, ...]:
+    Note:
+        We expect that Datasets produced by DatasetBuilder has all dimensions
+        embedded as NamedDimension, but we also support dimension name strings for
+        compatibility with Dataset produced in a different way.
+    """
+    shape: list[int] = []
+    for dim in var.dimensions:
+        if isinstance(dim, NamedDimension):
+            shape.append(dim.size)
+        if isinstance(dim, str):
+            named_dim = all_named_dims.get(dim)
+            if named_dim is None:
+                err = f"Dimension named '{dim}' can't be resolved to a NamedDimension."
+                raise ValueError(err)
+            shape.append(named_dim.size)
+    return tuple(shape)
+
+
+def _get_zarr_chunks(var: Variable, all_named_dims: dict[str, NamedDimension]) -> tuple[int, ...]:
     """Get the chunk shape for a variable, defaulting to its shape if no chunk grid is defined."""
     if var.metadata is not None and var.metadata.chunk_grid is not None:
-        return var.metadata.chunk_grid.configuration.chunk_shape
+        return tuple(var.metadata.chunk_grid.configuration.chunk_shape)
     # Default to full shape if no chunk grid is defined
-    return _get_zarr_shape(var)
+    return _get_zarr_shape(var, all_named_dims=all_named_dims)
 
 
 def _convert_compressor(
@@ -133,26 +160,6 @@ def _convert_compressor(
     raise TypeError(msg)
 
 
-# Do we already have it somewhere in the codebase? I could not find it.
-fill_value_map = {
-    ScalarType.BOOL: None,
-    ScalarType.FLOAT16: np_nan,
-    ScalarType.FLOAT32: np_nan,
-    ScalarType.FLOAT64: np_nan,
-    ScalarType.UINT8: 2**8 - 1,  # Max value for uint8
-    ScalarType.UINT16: 2**16 - 1,  # Max value for uint16
-    ScalarType.UINT32: 2**32 - 1,  # Max value for uint32
-    ScalarType.UINT64: 2**64 - 1,  # Max value for uint64
-    ScalarType.INT8: 2**7 - 1,  # Max value for int8
-    ScalarType.INT16: 2**15 - 1,  # Max value for int16
-    ScalarType.INT32: 2**31 - 1,  # Max value for int32
-    ScalarType.INT64: 2**63 - 1,  # Max value for int64
-    ScalarType.COMPLEX64: complex(np_nan, np_nan),
-    ScalarType.COMPLEX128: complex(np_nan, np_nan),
-    ScalarType.COMPLEX256: complex(np_nan, np_nan),
-}
-
-
 def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     """Get the fill value for a given data type.
 
@@ -185,16 +192,15 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
     # See the xarray tutorial for more details on how to create datasets:
     # https://tutorial.xarray.dev/fundamentals/01.1_creating_data_structures.html
 
-    # all_dims = _get_all_named_dimensions(ds)
-    # all_coords = _get_all_coordinates(ds)
+    all_named_dims = _get_all_named_dimensions(mdio_ds)
 
     # First pass: Build all variables
     data_arrays: dict[str, xr_DataArray] = {}
     for v in mdio_ds.variables:
         # Use dask array instead of numpy array for lazy evaluation
-        shape = _get_zarr_shape(v)
+        shape = _get_zarr_shape(v, all_named_dims=all_named_dims)
         dtype = _get_np_datatype(v)
-        chunks = _get_zarr_chunks(v)
+        chunks = _get_zarr_chunks(v, all_named_dims=all_named_dims)
         arr = dask_array.zeros(shape, dtype=dtype, chunks=chunks)
 
         # Create a DataArray for the variable. We will set coords in the second pass
@@ -213,30 +219,12 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
         if v.long_name:
             data_array.attrs["long_name"] = v.long_name
 
-        # Compression:
-        # https://docs.xarray.dev/en/stable/internals/zarr-encoding-spec.html#zarr-encoding
-        # If you don't explicitly specify a compressor when creating a Zarr array, Z
-        # arr will use a default compressor based on the Zarr format version and the data
-        # type of your array. Zarr V2 (Default is Blosc).
-        # Thus, if there is no compressor, we will explicitly set "compressor" to None.
-        #
         # Create a custom chunk key encoding with "/" as separator
         chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
         encoding = {
             "fill_value": _get_fill_value(v.data_type),
             "chunks": chunks,
             "chunk_key_encoding": chunk_key_encoding,
-            # I was hoping the following would work, but it does not.
-            # I see:
-            #    >_compressor = parse_compressor(compressor[0])
-            #    > return numcodecs.get_codec(data)
-            #    E - numcodecs.errors.UnknownCodecError: codec not available: 'None'"
-            # Example: https://zarr.readthedocs.io/en/stable/user-guide/arrays.html#compressors
-            # from zarr.codecs import BloscCodec
-            # compressor = BloscCodec(cname="zstd", clevel=3, shuffle="shuffle")
-            #
-            # "compressor": _to_dictionary(v.compressor)
-            # Thus, we will call the conversion function:
             "compressor": _convert_compressor(v.compressor),
         }
         data_array.encoding = encoding
@@ -276,14 +264,27 @@ def to_zarr(
     *args: str | int | float | bool,
     **kwargs: Mapping[str, str | int | float | bool],
 ) -> None:
-    """Write an XArray dataset to Zarr format."""
-    # MDIO only supports zarr_format=2
+    """Write an XArray dataset to Zarr format.
+
+    Args:
+        dataset: The XArray dataset to write.
+        store: The Zarr store to write to. If None, defaults to in-memory store.
+        *args: Additional positional arguments for the Zarr store.
+        **kwargs: Additional keyword arguments for the Zarr store.
+
+    Notes:
+        It sets the zarr_format to 2, which is the default for XArray datasets.
+        Since we set kwargs["compute"], this method will return a dask.delayed.Delayed object
+        and the arrays will not be immediately written.
+
+    References:
+            https://docs.xarray.dev/en/stable/user-guide/io.html
+            https://docs.xarray.dev/en/latest/generated/xarray.DataArray.to_zarr.html
+
+    Returns:
+        None: The function writes the dataset as dask.delayed.Delayed object to the
+        specified Zarr store.
+    """
     kwargs["zarr_format"] = 2
-    # compute: default: True) – If True write array data immediately,
-    # otherwise return a dask.delayed.Delayed object that can be computed
-    # to write array data later.
-    # *** Metadata is always updated eagerly. ***
     kwargs["compute"] = False
-    # https://docs.xarray.dev/en/stable/user-guide/io.html
-    # https://docs.xarray.dev/en/latest/generated/xarray.DataArray.to_zarr.html
     return dataset.to_zarr(*args, store=store, **kwargs)
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index ccd212895..d0ebe5d79 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -129,6 +129,7 @@ def _get_coordinate(
 
 
 def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
+    """Get all coordinates from the dataset."""
     all_coords: dict[str, Coordinate] = {}
     for v in dataset.variables:
         if v.coordinates is not None:
@@ -138,8 +139,24 @@ def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
     return list(all_coords.values())
 
 
-def make_campos_3d_acceptance_dataset() -> Dataset:
-    """Create in-memory campos_3d dataset."""
+def output_path(file_dir: str, file_name: str, debugging: bool = False) -> str:
+    """Generate the output path for the test file-system output.
+
+    Note:
+        Use debugging=True, if you need to retain the created files for debugging
+        purposes. Otherwise, the files will be created in-memory and not saved to disk.
+    """
+    if debugging:
+        # Use the following for debugging:
+        file_path = f"{file_dir}/mdio-tests/{file_name}.zarr"
+    else:
+        # Use the following for normal runs:
+        file_path = f"memory://path_to_zarr/mdio-tests/{file_name}.zarr"
+    return file_path
+
+
+def make_seismic_poststack_3d_acceptance_dataset() -> Dataset:
+    """Create in-memory Seismic PostStack 3D Acceptance dataset."""
     ds = MDIODatasetBuilder(
         "campos_3d",
         attributes=UserAttributes(
@@ -257,4 +274,3 @@ def make_campos_3d_acceptance_dataset() -> Dataset:
         ],
     )
     return ds.build()
-
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index d726c32d4..2a68c8337 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -12,7 +12,7 @@
 from mdio.schemas.v1.units import LengthUnitEnum
 from mdio.schemas.v1.units import SpeedUnitEnum
 
-from .helpers import make_campos_3d_acceptance_dataset
+from .helpers import make_seismic_poststack_3d_acceptance_dataset
 from .helpers import validate_variable
 
 
@@ -47,9 +47,9 @@ def test_build() -> None:
     assert next(v for v in dataset.variables if v.name == "data") is not None
 
 
-def test_build_campos_3d() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
-    """Test building a Campos 3D dataset with multiple variables and attributes."""
-    dataset = make_campos_3d_acceptance_dataset()
+def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
+    """Test building a Seismic PostStack 3D Acceptance dataset."""
+    dataset = make_seismic_poststack_3d_acceptance_dataset()
 
     # Verify dataset structure
     assert dataset.metadata.name == "campos_3d"
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index d1ec69a35..19e3db505 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -4,15 +4,348 @@
 # Thus, disable it for this file
 """Tests the schema v1 dataset_serializer public API."""
 
+import pytest
+from numpy import dtype as np_dtype
+from numpy import isnan as np_isnan
+
+from mdio.constants import fill_value_map
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.dimension import NamedDimension
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset import DatasetInfo
 from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.dataset_builder import _to_dictionary
+from mdio.schemas.v1.dataset_serializer import _convert_compressor
+from mdio.schemas.v1.dataset_serializer import _get_all_named_dimensions
+from mdio.schemas.v1.dataset_serializer import _get_coord_names
+from mdio.schemas.v1.dataset_serializer import _get_dimension_names
+from mdio.schemas.v1.dataset_serializer import _get_fill_value
+from mdio.schemas.v1.dataset_serializer import _get_np_datatype
+from mdio.schemas.v1.dataset_serializer import _get_zarr_chunks
+from mdio.schemas.v1.dataset_serializer import _get_zarr_shape
 from mdio.schemas.v1.dataset_serializer import to_xarray_dataset
 from mdio.schemas.v1.dataset_serializer import to_zarr
+from mdio.schemas.v1.variable import Coordinate
+from mdio.schemas.v1.variable import Variable
+
+from .helpers import make_seismic_poststack_3d_acceptance_dataset
+from .helpers import output_path
+
+try:
+    from zfpy import ZFPY as zfpy_ZFPY  # noqa: N811
+
+    HAS_ZFPY = True
+except ImportError:
+    zfpy_ZFPY = None  # noqa: N816
+    HAS_ZFPY = False
+
+from numcodecs import Blosc as nc_Blosc
+
+from mdio.schemas.compressors import ZFP as mdio_ZFP  # noqa: N811
+from mdio.schemas.compressors import Blosc as mdio_Blosc
+from mdio.schemas.compressors import BloscAlgorithm as mdio_BloscAlgorithm
+from mdio.schemas.compressors import BloscShuffle as mdio_BloscShuffle
+from mdio.schemas.compressors import ZFPMode as mdio_ZFPMode
+
+
+def test__get_all_named_dimensions() -> None:
+    """Test _get_all_named_dimensions function."""
+    dim1 = NamedDimension(name="inline", size=100)
+    dim2 = NamedDimension(name="crossline", size=200)
+    dim3 = NamedDimension(name="depth", size=300)
+    v1 = Variable(name="named_dims", data_type=ScalarType.FLOAT32, dimensions=[dim1, dim2, dim3])
+    v2 = Variable(
+        name="string_dims",
+        data_type=ScalarType.FLOAT32,
+        dimensions=["inline", "crossline", "depth"],
+    )
+    v3 = Variable(name="unresolved_dims", data_type=ScalarType.FLOAT32, dimensions=["x", "y", "z"])
+    ds = Dataset(
+        variables=[v1, v2, v3],
+        metadata=_to_dictionary(
+            [
+                DatasetInfo(
+                    name="test_dataset", api_version="1.0.0", created_on="2023-10-01T00:00:00Z"
+                )
+            ]
+        ),
+    )
+
+    all_dims = _get_all_named_dimensions(ds)
+    # Only 3 named dimensions could be resolved.
+    # The dimension names "x", "y', "z" are unresolvable.
+    assert set(all_dims) == {"inline", "crossline", "depth"}
+
+
+def test__get_dimension_names() -> None:
+    """Test _get_dimension_names function with various dimension types."""
+    dim1 = NamedDimension(name="inline", size=100)
+    dim2 = NamedDimension(name="crossline", size=200)
+
+    # Test case 1: Variable with NamedDimension
+    var_named_dims = Variable(
+        name="Variable with NamedDimension dimensions",
+        data_type=ScalarType.FLOAT32,
+        dimensions=[dim1, dim2],
+    )
+    assert set(_get_dimension_names(var_named_dims)) == {"inline", "crossline"}
+
+    # Test case 2: Variable with string dimensions
+    var_string_dims = Variable(
+        name="Variable with string dimensions",
+        data_type=ScalarType.FLOAT32,
+        dimensions=["x", "y", "z"],
+    )
+    assert set(_get_dimension_names(var_string_dims)) == {"x", "y", "z"}
+
+    # Test case 3: Mixed NamedDimension and string dimensions
+    # NOTE: mixing NamedDimension and string dimensions is not allowed by the Variable schema
+
+
+def test__get_coord_names() -> None:
+    """Comprehensive test for _get_coord_names function covering all scenarios."""
+    dim1 = NamedDimension(name="inline", size=100)
+    dim2 = NamedDimension(name="crossline", size=200)
+
+    # Test 1: Variable with Coordinate objects
+    coord1 = Coordinate(name="x_coord", dimensions=[dim1, dim2], data_type=ScalarType.FLOAT32)
+    coord2 = Coordinate(name="y_coord", dimensions=[dim1, dim2], data_type=ScalarType.FLOAT64)
+    variable_coords = Variable(
+        name="Variable with Coordinate objects",
+        data_type=ScalarType.FLOAT32,
+        dimensions=[dim1, dim2],
+        coordinates=[coord1, coord2],
+    )
+    assert set(_get_coord_names(variable_coords)) == {"x_coord", "y_coord"}
+
+    # Test 2: Variable with string coordinates
+    variable_strings = Variable(
+        name="Variable with string coordinates",
+        data_type=ScalarType.FLOAT32,
+        dimensions=[dim1, dim2],
+        coordinates=["lat", "lon", "time"],
+    )
+    assert set(_get_coord_names(variable_strings)) == {"lat", "lon", "time"}
+
+    # Test 3: Variable with mixed coordinate types
+    # NOTE: mixing Coordinate objects and coordinate name strings is not allowed by the
+    # Variable schema
+
+
+def test__get_np_datatype() -> None:
+    """Comprehensive test for _get_np_datatype function."""
+    # Test 1: ScalarType cases - all supported scalar types
+    scalar_type_tests = [
+        (ScalarType.FLOAT32, "float32"),
+        (ScalarType.FLOAT64, "float64"),
+        (ScalarType.INT8, "int8"),
+        (ScalarType.INT16, "int16"),
+        (ScalarType.INT32, "int32"),
+        (ScalarType.INT64, "int64"),
+        (ScalarType.UINT8, "uint8"),
+        (ScalarType.UINT16, "uint16"),
+        (ScalarType.UINT32, "uint32"),
+        (ScalarType.UINT64, "uint64"),
+        (ScalarType.COMPLEX64, "complex64"),
+        (ScalarType.COMPLEX128, "complex128"),
+        (ScalarType.BOOL, "bool"),
+    ]
+
+    for scalar_type, expected_numpy_type in scalar_type_tests:
+        variable = Variable(name="test_var", dimensions=[], data_type=scalar_type)
+
+        result = _get_np_datatype(variable)
+        expected = np_dtype(expected_numpy_type)
+
+        assert result == expected
+        assert isinstance(result, np_dtype)
+        assert result.name == expected.name
+
+    # Test 2: StructuredType with multiple fields
+    multi_fields = [
+        StructuredField(name="x", format=ScalarType.FLOAT64),
+        StructuredField(name="y", format=ScalarType.FLOAT64),
+        StructuredField(name="z", format=ScalarType.FLOAT64),
+        StructuredField(name="id", format=ScalarType.INT32),
+        StructuredField(name="valid", format=ScalarType.BOOL),
+    ]
+    structured_multi = StructuredType(fields=multi_fields)
+
+    variable_multi_struct = Variable(
+        name="multi_struct_var", dimensions=[], data_type=structured_multi
+    )
+
+    result_multi = _get_np_datatype(variable_multi_struct)
+    expected_multi = np_dtype(
+        [("x", "float64"), ("y", "float64"), ("z", "float64"), ("id", "int32"), ("valid", "bool")]
+    )
+
+    assert result_multi == expected_multi
+    assert isinstance(result_multi, np_dtype)
+    assert len(result_multi.names) == 5
+    assert set(result_multi.names) == {"x", "y", "z", "id", "valid"}
+
+
+def test__get_zarr_shape() -> None:
+    """Test for _get_zarr_shape function."""
+    d1 = NamedDimension(name="inline", size=100)
+    d2 = NamedDimension(name="crossline", size=200)
+    d3 = NamedDimension(name="depth", size=300)
+
+    v = Variable(name="seismic 3d var", data_type=ScalarType.FLOAT32, dimensions=[d1, d2, d3])
+    assert _get_zarr_shape(v, all_named_dims=[d1, d2, d3]) == (100, 200, 300)
+
+
+def test__get_zarr_chunks() -> None:
+    """Test for _get_zarr_chunks function."""
+    d1 = NamedDimension(name="inline", size=100)
+    d2 = NamedDimension(name="crossline", size=200)
+    d3 = NamedDimension(name="depth", size=300)
+
+    # Test 1: Variable with chunk defined in metadata
+    v = Variable(
+        name="seismic 3d var",
+        data_type=ScalarType.FLOAT32,
+        dimensions=[d1, d2, d3],
+        metadata=_to_dictionary(
+            ChunkGridMetadata(
+                chunk_grid=RegularChunkGrid(
+                    configuration=RegularChunkShape(chunk_shape=[10, 20, 30])
+                )
+            )
+        ),
+    )
+    assert _get_zarr_chunks(v, all_named_dims=[d1, d2, d3]) == (10, 20, 30)
+
+    # Test 2: Variable with no chunks defined
+    v = Variable(name="seismic 3d var", data_type=ScalarType.FLOAT32, dimensions=[d1, d2, d3])
+    assert _get_zarr_chunks(v, all_named_dims=[d1, d2, d3]) == (100, 200, 300)
+
+
+def test__get_fill_value() -> None:
+    """Test for _get_fill_value function."""
+    # Test 1: ScalarType cases - should return values from fill_value_map
+    scalar_types = [
+        ScalarType.BOOL,
+    ]
+    for scalar_type in scalar_types:
+        assert _get_fill_value(scalar_type) is None
+
+    scalar_types = [
+        ScalarType.FLOAT16,
+        ScalarType.FLOAT32,
+        ScalarType.FLOAT64,
+    ]
+    for scalar_type in scalar_types:
+        assert np_isnan(_get_fill_value(scalar_type))
+
+    scalar_types = [
+        ScalarType.UINT8,
+        ScalarType.UINT16,
+        ScalarType.UINT32,
+        ScalarType.INT8,
+        ScalarType.INT16,
+        ScalarType.INT32,
+    ]
+    for scalar_type in scalar_types:
+        assert fill_value_map[scalar_type] == _get_fill_value(scalar_type)
+
+    scalar_types = [
+        ScalarType.COMPLEX64,
+        ScalarType.COMPLEX128,
+        ScalarType.COMPLEX256,
+    ]
+    for scalar_type in scalar_types:
+        val = _get_fill_value(scalar_type)
+        assert isinstance(val, complex)
+        assert np_isnan(val.real)
+        assert np_isnan(val.imag)
+
+    # Test 2: StructuredType - should return "AAAAAAAAAAAAAAAA"
+    field = StructuredField(name="test_field", format=ScalarType.FLOAT32)
+    structured_type = StructuredType(fields=[field])
+    result_structured = _get_fill_value(structured_type)
+    assert result_structured == "AAAAAAAAAAAAAAAA"
+
+    # Test 3: String type - should return empty string
+    result_string = _get_fill_value("string_type")
+    assert result_string == ""
+
+    # Test 4: Unknown type - should return None
+    result_none = _get_fill_value(42)  # Invalid type
+    assert result_none is None
+
+    # Test 5: None input - should return None
+    result_none_input = _get_fill_value(None)
+    assert result_none_input is None
+
+
+def test__convert_compressor() -> None:
+    """Simple test for _convert_compressor function covering basic scenarios."""
+    # Test 1: None input - should return None
+    result_none = _convert_compressor(None)
+    assert result_none is None
+
+    # Test 2: mdio_Blosc compressor - should return nc_Blosc
+    result_blosc = _convert_compressor(
+        mdio_Blosc(
+            algorithm=mdio_BloscAlgorithm.LZ4,
+            level=5,
+            shuffle=mdio_BloscShuffle.AUTOSHUFFLE,
+            blocksize=1024,
+        )
+    )
+    assert isinstance(result_blosc, nc_Blosc)
+    assert result_blosc.cname == "lz4"  # BloscAlgorithm.LZ4.value
+    assert result_blosc.clevel == 5
+    assert result_blosc.shuffle == -1  # BloscShuffle.UTOSHUFFLE = -1
+    assert result_blosc.blocksize == 1024
+
+    # Test 3: mdio_Blosc with blocksize 0 - should use 0 as blocksize
+    result_blosc_zero = _convert_compressor(
+        mdio_Blosc(
+            algorithm=mdio_BloscAlgorithm.ZSTD,
+            level=3,
+            shuffle=mdio_BloscShuffle.AUTOSHUFFLE,
+            blocksize=0,
+        )
+    )
+    assert isinstance(result_blosc_zero, nc_Blosc)
+    assert result_blosc_zero.blocksize == 0
+
+    # Test 4: mdio_ZFP compressor - should return zfpy_ZFPY if available
+    zfp_compressor = mdio_ZFP(mode=mdio_ZFPMode.FIXED_RATE, tolerance=0.01, rate=8.0, precision=16)
+
+    if HAS_ZFPY:
+        result_zfp = _convert_compressor(zfp_compressor)
+        assert isinstance(result_zfp, zfpy_ZFPY)
+        assert result_zfp.mode == 1  # ZFPMode.FIXED_RATE.value = "fixed_rate"
+        assert result_zfp.tolerance == 0.01
+        assert result_zfp.rate == 8.0
+        assert result_zfp.precision == 16
+    else:
+        # Test 5: mdio_ZFP without zfpy installed - should raise ImportError
+        with pytest.raises(ImportError) as exc_info:
+            _convert_compressor(zfp_compressor)
+
+        error_message = str(exc_info.value)
+        assert "zfpy and numcodecs are required to use ZFP compression" in error_message
 
-from .helpers import make_campos_3d_acceptance_dataset
+    # Test 6: Unsupported compressor type - should raise TypeError
+    unsupported_compressor = "invalid_compressor"
+    with pytest.raises(TypeError) as exc_info:
+        _convert_compressor(unsupported_compressor)
+    error_message = str(exc_info.value)
+    assert "Unsupported compressor model" in error_message
+    assert "<class 'str'>" in error_message
 
 
-def test_to_xarray_dataset() -> None:
+def test_to_xarray_dataset(tmp_path) -> None:  # noqa: ANN001 - tmp_path is a pytest fixture
     """Test building a complete dataset."""
     dataset = (
         MDIODatasetBuilder("test_dataset")
@@ -35,16 +368,15 @@ def test_to_xarray_dataset() -> None:
 
     xr_ds = to_xarray_dataset(dataset)
 
-    file_name = "sample_dataset"
-    to_zarr(xr_ds, f"test-data/{file_name}.zarr", mode="w")
+    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
+    to_zarr(xr_ds, file_path, mode="w")
 
 
-def test_campos_3d_acceptance_to_xarray_dataset() -> None:
+def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path) -> None:  # noqa: ANN001
     """Test building a complete dataset."""
-    dataset = make_campos_3d_acceptance_dataset()
+    dataset = make_seismic_poststack_3d_acceptance_dataset()
 
     xr_ds = to_xarray_dataset(dataset)
 
-    # file_name = "XYZ"
-    file_name = f"{xr_ds.attrs['name']}"
-    to_zarr(xr_ds, f"test-data/{file_name}.zarr", mode="w")
+    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
+    to_zarr(xr_ds, file_path, mode="w")

From 7b3ba70ecc508cc28fd472390254ca47e37c1d62 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Mon, 14 Jul 2025 23:12:56 +0000
Subject: [PATCH 46/56] Update _get_fill_value for StructuredType

---
 src/mdio/schemas/v1/dataset_serializer.py | 10 ++++++++--
 tests/unit/v1/test_dataset_serializer.py  | 18 +++++++++++-------
 2 files changed, 19 insertions(+), 9 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index a8c871ac4..932816f25 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -170,8 +170,8 @@ def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     if isinstance(data_type, ScalarType):
         return fill_value_map.get(data_type)
     if isinstance(data_type, StructuredType):
-        return "AAAAAAAAAAAAAAAA"  # BUG: this does not work!!!
-    if isinstance(data_type, str):
+        return tuple(fill_value_map.get(field.format) for field in data_type.fields)
+    if isinstance(data_type, str): 
         return ""
     # If we do not have a fill value for this type, use None
     return None
@@ -222,6 +222,12 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
         # Create a custom chunk key encoding with "/" as separator
         chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
         encoding = {
+            # Is this a bug in Zarr? For datatype:  
+            #   dtype([('cdp-x', '<i4'), ('cdp-y', '<i4'), ('elevation', '<f2'), ('some_scalar', '<f2')])
+            # I specify fill_value as 
+            #   (2147483647, 2147483647, nan, nan)
+            # But the fill_value stored in .zmetadata as
+            #    "fill_value": null
             "fill_value": _get_fill_value(v.data_type),
             "chunks": chunks,
             "chunk_key_encoding": chunk_key_encoding,
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index 19e3db505..aa715e061 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -6,6 +6,7 @@
 
 import pytest
 from numpy import dtype as np_dtype
+from numpy import nan as np_nan
 from numpy import isnan as np_isnan
 
 from mdio.constants import fill_value_map
@@ -264,13 +265,16 @@ def test__get_fill_value() -> None:
         val = _get_fill_value(scalar_type)
         assert isinstance(val, complex)
         assert np_isnan(val.real)
-        assert np_isnan(val.imag)
-
-    # Test 2: StructuredType - should return "AAAAAAAAAAAAAAAA"
-    field = StructuredField(name="test_field", format=ScalarType.FLOAT32)
-    structured_type = StructuredType(fields=[field])
+        assert np_isnan(val.imag)   
+
+    # Test 2: StructuredType
+    f1 = StructuredField(name="cdp-x", format=ScalarType.INT32)
+    f2 = StructuredField(name="cdp-y", format=ScalarType.INT32)
+    f3 = StructuredField(name="elevation", format=ScalarType.FLOAT16)
+    f4 = StructuredField(name="some_scalar", format=ScalarType.FLOAT16)
+    structured_type = StructuredType(fields=[f1, f2, f3, f4])
     result_structured = _get_fill_value(structured_type)
-    assert result_structured == "AAAAAAAAAAAAAAAA"
+    assert result_structured == (2147483647, 2147483647, np_nan, np_nan)
 
     # Test 3: String type - should return empty string
     result_string = _get_fill_value("string_type")
@@ -378,5 +382,5 @@ def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path) -> None:  #
 
     xr_ds = to_xarray_dataset(dataset)
 
-    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
+    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=True)
     to_zarr(xr_ds, file_path, mode="w")

From a4ff4a988188fb5859082566c5db2f1095b98a8f Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 16 Jul 2025 20:05:30 +0000
Subject: [PATCH 47/56] Fix fill type issue for the Structured Types

---
 src/mdio/constants.py                     |  16 +--
 src/mdio/schemas/v1/dataset_serializer.py |  37 +++---
 tests/unit/v1/test_dataset_serializer.py  | 137 +++++++++++++++++++---
 3 files changed, 149 insertions(+), 41 deletions(-)

diff --git a/src/mdio/constants.py b/src/mdio/constants.py
index b6fff807c..5b8384e02 100644
--- a/src/mdio/constants.py
+++ b/src/mdio/constants.py
@@ -45,14 +45,14 @@
     ScalarType.FLOAT16: np_nan,
     ScalarType.FLOAT32: np_nan,
     ScalarType.FLOAT64: np_nan,
-    ScalarType.UINT8: 2**8 - 1,  # Max value for uint8
-    ScalarType.UINT16: 2**16 - 1,  # Max value for uint16
-    ScalarType.UINT32: 2**32 - 1,  # Max value for uint32
-    ScalarType.UINT64: 2**64 - 1,  # Max value for uint64
-    ScalarType.INT8: 2**7 - 1,  # Max value for int8
-    ScalarType.INT16: 2**15 - 1,  # Max value for int16
-    ScalarType.INT32: 2**31 - 1,  # Max value for int32
-    ScalarType.INT64: 2**63 - 1,  # Max value for int64
+    ScalarType.UINT8: UINT8_MAX,
+    ScalarType.UINT16: UINT16_MAX,
+    ScalarType.UINT32: UINT32_MAX,
+    ScalarType.UINT64: UINT64_MAX,
+    ScalarType.INT8: INT8_MAX,
+    ScalarType.INT16: INT16_MAX,
+    ScalarType.INT32: INT32_MAX,
+    ScalarType.INT64: INT64_MAX,
     ScalarType.COMPLEX64: complex(np_nan, np_nan),
     ScalarType.COMPLEX128: complex(np_nan, np_nan),
     ScalarType.COMPLEX256: complex(np_nan, np_nan),
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index 932816f25..f3dcdb169 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -2,11 +2,12 @@
 
 from collections.abc import Mapping
 
-from dask import array as dask_array
+import numpy as np
 from numcodecs import Blosc as nc_Blosc
 from numpy import dtype as np_dtype
 from xarray import DataArray as xr_DataArray
 from xarray import Dataset as xr_Dataset
+from zarr import zeros as zarr_zeros
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
 
 try:
@@ -90,15 +91,14 @@ def _get_coord_names(var: Variable) -> list[str]:
     return coord_names
 
 
-def _get_np_datatype(var: Variable) -> np_dtype:
+def _get_np_datatype(data_type: ScalarType | StructuredType) -> np_dtype:
     """Get the numpy dtype for a variable."""
-    data_type = var.data_type
     if isinstance(data_type, ScalarType):
         return np_dtype(data_type.value)
     if isinstance(data_type, StructuredType):
         return np_dtype([(f.name, f.format.value) for f in data_type.fields])
-    err = f"Unsupported data type: {type(data_type)} in variable {var.name}"
-    raise TypeError(err)
+    msg = f"Expected ScalarType or StructuredType, got {type(data_type).__name__}"
+    raise ValueError(msg)
 
 
 def _get_zarr_shape(var: Variable, all_named_dims: dict[str, NamedDimension]) -> tuple[int, ...]:
@@ -170,8 +170,9 @@ def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     if isinstance(data_type, ScalarType):
         return fill_value_map.get(data_type)
     if isinstance(data_type, StructuredType):
-        return tuple(fill_value_map.get(field.format) for field in data_type.fields)
-    if isinstance(data_type, str): 
+        d_type = _get_np_datatype(data_type)
+        return np.zeros((), dtype=d_type)
+    if isinstance(data_type, str):
         return ""
     # If we do not have a fill value for this type, use None
     return None
@@ -186,6 +187,10 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
     Args:
         mdio_ds: The source MDIO dataset to construct from.
 
+    Notes:
+        - We can't use Dask (e.g., dask_array.zeros) because of the problems with
+          structured type support. We will uze zarr.zeros instead
+
     Returns:
         The constructed dataset with proper MDIO structure and metadata.
     """
@@ -197,15 +202,16 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
     # First pass: Build all variables
     data_arrays: dict[str, xr_DataArray] = {}
     for v in mdio_ds.variables:
-        # Use dask array instead of numpy array for lazy evaluation
         shape = _get_zarr_shape(v, all_named_dims=all_named_dims)
-        dtype = _get_np_datatype(v)
+        dtype = _get_np_datatype(v.data_type)
         chunks = _get_zarr_chunks(v, all_named_dims=all_named_dims)
-        arr = dask_array.zeros(shape, dtype=dtype, chunks=chunks)
 
+        # Use zarr.zeros to create an empty array with the specified shape and dtype
+        # NOTE: zarr_format=2 is essential, to_zarr() will fail if zarr_format=2 is used
+        data = zarr_zeros(shape=shape, dtype=dtype, zarr_format=2)
         # Create a DataArray for the variable. We will set coords in the second pass
         dim_names = _get_dimension_names(v)
-        data_array = xr_DataArray(arr, dims=dim_names)
+        data_array = xr_DataArray(data, dims=dim_names)
 
         # Add array attributes
         if v.metadata is not None:
@@ -222,13 +228,8 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
         # Create a custom chunk key encoding with "/" as separator
         chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
         encoding = {
-            # Is this a bug in Zarr? For datatype:  
-            #   dtype([('cdp-x', '<i4'), ('cdp-y', '<i4'), ('elevation', '<f2'), ('some_scalar', '<f2')])
-            # I specify fill_value as 
-            #   (2147483647, 2147483647, nan, nan)
-            # But the fill_value stored in .zmetadata as
-            #    "fill_value": null
-            "fill_value": _get_fill_value(v.data_type),
+            # NOTE: See Zarr documentation on use of fill_value and _FillValue in Zarr v2 vs v3
+            "_FillValue": _get_fill_value(v.data_type),
             "chunks": chunks,
             "chunk_key_encoding": chunk_key_encoding,
             "compressor": _convert_compressor(v.compressor),
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index aa715e061..8aff471a4 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -5,9 +5,13 @@
 """Tests the schema v1 dataset_serializer public API."""
 
 import pytest
+from dask import array as dask_array
+from numpy import array as np_array
 from numpy import dtype as np_dtype
-from numpy import nan as np_nan
 from numpy import isnan as np_isnan
+from numpy import zeros as np_zeros
+from xarray import DataArray as xr_DataArray
+from zarr import zeros as zarr_zeros
 
 from mdio.constants import fill_value_map
 from mdio.schemas.chunk_grid import RegularChunkGrid
@@ -158,9 +162,7 @@ def test__get_np_datatype() -> None:
     ]
 
     for scalar_type, expected_numpy_type in scalar_type_tests:
-        variable = Variable(name="test_var", dimensions=[], data_type=scalar_type)
-
-        result = _get_np_datatype(variable)
+        result = _get_np_datatype(scalar_type)
         expected = np_dtype(expected_numpy_type)
 
         assert result == expected
@@ -176,12 +178,7 @@ def test__get_np_datatype() -> None:
         StructuredField(name="valid", format=ScalarType.BOOL),
     ]
     structured_multi = StructuredType(fields=multi_fields)
-
-    variable_multi_struct = Variable(
-        name="multi_struct_var", dimensions=[], data_type=structured_multi
-    )
-
-    result_multi = _get_np_datatype(variable_multi_struct)
+    result_multi = _get_np_datatype(structured_multi)
     expected_multi = np_dtype(
         [("x", "float64"), ("y", "float64"), ("z", "float64"), ("id", "int32"), ("valid", "bool")]
     )
@@ -254,7 +251,8 @@ def test__get_fill_value() -> None:
         ScalarType.INT32,
     ]
     for scalar_type in scalar_types:
-        assert fill_value_map[scalar_type] == _get_fill_value(scalar_type)
+        fill_value = _get_fill_value(scalar_type)
+        assert fill_value_map[scalar_type] == fill_value
 
     scalar_types = [
         ScalarType.COMPLEX64,
@@ -265,7 +263,7 @@ def test__get_fill_value() -> None:
         val = _get_fill_value(scalar_type)
         assert isinstance(val, complex)
         assert np_isnan(val.real)
-        assert np_isnan(val.imag)   
+        assert np_isnan(val.imag)
 
     # Test 2: StructuredType
     f1 = StructuredField(name="cdp-x", format=ScalarType.INT32)
@@ -273,8 +271,15 @@ def test__get_fill_value() -> None:
     f3 = StructuredField(name="elevation", format=ScalarType.FLOAT16)
     f4 = StructuredField(name="some_scalar", format=ScalarType.FLOAT16)
     structured_type = StructuredType(fields=[f1, f2, f3, f4])
-    result_structured = _get_fill_value(structured_type)
-    assert result_structured == (2147483647, 2147483647, np_nan, np_nan)
+
+    expected = np_array(
+        (0, 0, 0.0, 0.0),
+        dtype=np_dtype(
+            [("cdp-x", "<i4"), ("cdp-y", "<i4"), ("elevation", "<f2"), ("some_scalar", "<f2")]
+        ),
+    )
+    result = _get_fill_value(structured_type)
+    assert expected == result
 
     # Test 3: String type - should return empty string
     result_string = _get_fill_value("string_type")
@@ -382,5 +387,107 @@ def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path) -> None:  #
 
     xr_ds = to_xarray_dataset(dataset)
 
-    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=True)
+    file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
     to_zarr(xr_ds, file_path, mode="w")
+
+
+@pytest.mark.skip(reason="Issues serializing dask arrays of structured types to dask.")
+def test_to_zarr_dask(tmp_path) -> None:  # noqa: ANN001
+    """Test writing XArray dataset with data as dask array to Zar."""
+    # Create a data type and the fill value
+    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype_fill_value = np_zeros((), dtype=dtype)
+
+    # Use '_FillValue' instead of 'fill_value'
+    # 'fill_value' is not a valid encoding key in Zarr v2
+    my_attr_encoding = {
+        "_FillValue": dtype_fill_value,
+        "chunk_key_encoding": {"name": "v2", "separator": "/"},
+    }
+
+    # Create a dask array using the data type
+    # Do not specify encoding as the array attribute
+    data = dask_array.zeros((36,), dtype=dtype, chunks=(36,))
+    aa = xr_DataArray(name="myattr", data=data)
+
+    # Specify encoding per array
+    encoding = {"myattr": my_attr_encoding}
+    file_path = output_path(tmp_path, "to_zarr/zarr_dask", debugging=False)
+    aa.to_zarr(file_path, mode="w", zarr_format=2, encoding=encoding, compute=False)
+
+
+def test_to_zarr_zarr_zerros_1(tmp_path) -> None:  # noqa: ANN001
+    """Test writing XArray dataset with data as Zarr zero array to Zar.
+
+    Set encoding in as DataArray attributes
+    """
+    # Create a data type and the fill value
+    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype_fill_value = np_zeros((), dtype=dtype)
+
+    # Use '_FillValue' instead of 'fill_value'
+    # 'fill_value' is not a valid encoding key in Zarr v2
+    my_attr_encoding = {
+        "_FillValue": dtype_fill_value,
+        "chunk_key_encoding": {"name": "v2", "separator": "/"},
+    }
+
+    # Create a zarr array using the data type,
+    # Specify encoding as the array attribute
+    data = zarr_zeros((36, 36), dtype=dtype, zarr_format=2)
+    aa = xr_DataArray(name="myattr", data=data)
+    aa.encoding = my_attr_encoding
+
+    file_path = output_path(tmp_path, "to_zarr/zarr_zarr_zerros_1", debugging=False)
+    aa.to_zarr(file_path, mode="w", zarr_format=2, compute=False)
+
+
+def test_to_zarr_zarr_zerros_2(tmp_path) -> None:  # noqa: ANN001
+    """Test writing XArray dataset with data as Zarr zero array to Zar.
+
+    Set encoding in the to_zar method
+    """
+    # Create a data type and the fill value
+    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype_fill_value = np_zeros((), dtype=dtype)
+
+    # Use '_FillValue' instead of 'fill_value'
+    # 'fill_value' is not a valid encoding key in Zarr v2
+    my_attr_encoding = {
+        "_FillValue": dtype_fill_value,
+        "chunk_key_encoding": {"name": "v2", "separator": "/"},
+    }
+
+    # Create a zarr array using the data type,
+    # Do not specify encoding as the array attribute
+    data = zarr_zeros((36, 36), dtype=dtype, zarr_format=2)
+    aa = xr_DataArray(name="myattr", data=data)
+
+    file_path = output_path(tmp_path, "to_zarr/zarr_zarr_zerros_2", debugging=False)
+    # Specify encoding per array
+    encoding = {"myattr": my_attr_encoding}
+    aa.to_zarr(file_path, mode="w", zarr_format=2, encoding=encoding, compute=False)
+
+
+def test_to_zarr_np(tmp_path) -> None:  # noqa: ANN001
+    """Test writing XArray dataset with data as NumPy array to Zar."""
+    # Create a data type and the fill value
+    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype_fill_value = np_zeros((), dtype=dtype)
+
+    # Use '_FillValue' instead of 'fill_value'
+    # 'fill_value' is not a valid encoding key in Zarr v2
+    my_attr_encoding = {
+        "_FillValue": dtype_fill_value,
+        "chunk_key_encoding": {"name": "v2", "separator": "/"},
+    }
+
+    # Create a zarr array using the data type
+    # Do not specify encoding as the array attribute
+    data = np_zeros((36, 36), dtype=dtype)
+    aa = xr_DataArray(name="myattr", data=data)
+
+    file_path = output_path(tmp_path, "to_zarr/zarr_np", debugging=False)
+    # Specify encoding per array
+    encoding = {"myattr": my_attr_encoding}
+    aa.to_zarr(file_path, mode="w", zarr_format=2, encoding=encoding, compute=False)

From 81bfa762c8b6903a6ee7a46ab06cd1d381196c26 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Wed, 16 Jul 2025 20:43:11 +0000
Subject: [PATCH 48/56] Improve code coverage

---
 src/mdio/schemas/v1/dataset_serializer.py |  2 +-
 tests/unit/v1/test_dataset_serializer.py  | 23 ++++++++++++++++++++---
 2 files changed, 21 insertions(+), 4 deletions(-)

diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index f3dcdb169..f1d21221e 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -97,7 +97,7 @@ def _get_np_datatype(data_type: ScalarType | StructuredType) -> np_dtype:
         return np_dtype(data_type.value)
     if isinstance(data_type, StructuredType):
         return np_dtype([(f.name, f.format.value) for f in data_type.fields])
-    msg = f"Expected ScalarType or StructuredType, got {type(data_type).__name__}"
+    msg = f"Expected ScalarType or StructuredType, got '{type(data_type).__name__}'"
     raise ValueError(msg)
 
 
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index 8aff471a4..3b135f83d 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -160,6 +160,9 @@ def test__get_np_datatype() -> None:
         (ScalarType.COMPLEX128, "complex128"),
         (ScalarType.BOOL, "bool"),
     ]
+    err = "Expected ScalarType or StructuredType, got 'str'"
+    with pytest.raises(ValueError, match=err):
+        _get_np_datatype("parameter of invalid type")
 
     for scalar_type, expected_numpy_type in scalar_type_tests:
         result = _get_np_datatype(scalar_type)
@@ -194,9 +197,24 @@ def test__get_zarr_shape() -> None:
     d1 = NamedDimension(name="inline", size=100)
     d2 = NamedDimension(name="crossline", size=200)
     d3 = NamedDimension(name="depth", size=300)
+    all_named_dims = {"inline": d1, "crossline": d2, "depth": d3}
+    v1 = Variable(name="named dims var", data_type=ScalarType.FLOAT32, dimensions=[d1, d2, d3])
+    v2 = Variable(
+        name="str var", data_type=ScalarType.FLOAT32, dimensions=["inline", "crossline", "depth"]
+    )
+    Dataset(
+        variables=[v1, v2],
+        metadata=_to_dictionary(
+            [
+                DatasetInfo(
+                    name="test_dataset", api_version="1.0.0", created_on="2023-10-01T00:00:00Z"
+                )
+            ]
+        ),
+    )
 
-    v = Variable(name="seismic 3d var", data_type=ScalarType.FLOAT32, dimensions=[d1, d2, d3])
-    assert _get_zarr_shape(v, all_named_dims=[d1, d2, d3]) == (100, 200, 300)
+    assert _get_zarr_shape(v1, all_named_dims) == (100, 200, 300)
+    assert _get_zarr_shape(v2, all_named_dims) == (100, 200, 300)
 
 
 def test__get_zarr_chunks() -> None:
@@ -341,7 +359,6 @@ def test__convert_compressor() -> None:
         # Test 5: mdio_ZFP without zfpy installed - should raise ImportError
         with pytest.raises(ImportError) as exc_info:
             _convert_compressor(zfp_compressor)
-
         error_message = str(exc_info.value)
         assert "zfpy and numcodecs are required to use ZFP compression" in error_message
 

From 04476597f92721ccf2c040caba9c1e402ba5cea7 Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Thu, 17 Jul 2025 15:50:33 +0000
Subject: [PATCH 49/56] Fix spelling

---
 .devcontainer/Dockerfile.cli    | 48 +++++++++++++++++++++++++
 .devcontainer/Dockerfile.dev    | 63 +++++++++++++++++++++++++++++++++
 .devcontainer/Dockerfile.nox    | 49 +++++++++++++++++++++++++
 .devcontainer/devcontainer.json | 20 ++++++-----
 tests/unit/v1/helpers.py        |  2 +-
 5 files changed, 172 insertions(+), 10 deletions(-)
 create mode 100644 .devcontainer/Dockerfile.cli
 create mode 100644 .devcontainer/Dockerfile.dev
 create mode 100644 .devcontainer/Dockerfile.nox

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
new file mode 100644
index 000000000..f35cbac7b
--- /dev/null
+++ b/.devcontainer/Dockerfile.cli
@@ -0,0 +1,48 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# * Clone mdio-python and build a Docker image:
+#      git clone https://github.com/TGSAI/mdio-python.git
+#      cd mdio-python
+#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
+# * Run /bin/bash in the Docker container:
+#
+#
+# USAGE:
+#  docker run -it --rm --name mdio-cli mdio-cli --version
+#  docker run -it --rm --name mdio-cli mdio-cli --help
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy import \
+#     /DATA/segy_file.segy \
+#     /DATA/mdio_file.mdio \
+#     -loc 181,185 \
+#     -names inline,crossline
+#
+#  LOCAL_DATA_DIR=$(pwd); \
+#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
+#     segy export \
+#     /DATA/mdio_file.mdio \
+#     /DATA/segy_file_copy.segy
+#
+FROM python:3.13-bookworm
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
+
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install pre-commit ruff
+RUN pip install .
+
+ENTRYPOINT ["mdio"]
+CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
new file mode 100644
index 000000000..6657bf581
--- /dev/null
+++ b/.devcontainer/Dockerfile.dev
@@ -0,0 +1,63 @@
+# USAGE: 
+#   This file will be used by the VS Code DevContainer extension 
+#   to create a development environment for the mdio-python project.
+# HOW TO RUN TESTS
+#    1. Open the project in VS Code.
+#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
+#    3. Once the container is running, open a terminal in VS Code.
+#    4. Run the tests using the command: `nox -s test`.
+# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
+#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
+#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
+# NOTES: 
+#  1. The container will be run as the non-root user 'vscode' with UID 1000.
+#  2. The virtual environment will be setup at /home/vscode/venv 
+#  3. The project source code will be mounted at /workspaces/mdio-python
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
+
+# Install git for nox pre-commit
+RUN apt-get update \
+  && apt-get install -y --no-install-recommends \
+    git \
+  && rm -rf /var/lib/apt/lists/*
+
+ENV USERNAME="vscode"
+USER $USERNAME
+
+# # Add path to the user-installed packages
+# ENV PYTHONUSERBASE=/home/$USERNAME/.local
+# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
+
+WORKDIR /workspaces/mdio-python
+
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+# Initialize virtual environement in the container
+ENV VIRTUAL_ENV="/home/$USERNAME/venv"
+RUN python3 -m venv $VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+
+# installing pytest is required for VS Code Python Testing
+RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
+# install packages required to run `pre-commit run --all-files`
+RUN pip install ruff pre-commit pre-commit-hooks
+
+# Install the project in editable mode
+# This allows for live reloading of the code during development
+RUN pip install -e .
+
+# RUN uv pip install snakeviz
+
+
+
+
+
+
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
new file mode 100644
index 000000000..103673fd2
--- /dev/null
+++ b/.devcontainer/Dockerfile.nox
@@ -0,0 +1,49 @@
+# HOW TO BUILD AND RUN THIS DOCKERFILE
+# 1. Make sure you have Docker installed and running.
+# 2. Clone mdio-python and build the Docker image:
+#    git clone https://github.com/TGSAI/mdio-python.git
+#    cd mdio-python
+#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
+# 3. Run /bin/bash in the Docker container :
+#    LOCAL_DATA_DIR=$(pwd); \
+#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
+#
+# USAGE:
+#   docker run -it --rm mdio-nox --list
+#   docker run -it --rm mdio-nox -s tests-3.13
+#   docker run -it --rm mdio-nox --no-stop-on-first-error
+#
+# NOTE: nox will fail if run in the directory mounted from the host machine
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+ARG NOX_VERSION="2025.2.9"
+FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
+ARG PYTHON_VERSION
+ARG LINUX_DISTRO
+RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
+# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
+ENV USERNAME=python
+ENV USER_UID=1000
+ENV USER_GID=$USER_UID
+RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
+# Set the default non-root user
+USER $USERNAME
+
+# Add path to the user-installed packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
+
+WORKDIR /home/$USERNAME/mdio-python
+RUN pip install .
+
+# Install UV dependency manager and Nox test automator
+ARG UV_VERSION
+ARG NOX_VERSION
+RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
+RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
+
+ENTRYPOINT ["nox"]
+CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index b618a5260..9eaf41dc0 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile",
+    "dockerfile": "Dockerfile.dev",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    "post_create_script": "bash ./.devcontainer/post-install.sh"
+    // "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,8 +16,9 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-        "python.terminal.activateEnvInCurrentTerminal": true,
-        "python.defaultInterpreterPath": "/opt/venv/bin/python"
+        "python.testing.pytestArgs": ["tests"],
+        "python.testing.unittestEnabled": false,
+        "python.testing.pytestEnabled": true
       },
       "extensions": [
         "ms-python.python",
@@ -27,17 +28,18 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker"
+        "streetsidesoftware.code-spell-checker",
+        "eamodio.gitlens",
+        "visualstudioexptteam.vscodeintellicode"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
+  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
+  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // Re-use local Git configuration
-    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
+    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
   ]
 }
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index d0ebe5d79..c031f6c5e 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -129,7 +129,7 @@ def _get_coordinate(
 
 
 def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
-    """Get all coordinates from the dataset."""
+    """Get all Coordinates from the Dataset."""
     all_coords: dict[str, Coordinate] = {}
     for v in dataset.variables:
         if v.coordinates is not None:

From d08e2c43f0c10cb187ec5b0226984ff80c44b74e Mon Sep 17 00:00:00 2001
From: Dmitriy Repin <drepin@hotmail.com>
Date: Thu, 17 Jul 2025 11:19:14 -0500
Subject: [PATCH 50/56] Revert "Fix spelling"

This reverts commit 04476597f92721ccf2c040caba9c1e402ba5cea7.
---
 .devcontainer/Dockerfile.cli    | 48 -------------------------
 .devcontainer/Dockerfile.dev    | 63 ---------------------------------
 .devcontainer/Dockerfile.nox    | 49 -------------------------
 .devcontainer/devcontainer.json | 20 +++++------
 tests/unit/v1/helpers.py        |  2 +-
 5 files changed, 10 insertions(+), 172 deletions(-)
 delete mode 100644 .devcontainer/Dockerfile.cli
 delete mode 100644 .devcontainer/Dockerfile.dev
 delete mode 100644 .devcontainer/Dockerfile.nox

diff --git a/.devcontainer/Dockerfile.cli b/.devcontainer/Dockerfile.cli
deleted file mode 100644
index f35cbac7b..000000000
--- a/.devcontainer/Dockerfile.cli
+++ /dev/null
@@ -1,48 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# * Clone mdio-python and build a Docker image:
-#      git clone https://github.com/TGSAI/mdio-python.git
-#      cd mdio-python
-#      docker build -t mdio-cli -f .devcontainer/Dockerfile.cli . 
-# * Run /bin/bash in the Docker container:
-#
-#
-# USAGE:
-#  docker run -it --rm --name mdio-cli mdio-cli --version
-#  docker run -it --rm --name mdio-cli mdio-cli --help
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy import \
-#     /DATA/segy_file.segy \
-#     /DATA/mdio_file.mdio \
-#     -loc 181,185 \
-#     -names inline,crossline
-#
-#  LOCAL_DATA_DIR=$(pwd); \
-#  docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --name mdio-cli mdio-cli \
-#     segy export \
-#     /DATA/mdio_file.mdio \
-#     /DATA/segy_file_copy.segy
-#
-FROM python:3.13-bookworm
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME 
-
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install pre-commit ruff
-RUN pip install .
-
-ENTRYPOINT ["mdio"]
-CMD ["--version"]
diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
deleted file mode 100644
index 6657bf581..000000000
--- a/.devcontainer/Dockerfile.dev
+++ /dev/null
@@ -1,63 +0,0 @@
-# USAGE: 
-#   This file will be used by the VS Code DevContainer extension 
-#   to create a development environment for the mdio-python project.
-# HOW TO RUN TESTS
-#    1. Open the project in VS Code.
-#    2. Open the Command Palette (Ctrl+Shift+P) and select "Dev Containers: Reopen in Container".
-#    3. Once the container is running, open a terminal in VS Code.
-#    4. Run the tests using the command: `nox -s test`.
-# HOW TO MANUALLY BUILD AND RUN THE CONTAINER
-#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
-#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
-# NOTES: 
-#  1. The container will be run as the non-root user 'vscode' with UID 1000.
-#  2. The virtual environment will be setup at /home/vscode/venv 
-#  3. The project source code will be mounted at /workspaces/mdio-python
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
-
-# Install git for nox pre-commit
-RUN apt-get update \
-  && apt-get install -y --no-install-recommends \
-    git \
-  && rm -rf /var/lib/apt/lists/*
-
-ENV USERNAME="vscode"
-USER $USERNAME
-
-# # Add path to the user-installed packages
-# ENV PYTHONUSERBASE=/home/$USERNAME/.local
-# ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
-
-WORKDIR /workspaces/mdio-python
-
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-# Initialize virtual environement in the container
-ENV VIRTUAL_ENV="/home/$USERNAME/venv"
-RUN python3 -m venv $VIRTUAL_ENV
-ENV PATH="$VIRTUAL_ENV/bin:$PATH"
-
-# installing pytest is required for VS Code Python Testing
-RUN pip install pytest pytest-cov pytest-mock pytest-asyncio
-# install packages required to run `pre-commit run --all-files`
-RUN pip install ruff pre-commit pre-commit-hooks
-
-# Install the project in editable mode
-# This allows for live reloading of the code during development
-RUN pip install -e .
-
-# RUN uv pip install snakeviz
-
-
-
-
-
-
diff --git a/.devcontainer/Dockerfile.nox b/.devcontainer/Dockerfile.nox
deleted file mode 100644
index 103673fd2..000000000
--- a/.devcontainer/Dockerfile.nox
+++ /dev/null
@@ -1,49 +0,0 @@
-# HOW TO BUILD AND RUN THIS DOCKERFILE
-# 1. Make sure you have Docker installed and running.
-# 2. Clone mdio-python and build the Docker image:
-#    git clone https://github.com/TGSAI/mdio-python.git
-#    cd mdio-python
-#    docker build -t mdio-nox -f .devcontainer/Dockerfile.nox .
-# 3. Run /bin/bash in the Docker container :
-#    LOCAL_DATA_DIR=$(pwd); \
-#    docker run -it --rm -v $LOCAL_DATA_DIR:/DATA --entrypoint /bin/bash --name mdio-nox mdio-nox
-#
-# USAGE:
-#   docker run -it --rm mdio-nox --list
-#   docker run -it --rm mdio-nox -s tests-3.13
-#   docker run -it --rm mdio-nox --no-stop-on-first-error
-#
-# NOTE: nox will fail if run in the directory mounted from the host machine
-ARG PYTHON_VERSION="3.13"
-ARG LINUX_DISTRO="bookworm"
-ARG UV_VERSION="0.6.11"
-ARG NOX_VERSION="2025.2.9"
-FROM python:${PYTHON_VERSION}-${LINUX_DISTRO}
-ARG PYTHON_VERSION
-ARG LINUX_DISTRO
-RUN echo "Using python:${PYTHON_VERSION}-${LINUX_DISTRO}"
-# Create the user (https://code.visualstudio.com/remote/advancedcontainers/add-nonroot-user)
-ENV USERNAME=python
-ENV USER_UID=1000
-ENV USER_GID=$USER_UID
-RUN groupadd --gid $USER_GID $USERNAME && useradd --uid $USER_UID --gid $USER_GID -m $USERNAME
-# Set the default non-root user
-USER $USERNAME
-
-# Add path to the user-installed packages
-ENV PYTHONUSERBASE=/home/$USERNAME/.local
-ENV PATH="$PYTHONUSERBASE/bin:$PATH"
-
-COPY --chown=$USERNAME:$USERNAME ./ /home/$USERNAME/mdio-python
-
-WORKDIR /home/$USERNAME/mdio-python
-RUN pip install .
-
-# Install UV dependency manager and Nox test automator
-ARG UV_VERSION
-ARG NOX_VERSION
-RUN echo "Using uv: $UV_VERSION and nox: $NOX_VERSION"
-RUN python3 -m pip install uv==${UV_VERSION} nox==${NOX_VERSION} msgpack ipykernel
-
-ENTRYPOINT ["nox"]
-CMD ["--list"]
\ No newline at end of file
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index 9eaf41dc0..b618a5260 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile.dev",
+    "dockerfile": "Dockerfile",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    // "post_create_script": "bash ./.devcontainer/post-install.sh"
+    "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,9 +16,8 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-        "python.testing.pytestArgs": ["tests"],
-        "python.testing.unittestEnabled": false,
-        "python.testing.pytestEnabled": true
+        "python.terminal.activateEnvInCurrentTerminal": true,
+        "python.defaultInterpreterPath": "/opt/venv/bin/python"
       },
       "extensions": [
         "ms-python.python",
@@ -28,18 +27,17 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker",
-        "eamodio.gitlens",
-        "visualstudioexptteam.vscodeintellicode"
+        "streetsidesoftware.code-spell-checker"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
-  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
-  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
+    // Re-use local Git configuration
+    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
+    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
   ]
 }
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index c031f6c5e..d0ebe5d79 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -129,7 +129,7 @@ def _get_coordinate(
 
 
 def _get_all_coordinates(dataset: Dataset) -> list[Coordinate]:
-    """Get all Coordinates from the Dataset."""
+    """Get all coordinates from the dataset."""
     all_coords: dict[str, Coordinate] = {}
     for v in dataset.variables:
         if v.coordinates is not None:

From 657d2cf3438df71e2627a4b48de272b03e80581e Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Thu, 17 Jul 2025 13:11:48 -0500
Subject: [PATCH 51/56] extend per-file ignores for PLR2004 and remove noqa
 overrides in specific tests

---
 pyproject.toml                                       | 2 +-
 tests/integration/test_segy_import_export.py         | 4 ++--
 tests/unit/test_dimension.py                         | 2 +-
 tests/unit/v1/test_dataset_builder_add_coordinate.py | 4 ----
 tests/unit/v1/test_dataset_builder_add_dimension.py  | 4 ----
 tests/unit/v1/test_dataset_builder_add_variable.py   | 4 ----
 tests/unit/v1/test_dataset_builder_build.py          | 4 ----
 tests/unit/v1/test_dataset_builder_helpers.py        | 4 ----
 tests/unit/v1/test_dataset_serializer.py             | 4 ----
 9 files changed, 4 insertions(+), 28 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index e2f72190f..f57ecf196 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -134,7 +134,7 @@ ignore = [
 ]
 
 [tool.ruff.lint.per-file-ignores]
-"tests/*" = ["S101"]
+"tests/*" = ["S101", "PLR2004"]
 "tests/integration/test_segy_import_export_masked.py" = ["E501"]
 "docs/tutorials/*.ipynb" = ["S101"]
 
diff --git a/tests/integration/test_segy_import_export.py b/tests/integration/test_segy_import_export.py
index 9e3d0e1be..ecea8d1d2 100644
--- a/tests/integration/test_segy_import_export.py
+++ b/tests/integration/test_segy_import_export.py
@@ -272,8 +272,8 @@ class TestReader:
     def test_meta_read(self, zarr_tmp: Path) -> None:
         """Metadata reading tests."""
         mdio = MDIOReader(zarr_tmp.__str__())
-        assert mdio.binary_header["samples_per_trace"] == 1501  # noqa: PLR2004
-        assert mdio.binary_header["sample_interval"] == 2000  # noqa: PLR2004
+        assert mdio.binary_header["samples_per_trace"] == 1501
+        assert mdio.binary_header["sample_interval"] == 2000
 
     def test_grid(self, zarr_tmp: Path) -> None:
         """Grid reading tests."""
diff --git a/tests/unit/test_dimension.py b/tests/unit/test_dimension.py
index fc40da228..e5645290e 100644
--- a/tests/unit/test_dimension.py
+++ b/tests/unit/test_dimension.py
@@ -17,7 +17,7 @@ class TestDimension:
 
     def test_len(self, my_dimension: Dimension) -> None:
         """Test length method."""
-        assert len(my_dimension) == 4  # noqa: PLR2004
+        assert len(my_dimension) == 4
 
     @pytest.mark.parametrize(("index", "expected"), [(1, 12), (-1, 16), (2, 14)])
     def test_getitem(self, my_dimension: Dimension, index: int, expected: int) -> None:
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 20f686024..9d5f123b5 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_builder.add_coordinate() public API."""
 
 import pytest
diff --git a/tests/unit/v1/test_dataset_builder_add_dimension.py b/tests/unit/v1/test_dataset_builder_add_dimension.py
index ddcbd745c..112e7c9cf 100644
--- a/tests/unit/v1/test_dataset_builder_add_dimension.py
+++ b/tests/unit/v1/test_dataset_builder_add_dimension.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_builder.add_dimension() public API."""
 
 import pytest
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 6f46db501..2db85f3ca 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_builder.add_variable() public API."""
 
 import pytest
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 2a68c8337..833fad981 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_builder.build() public API."""
 
 from mdio.schemas.dtype import ScalarType
diff --git a/tests/unit/v1/test_dataset_builder_helpers.py b/tests/unit/v1/test_dataset_builder_helpers.py
index b1ab99647..619321d81 100644
--- a/tests/unit/v1/test_dataset_builder_helpers.py
+++ b/tests/unit/v1/test_dataset_builder_helpers.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_builder internal methods."""
 
 from datetime import UTC
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index 3b135f83d..e363b7ace 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -1,7 +1,3 @@
-# ruff: noqa: PLR2004
-# PLR2004 Magic value used in comparison, consider replacing `3` with a constant variable
-# The above erroneous warning is generated for every numerical assert.
-# Thus, disable it for this file
 """Tests the schema v1 dataset_serializer public API."""
 
 import pytest

From bfab1d7d19d9a50454b657bc1d533919fa5ef130 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Thu, 17 Jul 2025 13:12:09 -0500
Subject: [PATCH 52/56] Refactor tests: clarify Zarr-related test names, fix
 type hints, and clean unused `# noqa` comments.

---
 tests/unit/v1/test_dataset_serializer.py | 32 +++++++++++++-----------
 1 file changed, 17 insertions(+), 15 deletions(-)

diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index e363b7ace..f8439585e 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -1,5 +1,7 @@
 """Tests the schema v1 dataset_serializer public API."""
 
+from pathlib import Path
+
 import pytest
 from dask import array as dask_array
 from numpy import array as np_array
@@ -38,16 +40,16 @@
 from .helpers import output_path
 
 try:
-    from zfpy import ZFPY as zfpy_ZFPY  # noqa: N811
+    from zfpy import ZFPY
 
     HAS_ZFPY = True
 except ImportError:
-    zfpy_ZFPY = None  # noqa: N816
+    ZFPY = None
     HAS_ZFPY = False
 
 from numcodecs import Blosc as nc_Blosc
 
-from mdio.schemas.compressors import ZFP as mdio_ZFP  # noqa: N811
+from mdio.schemas.compressors import ZFP as MDIO_ZFP
 from mdio.schemas.compressors import Blosc as mdio_Blosc
 from mdio.schemas.compressors import BloscAlgorithm as mdio_BloscAlgorithm
 from mdio.schemas.compressors import BloscShuffle as mdio_BloscShuffle
@@ -342,11 +344,11 @@ def test__convert_compressor() -> None:
     assert result_blosc_zero.blocksize == 0
 
     # Test 4: mdio_ZFP compressor - should return zfpy_ZFPY if available
-    zfp_compressor = mdio_ZFP(mode=mdio_ZFPMode.FIXED_RATE, tolerance=0.01, rate=8.0, precision=16)
+    zfp_compressor = MDIO_ZFP(mode=mdio_ZFPMode.FIXED_RATE, tolerance=0.01, rate=8.0, precision=16)
 
     if HAS_ZFPY:
         result_zfp = _convert_compressor(zfp_compressor)
-        assert isinstance(result_zfp, zfpy_ZFPY)
+        assert isinstance(result_zfp, ZFPY)
         assert result_zfp.mode == 1  # ZFPMode.FIXED_RATE.value = "fixed_rate"
         assert result_zfp.tolerance == 0.01
         assert result_zfp.rate == 8.0
@@ -367,7 +369,7 @@ def test__convert_compressor() -> None:
     assert "<class 'str'>" in error_message
 
 
-def test_to_xarray_dataset(tmp_path) -> None:  # noqa: ANN001 - tmp_path is a pytest fixture
+def test_to_xarray_dataset(tmp_path: Path) -> None:
     """Test building a complete dataset."""
     dataset = (
         MDIODatasetBuilder("test_dataset")
@@ -394,7 +396,7 @@ def test_to_xarray_dataset(tmp_path) -> None:  # noqa: ANN001 - tmp_path is a py
     to_zarr(xr_ds, file_path, mode="w")
 
 
-def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path) -> None:  # noqa: ANN001
+def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path: Path) -> None:
     """Test building a complete dataset."""
     dataset = make_seismic_poststack_3d_acceptance_dataset()
 
@@ -405,8 +407,8 @@ def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path) -> None:  #
 
 
 @pytest.mark.skip(reason="Issues serializing dask arrays of structured types to dask.")
-def test_to_zarr_dask(tmp_path) -> None:  # noqa: ANN001
-    """Test writing XArray dataset with data as dask array to Zar."""
+def test_to_zarr_dask(tmp_path: Path) -> None:
+    """Test writing XArray dataset with data as dask array to Zarr."""
     # Create a data type and the fill value
     dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)
@@ -429,8 +431,8 @@ def test_to_zarr_dask(tmp_path) -> None:  # noqa: ANN001
     aa.to_zarr(file_path, mode="w", zarr_format=2, encoding=encoding, compute=False)
 
 
-def test_to_zarr_zarr_zerros_1(tmp_path) -> None:  # noqa: ANN001
-    """Test writing XArray dataset with data as Zarr zero array to Zar.
+def test_to_zarr_from_zarr_zeros_1(tmp_path: Path) -> None:
+    """Test writing XArray dataset with data as Zarr zero array to Zarr.
 
     Set encoding in as DataArray attributes
     """
@@ -455,8 +457,8 @@ def test_to_zarr_zarr_zerros_1(tmp_path) -> None:  # noqa: ANN001
     aa.to_zarr(file_path, mode="w", zarr_format=2, compute=False)
 
 
-def test_to_zarr_zarr_zerros_2(tmp_path) -> None:  # noqa: ANN001
-    """Test writing XArray dataset with data as Zarr zero array to Zar.
+def test_to_zarr_from_zarr_zeros_2(tmp_path: Path) -> None:
+    """Test writing XArray dataset with data as Zarr zero array to Zarr.
 
     Set encoding in the to_zar method
     """
@@ -482,8 +484,8 @@ def test_to_zarr_zarr_zerros_2(tmp_path) -> None:  # noqa: ANN001
     aa.to_zarr(file_path, mode="w", zarr_format=2, encoding=encoding, compute=False)
 
 
-def test_to_zarr_np(tmp_path) -> None:  # noqa: ANN001
-    """Test writing XArray dataset with data as NumPy array to Zar."""
+def test_to_zarr_from_np(tmp_path: Path) -> None:
+    """Test writing XArray dataset with data as NumPy array to Zarr."""
     # Create a data type and the fill value
     dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)

From 5878e97cc15371a5c69c8b4bbc346070269fa0cd Mon Sep 17 00:00:00 2001
From: Dima From Texas <34629861+dmitriyrepin@users.noreply.github.com>
Date: Mon, 21 Jul 2025 20:36:39 -0500
Subject: [PATCH 53/56] MDIO v1 Templates and Template Registry (#573)

* Templates and TemplateRegistry

* Fix pre-commit issues

* Rever dev container changes

* PR Review: address issues

* PR Review: register default templates at registry initialization
---
 docs/index.md                                 |   1 +
 docs/template_registry.md                     | 254 +++++++++++
 .../v1/templates/abstract_dataset_template.py | 152 +++++++
 .../v1/templates/seismic_2d_poststack.py      |  29 ++
 .../v1/templates/seismic_3d_poststack.py      |  29 ++
 .../v1/templates/seismic_3d_prestack_cdp.py   |  29 ++
 .../v1/templates/seismic_3d_prestack_shot.py  |  63 +++
 .../schemas/v1/templates/template_registry.py | 212 ++++++++++
 tests/unit/v1/helpers.py                      |   4 +-
 .../v1/templates/test_seismic_2d_poststack.py | 192 +++++++++
 .../v1/templates/test_seismic_3d_poststack.py | 182 ++++++++
 .../templates/test_seismic_3d_prestack_cdp.py | 192 +++++++++
 .../test_seismic_3d_prestack_shot.py          | 244 +++++++++++
 .../v1/templates/test_seismic_templates.py    |  59 +++
 .../v1/templates/test_template_registry.py    | 395 ++++++++++++++++++
 tests/unit/v1/test_dataset_builder_build.py   |   4 +-
 tests/unit/v1/test_dataset_serializer.py      |   2 +-
 17 files changed, 2038 insertions(+), 5 deletions(-)
 create mode 100644 docs/template_registry.md
 create mode 100644 src/mdio/schemas/v1/templates/abstract_dataset_template.py
 create mode 100644 src/mdio/schemas/v1/templates/seismic_2d_poststack.py
 create mode 100644 src/mdio/schemas/v1/templates/seismic_3d_poststack.py
 create mode 100644 src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
 create mode 100644 src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
 create mode 100644 src/mdio/schemas/v1/templates/template_registry.py
 create mode 100644 tests/unit/v1/templates/test_seismic_2d_poststack.py
 create mode 100644 tests/unit/v1/templates/test_seismic_3d_poststack.py
 create mode 100644 tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
 create mode 100644 tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
 create mode 100644 tests/unit/v1/templates/test_seismic_templates.py
 create mode 100644 tests/unit/v1/templates/test_template_registry.py

diff --git a/docs/index.md b/docs/index.md
index ba4db72de..da8408e32 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -35,6 +35,7 @@ data_models/dimensions
 data_models/chunk_grids
 data_models/data_types
 data_models/compressors
+template_registry
 ```
 
 ```{toctree}
diff --git a/docs/template_registry.md b/docs/template_registry.md
new file mode 100644
index 000000000..3b51de811
--- /dev/null
+++ b/docs/template_registry.md
@@ -0,0 +1,254 @@
+# Template Registry Singleton
+
+A thread-safe singleton registry for managing dataset templates in MDIO applications.
+
+## Overview
+
+The `TemplateRegistry` implements the singleton pattern to ensure there's only one instance managing all dataset templates throughout the application lifecycle. This provides a centralized registry for template management with thread-safe operations.
+
+## Features
+
+- **Singleton Pattern**: Ensures only one registry instance exists
+- **Thread Safety**: All operations are thread-safe using locks
+- **Global Access**: Convenient global functions for common operations
+- **Advanced Support**: Reset functionality for environment re-usability.
+- **Default Templates**: The registry is instantiated with the default set of templates:
+  - PostStack2DTime
+  - PostStack3DTime
+  - PreStackCdpGathers3DTime
+  - PreStackShotGathers3DTime
+  - PostStack2DDepth
+  - PostStack3DDepth
+  - PreStackCdpGathers3DDepth
+  - PreStackShotGathers3DDepth
+
+## Usage
+
+### Basic Usage
+
+```python
+from mdio.schemas.v1.templates.template_registry import TemplateRegistry
+
+# Get the singleton instance
+registry = TemplateRegistry()
+
+# Or use the class method
+registry = TemplateRegistry.get_instance()
+
+# Register a template
+template = MyDatasetTemplate()
+template_name=registry.register(template)
+print(f"Registered template named {template_name}")
+
+# Retrieve a template using a well-known name
+template = registry.get("my_template")
+# Retrieve a template using the name returned when the template was registered
+template = registry.get(template_name)
+
+# Check if template exists
+if registry.is_registered("my_template"):
+    print("Template is registered")
+
+# List all templates
+template_names = registry.list_all_templates()
+```
+
+### Global Functions
+
+For convenience, you can use global functions that operate on the singleton instance:
+
+```python
+from mdio.schemas.v1.templates.template_registry import (
+    register_template,
+    get_template,
+    is_template_registered,
+    list_templates
+)
+
+# Register a template globally
+register_template(Seismic3DTemplate())
+
+# Get a template
+template = get_template("seismic_3d")
+
+# Check registration
+if is_template_registered("seismic_3d"):
+    print("Template available")
+
+# List all registered templates
+templates = list_templates()
+```
+
+### Multiple Instantiation
+
+The singleton pattern ensures all instantiations return the same object:
+
+```python
+registry1 = TemplateRegistry()
+registry2 = TemplateRegistry()
+registry3 = TemplateRegistry.get_instance()
+
+# All variables point to the same instance
+assert registry1 is registry2 is registry3
+```
+
+## API Reference
+
+### Core Methods
+
+#### `register(instance: AbstractDatasetTemplate) -> str`
+
+Registers a template instance and returns its normalized name.
+
+- **Parameters:**
+  - `instance`: Template instance implementing `AbstractDatasetTemplate`
+- **Returns:** The template name
+- **Raises:** `ValueError` if template name is already registered
+
+#### `get(template_name: str) -> AbstractDatasetTemplate`
+
+Retrieves a registered template by name.
+
+- **Parameters:**
+  - `template_name`: Name of the template (case-insensitive)
+- **Returns:** The registered template instance
+- **Raises:** `KeyError` if template is not registered
+
+#### `unregister(template_name: str) -> None`
+
+Removes a template from the registry.
+
+- **Parameters:**
+  - `template_name`: Name of the template to remove
+- **Raises:** `KeyError` if template is not registered
+
+#### `is_registered(template_name: str) -> bool`
+
+Checks if a template is registered.
+
+- **Parameters:**
+  - `template_name`: Name of the template to check
+- **Returns:** `True` if template is registered, `False` otherwise
+
+#### `list_all_templates() -> List[str]`
+
+Returns a list of all registered template names.
+
+- **Returns:** List of template names
+
+#### `clear() -> None`
+
+Removes all registered templates. Useful for testing.
+
+### Class Methods
+
+#### `get_instance() -> TemplateRegistry`
+
+Alternative way to get the singleton instance.
+
+- **Returns:** The singleton registry instance
+
+### Global Functions
+
+#### `get_template_registry() -> TemplateRegistry`
+
+Returns the global singleton registry instance.
+
+#### `register_template(template: AbstractDatasetTemplate) -> str`
+
+Registers a template in the global registry.
+
+#### `get_template(name: str) -> AbstractDatasetTemplate`
+
+Gets a template from the global registry.
+
+#### `is_template_registered(name: str) -> bool`
+
+Checks if a template is registered in the global registry.
+
+#### `list_templates() -> List[str]`
+
+Lists all templates in the global registry.
+
+## Thread Safety
+
+All operations on the registry are thread-safe:
+
+```python
+import threading
+
+def register_templates():
+    registry = TemplateRegistry()
+    for i in range(10):
+        template = MyTemplate(f"template_{i}")
+        registry.register(template)
+
+# Multiple threads can safely access the registry
+threads = [threading.Thread(target=register_templates) for _ in range(5)]
+for thread in threads:
+    thread.start()
+for thread in threads:
+    thread.join()
+```
+
+## Best Practices
+
+1. **Use Global Functions**: For simple operations, prefer the global convenience functions
+2. **Register Early**: Register all templates during application startup
+3. **Thread Safety**: The registry is thread-safe, but individual templates may not be
+4. **Testing Isolation**: Always reset the singleton in test setup/teardown
+
+## Example: Complete Template Management
+
+```python
+from mdio.schemas.v1.templates.template_registry import TemplateRegistry
+from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack_time import Seismic3DPostStackTimeTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack import Seismic3DPreStackTemplate
+
+def setup_templates():
+    """Register MDIO templates runtime.
+    Custom templates can be created in external projects and added without modifying the MDIO library code
+    """
+    # Use strongly-typed template
+    template_name = TemplateRegistry.register(Seismic3DPostStackTimeTemplate())
+    print(f"Registered template named {template_name}")
+    # Use parametrized template
+    template_name = TemplateRegistry.register(Seismic3DPostStackTemplate("Depth"))
+    print(f"Registered template named {template_name}")
+    template_name = TemplateRegistry.register(Seismic3DPreStackTemplate())
+    print(f"Registered template named {template_name}")
+
+    print(f"Registered templates: {list_templates()}")
+
+# Application startup
+setup_standard_templates()
+
+# Later in the application
+template = TemplateRegistry().get_template("PostStack3DDepth")
+dataset = template.create_dataset(name="Seismic 3d m/m/ft",
+                                  sizes = [256, 512, 384]
+                                  coord_units = [
+                                    AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER)),
+                                    AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER)),
+                                    AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))]
+```
+
+## Error Handling
+
+The registry provides clear error messages:
+
+```python
+# Template not registered
+try:
+    template = get_template("nonexistent")
+except KeyError as e:
+    print(f"Error: {e}")  # "Template 'nonexistent' is not registered."
+
+# Duplicate registration
+try:
+    register_template("duplicate", template1)
+    register_template("duplicate", template2)
+except ValueError as e:
+    print(f"Error: {e}")  # "Template 'duplicate' is already registered."
+```
diff --git a/src/mdio/schemas/v1/templates/abstract_dataset_template.py b/src/mdio/schemas/v1/templates/abstract_dataset_template.py
new file mode 100644
index 000000000..776a65ce0
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/abstract_dataset_template.py
@@ -0,0 +1,152 @@
+"""Template method pattern implementation for MDIO v1 dataset template."""
+
+from abc import ABC
+from abc import abstractmethod
+
+from mdio.schemas import compressors
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.chunk_grid import RegularChunkShape
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import ChunkGridMetadata
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.dataset import Dataset
+from mdio.schemas.v1.dataset_builder import MDIODatasetBuilder
+from mdio.schemas.v1.units import AllUnits
+
+
+class AbstractDatasetTemplate(ABC):
+    """Abstract base class that defines the template method for Dataset building factory.
+
+    The template method defines the skeleton of the data processing algorithm,
+    while allowing subclasses to override specific steps.
+    """
+
+    def __init__(self, domain: str = "") -> None:
+        # Template attributes to be overridden by subclasses
+        # Domain of the seismic data, e.g. "time" or "depth"
+        self._trace_domain = domain.lower()
+        # Names of all coordinate dimensions in the dataset
+        # e.g. ["cdp"] for 2D post-stack depth
+        # e.g. ["inline", "crossline"] for 3D post-stack
+        # e.g. ["inline", "crossline"] for 3D pre-stack CDP gathers
+        # Note: For pre-stack Shot gathers, the coordinates are defined differently
+        #       and are not directly tied to _coord_dim_names.
+        self._coord_dim_names = []
+        # Names of all dimensions in the dataset
+        # e.g. ["cdp", "depth"] for 2D post-stack depth
+        # e.g. ["inline", "crossline", "depth"] for 3D post-stack depth
+        # e.g. ["inline", "crossline", "offset", "depth"] for 3D pre-stack depth CPD gathers
+        # e.g. ["shot_point", "cable", "channel", "time"] for 3D pre-stack time Shot gathers
+        self._dim_names = []
+        # Names of all coordinates in the dataset
+        # e.g. ["cdp-x", "cdp-y"] for 2D post-stack depth
+        # e.g. ["cdp-x", "cdp-y"] for 3D post-stack depth
+        # e.g. ["cdp-x", "cdp-y"] for 3D pre-stack CPD depth
+        # e.g. ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"] for 3D pre-stack
+        #      time Shot gathers
+        self._coord_names = []
+        # Name of the variable in the dataset
+        # e.g. "StackedAmplitude" for 2D post-stack depth
+        # e.g. "StackedAmplitude" for 3D post-stack depth
+        # e.g. "AmplitudeCDP" for 3D pre-stack CPD depth
+        # e.g. "AmplitudeShot" for 3D pre-stack time Shot gathers
+        self._var_name = ""
+        # Chunk shape for the variable in the dataset
+        # e.g. [1024, 1024] for 2D post-stack depth
+        # e.g. [128, 128, 128] for 3D post-stack depth
+        # e.g. [1, 1, 512, 4096] for 3D pre-stack CPD depth
+        # e.g. [1, 1, 512, 4096] for 3D pre-stack time Shot gathers
+        self._var_chunk_shape = []
+
+        # Variables instantiated when build_dataset() is called
+        self._builder: MDIODatasetBuilder = None
+        # Sizes of the dimensions in the dataset, to be set when build_dataset() is called
+        self._dim_sizes = []
+        # Horizontal units for the coordinates (e.g, "m", "ft"), to be set when
+        # build_dataset() is called
+        self._coord_units = []
+
+    def build_dataset(self, name: str, sizes: list[int], coord_units: list[AllUnits]) -> Dataset:
+        """Template method that builds the dataset.
+
+        Args:
+            name: The name of the dataset.
+            sizes: The sizes of the dimensions.
+            coord_units: The units for the coordinates.
+
+        Returns:
+            Dataset: The constructed dataset
+        """
+        self._dim_sizes = sizes
+        self._coord_units = coord_units
+
+        self._builder = MDIODatasetBuilder(name=name, attributes=self._load_dataset_attributes())
+        self._add_dimensions()
+        self._add_coordinates()
+        self._add_variables()
+        return self._builder.build()
+
+    def get_name(self) -> str:
+        """Returns the name of the template."""
+        return self._get_name()
+
+    @abstractmethod
+    def _get_name(self) -> str:
+        """Abstract method to get the name of the template.
+
+        Must be implemented by subclasses.
+
+        Returns:
+            str: The name of the template
+        """
+
+    @abstractmethod
+    def _load_dataset_attributes(self) -> UserAttributes:
+        """Abstract method to load dataset attributes.
+
+        Must be implemented by subclasses.
+
+        Returns:
+            UserAttributes: The dataset attributes
+        """
+
+    def _add_dimensions(self) -> None:
+        """A virtual method that can be overwritten by subclasses to add custom dimensions.
+
+        Uses the class field 'builder' to add dimensions to the dataset.
+        """
+        for i in range(len(self._dim_names)):
+            self._builder.add_dimension(self._dim_names[i], self._dim_sizes[i])
+
+    def _add_coordinates(self) -> None:
+        """A virtual method that can be overwritten by subclasses to add custom coordinates.
+
+        Uses the class field 'builder' to add coordinates to the dataset.
+        """
+        for i in range(len(self._coord_names)):
+            self._builder.add_coordinate(
+                self._coord_names[i],
+                dimensions=self._coord_dim_names,
+                data_type=ScalarType.FLOAT64,
+                metadata_info=[self._coord_units],
+            )
+
+    def _add_variables(self) -> None:
+        """A virtual method that can be overwritten by subclasses to add custom variables.
+
+        Uses the class field 'builder' to add variables to the dataset.
+        """
+        self._builder.add_variable(
+            name=self._var_name,
+            dimensions=self._dim_names,
+            data_type=ScalarType.FLOAT32,
+            compressor=compressors.Blosc(algorithm=compressors.BloscAlgorithm.ZSTD),
+            coordinates=self._coord_names,
+            metadata_info=[
+                ChunkGridMetadata(
+                    chunk_grid=RegularChunkGrid(
+                        configuration=RegularChunkShape(chunk_shape=self._var_chunk_shape)
+                    )
+                )
+            ],
+        )
diff --git a/src/mdio/schemas/v1/templates/seismic_2d_poststack.py b/src/mdio/schemas/v1/templates/seismic_2d_poststack.py
new file mode 100644
index 000000000..4f0d81b68
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/seismic_2d_poststack.py
@@ -0,0 +1,29 @@
+"""Seismic2DPostStackTemplate MDIO v1 dataset templates."""
+
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+
+
+class Seismic2DPostStackTemplate(AbstractDatasetTemplate):
+    """Seismic post-stack 2D time or depth Dataset template."""
+
+    def __init__(self, domain: str):
+        super().__init__(domain=domain)
+
+        self._coord_dim_names = ["cdp"]
+        self._dim_names = [*self._coord_dim_names, self._trace_domain]
+        self._coord_names = ["cdp-x", "cdp-y"]
+        self._var_name = "StackedAmplitude"
+        self._var_chunk_shape = [1024, 1024]
+
+    def _get_name(self) -> str:
+        return f"PostStack2D{self._trace_domain.capitalize()}"
+
+    def _load_dataset_attributes(self) -> UserAttributes:
+        return UserAttributes(
+            attributes={
+                "surveyDimensionality": "2D",
+                "ensembleType": "line",
+                "processingStage": "post-stack",
+            }
+        )
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_poststack.py b/src/mdio/schemas/v1/templates/seismic_3d_poststack.py
new file mode 100644
index 000000000..3fd3950a3
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/seismic_3d_poststack.py
@@ -0,0 +1,29 @@
+"""Seismic3DPostStackTemplate MDIO v1 dataset templates."""
+
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+
+
+class Seismic3DPostStackTemplate(AbstractDatasetTemplate):
+    """Seismic post-stack 3D time or depth Dataset template."""
+
+    def __init__(self, domain: str):
+        super().__init__(domain=domain)
+        # Template attributes to be overridden by subclasses
+        self._coord_dim_names = ["inline", "crossline"]
+        self._dim_names = [*self._coord_dim_names, self._trace_domain]
+        self._coord_names = ["cdp-x", "cdp-y"]
+        self._var_name = "StackedAmplitude"
+        self._var_chunk_shape = [128, 128, 128]
+
+    def _get_name(self) -> str:
+        return f"PostStack3D{self._trace_domain.capitalize()}"
+
+    def _load_dataset_attributes(self) -> UserAttributes:
+        return UserAttributes(
+            attributes={
+                "surveyDimensionality": "3D",
+                "ensembleType": "line",
+                "processingStage": "post-stack",
+            }
+        )
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py b/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
new file mode 100644
index 000000000..fa95729b8
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
@@ -0,0 +1,29 @@
+"""Seismic3DPreStackCDPTemplate MDIO v1 dataset templates."""
+
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+
+
+class Seismic3DPreStackCDPTemplate(AbstractDatasetTemplate):
+    """Seismic CDP pre-stack 3D time or depth Dataset template."""
+
+    def __init__(self, domain: str):
+        super().__init__(domain=domain)
+
+        self._coord_dim_names = ["inline", "crossline"]
+        self._dim_names = [*self._coord_dim_names, "offset", self._trace_domain]
+        self._coord_names = ["cdp-x", "cdp-y"]
+        self._var_name = "AmplitudeCDP"
+        self._var_chunk_shape = [1, 1, 512, 4096]
+
+    def _get_name(self) -> str:
+        return f"PreStackCdpGathers3D{self._trace_domain.capitalize()}"
+
+    def _load_dataset_attributes(self) -> UserAttributes:
+        return UserAttributes(
+            attributes={
+                "surveyDimensionality": "3D",
+                "ensembleType": "cdp",
+                "processingStage": "pre-stack",
+            }
+        )
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py b/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
new file mode 100644
index 000000000..a39331276
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
@@ -0,0 +1,63 @@
+"""Seismic3DPreStackShotTemplate MDIO v1 dataset templates."""
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.metadata import UserAttributes
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+from mdio.schemas.v1.units import AllUnits
+
+
+class Seismic3DPreStackShotTemplate(AbstractDatasetTemplate):
+    """Seismic Shot pre-stack 3D time or depth Dataset template."""
+
+    def __init__(self, domain: str):
+        super().__init__(domain=domain)
+
+        self._coord_dim_names = []  # Custom coordinate definition for shot gathers
+        self._dim_names = ["shot_point", "cable", "channel", self._trace_domain]
+        self._coord_names = ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
+        self._var_name = "AmplitudeShot"
+        self._var_chunk_shape = [1, 1, 512, 4096]
+
+    def _get_name(self) -> str:
+        return f"PreStackShotGathers3D{self._trace_domain.capitalize()}"
+
+    def _load_dataset_attributes(self) -> UserAttributes:
+        return UserAttributes(
+            attributes={
+                "surveyDimensionality": "3D",
+                "ensembleType": "shot",
+                "processingStage": "pre-stack",
+            }
+        )
+
+    def _add_coordinates(self) -> None:
+        self._builder.add_coordinate(
+            "gun",
+            dimensions=["shot_point"],
+            data_type=ScalarType.UINT8,
+            metadata_info=[AllUnits(units_v1=None)],
+        )
+        self._builder.add_coordinate(
+            "shot-x",
+            dimensions=["shot_point"],
+            data_type=ScalarType.FLOAT64,
+            metadata_info=[self._coord_units[0]],
+        )
+        self._builder.add_coordinate(
+            "shot-y",
+            dimensions=["shot_point"],
+            data_type=ScalarType.FLOAT64,
+            metadata_info=[self._coord_units[1]],
+        )
+        self._builder.add_coordinate(
+            "receiver-x",
+            dimensions=["shot_point", "cable", "channel"],
+            data_type=ScalarType.FLOAT64,
+            metadata_info=[self._coord_units[0]],
+        )
+        self._builder.add_coordinate(
+            "receiver-y",
+            dimensions=["shot_point", "cable", "channel"],
+            data_type=ScalarType.FLOAT64,
+            metadata_info=[self._coord_units[1]],
+        )
diff --git a/src/mdio/schemas/v1/templates/template_registry.py b/src/mdio/schemas/v1/templates/template_registry.py
new file mode 100644
index 000000000..c674b0c20
--- /dev/null
+++ b/src/mdio/schemas/v1/templates/template_registry.py
@@ -0,0 +1,212 @@
+"""Template registry for MDIO v1 dataset templates."""
+
+import threading
+from typing import Optional
+
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+from mdio.schemas.v1.templates.seismic_2d_poststack import Seismic2DPostStackTemplate
+from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack_cdp import Seismic3DPreStackCDPTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack_shot import Seismic3DPreStackShotTemplate
+
+
+class TemplateRegistry:
+    """A thread-safe singleton registry for dataset templates."""
+
+    _instance: Optional["TemplateRegistry"] = None
+    _lock = threading.RLock()
+    _initialized = False
+
+    def __new__(cls) -> "TemplateRegistry":
+        """Create or return the singleton instance.
+
+        Uses double-checked locking pattern to ensure thread safety.
+
+        Returns:
+            The singleton instance of TemplateRegistry.
+        """
+        if cls._instance is None:
+            with cls._lock:
+                # Double-checked locking pattern
+                if cls._instance is None:
+                    cls._instance = super().__new__(cls)
+        return cls._instance
+
+    def __init__(self) -> None:
+        if not self._initialized:
+            with self._lock:
+                if not self._initialized:
+                    self._templates: dict[str, AbstractDatasetTemplate] = {}
+                    self._registry_lock = threading.RLock()
+                    self._register_default_templates()
+                    TemplateRegistry._initialized = True
+
+    def register(self, instance: AbstractDatasetTemplate) -> str:
+        """Register a template instance by its name.
+
+        Args:
+            instance: An instance of template to register.
+
+        Returns:
+            The name of the registered template.
+
+        Raises:
+            ValueError: If the template name is already registered.
+        """
+        with self._registry_lock:
+            name = instance.get_name()
+            if name in self._templates:
+                err = f"Template '{name}' is already registered."
+                raise ValueError(err)
+            self._templates[name] = instance
+        return name
+
+    def _register_default_templates(self) -> None:
+        """Register default templates if needed.
+
+        This method can be overridden by subclasses to register default templates.
+        """
+        self.register(Seismic2DPostStackTemplate("time"))
+        self.register(Seismic2DPostStackTemplate("depth"))
+
+        self.register(Seismic3DPostStackTemplate("time"))
+        self.register(Seismic3DPostStackTemplate("depth"))
+
+        self.register(Seismic3DPreStackCDPTemplate("time"))
+        self.register(Seismic3DPreStackCDPTemplate("depth"))
+
+        self.register(Seismic3DPreStackShotTemplate("time"))
+        self.register(Seismic3DPreStackShotTemplate("depth"))
+
+    def get(self, template_name: str) -> AbstractDatasetTemplate:
+        """Get a template from the registry by its name.
+
+        Args:
+            template_name: The name of the template to retrieve.
+
+        Returns:
+            The template instance if found.
+
+        Raises:
+            KeyError: If the template is not registered.
+        """
+        with self._registry_lock:
+            name = template_name
+            if name not in self._templates:
+                err = f"Template '{name}' is not registered."
+                raise KeyError(err)
+            return self._templates[name]
+
+    def unregister(self, template_name: str) -> None:
+        """Unregister a template from the registry.
+
+        Args:
+            template_name: The name of the template to unregister.
+
+        Raises:
+            KeyError: If the template is not registered.
+        """
+        with self._registry_lock:
+            name = template_name
+            if name not in self._templates:
+                err_msg = f"Template '{name}' is not registered."
+                raise KeyError(err_msg)
+            del self._templates[name]
+
+    def is_registered(self, template_name: str) -> bool:
+        """Check if a template is registered in the registry.
+
+        Args:
+            template_name: The name of the template to check.
+
+        Returns:
+            True if the template is registered, False otherwise.
+        """
+        with self._registry_lock:
+            name = template_name
+            return name in self._templates
+
+    def list_all_templates(self) -> list[str]:
+        """Get all registered template names.
+
+        Returns:
+            A list of all registered template names.
+        """
+        with self._registry_lock:
+            return list(self._templates.keys())
+
+    def clear(self) -> None:
+        """Clear all registered templates (useful for testing)."""
+        with self._registry_lock:
+            self._templates.clear()
+
+    @classmethod
+    def get_instance(cls) -> "TemplateRegistry":
+        """Get the singleton instance (alternative to constructor).
+
+        Returns:
+            The singleton instance of TemplateRegistry.
+        """
+        return cls()
+
+    @classmethod
+    def _reset_instance(cls) -> None:
+        """Reset the singleton instance (useful for testing)."""
+        with cls._lock:
+            cls._instance = None
+            cls._initialized = False
+
+
+# Global convenience functions
+def get_template_registry() -> TemplateRegistry:
+    """Get the global template registry instance.
+
+    Returns:
+        The singleton instance of TemplateRegistry.
+    """
+    return TemplateRegistry.get_instance()
+
+
+def register_template(template: AbstractDatasetTemplate) -> str:
+    """Register a template in the global registry.
+
+    Args:
+        template: An instance of AbstractDatasetTemplate to register.
+
+    Returns:
+        The name of the registered template.
+    """
+    return get_template_registry().register(template)
+
+
+def get_template(name: str) -> AbstractDatasetTemplate:
+    """Get a template from the global registry.
+
+    Args:
+        name: The name of the template to retrieve.
+
+    Returns:
+        The template instance if found.
+    """
+    return get_template_registry().get(name)
+
+
+def is_template_registered(name: str) -> bool:
+    """Check if a template is registered in the global registry.
+
+    Args:
+        name: The name of the template to check.
+
+    Returns:
+        True if the template is registered, False otherwise.
+    """
+    return get_template_registry().is_registered(name)
+
+
+def list_templates() -> list[str]:
+    """List all registered template names.
+
+    Returns:
+        A list of all registered template names.
+    """
+    return get_template_registry().list_all_templates()
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index d0ebe5d79..f9d209690 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -155,10 +155,10 @@ def output_path(file_dir: str, file_name: str, debugging: bool = False) -> str:
     return file_path
 
 
-def make_seismic_poststack_3d_acceptance_dataset() -> Dataset:
+def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
     """Create in-memory Seismic PostStack 3D Acceptance dataset."""
     ds = MDIODatasetBuilder(
-        "campos_3d",
+        dataset_name,
         attributes=UserAttributes(
             attributes={
                 "textHeader": [
diff --git a/tests/unit/v1/templates/test_seismic_2d_poststack.py b/tests/unit/v1/templates/test_seismic_2d_poststack.py
new file mode 100644
index 000000000..79f795854
--- /dev/null
+++ b/tests/unit/v1/templates/test_seismic_2d_poststack.py
@@ -0,0 +1,192 @@
+"""Unit tests for Seismic2DPostStackTemplate."""
+
+from tests.unit.v1.helpers import validate_variable
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.v1.templates.seismic_2d_poststack import Seismic2DPostStackTemplate
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import TimeUnitEnum
+from mdio.schemas.v1.units import TimeUnitModel
+
+_UNIT_METER = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+_UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
+
+
+class TestSeismic2DPostStackTemplate:
+    """Unit tests for Seismic2DPostStackTemplate."""
+
+    def test_configuration_depth(self) -> None:
+        """Test configuration of Seismic2DPostStackTemplate with depth domain."""
+        t = Seismic2DPostStackTemplate("depth")
+
+        # Template attributes
+        assert t._trace_domain == "depth"
+        assert t._coord_dim_names == ["cdp"]
+        assert t._dim_names == ["cdp", "depth"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_name == "StackedAmplitude"
+        assert t._var_chunk_shape == [1024, 1024]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        # Verify dataset attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "2D",
+            "ensembleType": "line",
+            "processingStage": "post-stack",
+        }
+
+    def test_configuration_time(self) -> None:
+        """Test configuration of Seismic2DPostStackTemplate with time domain."""
+        t = Seismic2DPostStackTemplate("time")
+
+        # Template attributes
+        assert t._trace_domain == "time"
+        assert t._coord_dim_names == ["cdp"]
+        assert t._dim_names == ["cdp", "time"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_name == "StackedAmplitude"
+        assert t._var_chunk_shape == [1024, 1024]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+    def test_domain_case_handling(self) -> None:
+        """Test that domain parameter handles different cases correctly."""
+        # Test uppercase
+        t1 = Seismic2DPostStackTemplate("ELEVATION")
+        assert t1._trace_domain == "elevation"
+        assert t1.get_name() == "PostStack2DElevation"
+
+        # Test mixed case
+        t2 = Seismic2DPostStackTemplate("elevatioN")
+        assert t2._trace_domain == "elevation"
+        assert t2.get_name() == "PostStack2DElevation"
+
+    def test_build_dataset_depth(self) -> None:
+        """Test building a complete 2D depth dataset."""
+        t = Seismic2DPostStackTemplate("depth")
+
+        dataset = t.build_dataset(
+            "Seismic 2D Depth Line 001",
+            sizes=[2048, 4096],
+            coord_units=[_UNIT_METER, _UNIT_METER],  # Both coordinates and depth in meters
+        )
+
+        # Verify dataset metadata
+        assert dataset.metadata.name == "Seismic 2D Depth Line 001"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "2D"
+        assert dataset.metadata.attributes["ensembleType"] == "line"
+        assert dataset.metadata.attributes["processingStage"] == "post-stack"
+
+        # 2 coordinate variables + 1 data variable = 5 variables
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        cdp_x = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("cdp", 2048)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        cdp_y = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("cdp", 2048)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable
+        seismic = validate_variable(
+            dataset,
+            name="StackedAmplitude",
+            dims=[("cdp", 2048), ("depth", 4096)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1024, 1024]
+        assert seismic.metadata.stats_v1 is None
+
+    def test_build_dataset_time(self) -> None:
+        """Test building a complete 2D time dataset."""
+        t = Seismic2DPostStackTemplate("time")
+
+        dataset = t.build_dataset(
+            "Seismic 2D Time Line 001",
+            sizes=[2048, 4096],
+            coord_units=[_UNIT_METER, _UNIT_METER],  # Coordinates in meters, time in seconds
+        )
+
+        # Verify dataset metadata
+        assert dataset.metadata.name == "Seismic 2D Time Line 001"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "2D"
+        assert dataset.metadata.attributes["ensembleType"] == "line"
+        assert dataset.metadata.attributes["processingStage"] == "post-stack"
+
+        # Verify variables count
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        v = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("cdp", 2048)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert v.metadata.units_v1.length == LengthUnitEnum.METER
+
+        v = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("cdp", 2048)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert v.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable
+        v = validate_variable(
+            dataset,
+            name="StackedAmplitude",
+            dims=[("cdp", 2048), ("time", 4096)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(v.metadata.chunk_grid, RegularChunkGrid)
+        assert v.metadata.chunk_grid.configuration.chunk_shape == [1024, 1024]
+        assert v.metadata.stats_v1 is None
+
+    def test_time_vs_depth_comparison(self) -> None:
+        """Test differences between time and depth templates."""
+        time_template = Seismic2DPostStackTemplate("time")
+        depth_template = Seismic2DPostStackTemplate("depth")
+
+        # Different trace domains
+        assert time_template._trace_domain == "time"
+        assert depth_template._trace_domain == "depth"
+
+        # Different names
+        assert time_template.get_name() == "PostStack2DTime"
+        assert depth_template.get_name() == "PostStack2DDepth"
+
+        # Same other attributes
+        assert time_template._coord_dim_names == depth_template._coord_dim_names
+        assert time_template._coord_names == depth_template._coord_names
+        assert time_template._var_name == depth_template._var_name
+        assert time_template._var_chunk_shape == depth_template._var_chunk_shape
diff --git a/tests/unit/v1/templates/test_seismic_3d_poststack.py b/tests/unit/v1/templates/test_seismic_3d_poststack.py
new file mode 100644
index 000000000..3e205b0ae
--- /dev/null
+++ b/tests/unit/v1/templates/test_seismic_3d_poststack.py
@@ -0,0 +1,182 @@
+"""Unit tests for Seismic3DPostStackTemplate."""
+
+from tests.unit.v1.helpers import validate_variable
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import TimeUnitEnum
+from mdio.schemas.v1.units import TimeUnitModel
+
+_UNIT_METER = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+_UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
+
+
+class TestSeismic3DPostStackTemplate:
+    """Unit tests for Seismic3DPostStackTemplate."""
+
+    def test_configuration_depth(self) -> None:
+        """Unit tests for Seismic3DPostStackTemplate with depth domain."""
+        t = Seismic3DPostStackTemplate(domain="depth")
+
+        # Template attributes to be overridden by subclasses
+        assert t._trace_domain == "depth"  # Domain should be lowercased
+        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._dim_names == ["inline", "crossline", "depth"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_chunk_shape == [128, 128, 128]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        assert t._load_dataset_attributes().attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "line",
+            "processingStage": "post-stack",
+        }
+
+        assert t.get_name() == "PostStack3DDepth"
+
+    def test_configuration_time(self) -> None:
+        """Unit tests for Seismic3DPostStackTemplate with time domain."""
+        t = Seismic3DPostStackTemplate(domain="time")
+
+        # Template attributes to be overridden by subclasses
+        assert t._trace_domain == "time"  # Domain should be lowercased
+        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._dim_names == ["inline", "crossline", "time"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_chunk_shape == [128, 128, 128]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        assert t._load_dataset_attributes().attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "line",
+            "processingStage": "post-stack",
+        }
+
+        assert t.get_name() == "PostStack3DTime"
+
+    def test_domain_case_handling(self) -> None:
+        """Test that domain parameter handles different cases correctly."""
+        # Test uppercase
+        t1 = Seismic3DPostStackTemplate("ELEVATION")
+        assert t1._trace_domain == "elevation"
+        assert t1.get_name() == "PostStack3DElevation"
+
+        # Test mixed case
+        t2 = Seismic3DPostStackTemplate("elevatioN")
+        assert t2._trace_domain == "elevation"
+        assert t2.get_name() == "PostStack3DElevation"
+
+    def test_build_dataset_depth(self) -> None:
+        """Unit tests for Seismic3DPostStackTemplate build with depth domain."""
+        t = Seismic3DPostStackTemplate(domain="depth")
+
+        assert t.get_name() == "PostStack3DDepth"
+        dataset = t.build_dataset(
+            "Seismic 3D", sizes=[256, 512, 1024], coord_units=[_UNIT_METER, _UNIT_METER]
+        )
+
+        assert dataset.metadata.name == "Seismic 3D"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "line"
+        assert dataset.metadata.attributes["processingStage"] == "post-stack"
+
+        # Verify variables
+        # 2 coordinate variables + 1 data variables = 3 variables
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        cdp_x = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("inline", 256), ("crossline", 512)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        cdp_y = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("inline", 256), ("crossline", 512)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable
+        seismic = validate_variable(
+            dataset,
+            name="StackedAmplitude",
+            dims=[("inline", 256), ("crossline", 512), ("depth", 1024)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+        assert seismic.metadata.stats_v1 is None
+
+    def test_build_dataset_time(self) -> None:
+        """Unit tests for Seismic3DPostStackTimeTemplate build with time domain."""
+        t = Seismic3DPostStackTemplate(domain="time")
+
+        assert t.get_name() == "PostStack3DTime"
+        dataset = t.build_dataset(
+            "Seismic 3D", sizes=[256, 512, 1024], coord_units=[_UNIT_METER, _UNIT_METER]
+        )
+
+        assert dataset.metadata.name == "Seismic 3D"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "line"
+        assert dataset.metadata.attributes["processingStage"] == "post-stack"
+
+        # Verify variables
+        # 2 coordinate variables + 1 data variables = 3 variables
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        cdp_x = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("inline", 256), ("crossline", 512)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        cdp_y = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("inline", 256), ("crossline", 512)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable
+        seismic = validate_variable(
+            dataset,
+            name="StackedAmplitude",
+            dims=[("inline", 256), ("crossline", 512), ("time", 1024)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
+        assert seismic.metadata.stats_v1 is None
diff --git a/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py b/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
new file mode 100644
index 000000000..4f936940e
--- /dev/null
+++ b/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
@@ -0,0 +1,192 @@
+"""Unit tests for Seismic3DPreStackCDPTemplate."""
+
+from tests.unit.v1.helpers import validate_variable
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.v1.templates.seismic_3d_prestack_cdp import Seismic3DPreStackCDPTemplate
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import TimeUnitEnum
+from mdio.schemas.v1.units import TimeUnitModel
+
+_UNIT_METER = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+_UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
+
+
+class TestSeismic3DPreStackCDPTemplate:
+    """Unit tests for Seismic3DPreStackCDPTemplate."""
+
+    def test_configuration_depth(self) -> None:
+        """Unit tests for Seismic3DPreStackCDPTemplate."""
+        t = Seismic3DPreStackCDPTemplate(domain="DEPTH")
+
+        # Template attributes for prestack CDP
+        assert t._trace_domain == "depth"
+        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._dim_names == ["inline", "crossline", "offset", "depth"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_name == "AmplitudeCDP"
+        assert t._var_chunk_shape == [1, 1, 512, 4096]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        # Verify prestack CDP attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "cdp",
+            "processingStage": "pre-stack",
+        }
+
+        assert t.get_name() == "PreStackCdpGathers3DDepth"
+
+    def test_configuration_time(self) -> None:
+        """Unit tests for Seismic3DPreStackCDPTemplate."""
+        t = Seismic3DPreStackCDPTemplate(domain="TIME")
+
+        # Template attributes for prestack CDP
+        assert t._trace_domain == "time"
+        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._dim_names == ["inline", "crossline", "offset", "time"]
+        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._var_name == "AmplitudeCDP"
+        assert t._var_chunk_shape == [1, 1, 512, 4096]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        # Verify prestack CDP attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "cdp",
+            "processingStage": "pre-stack",
+        }
+
+        assert t.get_name() == "PreStackCdpGathers3DTime"
+
+    def test_domain_case_handling(self) -> None:
+        """Test that domain parameter handles different cases correctly."""
+        # Test uppercase
+        t1 = Seismic3DPreStackCDPTemplate("ELEVATION")
+        assert t1._trace_domain == "elevation"
+        assert t1.get_name() == "PreStackCdpGathers3DElevation"
+
+        # Test mixed case
+        t2 = Seismic3DPreStackCDPTemplate("elevatioN")
+        assert t2._trace_domain == "elevation"
+        assert t2.get_name() == "PreStackCdpGathers3DElevation"
+
+    def test_build_dataset_depth(self) -> None:
+        """Unit tests for Seismic3DPreStackCDPDepthTemplate build with depth domain."""
+        t = Seismic3DPreStackCDPTemplate(domain="depth")
+
+        assert t.get_name() == "PreStackCdpGathers3DDepth"
+        dataset = t.build_dataset(
+            "North Sea 3D Prestack Depth",
+            sizes=[512, 768, 36, 1536],
+            coord_units=[_UNIT_METER, _UNIT_METER],
+        )
+
+        assert dataset.metadata.name == "North Sea 3D Prestack Depth"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "cdp"
+        assert dataset.metadata.attributes["processingStage"] == "pre-stack"
+
+        # Verify variables
+        # 2 coordinate variables + 1 data variable = 3 variables
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        cdp_x = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("inline", 512), ("crossline", 768)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        cdp_y = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("inline", 512), ("crossline", 768)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable (prestack depth data)
+        seismic = validate_variable(
+            dataset,
+            name="AmplitudeCDP",
+            dims=[("inline", 512), ("crossline", 768), ("offset", 36), ("depth", 1536)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
+        assert seismic.metadata.stats_v1 is None
+
+    def test_build_dataset_time(self) -> None:
+        """Unit tests for Seismic3DPreStackCDPTimeTemplate build with time domain."""
+        t = Seismic3DPreStackCDPTemplate(domain="time")
+
+        assert t.get_name() == "PreStackCdpGathers3DTime"
+        dataset = t.build_dataset(
+            "Santos Basin 3D Prestack",
+            sizes=[512, 768, 36, 1536],
+            coord_units=[_UNIT_METER, _UNIT_METER],
+        )
+
+        assert dataset.metadata.name == "Santos Basin 3D Prestack"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "cdp"
+        assert dataset.metadata.attributes["processingStage"] == "pre-stack"
+
+        # Verify variables
+        # 2 coordinate variables + 1 data variable = 3 variables
+        assert len(dataset.variables) == 3
+
+        # Verify coordinate variables
+        cdp_x = validate_variable(
+            dataset,
+            name="cdp-x",
+            dims=[("inline", 512), ("crossline", 768)],
+            coords=["cdp-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        cdp_y = validate_variable(
+            dataset,
+            name="cdp-y",
+            dims=[("inline", 512), ("crossline", 768)],
+            coords=["cdp-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable (prestack time data)
+        seismic = validate_variable(
+            dataset,
+            name="AmplitudeCDP",
+            dims=[("inline", 512), ("crossline", 768), ("offset", 36), ("time", 1536)],
+            coords=["cdp-x", "cdp-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
+        assert seismic.metadata.stats_v1 is None
diff --git a/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py b/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
new file mode 100644
index 000000000..eea66cf6b
--- /dev/null
+++ b/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
@@ -0,0 +1,244 @@
+"""Unit tests for Seismic3DPreStackShotTemplate."""
+
+from tests.unit.v1.helpers import validate_variable
+
+from mdio.schemas.chunk_grid import RegularChunkGrid
+from mdio.schemas.compressors import Blosc
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.v1.templates.seismic_3d_prestack_shot import Seismic3DPreStackShotTemplate
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
+from mdio.schemas.v1.units import TimeUnitEnum
+from mdio.schemas.v1.units import TimeUnitModel
+
+_UNIT_METER = AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+_UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
+
+
+class TestSeismic3DPreStackShotTemplate:
+    """Unit tests for Seismic3DPreStackShotTemplate."""
+
+    def test_configuration_depth(self) -> None:
+        """Unit tests for Seismic3DPreStackShotTemplate in depth domain."""
+        t = Seismic3DPreStackShotTemplate(domain="DEPTH")
+
+        # Template attributes for prestack shot
+        assert t._trace_domain == "depth"
+        assert t._coord_dim_names == []
+        assert t._dim_names == ["shot_point", "cable", "channel", "depth"]
+        assert t._coord_names == ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
+        assert t._var_name == "AmplitudeShot"
+        assert t._var_chunk_shape == [1, 1, 512, 4096]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        # Verify prestack shot attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "shot",
+            "processingStage": "pre-stack",
+        }
+
+        assert t.get_name() == "PreStackShotGathers3DDepth"
+
+    def test_configuration_time(self) -> None:
+        """Unit tests for Seismic3DPreStackShotTemplate in time domain."""
+        t = Seismic3DPreStackShotTemplate(domain="TIME")
+
+        # Template attributes for prestack shot
+        assert t._trace_domain == "time"
+        assert t._coord_dim_names == []
+        assert t._dim_names == ["shot_point", "cable", "channel", "time"]
+        assert t._coord_names == ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
+        assert t._var_name == "AmplitudeShot"
+        assert t._var_chunk_shape == [1, 1, 512, 4096]
+
+        # Variables instantiated when build_dataset() is called
+        assert t._builder is None
+        assert t._dim_sizes == []
+        assert t._coord_units == []
+
+        # Verify prestack shot attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "3D",
+            "ensembleType": "shot",
+            "processingStage": "pre-stack",
+        }
+
+        assert t.get_name() == "PreStackShotGathers3DTime"
+
+    def test_domain_case_handling(self) -> None:
+        """Test that domain parameter handles different cases correctly."""
+        # Test uppercase
+        t1 = Seismic3DPreStackShotTemplate("ELEVATION")
+        assert t1._trace_domain == "elevation"
+        assert t1.get_name() == "PreStackShotGathers3DElevation"
+
+        # Test mixed case
+        t2 = Seismic3DPreStackShotTemplate("elevatioN")
+        assert t2._trace_domain == "elevation"
+        assert t2.get_name() == "PreStackShotGathers3DElevation"
+
+    def test_build_dataset_depth(self) -> None:
+        """Unit tests for Seismic3DPreStackShotTemplate build in depth domain."""
+        t = Seismic3DPreStackShotTemplate(domain="depth")
+
+        assert t.get_name() == "PreStackShotGathers3DDepth"
+        dataset = t.build_dataset(
+            "Gulf of Mexico 3D Shot Depth",
+            sizes=[256, 512, 24, 2048],
+            coord_units=[_UNIT_METER, _UNIT_METER],
+        )
+
+        assert dataset.metadata.name == "Gulf of Mexico 3D Shot Depth"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "shot"
+        assert dataset.metadata.attributes["processingStage"] == "pre-stack"
+
+        # Verify variables (including dimension variables)
+        # 5 coordinate variables + 1 data variable = 6 variables
+        assert len(dataset.variables) == 6
+
+        # Verify coordinate variables
+        validate_variable(
+            dataset,
+            name="gun",
+            dims=[("shot_point", 256)],
+            coords=["gun"],
+            dtype=ScalarType.UINT8,
+        )
+
+        shot_x = validate_variable(
+            dataset,
+            name="shot-x",
+            dims=[("shot_point", 256)],
+            coords=["shot-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert shot_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        shot_y = validate_variable(
+            dataset,
+            name="shot-y",
+            dims=[("shot_point", 256)],
+            coords=["shot-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert shot_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        receiver_x = validate_variable(
+            dataset,
+            name="receiver-x",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+            coords=["receiver-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert receiver_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        receiver_y = validate_variable(
+            dataset,
+            name="receiver-y",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+            coords=["receiver-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert receiver_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable (prestack shot depth data)
+        seismic = validate_variable(
+            dataset,
+            name="AmplitudeShot",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24), ("depth", 2048)],
+            coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
+        assert seismic.metadata.stats_v1 is None
+
+    def test_build_dataset_time(self) -> None:
+        """Unit tests for Seismic3DPreStackShotTemplate build in time domain."""
+        t = Seismic3DPreStackShotTemplate(domain="time")
+
+        assert t.get_name() == "PreStackShotGathers3DTime"
+        dataset = t.build_dataset(
+            "North Sea 3D Shot Time",
+            sizes=[256, 512, 24, 2048],
+            coord_units=[_UNIT_METER, _UNIT_METER],
+        )
+
+        assert dataset.metadata.name == "North Sea 3D Shot Time"
+        assert dataset.metadata.attributes["surveyDimensionality"] == "3D"
+        assert dataset.metadata.attributes["ensembleType"] == "shot"
+        assert dataset.metadata.attributes["processingStage"] == "pre-stack"
+
+        # Verify variables (including dimension variables)
+        # 5 coordinate variables + 1 data variable = 6 variables
+        assert len(dataset.variables) == 6
+
+        # Verify coordinate variables
+        validate_variable(
+            dataset,
+            name="gun",
+            dims=[("shot_point", 256)],
+            coords=["gun"],
+            dtype=ScalarType.UINT8,
+        )
+
+        shot_x = validate_variable(
+            dataset,
+            name="shot-x",
+            dims=[("shot_point", 256)],
+            coords=["shot-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert shot_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        shot_y = validate_variable(
+            dataset,
+            name="shot-y",
+            dims=[("shot_point", 256)],
+            coords=["shot-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert shot_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        receiver_x = validate_variable(
+            dataset,
+            name="receiver-x",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+            coords=["receiver-x"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert receiver_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+        receiver_y = validate_variable(
+            dataset,
+            name="receiver-y",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+            coords=["receiver-y"],
+            dtype=ScalarType.FLOAT64,
+        )
+        assert receiver_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+        # Verify seismic variable (prestack shot time data)
+        seismic = validate_variable(
+            dataset,
+            name="AmplitudeShot",
+            dims=[("shot_point", 256), ("cable", 512), ("channel", 24), ("time", 2048)],
+            coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
+            dtype=ScalarType.FLOAT32,
+        )
+        assert isinstance(seismic.compressor, Blosc)
+        assert seismic.compressor.algorithm == "zstd"
+        assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
+        assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
+        assert seismic.metadata.stats_v1 is None
diff --git a/tests/unit/v1/templates/test_seismic_templates.py b/tests/unit/v1/templates/test_seismic_templates.py
new file mode 100644
index 000000000..46d2245a2
--- /dev/null
+++ b/tests/unit/v1/templates/test_seismic_templates.py
@@ -0,0 +1,59 @@
+"""Unit tests for concrete seismic dataset template implementations."""
+
+# Import all concrete template classes
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+from mdio.schemas.v1.templates.seismic_2d_poststack import Seismic2DPostStackTemplate
+from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack_cdp import Seismic3DPreStackCDPTemplate
+from mdio.schemas.v1.templates.seismic_3d_prestack_shot import Seismic3DPreStackShotTemplate
+
+
+class TestSeismicTemplates:
+    """Test cases for Seismic2DPostStackTemplate."""
+
+    def test_get_name_time(self) -> None:
+        """Test get_name with domain."""
+        time_template = Seismic2DPostStackTemplate("time")
+        dpth_template = Seismic2DPostStackTemplate("depth")
+
+        assert time_template.get_name() == "PostStack2DTime"
+        assert dpth_template.get_name() == "PostStack2DDepth"
+
+        time_template = Seismic3DPostStackTemplate("time")
+        dpth_template = Seismic3DPostStackTemplate("depth")
+
+        assert time_template.get_name() == "PostStack3DTime"
+        assert dpth_template.get_name() == "PostStack3DDepth"
+
+        time_template = Seismic3DPreStackCDPTemplate("time")
+        dpth_template = Seismic3DPreStackCDPTemplate("depth")
+
+        assert time_template.get_name() == "PreStackCdpGathers3DTime"
+        assert dpth_template.get_name() == "PreStackCdpGathers3DDepth"
+
+        time_template = Seismic3DPreStackShotTemplate("time")
+        dpth_template = Seismic3DPreStackShotTemplate("depth")
+
+        assert time_template.get_name() == "PreStackShotGathers3DTime"
+        assert dpth_template.get_name() == "PreStackShotGathers3DDepth"
+
+    def test_all_templates_inherit_from_abstract(self) -> None:
+        """Test that all concrete templates inherit from AbstractDatasetTemplate."""
+        templates = [
+            Seismic2DPostStackTemplate("time"),
+            Seismic3DPostStackTemplate("time"),
+            Seismic3DPreStackCDPTemplate("time"),
+            Seismic3DPreStackShotTemplate("time"),
+            Seismic2DPostStackTemplate("depth"),
+            Seismic3DPostStackTemplate("depth"),
+            Seismic3DPreStackCDPTemplate("depth"),
+            Seismic3DPreStackShotTemplate("depth"),
+        ]
+
+        for template in templates:
+            assert isinstance(template, AbstractDatasetTemplate)
+            assert hasattr(template, "get_name")
+            assert hasattr(template, "build_dataset")
+
+        names = [template.get_name() for template in templates]
+        assert len(names) == len(set(names)), f"Duplicate template names found: {names}"
diff --git a/tests/unit/v1/templates/test_template_registry.py b/tests/unit/v1/templates/test_template_registry.py
new file mode 100644
index 000000000..a40f5021c
--- /dev/null
+++ b/tests/unit/v1/templates/test_template_registry.py
@@ -0,0 +1,395 @@
+"""Tests for the singleton TemplateRegistry implementation."""
+
+import threading
+import time
+
+import pytest
+
+from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+from mdio.schemas.v1.templates.template_registry import TemplateRegistry
+from mdio.schemas.v1.templates.template_registry import get_template
+from mdio.schemas.v1.templates.template_registry import get_template_registry
+from mdio.schemas.v1.templates.template_registry import is_template_registered
+from mdio.schemas.v1.templates.template_registry import list_templates
+from mdio.schemas.v1.templates.template_registry import register_template
+
+
+class MockDatasetTemplate(AbstractDatasetTemplate):
+    """Mock template for testing."""
+
+    def __init__(self, name: str):
+        super().__init__()
+        self.template_name = name
+
+    def _get_name(self) -> str:
+        return self.template_name
+
+    def _load_dataset_attributes(self) -> None:
+        return None  # Mock implementation
+
+    def create_dataset(self) -> str:
+        """Create a mock dataset.
+
+        Returns:
+            str: A message indicating the dataset creation.
+        """
+        return f"Mock dataset created by {self.template_name}"
+
+
+class TestTemplateRegistrySingleton:
+    """Test cases for TemplateRegistry singleton pattern."""
+
+    def setup_method(self) -> None:
+        """Reset singleton before each test."""
+        TemplateRegistry._reset_instance()
+
+    def teardown_method(self) -> None:
+        """Clean up after each test."""
+        if TemplateRegistry._instance:
+            TemplateRegistry._instance.clear()
+        TemplateRegistry._reset_instance()
+
+    def test_singleton_same_instance(self) -> None:
+        """Test that multiple instantiations return the same instance."""
+        registry1 = TemplateRegistry()
+        registry2 = TemplateRegistry()
+        registry3 = TemplateRegistry.get_instance()
+
+        assert registry1 is registry2
+        assert registry2 is registry3
+        assert id(registry1) == id(registry2) == id(registry3)
+
+    def test_singleton_thread_safety(self) -> None:
+        """Test that singleton is thread-safe during creation."""
+        instances = []
+        errors = []
+
+        def create_instance() -> None:
+            try:
+                instance = TemplateRegistry()
+                instances.append(instance)
+                time.sleep(0.001)  # Small delay to increase contention
+            except Exception as e:
+                errors.append(e)
+
+        # Create multiple threads trying to create instances
+        threads = [threading.Thread(target=create_instance) for _ in range(10)]
+
+        for thread in threads:
+            thread.start()
+
+        for thread in threads:
+            thread.join()
+
+        # All instances should be the same
+        assert len(errors) == 0
+        assert len(instances) == 10
+        assert all(instance is instances[0] for instance in instances)
+
+    def test_initialization_only_once(self) -> None:
+        """Test that internal state is initialized only once."""
+        registry1 = TemplateRegistry()
+        template1 = MockDatasetTemplate("test_template")
+        registry1.register(template1)
+
+        # Create another instance - should have same templates
+        registry2 = TemplateRegistry()
+
+        assert registry1 is registry2
+        assert registry2.is_registered("test_template")
+        assert registry2.get("test_template") is template1
+
+    def test_register_template(self) -> None:
+        """Test template registration."""
+        registry = TemplateRegistry()
+        template = MockDatasetTemplate("test")
+
+        name = registry.register(template)
+
+        assert name == "test"  # Should be the template name
+        assert registry.is_registered("test")
+        assert registry.get("test") is template
+
+    def test_register_duplicate_template(self) -> None:
+        """Test error when registering duplicate template."""
+        registry = TemplateRegistry()
+        template1 = MockDatasetTemplate("duplicate")
+        template2 = MockDatasetTemplate("duplicate")
+
+        registry.register(template1)
+
+        with pytest.raises(ValueError, match="Template 'duplicate' is already registered"):
+            registry.register(template2)
+
+    def test_get_nonexistent_template(self) -> None:
+        """Test error when getting non-existent template."""
+        registry = TemplateRegistry()
+
+        with pytest.raises(KeyError, match="Template 'nonexistent' is not registered"):
+            registry.get("nonexistent")
+
+    def test_unregister_template(self) -> None:
+        """Test template unregistration."""
+        registry = TemplateRegistry()
+        template = MockDatasetTemplate("test_template")
+
+        registry.register(template)
+        assert registry.is_registered("test_template")
+
+        registry.unregister("test_template")
+        assert not registry.is_registered("test_template")
+
+    def test_unregister_nonexistent_template(self) -> None:
+        """Test error when unregistering non-existent template."""
+        registry = TemplateRegistry()
+
+        with pytest.raises(KeyError, match="Template 'nonexistent' is not registered"):
+            registry.unregister("nonexistent")
+
+    def test_list_all_templates(self) -> None:
+        """Test listing all registered templates."""
+        registry = TemplateRegistry()
+
+        # Default templates are always installed
+        templates = list_templates()
+        assert len(templates) == 8
+        assert "PostStack2DTime" in templates
+        assert "PostStack3DTime" in templates
+        assert "PreStackCdpGathers3DTime" in templates
+        assert "PreStackShotGathers3DTime" in templates
+
+        assert "PostStack2DDepth" in templates
+        assert "PostStack3DDepth" in templates
+        assert "PreStackCdpGathers3DDepth" in templates
+        assert "PreStackShotGathers3DDepth" in templates
+
+        # Add some templates
+        template1 = MockDatasetTemplate("Template_One")
+        template2 = MockDatasetTemplate("Template_Two")
+
+        registry.register(template1)
+        registry.register(template2)
+
+        templates = registry.list_all_templates()
+        assert len(templates) == 10
+        assert "Template_One" in templates
+        assert "Template_Two" in templates
+
+    def test_clear_templates(self) -> None:
+        """Test clearing all templates."""
+        registry = TemplateRegistry()
+
+        # Default templates are always installed
+        templates = list_templates()
+        assert len(templates) == 8
+
+        # Add some templates
+        template1 = MockDatasetTemplate("Template1")
+        template2 = MockDatasetTemplate("Template2")
+
+        registry.register(template1)
+        registry.register(template2)
+
+        assert len(registry.list_all_templates()) == 10
+
+        # Clear all
+        registry.clear()
+
+        assert len(registry.list_all_templates()) == 0
+        assert not registry.is_registered("Template1")
+        assert not registry.is_registered("Template2")
+        # default templates are also cleared
+        assert not registry.is_registered("PostStack2DTime")
+        assert not registry.is_registered("PostStack3DTime")
+        assert not registry.is_registered("PreStackCdpGathers3DTime")
+        assert not registry.is_registered("PreStackShotGathers3DTime")
+        assert not registry.is_registered("PostStack2DDepth")
+        assert not registry.is_registered("PostStack3DDepth")
+        assert not registry.is_registered("PreStackCdpGathers3DDepth")
+        assert not registry.is_registered("PreStackShotGathers3DDepth")
+
+    def test_reset_instance(self) -> None:
+        """Test resetting the singleton instance."""
+        registry1 = TemplateRegistry()
+        template = MockDatasetTemplate("test")
+        registry1.register(template)
+
+        # Reset the instance
+        TemplateRegistry._reset_instance()
+
+        # New instance should be different and contain default templates only
+        registry2 = TemplateRegistry()
+
+        assert registry1 is not registry2
+        assert not registry2.is_registered("test")
+
+        # default templates are registered
+        assert len(registry2.list_all_templates()) == 8
+        assert registry2.is_registered("PostStack2DTime")
+        assert registry2.is_registered("PostStack3DTime")
+        assert registry2.is_registered("PreStackCdpGathers3DTime")
+        assert registry2.is_registered("PreStackShotGathers3DTime")
+        assert registry2.is_registered("PostStack2DDepth")
+        assert registry2.is_registered("PostStack3DDepth")
+        assert registry2.is_registered("PreStackCdpGathers3DDepth")
+        assert registry2.is_registered("PreStackShotGathers3DDepth")
+
+
+class TestGlobalFunctions:
+    """Test cases for global convenience functions."""
+
+    def setup_method(self) -> None:
+        """Reset singleton before each test."""
+        TemplateRegistry._reset_instance()
+
+    def teardown_method(self) -> None:
+        """Clean up after each test."""
+        if TemplateRegistry._instance:
+            TemplateRegistry._instance.clear()
+        TemplateRegistry._reset_instance()
+
+    def test_get_template_registry(self) -> None:
+        """Test global registry getter."""
+        registry1 = get_template_registry()
+        registry2 = get_template_registry()
+        direct_registry = TemplateRegistry()
+
+        assert registry1 is registry2
+        assert registry1 is direct_registry
+
+    def test_register_template_global(self) -> None:
+        """Test global template registration."""
+        template = MockDatasetTemplate("global_test")
+
+        name = register_template(template)
+
+        assert name == "global_test"
+        assert is_template_registered("global_test")
+        assert get_template("global_test") is template
+
+    def test_list_templates_global(self) -> None:
+        """Test global template listing."""
+        # Default templates are always installed
+        templates = list_templates()
+        assert len(templates) == 8
+        assert "PostStack2DTime" in templates
+        assert "PostStack3DTime" in templates
+        assert "PreStackCdpGathers3DTime" in templates
+        assert "PreStackShotGathers3DTime" in templates
+
+        assert "PostStack2DDepth" in templates
+        assert "PostStack3DDepth" in templates
+        assert "PreStackCdpGathers3DDepth" in templates
+        assert "PreStackShotGathers3DDepth" in templates
+
+        template1 = MockDatasetTemplate("template1")
+        template2 = MockDatasetTemplate("template2")
+
+        register_template(template1)
+        register_template(template2)
+
+        templates = list_templates()
+        assert len(templates) == 10
+        assert "template1" in templates
+        assert "template2" in templates
+
+
+class TestConcurrentAccess:
+    """Test concurrent access to the singleton registry."""
+
+    def setup_method(self) -> None:
+        """Reset singleton before each test."""
+        TemplateRegistry._reset_instance()
+
+    def teardown_method(self) -> None:
+        """Clean up after each test."""
+        if TemplateRegistry._instance:
+            TemplateRegistry._instance.clear()
+        TemplateRegistry._reset_instance()
+
+    def test_concurrent_registration(self) -> None:
+        """Test concurrent template registration."""
+        registry = TemplateRegistry()
+        results = []
+        errors = []
+
+        def register_template_worker(template_id: int) -> None:
+            try:
+                template = MockDatasetTemplate(f"template_{template_id}")
+                name = registry.register(template)
+                results.append((template_id, name))
+                time.sleep(0.001)  # Small delay
+            except Exception as e:
+                errors.append((template_id, e))
+
+        # Create multiple threads registering different templates
+        threads = [threading.Thread(target=register_template_worker, args=(i,)) for i in range(10)]
+
+        for thread in threads:
+            thread.start()
+
+        for thread in threads:
+            thread.join()
+
+        # All registrations should succeed
+        assert len(errors) == 0
+        assert len(results) == 10
+        # Including 8 default templates
+        assert len(registry.list_all_templates()) == 18
+
+        # Check all templates are registered
+        for i in range(10):
+            assert registry.is_registered(f"template_{i}")
+
+    def test_concurrent_access_mixed_operations(self) -> None:
+        """Test concurrent mixed operations (register, get, list)."""
+        registry = TemplateRegistry()
+
+        # Pre-register some templates
+        for i in range(5):
+            template = MockDatasetTemplate(f"initial_{i}")
+            registry.register(template)
+
+        results = []
+        errors = []
+
+        def mixed_operations_worker(worker_id: int) -> None:
+            try:
+                operations_results = []
+
+                # Get existing template
+                if worker_id % 2 == 0:
+                    template = registry.get("initial_0")
+                    operations_results.append(("get", template.template_name))
+
+                # Register new template
+                if worker_id % 3 == 0:
+                    new_template = MockDatasetTemplate(f"worker_{worker_id}")
+                    name = registry.register(new_template)
+                    operations_results.append(("register", name))
+
+                # List templates
+                templates = registry.list_all_templates()
+                operations_results.append(("list", len(templates)))
+
+                results.append((worker_id, operations_results))
+
+            except Exception as e:
+                errors.append((worker_id, e))
+
+        # Run concurrent operations
+        threads = [threading.Thread(target=mixed_operations_worker, args=(i,)) for i in range(15)]
+
+        for thread in threads:
+            thread.start()
+
+        for thread in threads:
+            thread.join()
+
+        # Check that operations completed without errors
+        assert len(errors) == 0
+        assert len(results) == 15
+
+        # Verify final state is consistent
+        final_templates = registry.list_all_templates()
+        assert len(final_templates) >= 5  # At least the initial templates
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 833fad981..43b87fb5f 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -45,10 +45,10 @@ def test_build() -> None:
 
 def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR0915 Too many statements (57 > 50)
     """Test building a Seismic PostStack 3D Acceptance dataset."""
-    dataset = make_seismic_poststack_3d_acceptance_dataset()
+    dataset = make_seismic_poststack_3d_acceptance_dataset("Seismic")
 
     # Verify dataset structure
-    assert dataset.metadata.name == "campos_3d"
+    assert dataset.metadata.name == "Seismic"
     assert dataset.metadata.api_version == "1.0.0a1"
     assert dataset.metadata.attributes["foo"] == "bar"
     assert len(dataset.metadata.attributes["textHeader"]) == 3
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index f8439585e..9db2deee1 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -398,7 +398,7 @@ def test_to_xarray_dataset(tmp_path: Path) -> None:
 
 def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path: Path) -> None:
     """Test building a complete dataset."""
-    dataset = make_seismic_poststack_3d_acceptance_dataset()
+    dataset = make_seismic_poststack_3d_acceptance_dataset("Seismic")
 
     xr_ds = to_xarray_dataset(dataset)
 

From bc35bdfa5b53cb4cd6822094569c5fa77a282582 Mon Sep 17 00:00:00 2001
From: Altay Sansal <tasansal@users.noreply.github.com>
Date: Tue, 5 Aug 2025 20:29:09 -0500
Subject: [PATCH 54/56] update deps

---
 pyproject.toml |   18 +-
 uv.lock        | 3668 ++++++++++++++++++++++++------------------------
 2 files changed, 1852 insertions(+), 1834 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 2a1c821dd..4bbf4c18f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -25,27 +25,27 @@ classifiers = [
 dependencies = [
     "click (>=8.2.1,<9.0.0)",
     "click-params (>=0.5.0,<0.6.0)",
-    "dask (>=2025.5.1)",
-    "fsspec (>=2025.5.1)",
+    "dask (>=2025.7.0)",
+    "fsspec (>=2025.7.0)",
     "pint>=0.24.4,<0.25",
     "psutil (>=7.0.0,<8.0.0)",
     "pydantic (>=2.11.7,<3.0.0)",
     "pydantic-settings (>=2.10.1,<3.0.0)",
-    "rich (>=14.0.0,<15.0.0)",
-    "segy (>=0.4.1.post2,<0.5.0)",
+    "rich (>=14.1.0,<15.0.0)",
+    "segy (>=0.4.2,<0.5.0)",
     "tqdm (>=4.67.1,<5.0.0)",
-    "xarray>=2025.6.1",
-    "zarr (>=3.1.0,<4.0.0)",
+    "xarray>=2025.7.1",
+    "zarr (>=3.1.1,<4.0.0)",
 ]
 
 [project.optional-dependencies]
 cloud = [
-    "s3fs == 2025.5.1",
-    "gcsfs (>=2025.5.1)",
+    "s3fs (>=2025.7.0)",
+    "gcsfs (>=2025.7.0)",
     "adlfs (>=2024.12.0)",
 ]
 distributed = [
-    "distributed (>=2025.5.1)",
+    "distributed (>=2025.7.0)",
     "bokeh (>=3.7.3,<4.0.0)",
 ]
 lossy = ["zfpy (>=1.0.1,<2.0.0)"]
diff --git a/uv.lock b/uv.lock
index a580acd5c..9ecc1d26f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
 version = 1
-revision = 1
+revision = 2
 requires-python = ">=3.11, <3.14"
 resolution-markers = [
     "python_full_version >= '3.13'",
@@ -7,6 +7,18 @@ resolution-markers = [
     "python_full_version < '3.12'",
 ]
 
+[[package]]
+name = "accessible-pygments"
+version = "0.0.5"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "pygments" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/bc/c1/bbac6a50d02774f91572938964c582fff4270eee73ab822a4aeea4d8b11b/accessible_pygments-0.0.5.tar.gz", hash = "sha256:40918d3e6a2b619ad424cb91e556bd3bd8865443d9f22f1dcdf79e33c8046872", size = 1377899, upload-time = "2024-05-10T11:23:10.216Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/8d/3f/95338030883d8c8b91223b4e21744b04d11b161a3ef117295d8241f50ab4/accessible_pygments-0.0.5-py3-none-any.whl", hash = "sha256:88ae3211e68a1d0b011504b2ffc1691feafce124b845bd072ab6f9f66f34d4b7", size = 1395903, upload-time = "2024-05-10T11:23:08.421Z" },
+]
+
 [[package]]
 name = "adlfs"
 version = "2024.12.0"
@@ -19,14 +31,14 @@ dependencies = [
     { name = "azure-storage-blob" },
     { name = "fsspec" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/76/82/e30891af574fb358449fb9436aac53569814452cb88b0cba4f488171b8dc/adlfs-2024.12.0.tar.gz", hash = "sha256:04582bf7461a57365766d01a295a0a88b2b8c42c4fea06e2d673f62675cac5c6", size = 49189 }
+sdist = { url = "https://files.pythonhosted.org/packages/76/82/e30891af574fb358449fb9436aac53569814452cb88b0cba4f488171b8dc/adlfs-2024.12.0.tar.gz", hash = "sha256:04582bf7461a57365766d01a295a0a88b2b8c42c4fea06e2d673f62675cac5c6", size = 49189, upload-time = "2024-12-15T19:06:30.939Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/cb/ed/d1bf75c089857d38332cf45416e419b47382b345ba5dfc4fae69397830d9/adlfs-2024.12.0-py3-none-any.whl", hash = "sha256:00aab061ddec0413b2039487e656b62e01ece8ef1ca0493f76034a596cf069e3", size = 41792 },
+    { url = "https://files.pythonhosted.org/packages/cb/ed/d1bf75c089857d38332cf45416e419b47382b345ba5dfc4fae69397830d9/adlfs-2024.12.0-py3-none-any.whl", hash = "sha256:00aab061ddec0413b2039487e656b62e01ece8ef1ca0493f76034a596cf069e3", size = 41792, upload-time = "2024-12-15T19:06:27.718Z" },
 ]
 
 [[package]]
 name = "aiobotocore"
-version = "2.23.0"
+version = "2.23.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
@@ -37,23 +49,23 @@ dependencies = [
     { name = "python-dateutil" },
     { name = "wrapt" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/9d/25/4b06ea1214ddf020a28df27dc7136ac9dfaf87929d51e6f6044dd350ed67/aiobotocore-2.23.0.tar.gz", hash = "sha256:0333931365a6c7053aee292fe6ef50c74690c4ae06bb019afdf706cb6f2f5e32", size = 115825 }
+sdist = { url = "https://files.pythonhosted.org/packages/1d/ae/523d48504902a6f17f6ec94311899f217f1bf64b9ca394c89c690c37434c/aiobotocore-2.23.2.tar.gz", hash = "sha256:9c2cbd6e813bb6c60b7f20fc11897976a583c57b0093a87bebfe80a9b08746b2", size = 115881, upload-time = "2025-07-24T17:48:15.957Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/ea/43/ccf9b29669cdb09fd4bfc0a8effeb2973b22a0f3c3be4142d0b485975d11/aiobotocore-2.23.0-py3-none-any.whl", hash = "sha256:8202cebbf147804a083a02bc282fbfda873bfdd0065fd34b64784acb7757b66e", size = 84161 },
+    { url = "https://files.pythonhosted.org/packages/c9/2e/55780065672a69ab3d16062368d358ace7eac196b246e6b15b07301f8fbf/aiobotocore-2.23.2-py3-none-any.whl", hash = "sha256:5ca24feb49be73bd6cd92e82e95aefb0647c07bb85ca57000a0361b9554503d8", size = 84301, upload-time = "2025-07-24T17:48:14.494Z" },
 ]
 
 [[package]]
 name = "aiohappyeyeballs"
 version = "2.6.1"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760 }
+sdist = { url = "https://files.pythonhosted.org/packages/26/30/f84a107a9c4331c14b2b586036f40965c128aa4fee4dda5d3d51cb14ad54/aiohappyeyeballs-2.6.1.tar.gz", hash = "sha256:c3f9d0113123803ccadfdf3f0faa505bc78e6a72d1cc4806cbd719826e943558", size = 22760, upload-time = "2025-03-12T01:42:48.764Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265 },
+    { url = "https://files.pythonhosted.org/packages/0f/15/5bf3b99495fb160b63f95972b81750f18f7f4e02ad051373b669d17d44f2/aiohappyeyeballs-2.6.1-py3-none-any.whl", hash = "sha256:f349ba8f4b75cb25c99c5c2d84e997e485204d2902a9597802b0371f09331fb8", size = 15265, upload-time = "2025-03-12T01:42:47.083Z" },
 ]
 
 [[package]]
 name = "aiohttp"
-version = "3.12.14"
+version = "3.12.15"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohappyeyeballs" },
@@ -64,68 +76,68 @@ dependencies = [
     { name = "propcache" },
     { name = "yarl" },
 ]
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From d21278c28857c4b6daab2545568fcf50dced11be Mon Sep 17 00:00:00 2001
From: Dima From Texas <34629861+dmitriyrepin@users.noreply.github.com>
Date: Thu, 7 Aug 2025 09:10:41 -0500
Subject: [PATCH 55/56] address issues with VS Code dev containers (see issue
 559) (#576)

* Templates and TemplateRegistry

* Fix pre-commit issues

* Rever dev container changes

* PR Review: address issues

* PR Review: register default templates at registry initialization

* Dockerfile.dev

---------

Co-authored-by: Altay Sansal <tasansal@users.noreply.github.com>
---
 .devcontainer/Dockerfile.dev    | 46 +++++++++++++++++++++++++++++++++
 .devcontainer/devcontainer.json | 21 ++++++++-------
 2 files changed, 58 insertions(+), 9 deletions(-)
 create mode 100644 .devcontainer/Dockerfile.dev

diff --git a/.devcontainer/Dockerfile.dev b/.devcontainer/Dockerfile.dev
new file mode 100644
index 000000000..ea04d0aae
--- /dev/null
+++ b/.devcontainer/Dockerfile.dev
@@ -0,0 +1,46 @@
+# USAGE:
+#   This file will be used by the VS Code DevContainer extension
+#   to create a development environment for the mdio-python project.
+# HOW TO MANUALLY BUILD AND DEBUG THE CONTAINER
+#    docker build -t mdio-dev -f .devcontainer/Dockerfile.dev .
+#    docker run -it --rm --entrypoint /bin/bash --name mdio-dev mdio-dev
+# NOTES:
+#  1. The container will be run as the non-root user 'vscode' with UID 1000.
+#  2. The virtual environment will be setup at /home/vscode/.venv
+#  3. The project source code will be host-mounted at /workspaces/mdio-python
+ARG PYTHON_VERSION="3.13"
+ARG LINUX_DISTRO="bookworm"
+ARG UV_VERSION="0.6.11"
+FROM mcr.microsoft.com/devcontainers/python:1-${PYTHON_VERSION}-${LINUX_DISTRO}
+
+ENV USERNAME="vscode"
+USER $USERNAME
+
+COPY --chown=$USERNAME:$USERNAME ./ /workspaces/mdio-python
+
+WORKDIR /workspaces/mdio-python
+
+ARG UV_VERSION
+# Install UV as described in https://devblogs.microsoft.com/ise/dockerizing-uv/
+RUN python3 -m pip install --no-cache-dir uv==${UV_VERSION}
+# Prevent uv from trying to create hard links, which does not work in a container
+# that mounts local file systems (e.g. VS Code Dev Containers)
+ENV UV_LINK_MODE=copy
+# Add path to the site-packages
+ENV PYTHONUSERBASE=/home/$USERNAME/.local
+ENV PATH="$PYTHONUSERBASE/bin:$PATH"
+
+# Initialize virtual environment in the container
+ENV VIRTUAL_ENV="/home/$USERNAME/.venv"
+ENV UV_PROJECT_ENVIRONMENT=$VIRTUAL_ENV
+ENV PATH="$VIRTUAL_ENV/bin:$PATH"
+RUN uv venv $VIRTUAL_ENV
+
+# Install the project in the editable mode
+# https://setuptools.pypa.io/en/latest/userguide/development_mode.html
+# This allows for live reloading of the code during development
+RUN uv pip install -e .
+# Install "extras" (development dependencies) in pyproject.toml
+RUN uv sync --group dev
+# Now one can run:
+#    pre-commit run --all-files
diff --git a/.devcontainer/devcontainer.json b/.devcontainer/devcontainer.json
index b618a5260..cc26bcf29 100755
--- a/.devcontainer/devcontainer.json
+++ b/.devcontainer/devcontainer.json
@@ -2,12 +2,12 @@
 // README at: https://github.com/devcontainers/templates/tree/main/src/python
 {
   "build": {
-    "dockerfile": "Dockerfile",
+    "dockerfile": "Dockerfile.dev",
     "context": ".."
   },
   // Use 'postCreateCommand' to run commands after the container is created.
   "postCreateCommand": {
-    "post_create_script": "bash ./.devcontainer/post-install.sh"
+    // "post_create_script": "bash ./.devcontainer/post-install.sh"
   },
   // Forward 8787 to enable us to view dask dashboard
   "forwardPorts": [8787],
@@ -16,8 +16,9 @@
     // Configure properties specific to VS Code.
     "vscode": {
       "settings": {
-        "python.terminal.activateEnvInCurrentTerminal": true,
-        "python.defaultInterpreterPath": "/opt/venv/bin/python"
+        "python.testing.pytestArgs": ["tests"],
+        "python.testing.unittestEnabled": false,
+        "python.testing.pytestEnabled": true
       },
       "extensions": [
         "ms-python.python",
@@ -27,17 +28,19 @@
         "ms-toolsai.jupyter-renderers",
         "vscode-icons-team.vscode-icons",
         "wayou.vscode-todo-highlight",
-        "streetsidesoftware.code-spell-checker"
+        "streetsidesoftware.code-spell-checker",
+        "eamodio.gitlens",
+        "visualstudioexptteam.vscodeintellicode",
+        "richie5um2.vscode-sort-json"
       ]
     }
   },
   // Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
   // "remoteUser": "root",
   "updateRemoteUserUID": true,
+  "workspaceMount": "source=${localWorkspaceFolder},target=/workspaces/mdio-python,type=bind",
+  "workspaceFolder": "/workspaces/mdio-python",
   "mounts": [
-    // Re-use local Git configuration
-    "source=${localEnv:HOME}/.gitconfig,target=/home/vscode/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:HOME}/.gitconfig,target=/root/.gitconfig_tmp,type=bind,consistency=cached",
-    "source=${localEnv:SCRATCH_DIR}/${localEnv:USER},target=/scratch/,type=bind,consistency=cached"
+    // "source=${localWorkspaceFolder}/../DATA/,target=/DATA/,type=bind,consistency=cached"
   ]
 }

From d3a7da28e1d5bc184785b8e3716a9dabc23abbcb Mon Sep 17 00:00:00 2001
From: Dima From Texas <34629861+dmitriyrepin@users.noreply.github.com>
Date: Fri, 8 Aug 2025 15:12:00 -0500
Subject: [PATCH 56/56] segy_to_mdio_v1 (#577)

* Templates and TemplateRegistry

* Fix pre-commit issues

* Rever dev container changes

* PR Review: address issues

* PR Review: register default templates at registry initialization

* Dockerfile.dev

* segy_to_mdio_v1

* Clean up

* Prototype review notes

* Add dev comment

* Add notes that will be deleted later

* segy_to_mdio_v1 pass 1

* indexing_v1 and blocked_io_v1

* Remove DEV notes

* Clean up

* Document bug location

* Work around IndexError

* Clean temporary code

* More clean up

* Remove *_1 infrastructure files

* Restore accidently removed dask.array

* Created an issue reproducer

* Make the required template properties public

* Simplify type converter

* Improve templates

* Move test_type_converter.py

* Move test_type_converter.py

* Revert to use the original grid

* Integrate segy_to_mdio_v1_customized, fix indexing

* Add dimension coordinates in tem,plates

* Write statistics to Zarr

* Delete factory_v1.py

* Complete integrationtest. Fix coordinates

* Fir pre-commit errors

* PR review: fix trace_worker docstring

* Review: address some of the issue

* Fix bug

* dding todo for sum squares calculation

* Refactor ChunkIterator

* Refactor ChunkIterator into ChunkIteratorV1

* Remove segy_to_mdio_v1_customized, dataset_serializer.to_zarr

* Add support for trace headers without using _FillValue

* Use StorageLocation in trace_worker_v1

* Fix statistics attribute name

* PR review changes

* PR Improvements: do a single write

* TODO:  chunked write for non-dimensional coordinates and trace_mask

* Update StorageLocation to use fsspec

* Reformat with pre-commit

* Use domain name in get_grid_plan

* Fix non-dim coords and chunk_samples=False

* Convert test_3d_import_v1 to V1

* Fix test_meta_dataset_read

* remove whitespace

* clean up comments

* update deps in lockfile

* simplify dim and non-dim coordinate handling after scan

* remove compatibility tests

* add filtering capability to header worker

* accept subset filter to pass to workers

* make v1 grid planner awesome

* double to single underscores in test names

* fix broken test harnesses due to incorrect Sequence import

* clean up dev comment

* clean up whitespace

* use new module name

* clean up segy_to_mdio_v1

* fix whitespace and remove unnecessary list call

* these are defined as float64 in template

Previous check was passing due to an error in assignment during creation of coordinate variables

* fix missing dimension coordinate for vertical axis

* fix incorrect dtype comparison for time variable

* simplify and fix critical bugs

* rename v1 out of things and get rid of old code

* remove fixed todo

* remove more v1 from names

* rename chunk iterator

* fix dimensionality in tests due to new (missing) vertical dimension coordinate

* add todo for numpy ingestion

* fix references to non-v1 naming

* extract grid operations to its own function

* fix typo

Co-authored-by: Brian Michell <brianm314@comcast.net>

* add todo for simplifying storage location

* Remove no_fill_var_names, add domain var to Seismic3DPreStackShotTemplate

* Part 2 of the previous commit

* pre-commit formatting

* remove dev mount

---------

Co-authored-by: Dmitriy Repin <dmitriy_repin@epam.com>
Co-authored-by: Altay Sansal <tasansal@users.noreply.github.com>
Co-authored-by: Brian Michell <brianm314@comcast.net>
---
 src/mdio/api/convenience.py                   |  11 +-
 src/mdio/converters/numpy.py                  |   6 +-
 src/mdio/converters/segy.py                   | 607 ++++++++----------
 src/mdio/converters/type_converter.py         |  85 +++
 src/mdio/core/indexing.py                     | 117 ++--
 src/mdio/core/storage_location.py             |  87 +++
 src/mdio/schemas/v1/dataset_serializer.py     |  63 +-
 .../v1/templates/abstract_dataset_template.py | 136 +++-
 .../v1/templates/seismic_2d_poststack.py      |   6 +-
 .../v1/templates/seismic_3d_poststack.py      |   6 +-
 .../v1/templates/seismic_3d_prestack_cdp.py   |  10 +-
 .../v1/templates/seismic_3d_prestack_shot.py  |  30 +-
 .../schemas/v1/templates/template_registry.py |   2 +-
 src/mdio/segy/_workers.py                     | 125 ++--
 src/mdio/segy/blocked_io.py                   | 159 +++--
 src/mdio/segy/parsers.py                      |   6 +-
 src/mdio/segy/utilities.py                    |  38 +-
 tests/integration/test_segy_import_export.py  | 154 ++++-
 tests/integration/testing_helpers.py          |  69 ++
 tests/integration/v1/test_segy_to_mdio_v1.py  | 354 ++++++++++
 tests/unit/test_compat.py                     | 106 ---
 .../unit/v1/converters/test_type_converter.py |  95 +++
 tests/unit/v1/core/test_indexing.py           | 128 ++++
 tests/unit/v1/core/test_storage_location.py   | 132 ++++
 tests/unit/v1/helpers.py                      |  16 +-
 tests/unit/v1/templates/conftest.py           |  21 +
 .../v1/templates/test_seismic_2d_poststack.py | 158 +++--
 .../v1/templates/test_seismic_3d_poststack.py | 168 +++--
 .../templates/test_seismic_3d_prestack_cdp.py | 175 +++--
 .../test_seismic_3d_prestack_shot.py          | 245 +++----
 .../v1/templates/test_seismic_templates.py    |  62 +-
 .../v1/templates/test_template_registry.py    |   3 +-
 .../v1/test_dataset_builder_add_coordinate.py |  12 +-
 .../v1/test_dataset_builder_add_variable.py   |  16 +-
 tests/unit/v1/test_dataset_builder_build.py   |  22 +-
 tests/unit/v1/test_dataset_serializer.py      |  93 +--
 uv.lock                                       | 237 +++----
 37 files changed, 2441 insertions(+), 1319 deletions(-)
 create mode 100644 src/mdio/converters/type_converter.py
 create mode 100644 src/mdio/core/storage_location.py
 create mode 100644 tests/integration/testing_helpers.py
 create mode 100644 tests/integration/v1/test_segy_to_mdio_v1.py
 delete mode 100644 tests/unit/test_compat.py
 create mode 100644 tests/unit/v1/converters/test_type_converter.py
 create mode 100644 tests/unit/v1/core/test_indexing.py
 create mode 100644 tests/unit/v1/core/test_storage_location.py
 create mode 100644 tests/unit/v1/templates/conftest.py

diff --git a/src/mdio/api/convenience.py b/src/mdio/api/convenience.py
index a0536214d..4d8b5df6a 100644
--- a/src/mdio/api/convenience.py
+++ b/src/mdio/api/convenience.py
@@ -79,7 +79,11 @@ def copy_mdio(  # noqa: PLR0913
 
         writer.live_mask[:] = reader.live_mask[:]
 
-        iterator = ChunkIterator(reader._traces, chunk_samples=False)
+        shape = reader._traces.shape
+        chunks = reader._traces.chunks
+        chunks = chunks[:-1] + (shape[-1],)  # don't chunk samples
+
+        iterator = ChunkIterator(shape=shape, chunks=chunks)
         progress = tqdm(iterator, unit="block")
         progress.set_description(desc=f"Copying data for '{access_pattern=}'")
         for slice_ in progress:
@@ -177,7 +181,10 @@ def create_rechunk_plan(
 
     n_dimension = len(data_array.shape)
     dummy_array = zarr.empty(shape=data_array.shape, chunks=(MAX_BUFFER,) * n_dimension)
-    iterator = ChunkIterator(dummy_array)
+
+    shape = dummy_array.shape
+    chunks = dummy_array.chunks
+    iterator = ChunkIterator(shape=shape, chunks=chunks)
 
     return metadata_arrs, data_arrs, live_mask, iterator
 
diff --git a/src/mdio/converters/numpy.py b/src/mdio/converters/numpy.py
index 832b96563..de52e3143 100644
--- a/src/mdio/converters/numpy.py
+++ b/src/mdio/converters/numpy.py
@@ -7,7 +7,6 @@
 import numpy as np
 
 from mdio.api.accessor import MDIOWriter
-from mdio.converters.segy import get_compressor
 from mdio.core.dimension import Dimension
 from mdio.core.factory import MDIOCreateConfig
 from mdio.core.factory import MDIOVariableConfig
@@ -137,6 +136,11 @@ def numpy_to_mdio(  # noqa: PLR0913
     suffix = [str(idx) for idx, value in enumerate(suffix) if value is not None]
     suffix = "".join(suffix)
 
+    # TODO(Dmitrit Repin): Implement Numpy converted in MDIO v1
+    # https://github.com/TGSAI/mdio-python/issues/596
+    def get_compressor(lossless: bool, tolerance: float) -> list[str]:
+        pass
+
     compressors = get_compressor(lossless, compression_tolerance)
     mdio_var = MDIOVariableConfig(
         name=f"chunked_{suffix}",
diff --git a/src/mdio/converters/segy.py b/src/mdio/converters/segy.py
index 15946e84c..96f3ad1ae 100644
--- a/src/mdio/converters/segy.py
+++ b/src/mdio/converters/segy.py
@@ -1,42 +1,39 @@
-"""Conversion from SEG-Y to MDIO."""
+"""Conversion from SEG-Y to MDIO v1 format."""
 
 from __future__ import annotations
 
 import logging
 import os
 from typing import TYPE_CHECKING
-from typing import Any
 
 import numpy as np
-import zarr
-from numcodecs import Blosc
 from segy import SegyFile
 from segy.config import SegySettings
-from segy.schema import HeaderField
+from segy.standards.codes import MeasurementSystem as segy_MeasurementSystem
+from segy.standards.fields.trace import Rev0 as TraceHeaderFieldsRev0
 
+from mdio.constants import UINT32_MAX
 from mdio.converters.exceptions import EnvironmentFormatError
 from mdio.converters.exceptions import GridTraceCountError
 from mdio.converters.exceptions import GridTraceSparsityError
-from mdio.core import Grid
-from mdio.core.factory import MDIOCreateConfig
-from mdio.core.factory import MDIOVariableConfig
-from mdio.core.factory import create_empty
-from mdio.core.utils_write import write_attribute
+from mdio.converters.type_converter import to_structured_type
+from mdio.core.grid import Grid
+from mdio.schemas.v1.dataset_serializer import to_xarray_dataset
+from mdio.schemas.v1.units import AllUnits
+from mdio.schemas.v1.units import LengthUnitEnum
+from mdio.schemas.v1.units import LengthUnitModel
 from mdio.segy import blocked_io
-from mdio.segy.compat import mdio_segy_spec
 from mdio.segy.utilities import get_grid_plan
 
 if TYPE_CHECKING:
-    from collections.abc import Sequence
-    from pathlib import Path
-
-try:
-    import zfpy  # Base library
-    from numcodecs import ZFPY  # Codec
-except ImportError:
-    ZFPY = None
-    zfpy = None
+    from segy.arrays import HeaderArray as SegyHeaderArray
+    from segy.schema import SegySpec
+    from xarray import Dataset as xr_Dataset
 
+    from mdio.core.dimension import Dimension
+    from mdio.core.storage_location import StorageLocation
+    from mdio.schemas.v1.dataset import Dataset
+    from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
 
 logger = logging.getLogger(__name__)
 
@@ -115,354 +112,262 @@ def grid_density_qc(grid: Grid, num_traces: int) -> None:
         raise GridTraceSparsityError(grid.shape, num_traces, msg)
 
 
-def get_compressor(lossless: bool, compression_tolerance: float = -1) -> Blosc | ZFPY | None:
-    """Get the appropriate compressor for the seismic traces."""
-    if lossless:
-        compressor = Blosc("zstd")
-    else:
-        if zfpy is None or ZFPY is None:
-            msg = (
-                "Lossy compression requires the 'zfpy' library. It is not installed in your "
-                "environment. To proceed, please install 'zfpy' or install mdio `lossy` extra."
-            )
-            raise ImportError(msg)
-
-        compressor = ZFPY(mode=zfpy.mode_fixed_accuracy, tolerance=compression_tolerance)
-    return compressor
-
-
-def segy_to_mdio(  # noqa: PLR0913, PLR0915
-    segy_path: str | Path,
-    mdio_path_or_buffer: str | Path,
-    index_bytes: Sequence[int],
-    index_names: Sequence[str] | None = None,
-    index_types: Sequence[str] | None = None,
-    chunksize: tuple[int, ...] | None = None,
-    lossless: bool = True,
-    compression_tolerance: float = 0.01,
-    storage_options_input: dict[str, Any] | None = None,
-    storage_options_output: dict[str, Any] | None = None,
-    overwrite: bool = False,
-    grid_overrides: dict | None = None,
-) -> None:
-    """Convert SEG-Y file to MDIO format.
-
-    MDIO allows ingesting flattened seismic surveys in SEG-Y format into a multidimensional tensor
-    that represents the correct geometry of the seismic dataset.
-
-    The SEG-Y file must be on disk, MDIO currently does not support reading SEG-Y directly from
-    the cloud object store.
-
-    The output MDIO file can be local or on the cloud. For local files, a UNIX or Windows path is
-    sufficient. However, for cloud stores, an appropriate protocol must be provided. See examples
-    for more details.
+def _scan_for_headers(
+    segy_file: SegyFile, template: AbstractDatasetTemplate
+) -> tuple[list[Dimension], SegyHeaderArray]:
+    """Extract trace dimensions and index headers from the SEG-Y file.
 
-    The SEG-Y headers for indexing must also be specified. The index byte locations (starts from 1)
-    are the minimum amount of information needed to index the file. However, we suggest giving
-    names to the index dimensions, and if needed providing the header lengths if they are not
-    standard. By default, all header entries are assumed to be 4-byte long.
+    This is an expensive operation.
+    It scans the SEG-Y file in chunks by using ProcessPoolExecutor
+    """
+    # TODO(Dmitriy): implement grid overrides
+    # https://github.com/TGSAI/mdio-python/issues/585
+    # The 'grid_chunksize' is used only for grid_overrides
+    # While we do not support grid override, we can set it to None
+    grid_chunksize = None
+    segy_dimensions, chunksize, segy_headers = get_grid_plan(
+        segy_file=segy_file,
+        return_headers=True,
+        template=template,
+        chunksize=grid_chunksize,
+        grid_overrides=None,
+    )
+    return segy_dimensions, segy_headers
 
-    The chunk size depends on the data type, however, it can be chosen to accommodate any
-    workflow's access patterns. See examples below for some common use cases.
 
-    By default, the data is ingested with LOSSLESS compression. This saves disk space in the range
-    of 20% to 40%. MDIO also allows data to be compressed using the ZFP compressor's fixed rate
-    lossy compression. If lossless parameter is set to False and MDIO was installed using the lossy
-    extra; then the data will be compressed to approximately 30% of its original size and will be
-    perceptually lossless. The compression ratio can be adjusted using the option compression_ratio
-    (integer). Higher values will compress more, but will introduce artifacts.
+def _build_and_check_grid(
+    segy_dimensions: list[Dimension], segy_file: SegyFile, segy_headers: SegyHeaderArray
+) -> Grid:
+    """Build and check the grid from the SEG-Y headers and dimensions.
 
     Args:
-        segy_path: Path to the input SEG-Y file
-        mdio_path_or_buffer: Output path for the MDIO file, either local or cloud-based (e.g.,
-            with `s3://`, `gcs://`, or `abfs://` protocols).
-        index_bytes: Tuple of the byte location for the index attributes
-        index_names: List of names for the index dimensions. If not provided, defaults to `dim_0`,
-            `dim_1`, ..., with the last dimension named `sample`.
-        index_types: Tuple of the data-types for the index attributes. Must be in {"int16, int32,
-            float16, float32, ibm32"}. Default is 4-byte integers for each index key.
-        chunksize: Tuple specifying the chunk sizes for each dimension of the array. It must match
-            the number of dimensions in the input array.
-        lossless: If True, uses lossless Blosc compression with zstandard. If False, uses ZFP lossy
-            compression (requires `zfpy` library).
-        compression_tolerance: Tolerance for ZFP compression in lossy mode. Ignored if
-            `lossless=True`. Default is 0.01, providing ~70% size reduction.
-        storage_options_input: Dictionary of storage options for the SEGY input output file (e.g.,
-            cloud credentials). Defaults to None.
-        storage_options_output: Dictionary of storage options for the MDIO output output file
-            (e.g., cloud credentials). Defaults to None.
-        overwrite: If True, overwrites existing MDIO file at the specified path.
-        grid_overrides: Option to add grid overrides. See examples.
+        segy_dimensions: List of of all SEG-Y dimensions to build grid from.
+        segy_file: Instance of SegyFile to check for trace count.
+        segy_headers: Headers read in from SEG-Y file for building the trace map.
+
+    Returns:
+        A grid instance populated with the dimensions and trace index map.
 
     Raises:
-        GridTraceCountError: Raised if grid won't hold all traces in the SEG-Y file.
-        ValueError: If length of chunk sizes don't match number of dimensions.
-        NotImplementedError: If can't determine chunking automatically for 4D+.
-
-    Examples:
-        If we are working locally and ingesting a 3D post-stack seismic file, we can use the
-        following example. This will ingest with default chunks of 128 x 128 x 128.
-
-        >>> from mdio import segy_to_mdio
-        >>>
-        >>>
-        >>> segy_to_mdio(
-        ...     segy_path="prefix1/file.segy",
-        ...     mdio_path_or_buffer="prefix2/file.mdio",
-        ...     index_bytes=(189, 193),
-        ...     index_names=("inline", "crossline")
-        ... )
-
-        If we are on Amazon Web Services, we can do it like below. The protocol before the URL can
-        be `s3` for AWS, `gcs` for Google Cloud, and `abfs` for Microsoft Azure. In this example we
-        also change the chunk size as a demonstration.
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/file.mdio",
-        ...     index_bytes=(189, 193),
-        ...     index_names=("inline", "crossline"),
-        ...     chunksize=(64, 64, 512),
-        ... )
-
-        Another example of loading a 4D seismic such as 3D seismic pre-stack gathers is below. This
-        will allow us to extract offset planes efficiently or run things in a local neighborhood
-        very efficiently.
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/file.mdio",
-        ...     index_bytes=(189, 193, 37),
-        ...     index_names=("inline", "crossline", "offset"),
-        ...     chunksize=(16, 16, 16, 512),
-        ... )
-
-        We can override the dataset grid by the `grid_overrides` parameter. This allows us to
-        ingest files that don't conform to the true geometry of the seismic acquisition.
-
-        For example if we are ingesting 3D seismic shots that don't have a cable number and channel
-        numbers are sequential (i.e. each cable doesn't start with channel number 1; we can tell
-        MDIO to ingest this with the correct geometry by calculating cable numbers and wrapped
-        channel numbers. Note the missing byte location and word length for the "cable" index.
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/shot_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/shot_file.mdio",
-        ...     index_bytes=(17, None, 13),
-        ...     index_lengths=(4, None, 4),
-        ...     index_names=("shot", "cable", "channel"),
-        ...     chunksize=(8, 2, 128, 1024),
-        ...     grid_overrides={
-        ...         "ChannelWrap": True, "ChannelsPerCable": 800,
-        ...         "CalculateCable": True
-        ...     },
-        ... )
-
-        If we do have cable numbers in the headers, but channels are still sequential (aka.
-        unwrapped), we can still ingest it like this.
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/shot_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/shot_file.mdio",
-        ...     index_bytes=(17, 137, 13),
-        ...     index_lengths=(4, 2, 4),
-        ...     index_names=("shot_point", "cable", "channel"),
-        ...     chunksize=(8, 2, 128, 1024),
-        ...     grid_overrides={"ChannelWrap": True, "ChannelsPerCable": 800},
-        ... )
-
-        For shot gathers with channel numbers and wrapped channels, no grid overrides necessary.
-
-        In cases where the user does not know if the input has unwrapped channels but desires to
-        store with wrapped channel index use:
-        >>> grid_overrides = {
-        ...    "AutoChannelWrap": True,
-        ...    "AutoChannelTraceQC": 1000000
-        ... }
-
-        For ingestion of pre-stack streamer data where the user needs to access/index
-        *common-channel gathers* (single gun) then the following strategy can be used to densely
-        ingest while indexing on gun number:
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/shot_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/shot_file.mdio",
-        ...     index_bytes=(133, 171, 17, 137, 13),
-        ...     index_lengths=(2, 2, 4, 2, 4),
-        ...     index_names=("shot_line", "gun", "shot_point", "cable", "channel"),
-        ...     chunksize=(1, 1, 8, 1, 128, 1024),
-        ...     grid_overrides={
-        ...         "AutoShotWrap": True,
-        ...         "AutoChannelWrap": True,
-        ...         "AutoChannelTraceQC":  1000000
-        ...     },
-        ... )
-
-        For AutoShotWrap and AutoChannelWrap to work, the user must provide "shot_line", "gun",
-        "shot_point", "cable", "channel". For improved common-channel performance consider
-        modifying the chunksize to be (1, 1, 32, 1, 32, 2048) for good common-shot and
-        common-channel performance or (1, 1, 128, 1, 1, 2048) for common-channel performance.
-
-        For cases with no well-defined trace header for indexing a NonBinned grid override is
-        provided.This creates the index and attributes an incrementing integer to the trace for
-        the index based on first in first out. For example a CDP and Offset keyed file might have a
-        header for offset as real world offset which would result in a very sparse populated index.
-        Instead, the following override will create a new index from 1 to N, where N is the number
-        of offsets within a CDP ensemble. The index to be auto generated is called "trace". Note
-        the required "chunksize" parameter in the grid override. This is due to the non-binned
-        ensemble chunksize is irrelevant to the index dimension chunksizes and has to be specified
-        in the grid override itself. Note the lack of offset, only indexing CDP, providing CDP
-        header type, and chunksize for only CDP and Sample dimension. The chunksize for non-binned
-        dimension is in the grid overrides as described above. The below configuration will yield
-        1MB chunks:
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/cdp_offset_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/cdp_offset_file.mdio",
-        ...     index_bytes=(21,),
-        ...     index_types=("int32",),
-        ...     index_names=("cdp",),
-        ...     chunksize=(4, 1024),
-        ...     grid_overrides={"NonBinned": True, "chunksize": 64},
-        ... )
-
-        A more complicated case where you may have a 5D dataset that is not binned in Offset and
-        Azimuth directions can be ingested like below. However, the Offset and Azimuth dimensions
-        will be combined to "trace" dimension. The below configuration will yield 1MB chunks.
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/cdp_offset_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/cdp_offset_file.mdio",
-        ...     index_bytes=(189, 193),
-        ...     index_types=("int32", "int32"),
-        ...     index_names=("inline", "crossline"),
-        ...     chunksize=(4, 4, 1024),
-        ...     grid_overrides={"NonBinned": True, "chunksize": 64},
-        ... )
-
-        For dataset with expected duplicate traces we have the following parameterization. This
-        will use the same logic as NonBinned with a fixed chunksize of 1. The other keys are still
-        important. The below example allows multiple traces per receiver (i.e. reshoot).
-
-        >>> segy_to_mdio(
-        ...     segy_path="prefix/cdp_offset_file.segy",
-        ...     mdio_path_or_buffer="s3://bucket/cdp_offset_file.mdio",
-        ...     index_bytes=(9, 213, 13),
-        ...     index_types=("int32", "int16", "int32"),
-        ...     index_names=("shot", "cable", "chan"),
-        ...     chunksize=(8, 2, 256, 512),
-        ...     grid_overrides={"HasDuplicates": True},
-        ... )
+        GridTraceCountError: If number of traces in SEG-Y file does not match the parsed grid
     """
-    index_names = index_names or [f"dim_{i}" for i in range(len(index_bytes))]
-    index_types = index_types or ["int32"] * len(index_bytes)
-
-    if chunksize is not None and len(chunksize) != len(index_bytes) + 1:
-        message = (
-            f"Length of chunks={len(chunksize)} must be equal to array "
-            f"dimensions={len(index_bytes) + 1}"
-        )
-        raise ValueError(message)
-
-    # Handle storage options and check permissions etc
-    storage_options_input = storage_options_input or {}
-    storage_options_output = storage_options_output or {}
-
-    # Open SEG-Y with MDIO's SegySpec. Endianness will be inferred.
-    mdio_spec = mdio_segy_spec()
-    segy_settings = SegySettings(storage_options=storage_options_input)
-    segy = SegyFile(url=segy_path, spec=mdio_spec, settings=segy_settings)
-
-    text_header = segy.text_header
-    binary_header = segy.binary_header
-    num_traces = segy.num_traces
-
-    # Index the dataset using a spec that interprets the user provided index headers.
-    index_fields = []
-    for name, byte, format_ in zip(index_names, index_bytes, index_types, strict=True):
-        index_fields.append(HeaderField(name=name, byte=byte, format=format_))
-    mdio_spec_grid = mdio_spec.customize(trace_header_fields=index_fields)
-    segy_grid = SegyFile(url=segy_path, spec=mdio_spec_grid, settings=segy_settings)
-
-    dimensions, chunksize, index_headers = get_grid_plan(
-        segy_file=segy_grid,
-        return_headers=True,
-        chunksize=chunksize,
-        grid_overrides=grid_overrides,
-    )
-    grid = Grid(dims=dimensions)
-    grid_density_qc(grid, num_traces)
-    grid.build_map(index_headers)
-
+    grid = Grid(dims=segy_dimensions)
+    grid_density_qc(grid, segy_file.num_traces)
+    grid.build_map(segy_headers)
     # Check grid validity by comparing trace numbers
-    if np.sum(grid.live_mask) != num_traces:
+    if np.sum(grid.live_mask) != segy_file.num_traces:
         for dim_name in grid.dim_names:
             dim_min, dim_max = grid.get_min(dim_name), grid.get_max(dim_name)
             logger.warning("%s min: %s max: %s", dim_name, dim_min, dim_max)
         logger.warning("Ingestion grid shape: %s.", grid.shape)
-        raise GridTraceCountError(np.sum(grid.live_mask), num_traces)
-
-    if chunksize is None:
-        dim_count = len(index_names) + 1
-        if dim_count == 2:  # noqa: PLR2004
-            chunksize = (512,) * 2
-
-        elif dim_count == 3:  # noqa: PLR2004
-            chunksize = (64,) * 3
-
-        else:
-            msg = (
-                f"Default chunking for {dim_count}-D seismic data is not implemented yet. "
-                "Please explicity define chunk sizes."
-            )
-            raise NotImplementedError(msg)
-
-        suffix = [str(x) for x in range(dim_count)]
-        suffix = "".join(suffix)
-    else:
-        suffix = [dim_chunks if dim_chunks > 0 else None for dim_chunks in chunksize]
-        suffix = [str(idx) for idx, value in enumerate(suffix) if value is not None]
-        suffix = "".join(suffix)
-
-    compressors = get_compressor(lossless, compression_tolerance)
-    header_dtype = segy.spec.trace.header.dtype.newbyteorder("=")
-    var_conf = MDIOVariableConfig(
-        name=f"chunked_{suffix}",
-        dtype="float32",
-        chunks=chunksize,
-        compressors=compressors,
-        header_dtype=header_dtype,
+        raise GridTraceCountError(np.sum(grid.live_mask), segy_file.num_traces)
+    return grid
+
+
+def _get_coordinates(
+    segy_dimensions: list[Dimension],
+    segy_headers: SegyHeaderArray,
+    mdio_template: AbstractDatasetTemplate,
+) -> tuple[list[Dimension], dict[str, SegyHeaderArray]]:
+    """Get the data dim and non-dim coordinates from the SEG-Y headers and MDIO template.
+
+    Select a subset of the segy_dimensions that corresponds to the MDIO dimensions
+    The dimensions are ordered as in the MDIO template.
+    The last dimension is always the vertical domain dimension
+
+    Args:
+        segy_dimensions: List of of all SEG-Y dimensions.
+        segy_headers: Headers read in from SEG-Y file.
+        mdio_template: The MDIO template to use for the conversion.
+
+    Raises:
+        ValueError: If a dimension or coordinate name from the MDIO template is not found in
+                    the SEG-Y headers.
+
+    Returns:
+        A tuple containing:
+            - A list of dimension coordinates (1-D arrays).
+            - A dict of non-dimension coordinates (str: N-D arrays).
+    """
+    dimensions_coords = []
+    dim_names = [dim.name for dim in segy_dimensions]
+    for dim_name in mdio_template.dimension_names:
+        try:
+            dim_index = dim_names.index(dim_name)
+        except ValueError:
+            err = f"Dimension '{dim_name}' was not found in SEG-Y dimensions."
+            raise ValueError(err) from err
+        dimensions_coords.append(segy_dimensions[dim_index])
+
+    non_dim_coords: dict[str, SegyHeaderArray] = {}
+    available_headers = segy_headers.dtype.names
+    for coord_name in mdio_template.coordinate_names:
+        if coord_name not in available_headers:
+            err = f"Coordinate '{coord_name}' not found in SEG-Y dimensions."
+            raise ValueError(err)
+        non_dim_coords[coord_name] = segy_headers[coord_name]
+
+    return dimensions_coords, non_dim_coords
+
+
+def populate_dim_coordinates(
+    dataset: xr_Dataset, grid: Grid, drop_vars_delayed: list[str]
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate the xarray dataset with dimension coordinate variables."""
+    for dim in grid.dims:
+        dataset[dim.name].values[:] = dim.coords
+        drop_vars_delayed.append(dim.name)
+    return dataset, drop_vars_delayed
+
+
+def populate_non_dim_coordinates(
+    dataset: xr_Dataset,
+    grid: Grid,
+    coordinates: dict[str, SegyHeaderArray],
+    drop_vars_delayed: list[str],
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate the xarray dataset with coordinate variables."""
+    not_null = grid.map[:] != UINT32_MAX
+    for c_name, c_values in coordinates.items():
+        dataset[c_name].values[not_null] = c_values
+        drop_vars_delayed.append(c_name)
+    return dataset, drop_vars_delayed
+
+
+def _get_horizontal_coordinate_unit(segy_headers: list[Dimension]) -> LengthUnitEnum | None:
+    """Get the coordinate unit from the SEG-Y headers."""
+    name = TraceHeaderFieldsRev0.COORDINATE_UNIT.name.upper()
+    unit_hdr = next((c for c in segy_headers if c.name.upper() == name), None)
+    if unit_hdr is None or len(unit_hdr.coords) == 0:
+        # If the coordinate unit header is not found or empty, return None
+        # This is a common case for SEG-Y files, where the coordinate unit is not specified
+        return None
+
+    if segy_MeasurementSystem(unit_hdr.coords[0]) == segy_MeasurementSystem.METERS:
+        # If the coordinate unit is in meters, return "m"
+        return AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))
+    if segy_MeasurementSystem(unit_hdr.coords[0]) == segy_MeasurementSystem.FEET:
+        # If the coordinate unit is in feet, return "ft"
+        return AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT))
+    err = f"Unsupported coordinate unit value: {unit_hdr.value[0]} in SEG-Y file."
+    raise ValueError(err)
+
+
+def _populate_coordinates(
+    dataset: xr_Dataset,
+    grid: Grid,
+    coords: dict[str, SegyHeaderArray],
+) -> tuple[xr_Dataset, list[str]]:
+    """Populate dim and non-dim coordinates in the xarray dataset and write to Zarr.
+
+    This will write the xr Dataset with coords and dimensions, but empty traces and headers.
+
+    Args:
+        dataset: The xarray dataset to populate.
+        grid: The grid object containing the grid map.
+        coords: The non-dim coordinates to populate.
+
+    Returns:
+        Xarray dataset with filled coordinates and updated variables to drop after writing
+    """
+    drop_vars_delayed = []
+    # Populate the dimension coordinate variables (1-D arrays)
+    dataset, vars_to_drop_later = populate_dim_coordinates(
+        dataset, grid, drop_vars_delayed=drop_vars_delayed
     )
-    config = MDIOCreateConfig(path=mdio_path_or_buffer, grid=grid, variables=[var_conf])
 
-    root_group = create_empty(
-        config,
-        overwrite=overwrite,
-        storage_options=storage_options_output,
-        consolidate_meta=False,
+    # Populate the non-dimension coordinate variables (N-dim arrays)
+    dataset, vars_to_drop_later = populate_non_dim_coordinates(
+        dataset, grid, coordinates=coords, drop_vars_delayed=drop_vars_delayed
     )
-    data_group = root_group["data"]
-    meta_group = root_group["metadata"]
-    data_array = data_group[f"chunked_{suffix}"]
-    header_array = meta_group[f"chunked_{suffix}_trace_headers"]
-
-    # Write actual live mask and metadata to empty MDIO
-    meta_group["live_mask"][:] = grid.live_mask[:]
-    nonzero_count = np.count_nonzero(grid.live_mask)
-    write_attribute(name="trace_count", zarr_group=root_group, attribute=nonzero_count)
-    write_attribute(name="text_header", zarr_group=meta_group, attribute=text_header.split("\n"))
-    write_attribute(name="binary_header", zarr_group=meta_group, attribute=binary_header.to_dict())
-
-    # Write traces
-    stats = blocked_io.to_zarr(
-        segy_file=segy,
+
+    return dataset, drop_vars_delayed
+
+
+def segy_to_mdio(
+    segy_spec: SegySpec,
+    mdio_template: AbstractDatasetTemplate,
+    input_location: StorageLocation,
+    output_location: StorageLocation,
+    overwrite: bool = False,
+) -> None:
+    """A function that converts a SEG-Y file to an MDIO v1 file.
+
+    Ingest a SEG-Y file according to the segy_spec. This could be a spec from registry or custom.
+
+    Args:
+        segy_spec: The SEG-Y specification to use for the conversion.
+        mdio_template: The MDIO template to use for the conversion.
+        input_location: The storage location of the input SEG-Y file.
+        output_location: The storage location for the output MDIO v1 file.
+        overwrite: Whether to overwrite the output file if it already exists. Defaults to False.
+
+    Raises:
+        FileExistsError: If the output location already exists and overwrite is False.
+    """
+    if not overwrite and output_location.exists():
+        err = f"Output location '{output_location.uri}' exists. Set `overwrite=True` if intended."
+        raise FileExistsError(err)
+
+    segy_settings = SegySettings(storage_options=input_location.options)
+    segy_file = SegyFile(url=input_location.uri, spec=segy_spec, settings=segy_settings)
+
+    # Scan the SEG-Y file for headers
+    segy_dimensions, segy_headers = _scan_for_headers(segy_file, mdio_template)
+
+    grid = _build_and_check_grid(segy_dimensions, segy_file, segy_headers)
+
+    dimensions, non_dim_coords = _get_coordinates(segy_dimensions, segy_headers, mdio_template)
+    shape = [len(dim.coords) for dim in dimensions]
+    headers = to_structured_type(segy_headers.dtype)
+
+    horizontal_unit = _get_horizontal_coordinate_unit(segy_dimensions)
+    mdio_ds: Dataset = mdio_template.build_dataset(
+        name=mdio_template.name, sizes=shape, horizontal_coord_unit=horizontal_unit, headers=headers
+    )
+
+    xr_dataset: xr_Dataset = to_xarray_dataset(mdio_ds=mdio_ds)
+
+    xr_dataset, drop_vars_delayed = _populate_coordinates(
+        dataset=xr_dataset,
         grid=grid,
-        data_array=data_array,
-        header_array=header_array,
+        coords=non_dim_coords,
     )
 
-    # Write actual stats
-    for key, value in stats.items():
-        write_attribute(name=key, zarr_group=root_group, attribute=value)
+    xr_dataset.trace_mask.data[:] = grid.live_mask
+
+    # TODO(Dmitriy Repin): Write out text and binary headers.
+    # https://github.com/TGSAI/mdio-python/issues/595
+
+    # IMPORTANT: Do not drop the "trace_mask" here, as it will be used later in
+    # blocked_io.to_zarr() -> _workers.trace_worker()
+
+    # Write the xarray dataset to Zarr with as following:
+    # Populated arrays:
+    # - 1D dimensional coordinates
+    # - ND non-dimensional coordinates
+    # - ND trace_mask
+    # Empty arrays (will be populated later in chunks):
+    # - ND+1 traces
+    # - ND headers (no _FillValue set due to the bug https://github.com/TGSAI/mdio-python/issues/582)
+    # This will create the Zarr store with the correct structure
+    # TODO(Dmitriy Repin): do chunked write for non-dimensional coordinates and trace_mask
+    # https://github.com/TGSAI/mdio-python/issues/587
+    xr_dataset.to_zarr(
+        store=output_location.uri, mode="w", write_empty_chunks=False, zarr_format=2, compute=True
+    )
 
-    zarr.consolidate_metadata(root_group.store)
+    # Now we can drop them to simplify chunked write of the data variable
+    xr_dataset = xr_dataset.drop_vars(drop_vars_delayed)
+
+    # Write the headers and traces in chunks using grid_map to indicate dead traces
+    data_variable_name = mdio_template.trace_variable_name
+    # This is an memory-expensive and time-consuming read-write operation
+    # performed in chunks to save the memory
+    blocked_io.to_zarr(
+        segy_file=segy_file,
+        output_location=output_location,
+        grid_map=grid.map,
+        dataset=xr_dataset,
+        data_variable_name=data_variable_name,
+    )
diff --git a/src/mdio/converters/type_converter.py b/src/mdio/converters/type_converter.py
new file mode 100644
index 000000000..20ce63d2e
--- /dev/null
+++ b/src/mdio/converters/type_converter.py
@@ -0,0 +1,85 @@
+"""A module for converting numpy dtypes to MDIO scalar and structured types."""
+
+from numpy import dtype as np_dtype
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+
+
+def to_scalar_type(data_type: np_dtype) -> ScalarType:
+    """Convert numpy dtype to MDIO ScalarType.
+
+    Out of the 24 built-in numpy scalar type objects
+    (see https://numpy.org/doc/stable/reference/arrays.dtypes.html)
+    this function supports only a limited subset:
+        ScalarType.INT8 <-> int8
+        ScalarType.INT16 <-> int16
+        ScalarType.INT32 <-> int32
+        ScalarType.INT64 <-> int64
+        ScalarType.UINT8 <-> uint8
+        ScalarType.UINT16 <-> uint16
+        ScalarType.UINT32 <-> uint32
+        ScalarType.UINT64 <-> uint64
+        ScalarType.FLOAT32 <-> float32
+        ScalarType.FLOAT64 <-> float64
+        ScalarType.COMPLEX64 <-> complex64
+        ScalarType.COMPLEX128 <-> complex128
+        ScalarType.BOOL <-> bool
+
+    Args:
+        data_type: numpy dtype to convert
+
+    Returns:
+        ScalarType: corresponding MDIO scalar type
+
+    Raises:
+        ValueError: if dtype is not supported
+    """
+    try:
+        return ScalarType(data_type.name)
+    except ValueError as exc:
+        err = f"Unsupported numpy dtype '{data_type.name}' for conversion to ScalarType."
+        raise ValueError(err) from exc
+
+
+def to_structured_type(data_type: np_dtype) -> StructuredType:
+    """Convert numpy dtype to MDIO StructuredType.
+
+    This function supports only a limited subset of structured types.
+    In particular:
+    It does not support nested structured types.
+    It supports fields of only 13 out of 24 built-in numpy scalar types.
+    (see `to_scalar_type` for details).
+
+    Args:
+        data_type: numpy dtype to convert
+
+    Returns:
+        StructuredType: corresponding MDIO structured type
+
+    Raises:
+        ValueError: if dtype is not structured or has no fields
+
+    """
+    if data_type is None or len(data_type.names or []) == 0:
+        err = "None or empty dtype provided, cannot convert to StructuredType."
+        raise ValueError(err)
+
+    fields = []
+    for field_name in data_type.names:
+        field_dtype = data_type.fields[field_name][0]
+        scalar_type = to_scalar_type(field_dtype)
+        structured_field = StructuredField(name=field_name, format=scalar_type)
+        fields.append(structured_field)
+    return StructuredType(fields=fields)
+
+
+def to_numpy_dtype(data_type: ScalarType | StructuredType) -> np_dtype:
+    """Get the numpy dtype for a variable."""
+    if isinstance(data_type, ScalarType):
+        return np_dtype(data_type.value)
+    if isinstance(data_type, StructuredType):
+        return np_dtype([(f.name, f.format.value) for f in data_type.fields])
+    msg = f"Expected ScalarType or StructuredType, got '{type(data_type).__name__}'"
+    raise ValueError(msg)
diff --git a/src/mdio/core/indexing.py b/src/mdio/core/indexing.py
index 936178f8d..1e10cadfb 100644
--- a/src/mdio/core/indexing.py
+++ b/src/mdio/core/indexing.py
@@ -4,78 +4,83 @@
 from math import ceil
 
 import numpy as np
-from zarr import Array
 
 
 class ChunkIterator:
-    """Iterator for traversing a Zarr array in chunks.
+    """Chunk iterator for multi-dimensional arrays.
 
-    This iterator yields tuples of slices corresponding to the chunk boundaries of a Zarr array.
-    It supports chunking all dimensions or taking the full extent of the last dimension.
+    This iterator takes an array shape and chunks and every time it is iterated, it returns
+    a dictionary (if dimensions are provided) or a tuple of slices that align with
+    chunk boundaries. When dimensions are provided, they are used as the dictionary keys.
 
     Args:
-        array: The Zarr array to iterate, providing shape and chunk sizes.
-        chunk_samples: If True, chunks all dimensions. If False, takes the full extent of the
-            last dimension. Defaults to True.
-
-
-    Example:
-        >>> import zarr
-        >>> arr = zarr.array(np.zeros((10, 20)), chunks=(3, 4))
-        >>> it = ChunkIterator(arr)
-        >>> for slices in it:
-        ...     print(slices)
-        (slice(0, 3, None), slice(0, 4, None))
-        (slice(0, 3, None), slice(4, 8, None))
-        ...
-        >>> it = ChunkIterator(arr, chunk_samples=False)
-        >>> for slices in it:
-        ...     print(slices)
-        (slice(0, 3, None), slice(0, 20, None))
-        (slice(3, 6, None), slice(0, 20, None))
-        ...
+        shape: The shape of the array.
+        chunks: The chunk sizes for each dimension.
+        dim_names: The names of the array dimensions, to be used with DataArray.isel().
+                   If the dim_names are not provided, a tuple of the slices will be returned.
+
+    Attributes:             # noqa: DOC602
+        arr_shape: Shape of the array.
+        len_chunks: Length of chunks in each dimension.
+        dim_chunks: Number of chunks in each dimension.
+        num_chunks: Total number of chunks.
+
+    Examples:
+        >> chunks = (3, 4, 5)
+        >> shape = (5, 11, 19)
+        >> dims = ["inline", "crossline", "depth"]
+        >>
+        >> iter = ChunkIterator(shape=shape, chunks=chunks, dim_names=dims)
+        >> for i in range(13):
+        >>    region = iter.__next__()
+        >> print(region)
+        { "inline": slice(3,6, None), "crossline": slice(0,4, None), "depth": slice(0,5, None) }
+
+        >> iter = ChunkIterator(shape=shape, chunks=chunks, dim_names=None)
+        >> for i in range(13):
+        >>    region = iter.__next__()
+        >> print(region)
+        (slice(3,6,None), slice(0,4,None), slice(0,5,None))
     """
 
-    def __init__(self, array: Array, chunk_samples: bool = True):
-        self.arr_shape = array.shape
-        self.len_chunks = array.chunks
-
-        # If chunk_samples is False, set the last dimension's chunk size to its full extent
-        if not chunk_samples:
-            self.len_chunks = self.len_chunks[:-1] + (self.arr_shape[-1],)
-
-        # Calculate the number of chunks per dimension
-        self.dim_chunks = [
-            ceil(len_dim / chunk)
-            for len_dim, chunk in zip(self.arr_shape, self.len_chunks, strict=True)
-        ]
+    def __init__(
+        self, shape: tuple[int, ...], chunks: tuple[int, ...], dim_names: tuple[str, ...] = None
+    ):
+        self.arr_shape = tuple(shape)  # Deep copy to ensure immutability
+        self.len_chunks = tuple(chunks)  # Deep copy to ensure immutability
+        self.dims = dim_names
+
+        # Compute number of chunks per dimension, and total number of chunks
+        self.dim_chunks = tuple(
+            [
+                ceil(len_dim / chunk)
+                for len_dim, chunk in zip(self.arr_shape, self.len_chunks, strict=True)
+            ]
+        )
         self.num_chunks = np.prod(self.dim_chunks)
 
-        # Set up chunk index combinations using ranges for each dimension
+        # Under the hood stuff for the iterator. This generates C-ordered
+        # permutation of chunk indices.
         dim_ranges = [range(dim_len) for dim_len in self.dim_chunks]
         self._ranges = itertools.product(*dim_ranges)
         self._idx = 0
 
     def __iter__(self) -> "ChunkIterator":
-        """Return the iterator object itself."""
+        """Iteration context."""
         return self
 
     def __len__(self) -> int:
-        """Return the total number of chunks."""
+        """Get total number of chunks."""
         return self.num_chunks
 
-    def __next__(self) -> tuple[slice, ...]:
-        """Yield the next set of chunk slices.
-
-        Returns:
-            A tuple of slice objects for each dimension.
-
-        Raises:
-            StopIteration: When all chunks have been iterated over.
-        """
-        if self._idx < self.num_chunks:
+    def __next__(self) -> dict[str, slice]:
+        """Iteration logic."""
+        if self._idx <= self.num_chunks:
+            # We build slices here. It is dimension agnostic
             current_start = next(self._ranges)
 
+            # TODO (Dmitriy Repin): Enhance ChunkIterator to make the last slice, if needed, smaller
+            # https://github.com/TGSAI/mdio-python/issues/586
             start_indices = tuple(
                 dim * chunk for dim, chunk in zip(current_start, self.len_chunks, strict=True)
             )
@@ -88,7 +93,17 @@ def __next__(self) -> tuple[slice, ...]:
                 slice(start, stop) for start, stop in zip(start_indices, stop_indices, strict=True)
             )
 
+            if self.dims:  # noqa SIM108
+                # Example
+                # {"inline":slice(3,6,None), "crossline":slice(0,4,None), "depth":slice(0,5,None)}
+                result = dict(zip(self.dims, slices, strict=False))
+            else:
+                # Example
+                # (slice(3,6,None), slice(0,4,None), slice(0,5,None))
+                result = slices
+
             self._idx += 1
-            return slices
+
+            return result
 
         raise StopIteration
diff --git a/src/mdio/core/storage_location.py b/src/mdio/core/storage_location.py
new file mode 100644
index 000000000..3a5adb2a1
--- /dev/null
+++ b/src/mdio/core/storage_location.py
@@ -0,0 +1,87 @@
+"""StorageLocation class for managing local and cloud storage locations."""
+
+from pathlib import Path
+from typing import Any
+
+import fsspec
+
+
+# TODO(Dmitriy Repin): Reuse fsspec functions for some methods we implemented here
+# https://github.com/TGSAI/mdio-python/issues/597
+class StorageLocation:
+    """A class to represent a local or cloud storage location for SEG-Y or MDIO files.
+
+    This class abstracts the storage location, allowing for both local file paths and
+    cloud storage URIs (e.g., S3, GCS). It uses fsspec to check existence and manage options.
+    Note, we do not want to make it a dataclass because we want the uri and the options to
+    be read-only immutable properties.
+
+        uri: The URI of the storage location (e.g., '/path/to/file', 'file:///path/to/file',
+                's3://bucket/path', 'gs://bucket/path').
+        options: Optional dictionary of options for the cloud, such as credentials.
+
+    """
+
+    def __init__(self, uri: str = "", options: dict[str, Any] = None):
+        self._uri = uri
+        self._options = options or {}
+        self._fs = None
+
+        if uri.startswith(("s3://", "gs://")):
+            return
+
+        if uri.startswith("file://"):
+            self._uri = self._uri.removeprefix("file://")
+        # For local paths, ensure they are absolute and resolved
+        self._uri = str(Path(self._uri).resolve())
+        return
+
+    @property
+    def uri(self) -> str:
+        """Get the URI (read-only)."""
+        return self._uri
+
+    @property
+    def options(self) -> dict[str, Any]:
+        """Get the options (read-only)."""
+        # Return a copy to prevent external modification
+        return self._options.copy()
+
+    @property
+    def _filesystem(self) -> fsspec.AbstractFileSystem:
+        """Get the fsspec filesystem instance for this storage location."""
+        if self._fs is None:
+            self._fs = fsspec.filesystem(self._protocol, **self._options)
+        return self._fs
+
+    @property
+    def _path(self) -> str:
+        """Extract the path portion from the URI."""
+        if "://" in self._uri:
+            return self._uri.split("://", 1)[1]
+        return self._uri  # For local paths without file:// prefix
+
+    @property
+    def _protocol(self) -> str:
+        """Extract the protocol/scheme from the URI."""
+        if "://" in self._uri:
+            return self._uri.split("://", 1)[0]
+        return "file"  # Default to file protocol
+
+    def exists(self) -> bool:
+        """Check if the storage location exists using fsspec."""
+        try:
+            return self._filesystem.exists(self._path)
+        except Exception as e:
+            # Log the error and return False for safety
+            # In a production environment, you might want to use proper logging
+            print(f"Error checking existence of {self._uri}: {e}")
+            return False
+
+    def __str__(self) -> str:
+        """String representation of the storage location."""
+        return self._uri
+
+    def __repr__(self) -> str:
+        """Developer representation of the storage location."""
+        return f"StorageLocation(uri='{self._uri}', options={self._options})"
diff --git a/src/mdio/schemas/v1/dataset_serializer.py b/src/mdio/schemas/v1/dataset_serializer.py
index f1d21221e..af77e0c2e 100644
--- a/src/mdio/schemas/v1/dataset_serializer.py
+++ b/src/mdio/schemas/v1/dataset_serializer.py
@@ -1,15 +1,14 @@
 """Convert MDIO v1 schema Dataset to Xarray DataSet and write it in Zarr."""
 
-from collections.abc import Mapping
-
 import numpy as np
 from numcodecs import Blosc as nc_Blosc
-from numpy import dtype as np_dtype
 from xarray import DataArray as xr_DataArray
 from xarray import Dataset as xr_Dataset
 from zarr import zeros as zarr_zeros
 from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
 
+from mdio.converters.type_converter import to_numpy_dtype
+
 try:
     # zfpy is an optional dependency for ZFP compression
     # It is not installed by default, so we check for its presence and import it only if available.
@@ -91,16 +90,6 @@ def _get_coord_names(var: Variable) -> list[str]:
     return coord_names
 
 
-def _get_np_datatype(data_type: ScalarType | StructuredType) -> np_dtype:
-    """Get the numpy dtype for a variable."""
-    if isinstance(data_type, ScalarType):
-        return np_dtype(data_type.value)
-    if isinstance(data_type, StructuredType):
-        return np_dtype([(f.name, f.format.value) for f in data_type.fields])
-    msg = f"Expected ScalarType or StructuredType, got '{type(data_type).__name__}'"
-    raise ValueError(msg)
-
-
 def _get_zarr_shape(var: Variable, all_named_dims: dict[str, NamedDimension]) -> tuple[int, ...]:
     """Get the shape of a variable for Zarr storage.
 
@@ -170,7 +159,7 @@ def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     if isinstance(data_type, ScalarType):
         return fill_value_map.get(data_type)
     if isinstance(data_type, StructuredType):
-        d_type = _get_np_datatype(data_type)
+        d_type = to_numpy_dtype(data_type)
         return np.zeros((), dtype=d_type)
     if isinstance(data_type, str):
         return ""
@@ -178,7 +167,7 @@ def _get_fill_value(data_type: ScalarType | StructuredType | str) -> any:
     return None
 
 
-def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
+def to_xarray_dataset(mdio_ds: Dataset) -> xr_Dataset:  # noqa: PLR0912
     """Build an XArray dataset with correct dimensions and dtypes.
 
     This function constructs the underlying data structure for an XArray dataset,
@@ -203,7 +192,7 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
     data_arrays: dict[str, xr_DataArray] = {}
     for v in mdio_ds.variables:
         shape = _get_zarr_shape(v, all_named_dims=all_named_dims)
-        dtype = _get_np_datatype(v.data_type)
+        dtype = to_numpy_dtype(v.data_type)
         chunks = _get_zarr_chunks(v, all_named_dims=all_named_dims)
 
         # Use zarr.zeros to create an empty array with the specified shape and dtype
@@ -228,12 +217,18 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
         # Create a custom chunk key encoding with "/" as separator
         chunk_key_encoding = V2ChunkKeyEncoding(separator="/").to_dict()
         encoding = {
-            # NOTE: See Zarr documentation on use of fill_value and _FillValue in Zarr v2 vs v3
-            "_FillValue": _get_fill_value(v.data_type),
             "chunks": chunks,
             "chunk_key_encoding": chunk_key_encoding,
             "compressor": _convert_compressor(v.compressor),
         }
+        # NumPy structured data types have fields attribute, while scalar types do not.
+        if not hasattr(v.data_type, "fields"):
+            # TODO(Dmitriy Repin): work around of the bug
+            # https://github.com/TGSAI/mdio-python/issues/582
+            # For structured data types we will not use the _FillValue
+            # NOTE: See Zarr documentation on use of fill_value and _FillValue in Zarr v2 vs v3
+            encoding["_FillValue"] = _get_fill_value(v.data_type)
+
         data_array.encoding = encoding
 
         # Let's store the data array for the second pass
@@ -263,35 +258,3 @@ def to_xarray_dataset(mdio_ds: Dataset) -> xr_DataArray:  # noqa: PLR0912
             xr_ds.attrs["attributes"] = mdio_ds.metadata.attributes
 
     return xr_ds
-
-
-def to_zarr(
-    dataset: xr_Dataset,
-    store: str | None = None,
-    *args: str | int | float | bool,
-    **kwargs: Mapping[str, str | int | float | bool],
-) -> None:
-    """Write an XArray dataset to Zarr format.
-
-    Args:
-        dataset: The XArray dataset to write.
-        store: The Zarr store to write to. If None, defaults to in-memory store.
-        *args: Additional positional arguments for the Zarr store.
-        **kwargs: Additional keyword arguments for the Zarr store.
-
-    Notes:
-        It sets the zarr_format to 2, which is the default for XArray datasets.
-        Since we set kwargs["compute"], this method will return a dask.delayed.Delayed object
-        and the arrays will not be immediately written.
-
-    References:
-            https://docs.xarray.dev/en/stable/user-guide/io.html
-            https://docs.xarray.dev/en/latest/generated/xarray.DataArray.to_zarr.html
-
-    Returns:
-        None: The function writes the dataset as dask.delayed.Delayed object to the
-        specified Zarr store.
-    """
-    kwargs["zarr_format"] = 2
-    kwargs["compute"] = False
-    return dataset.to_zarr(*args, store=store, **kwargs)
diff --git a/src/mdio/schemas/v1/templates/abstract_dataset_template.py b/src/mdio/schemas/v1/templates/abstract_dataset_template.py
index 776a65ce0..ef3cfcbae 100644
--- a/src/mdio/schemas/v1/templates/abstract_dataset_template.py
+++ b/src/mdio/schemas/v1/templates/abstract_dataset_template.py
@@ -1,5 +1,6 @@
 """Template method pattern implementation for MDIO v1 dataset template."""
 
+import copy
 from abc import ABC
 from abc import abstractmethod
 
@@ -7,6 +8,7 @@
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.chunk_grid import RegularChunkShape
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
 from mdio.schemas.metadata import ChunkGridMetadata
 from mdio.schemas.metadata import UserAttributes
 from mdio.schemas.v1.dataset import Dataset
@@ -32,25 +34,19 @@ def __init__(self, domain: str = "") -> None:
         # Note: For pre-stack Shot gathers, the coordinates are defined differently
         #       and are not directly tied to _coord_dim_names.
         self._coord_dim_names = []
-        # Names of all dimensions in the dataset
+        # *ORDERED* list of names of all dimensions in the dataset
         # e.g. ["cdp", "depth"] for 2D post-stack depth
         # e.g. ["inline", "crossline", "depth"] for 3D post-stack depth
         # e.g. ["inline", "crossline", "offset", "depth"] for 3D pre-stack depth CPD gathers
         # e.g. ["shot_point", "cable", "channel", "time"] for 3D pre-stack time Shot gathers
         self._dim_names = []
         # Names of all coordinates in the dataset
-        # e.g. ["cdp-x", "cdp-y"] for 2D post-stack depth
-        # e.g. ["cdp-x", "cdp-y"] for 3D post-stack depth
-        # e.g. ["cdp-x", "cdp-y"] for 3D pre-stack CPD depth
+        # e.g. ["cdp_x", "cdp_y"] for 2D post-stack depth
+        # e.g. ["cdp_x", "cdp_y"] for 3D post-stack depth
+        # e.g. ["cdp_x", "cdp_y"] for 3D pre-stack CPD depth
         # e.g. ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"] for 3D pre-stack
         #      time Shot gathers
         self._coord_names = []
-        # Name of the variable in the dataset
-        # e.g. "StackedAmplitude" for 2D post-stack depth
-        # e.g. "StackedAmplitude" for 3D post-stack depth
-        # e.g. "AmplitudeCDP" for 3D pre-stack CPD depth
-        # e.g. "AmplitudeShot" for 3D pre-stack time Shot gathers
-        self._var_name = ""
         # Chunk shape for the variable in the dataset
         # e.g. [1024, 1024] for 2D post-stack depth
         # e.g. [128, 128, 128] for 3D post-stack depth
@@ -64,34 +60,66 @@ def __init__(self, domain: str = "") -> None:
         self._dim_sizes = []
         # Horizontal units for the coordinates (e.g, "m", "ft"), to be set when
         # build_dataset() is called
-        self._coord_units = []
-
-    def build_dataset(self, name: str, sizes: list[int], coord_units: list[AllUnits]) -> Dataset:
+        self._horizontal_coord_unit = None
+
+    def build_dataset(
+        self,
+        name: str,
+        sizes: list[int],
+        horizontal_coord_unit: AllUnits,
+        headers: StructuredType = None,
+    ) -> Dataset:
         """Template method that builds the dataset.
 
         Args:
             name: The name of the dataset.
             sizes: The sizes of the dimensions.
-            coord_units: The units for the coordinates.
+            horizontal_coord_unit: The units for the horizontal coordinates.
+            headers: Optional structured headers for the dataset.
 
         Returns:
             Dataset: The constructed dataset
         """
         self._dim_sizes = sizes
-        self._coord_units = coord_units
+        self._horizontal_coord_unit = horizontal_coord_unit
 
         self._builder = MDIODatasetBuilder(name=name, attributes=self._load_dataset_attributes())
         self._add_dimensions()
         self._add_coordinates()
         self._add_variables()
+        self._add_trace_mask()
+        if headers:
+            self._add_trace_headers(headers)
         return self._builder.build()
 
-    def get_name(self) -> str:
+    @property
+    def name(self) -> str:
         """Returns the name of the template."""
-        return self._get_name()
+        return self._name
+
+    @property
+    def trace_variable_name(self) -> str:
+        """Returns the name of the trace variable."""
+        return self._trace_variable_name
+
+    @property
+    def trace_domain(self) -> str:
+        """Returns the name of the trace domain."""
+        return self._trace_domain
+
+    @property
+    def dimension_names(self) -> list[str]:
+        """Returns the names of the dimensions."""
+        return copy.deepcopy(self._dim_names)
 
+    @property
+    def coordinate_names(self) -> list[str]:
+        """Returns the names of the coordinates."""
+        return copy.deepcopy(self._coord_names)
+
+    @property
     @abstractmethod
-    def _get_name(self) -> str:
+    def _name(self) -> str:
         """Abstract method to get the name of the template.
 
         Must be implemented by subclasses.
@@ -100,6 +128,18 @@ def _get_name(self) -> str:
             str: The name of the template
         """
 
+    @property
+    def _trace_variable_name(self) -> str:
+        """Get the name of the data variable.
+
+        A virtual method that can be overwritten by subclasses to return a
+        custom data variable name.
+
+        Returns:
+            str: The name of the data variable
+        """
+        return "amplitude"
+
     @abstractmethod
     def _load_dataset_attributes(self) -> UserAttributes:
         """Abstract method to load dataset attributes.
@@ -111,33 +151,83 @@ def _load_dataset_attributes(self) -> UserAttributes:
         """
 
     def _add_dimensions(self) -> None:
-        """A virtual method that can be overwritten by subclasses to add custom dimensions.
+        """Add custom dimensions.
 
+        A virtual method that can be overwritten by subclasses to add custom dimensions.
         Uses the class field 'builder' to add dimensions to the dataset.
         """
         for i in range(len(self._dim_names)):
             self._builder.add_dimension(self._dim_names[i], self._dim_sizes[i])
 
     def _add_coordinates(self) -> None:
-        """A virtual method that can be overwritten by subclasses to add custom coordinates.
+        """Add custom coordinates.
 
+        A virtual method that can be overwritten by subclasses to add custom coordinates.
         Uses the class field 'builder' to add coordinates to the dataset.
         """
+        # Add dimension coordinates
+        for name in self._dim_names:
+            self._builder.add_coordinate(
+                name,
+                dimensions=[name],
+                data_type=ScalarType.INT32,
+                metadata_info=None,
+            )
+
+        # Add non-dimension coordinates
+        # TODO(Dmitriy Repin): do chunked write for non-dimensional coordinates and trace_mask
+        # https://github.com/TGSAI/mdio-python/issues/587
+        # The chunk size used for trace mask will be different from the _var_chunk_shape
+        hor_coord_units = [self._horizontal_coord_unit] * len(self._coord_dim_names)
         for i in range(len(self._coord_names)):
             self._builder.add_coordinate(
                 self._coord_names[i],
                 dimensions=self._coord_dim_names,
                 data_type=ScalarType.FLOAT64,
-                metadata_info=[self._coord_units],
+                metadata_info=hor_coord_units,
             )
 
+    def _add_trace_mask(self) -> None:
+        """Add trace mask variables."""
+        # TODO(Dmitriy Repin): do chunked write for non-dimensional coordinates and trace_mask
+        # https://github.com/TGSAI/mdio-python/issues/587
+        # The chunk size used for trace mask will be different from the _var_chunk_shape
+        self._builder.add_variable(
+            name="trace_mask",
+            dimensions=self._dim_names[:-1],  # All dimensions except vertical (the last one)
+            data_type=ScalarType.BOOL,
+            compressor=compressors.Blosc(algorithm=compressors.BloscAlgorithm.ZSTD),
+            coordinates=self._coord_names,
+            metadata_info=None,
+        )
+
+    def _add_trace_headers(self, headers: StructuredType) -> None:
+        """Add trace mask variables."""
+        # headers = StructuredType.model_validate(header_fields)
+
+        self._builder.add_variable(
+            name="headers",
+            dimensions=self._dim_names[:-1],  # All dimensions except vertical (the last one)
+            data_type=headers,
+            compressor=compressors.Blosc(algorithm=compressors.BloscAlgorithm.ZSTD),
+            coordinates=self._coord_names,
+            metadata_info=[
+                ChunkGridMetadata(
+                    chunk_grid=RegularChunkGrid(
+                        configuration=RegularChunkShape(chunk_shape=self._var_chunk_shape[:-1])
+                    )
+                )
+            ],
+        )
+
     def _add_variables(self) -> None:
-        """A virtual method that can be overwritten by subclasses to add custom variables.
+        """Add custom variables.
 
+        A virtual method that can be overwritten by subclasses to add custom variables.
         Uses the class field 'builder' to add variables to the dataset.
         """
         self._builder.add_variable(
-            name=self._var_name,
+            name=self._trace_variable_name,
             dimensions=self._dim_names,
             data_type=ScalarType.FLOAT32,
             compressor=compressors.Blosc(algorithm=compressors.BloscAlgorithm.ZSTD),
diff --git a/src/mdio/schemas/v1/templates/seismic_2d_poststack.py b/src/mdio/schemas/v1/templates/seismic_2d_poststack.py
index 4f0d81b68..297d598bc 100644
--- a/src/mdio/schemas/v1/templates/seismic_2d_poststack.py
+++ b/src/mdio/schemas/v1/templates/seismic_2d_poststack.py
@@ -12,11 +12,11 @@ def __init__(self, domain: str):
 
         self._coord_dim_names = ["cdp"]
         self._dim_names = [*self._coord_dim_names, self._trace_domain]
-        self._coord_names = ["cdp-x", "cdp-y"]
-        self._var_name = "StackedAmplitude"
+        self._coord_names = ["cdp_x", "cdp_y"]
         self._var_chunk_shape = [1024, 1024]
 
-    def _get_name(self) -> str:
+    @property
+    def _name(self) -> str:
         return f"PostStack2D{self._trace_domain.capitalize()}"
 
     def _load_dataset_attributes(self) -> UserAttributes:
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_poststack.py b/src/mdio/schemas/v1/templates/seismic_3d_poststack.py
index 3fd3950a3..78021f72e 100644
--- a/src/mdio/schemas/v1/templates/seismic_3d_poststack.py
+++ b/src/mdio/schemas/v1/templates/seismic_3d_poststack.py
@@ -12,11 +12,11 @@ def __init__(self, domain: str):
         # Template attributes to be overridden by subclasses
         self._coord_dim_names = ["inline", "crossline"]
         self._dim_names = [*self._coord_dim_names, self._trace_domain]
-        self._coord_names = ["cdp-x", "cdp-y"]
-        self._var_name = "StackedAmplitude"
+        self._coord_names = ["cdp_x", "cdp_y"]
         self._var_chunk_shape = [128, 128, 128]
 
-    def _get_name(self) -> str:
+    @property
+    def _name(self) -> str:
         return f"PostStack3D{self._trace_domain.capitalize()}"
 
     def _load_dataset_attributes(self) -> UserAttributes:
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py b/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
index fa95729b8..2ae22b550 100644
--- a/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
+++ b/src/mdio/schemas/v1/templates/seismic_3d_prestack_cdp.py
@@ -10,13 +10,13 @@ class Seismic3DPreStackCDPTemplate(AbstractDatasetTemplate):
     def __init__(self, domain: str):
         super().__init__(domain=domain)
 
-        self._coord_dim_names = ["inline", "crossline"]
-        self._dim_names = [*self._coord_dim_names, "offset", self._trace_domain]
-        self._coord_names = ["cdp-x", "cdp-y"]
-        self._var_name = "AmplitudeCDP"
+        self._coord_dim_names = ["inline", "crossline", "offset"]
+        self._dim_names = [*self._coord_dim_names, self._trace_domain]
+        self._coord_names = ["cdp_x", "cdp_y"]
         self._var_chunk_shape = [1, 1, 512, 4096]
 
-    def _get_name(self) -> str:
+    @property
+    def _name(self) -> str:
         return f"PreStackCdpGathers3D{self._trace_domain.capitalize()}"
 
     def _load_dataset_attributes(self) -> UserAttributes:
diff --git a/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py b/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
index a39331276..ac644fbd1 100644
--- a/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
+++ b/src/mdio/schemas/v1/templates/seismic_3d_prestack_shot.py
@@ -12,13 +12,17 @@ class Seismic3DPreStackShotTemplate(AbstractDatasetTemplate):
     def __init__(self, domain: str):
         super().__init__(domain=domain)
 
-        self._coord_dim_names = []  # Custom coordinate definition for shot gathers
-        self._dim_names = ["shot_point", "cable", "channel", self._trace_domain]
+        self._coord_dim_names = [
+            "shot_point",
+            "cable",
+            "channel",
+        ]  # Custom coordinate definition for shot gathers
+        self._dim_names = [*self._coord_dim_names, self._trace_domain]
         self._coord_names = ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
-        self._var_name = "AmplitudeShot"
         self._var_chunk_shape = [1, 1, 512, 4096]
 
-    def _get_name(self) -> str:
+    @property
+    def _name(self) -> str:
         return f"PreStackShotGathers3D{self._trace_domain.capitalize()}"
 
     def _load_dataset_attributes(self) -> UserAttributes:
@@ -31,6 +35,16 @@ def _load_dataset_attributes(self) -> UserAttributes:
         )
 
     def _add_coordinates(self) -> None:
+        # Add dimension coordinates
+        for name in self._dim_names:
+            self._builder.add_coordinate(
+                name,
+                dimensions=[name],
+                data_type=ScalarType.INT32,
+                metadata_info=None,
+            )
+
+        # Add non-dimension coordinates
         self._builder.add_coordinate(
             "gun",
             dimensions=["shot_point"],
@@ -41,23 +55,23 @@ def _add_coordinates(self) -> None:
             "shot-x",
             dimensions=["shot_point"],
             data_type=ScalarType.FLOAT64,
-            metadata_info=[self._coord_units[0]],
+            metadata_info=[self._horizontal_coord_unit],
         )
         self._builder.add_coordinate(
             "shot-y",
             dimensions=["shot_point"],
             data_type=ScalarType.FLOAT64,
-            metadata_info=[self._coord_units[1]],
+            metadata_info=[self._horizontal_coord_unit],
         )
         self._builder.add_coordinate(
             "receiver-x",
             dimensions=["shot_point", "cable", "channel"],
             data_type=ScalarType.FLOAT64,
-            metadata_info=[self._coord_units[0]],
+            metadata_info=[self._horizontal_coord_unit],
         )
         self._builder.add_coordinate(
             "receiver-y",
             dimensions=["shot_point", "cable", "channel"],
             data_type=ScalarType.FLOAT64,
-            metadata_info=[self._coord_units[1]],
+            metadata_info=[self._horizontal_coord_unit],
         )
diff --git a/src/mdio/schemas/v1/templates/template_registry.py b/src/mdio/schemas/v1/templates/template_registry.py
index c674b0c20..b1c7550a3 100644
--- a/src/mdio/schemas/v1/templates/template_registry.py
+++ b/src/mdio/schemas/v1/templates/template_registry.py
@@ -54,7 +54,7 @@ def register(self, instance: AbstractDatasetTemplate) -> str:
             ValueError: If the template name is already registered.
         """
         with self._registry_lock:
-            name = instance.get_name()
+            name = instance.name
             if name in self._templates:
                 err = f"Template '{name}' is already registered."
                 raise ValueError(err)
diff --git a/src/mdio/segy/_workers.py b/src/mdio/segy/_workers.py
index 2380b16fa..2be530034 100644
--- a/src/mdio/segy/_workers.py
+++ b/src/mdio/segy/_workers.py
@@ -4,7 +4,6 @@
 
 import os
 from typing import TYPE_CHECKING
-from typing import Any
 from typing import TypedDict
 from typing import cast
 
@@ -15,9 +14,14 @@
     from segy.arrays import HeaderArray
     from segy.config import SegySettings
     from segy.schema import SegySpec
-    from zarr import Array
+    from xarray import Dataset as xr_Dataset
+    from zarr import Array as zarr_Array
 
-    from mdio.core import Grid
+    from mdio.core.storage_location import StorageLocation
+
+from mdio.constants import UINT32_MAX
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import SummaryStatistics
 
 
 class SegyFileArguments(TypedDict):
@@ -29,8 +33,7 @@ class SegyFileArguments(TypedDict):
 
 
 def header_scan_worker(
-    segy_kw: SegyFileArguments,
-    trace_range: tuple[int, int],
+    segy_kw: SegyFileArguments, trace_range: tuple[int, int], subset: list[str] | None = None
 ) -> HeaderArray:
     """Header scan worker.
 
@@ -40,6 +43,7 @@ def header_scan_worker(
     Args:
         segy_kw: Arguments to open SegyFile instance.
         trace_range: Tuple consisting of the trace ranges to read.
+        subset: List of header names to filter and keep.
 
     Returns:
         HeaderArray parsed from SEG-Y library.
@@ -55,6 +59,9 @@ def header_scan_worker(
     else:
         trace_header = segy_file.header[slice_]
 
+    if subset is not None:
+        trace_header = trace_header[subset]
+
     # Get non-void fields from dtype and copy to new array for memory efficiency
     fields = trace_header.dtype.fields
     non_void_fields = [(name, dtype) for name, (dtype, _) in fields.items()]
@@ -67,72 +74,68 @@ def header_scan_worker(
     return cast("HeaderArray", trace_header)
 
 
-def trace_worker(
+def trace_worker(  # noqa: PLR0913
     segy_kw: SegyFileArguments,
-    data_array: Array,
-    metadata_array: Array,
-    grid: Grid,
-    chunk_indices: tuple[slice, ...],
-) -> tuple[Any, ...] | None:
-    """Worker function for multi-process enabled blocked SEG-Y I/O.
-
-    Performance of `zarr.Array` writes is slow if data isn't aligned with chunk boundaries,
-    sacrificing sequential reads of SEG-Y files. This won't be an issue with SSDs or cloud.
-
-    It retrieves trace numbers from the grid and gathers the current chunk's SEG-Y trace indices.
-    Then, it fills a temporary array in memory and writes to the `zarr.Array` chunk. We take full
-    slices across the sample dimension since SEG-Y data isn't chunked, eliminating concern.
+    output_location: StorageLocation,
+    data_variable_name: str,
+    region: dict[str, slice],
+    grid_map: zarr_Array,
+    dataset: xr_Dataset,
+) -> SummaryStatistics | None:
+    """Writes a subset of traces from a region of the dataset of Zarr file.
 
     Args:
         segy_kw: Arguments to open SegyFile instance.
-        data_array: Handle for zarr.Array we are writing traces to
-        metadata_array: Handle for zarr.Array we are writing trace headers
-        grid: mdio.Grid instance
-        chunk_indices: Tuple consisting of the chunk slice indices for each dimension
+        output_location: StorageLocation for the output Zarr dataset
+            (e.g. local file path or cloud storage URI) the location
+            also includes storage options for cloud storage.
+        data_variable_name: Name of the data variable to write.
+        region: Region of the dataset to write to.
+        grid_map: Zarr array mapping live traces to their positions in the dataset.
+        dataset: Xarray dataset containing the data to write.
 
     Returns:
-        Partial statistics for chunk, or None
+        SummaryStatistics object containing statistics about the written traces.
     """
-    # Special case where there are no traces inside chunk.
-    segy_file = SegyFile(**segy_kw)
-    live_subset = grid.live_mask[chunk_indices[:-1]]
-
-    if np.count_nonzero(live_subset) == 0:
+    if not dataset.trace_mask.any():
         return None
 
-    # Let's get trace numbers from grid map using the chunk indices.
-    seq_trace_indices = grid.map[chunk_indices[:-1]]
-
-    tmp_data = np.zeros(seq_trace_indices.shape + (grid.shape[-1],), dtype=data_array.dtype)
-    tmp_metadata = np.zeros(seq_trace_indices.shape, dtype=metadata_array.dtype)
-
-    del grid  # To save some memory
-
-    # Read headers and traces for block
-    valid_indices = seq_trace_indices[live_subset]
-
-    traces = segy_file.trace[valid_indices.tolist()]
-    headers, samples = traces["header"], traces["data"]
-
-    tmp_metadata[live_subset] = headers.view(tmp_metadata.dtype)
-    tmp_data[live_subset] = samples
-
-    # Flush metadata to zarr
-    metadata_array.set_basic_selection(selection=chunk_indices[:-1], value=tmp_metadata)
-
-    nonzero_mask = samples != 0
-    nonzero_count = nonzero_mask.sum(dtype="uint32")
+    # Open the SEG-Y file in every new process / spawned worker since the
+    # open file handles cannot be shared across processes.
+    segy_file = SegyFile(**segy_kw)
 
-    if nonzero_count == 0:
-        return None
+    not_null = grid_map != UINT32_MAX
 
-    data_array.set_basic_selection(selection=chunk_indices, value=tmp_data)
+    live_trace_indexes = grid_map[not_null].tolist()
+    traces = segy_file.trace[live_trace_indexes]
 
-    # Calculate statistics
-    tmp_data = samples[nonzero_mask]
-    chunk_sum = tmp_data.sum(dtype="float64")
-    chunk_sum_squares = np.square(tmp_data, dtype="float64").sum()
-    min_val = tmp_data.min()
-    max_val = tmp_data.max()
+    # Get subset of the dataset that has not yet been saved
+    # The headers might not be present in the dataset
+    # TODO(Dmitriy Repin): Check, should we overwrite the 'dataset' instead to save the memory
+    # https://github.com/TGSAI/mdio-python/issues/584
+    if "headers" in dataset.data_vars:
+        ds_to_write = dataset[[data_variable_name, "headers"]]
+        ds_to_write = ds_to_write.reset_coords()
 
-    return nonzero_count, chunk_sum, chunk_sum_squares, min_val, max_val
+        ds_to_write["headers"].data[not_null] = traces.header
+        ds_to_write["headers"].data[~not_null] = 0
+    else:
+        ds_to_write = dataset[[data_variable_name]]
+        ds_to_write = ds_to_write.reset_coords()
+
+    ds_to_write[data_variable_name].data[not_null] = traces.sample
+
+    out_path = output_location.uri
+    ds_to_write.to_zarr(out_path, region=region, mode="r+", write_empty_chunks=False, zarr_format=2)
+
+    histogram = CenteredBinHistogram(bin_centers=[], counts=[])
+    return SummaryStatistics(
+        count=traces.sample.size,
+        min=traces.sample.min(),
+        max=traces.sample.max(),
+        sum=traces.sample.sum(),
+        # TODO(Altay): Look at how to do the sum squares statistic correctly
+        # https://github.com/TGSAI/mdio-python/issues/581
+        sum_squares=(traces.sample**2).sum(),
+        histogram=histogram,
+    )
diff --git a/src/mdio/segy/blocked_io.py b/src/mdio/segy/blocked_io.py
index 6e23be1f4..e92aed2e6 100644
--- a/src/mdio/segy/blocked_io.py
+++ b/src/mdio/segy/blocked_io.py
@@ -2,9 +2,10 @@
 
 from __future__ import annotations
 
+import multiprocessing as mp
 import os
 from concurrent.futures import ProcessPoolExecutor
-from itertools import repeat
+from concurrent.futures import as_completed
 from pathlib import Path
 from typing import TYPE_CHECKING
 
@@ -13,8 +14,12 @@
 from dask.array import map_blocks
 from psutil import cpu_count
 from tqdm.auto import tqdm
+from zarr import consolidate_metadata as zarr_consolidate_metadata
+from zarr import open_group as zarr_open_group
 
 from mdio.core.indexing import ChunkIterator
+from mdio.schemas.v1.stats import CenteredBinHistogram
+from mdio.schemas.v1.stats import SummaryStatistics
 from mdio.segy._workers import trace_worker
 from mdio.segy.creation import SegyPartRecord
 from mdio.segy.creation import concat_files
@@ -25,89 +30,119 @@
     from numpy.typing import NDArray
     from segy import SegyFactory
     from segy import SegyFile
+    from xarray import Dataset as xr_Dataset
+    from zarr import Array as zarr_Array
 
-    from mdio.core import Grid
+    from mdio.core.storage_location import StorageLocation
 
 default_cpus = cpu_count(logical=True)
 
 
-def to_zarr(segy_file: SegyFile, grid: Grid, data_array: Array, header_array: Array) -> dict:
-    """Blocked I/O from SEG-Y to chunked `zarr.core.Array`.
+def _create_stats() -> SummaryStatistics:
+    histogram = CenteredBinHistogram(bin_centers=[], counts=[])
+    return SummaryStatistics(count=0, min=0, max=0, sum=0, sum_squares=0, histogram=histogram)
+
+
+def _update_stats(final_stats: SummaryStatistics, partial_stats: SummaryStatistics) -> None:
+    final_stats.count += partial_stats.count
+    final_stats.min = min(final_stats.min, partial_stats.min)
+    final_stats.max = min(final_stats.max, partial_stats.max)
+    final_stats.sum += partial_stats.sum
+    final_stats.sum_squares += partial_stats.sum_squares
+
+
+def to_zarr(  # noqa: PLR0913, PLR0915
+    segy_file: SegyFile,
+    output_location: StorageLocation,
+    grid_map: zarr_Array,
+    dataset: xr_Dataset,
+    data_variable_name: str,
+) -> None:
+    """Blocked I/O from SEG-Y to chunked `xarray.Dataset`.
 
     Args:
         segy_file: SEG-Y file instance.
-        grid: mdio.Grid instance
-        data_array: Handle for zarr.core.Array we are writing trace data
-        header_array: Handle for zarr.core.Array we are writing trace headers
+        output_location: StorageLocation for the output Zarr dataset
+            (e.g. local file path or cloud storage URI) the location
+            also includes storage options for cloud storage.
+        grid_map: Zarr array with grid map for the traces.
+        dataset: Handle for xarray.Dataset we are writing trace data
+        data_variable_name: Name of the data variable in the dataset.
 
     Returns:
-        Global statistics for the SEG-Y as a dictionary.
+        None
     """
-    # Initialize chunk iterator (returns next chunk slice indices each iteration)
-    chunker = ChunkIterator(data_array, chunk_samples=False)
-    num_chunks = len(chunker)
-
+    data = dataset[data_variable_name]
+
+    final_stats = _create_stats()
+
+    # Must use data.encoding.get instead of data.chunks
+    chunks_t_of_t = (data.encoding.get("chunks"),)
+    # Unroll tuple of tuples into a flat list
+    chunks = [c for sub_tuple in chunks_t_of_t for c in sub_tuple]
+    # We will not chunk traces (old option chunk_samples=False)
+    chunks[-1] = data.shape[-1]
+    dim_names = list(data.dims)
+    # Initialize chunk iterator
+    # Since the dimensions are provided, it will return a dict of slices
+    chunk_iter = ChunkIterator(shape=data.shape, chunks=chunks, dim_names=dim_names)
+    num_chunks = chunk_iter.num_chunks
+
+    # The following could be extracted in a function to allow executor injection
+    # (e.g. for unit testing or for debugging with non-parallelized processing)
+    # def _create_executor(num_chunks: int)-> ProcessPoolExecutor:
+
+    # For Unix async writes with s3fs/fsspec & multiprocessing, use 'spawn' instead of default
+    # 'fork' to avoid deadlocks on cloud stores. Slower but necessary. Default on Windows.
     num_cpus = int(os.getenv("MDIO__IMPORT__CPU_COUNT", default_cpus))
     num_workers = min(num_chunks, num_cpus)
-
-    # Chunksize here is for multiprocessing, not Zarr chunksize.
-    pool_chunksize, extra = divmod(num_chunks, num_workers * 4)
-    pool_chunksize += 1 if extra else pool_chunksize
+    context = mp.get_context("spawn")
+    executor = ProcessPoolExecutor(max_workers=num_workers, mp_context=context)
+    # return executor
 
     segy_kw = {
         "url": segy_file.fs.unstrip_protocol(segy_file.url),
         "spec": segy_file.spec,
         "settings": segy_file.settings,
     }
-    tqdm_kw = {"unit": "block", "dynamic_ncols": True}
-    with ProcessPoolExecutor(max_workers=num_workers) as executor:
-        lazy_work = executor.map(
-            trace_worker,  # fn
-            repeat(segy_kw),
-            repeat(data_array),
-            repeat(header_array),
-            repeat(grid),
-            chunker,
-            chunksize=pool_chunksize,
-        )
-
-        lazy_work = tqdm(
-            iterable=lazy_work,
+    with executor:
+        futures = []
+        common_args = (segy_kw, output_location, data_variable_name)
+        for region in chunk_iter:
+            index_slices = tuple(region[key] for key in data.dims[:-1])
+            subset_args = (
+                region,
+                grid_map[index_slices],
+                dataset.isel(region),
+            )
+            future = executor.submit(trace_worker, *common_args, *subset_args)
+            futures.append(future)
+
+        iterable = tqdm(
+            as_completed(futures),
             total=num_chunks,
-            desc=f"Ingesting SEG-Y in {num_chunks} chunks",
-            **tqdm_kw,
+            unit="block",
+            desc="Ingesting traces",
         )
 
-        # This executes the lazy work.
-        chunk_stats = list(lazy_work)
-
-    # This comes in as n_chunk x 5 columns.
-    # Columns in order: count, sum, sum of squared, min, max.
-    # We can compute global mean, std, rms, min, max.
-    # Transposing because we want each statistic as a row to unpack later.
-    # REF: https://math.stackexchange.com/questions/1547141/aggregating-standard-deviation-to-a-summary-point  # noqa: E501
-    # REF: https://www.mathwords.com/r/root_mean_square.htm
-    chunk_stats = [stat for stat in chunk_stats if stat is not None]
-
-    chunk_stats = zip(*chunk_stats)  # noqa: B905
-    glob_count, glob_sum, glob_sum_square, glob_min, glob_max = chunk_stats
-
-    glob_count = np.sum(glob_count)  # Comes in as `uint32`
-    glob_sum = np.sum(glob_sum)  # `float64`
-    glob_sum_square = np.sum(glob_sum_square)  # `float64`
-    glob_min = np.min(glob_min)  # `float32`
-    glob_max = np.max(glob_max)  # `float32`
-
-    glob_mean = glob_sum / glob_count
-    glob_std = np.sqrt(glob_sum_square / glob_count - (glob_sum / glob_count) ** 2)
-    glob_rms = np.sqrt(glob_sum_square / glob_count)
-
-    # We need to write these as float64 because float32 is not JSON serializable
-    # Trace data is originally float32, hence min/max
-    glob_min = glob_min.min().astype("float64")
-    glob_max = glob_max.max().astype("float64")
-
-    return {"mean": glob_mean, "std": glob_std, "rms": glob_rms, "min": glob_min, "max": glob_max}
+        for future in iterable:
+            result = future.result()
+            if result is not None:
+                _update_stats(final_stats, result)
+
+    # Xarray doesn't directly support incremental attribute updates when appending to an
+    # existing Zarr store.
+    # HACK: We will update the array attribute using zarr's API directly.
+    # Open the Zarr store using zarr directly
+    zarr_group = zarr_open_group(output_location.uri, mode="a")
+    attr_json = final_stats.model_dump_json()
+    # Use the data_variable_name to get the array in the Zarr group
+    # and write "statistics" metadata there
+    zarr_group[data_variable_name].attrs.update({"statsV1": attr_json})
+    # Consolidate metadata (important for Xarray to recognize changes)
+    zarr_consolidate_metadata(output_location.uri)
+
+    return final_stats
 
 
 def segy_record_concat(
diff --git a/src/mdio/segy/parsers.py b/src/mdio/segy/parsers.py
index 810924fb6..d46c61b3f 100644
--- a/src/mdio/segy/parsers.py
+++ b/src/mdio/segy/parsers.py
@@ -21,8 +21,9 @@
 default_cpus = cpu_count(logical=True)
 
 
-def parse_index_headers(
+def parse_headers(
     segy_file: SegyFile,
+    subset: list[str] | None = None,
     block_size: int = 10000,
     progress_bar: bool = True,
 ) -> HeaderArray:
@@ -30,6 +31,7 @@ def parse_index_headers(
 
     Args:
         segy_file: SegyFile instance.
+        subset: List of header names to filter and keep.
         block_size: Number of traces to read for each block.
         progress_bar: Enable or disable progress bar. Default is True.
 
@@ -57,7 +59,7 @@ def parse_index_headers(
     }
     tqdm_kw = {"unit": "block", "dynamic_ncols": True}
     with ProcessPoolExecutor(num_workers) as executor:
-        lazy_work = executor.map(header_scan_worker, repeat(segy_kw), trace_ranges)
+        lazy_work = executor.map(header_scan_worker, repeat(segy_kw), trace_ranges, repeat(subset))
 
         if progress_bar is True:
             lazy_work = tqdm(
diff --git a/src/mdio/segy/utilities.py b/src/mdio/segy/utilities.py
index 031d8b491..f5677e96b 100644
--- a/src/mdio/segy/utilities.py
+++ b/src/mdio/segy/utilities.py
@@ -12,20 +12,23 @@
 
 from mdio.core import Dimension
 from mdio.segy.geometry import GridOverrider
-from mdio.segy.parsers import parse_index_headers
+from mdio.segy.parsers import parse_headers
 
 if TYPE_CHECKING:
     from numpy.typing import DTypeLike
     from segy import SegyFile
     from segy.arrays import HeaderArray
 
+    from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
+
 
 logger = logging.getLogger(__name__)
 
 
 def get_grid_plan(  # noqa:  C901
     segy_file: SegyFile,
-    chunksize: list[int],
+    chunksize: tuple[int, ...] | None,
+    template: AbstractDatasetTemplate,
     return_headers: bool = False,
     grid_overrides: dict[str, Any] | None = None,
 ) -> tuple[list[Dimension], tuple[int, ...]] | tuple[list[Dimension], tuple[int, ...], HeaderArray]:
@@ -40,6 +43,7 @@ def get_grid_plan(  # noqa:  C901
     Args:
         segy_file: SegyFile instance.
         chunksize:  Chunk sizes to be used in grid plan.
+        template: MDIO template where coordinate names and domain will be taken.
         return_headers: Option to return parsed headers with `Dimension` objects. Default is False.
         grid_overrides: Option to add grid overrides. See main documentation.
 
@@ -49,37 +53,37 @@ def get_grid_plan(  # noqa:  C901
     if grid_overrides is None:
         grid_overrides = {}
 
-    index_headers = parse_index_headers(segy_file=segy_file)
-    index_names = list(index_headers.dtype.names)
-
-    dims = []
+    # Keep only dimension and non-dimension coordinates excluding the vertical axis
+    horizontal_dimensions = template.dimension_names[:-1]
+    horizontal_coordinates = horizontal_dimensions + template.coordinate_names
+    headers_subset = parse_headers(segy_file=segy_file, subset=horizontal_coordinates)
 
     # Handle grid overrides.
     override_handler = GridOverrider()
-    index_headers, index_names, chunksize = override_handler.run(
-        index_headers,
-        index_names,
+    headers_subset, horizontal_coordinates, chunksize = override_handler.run(
+        headers_subset,
+        horizontal_coordinates,
         chunksize=chunksize,
         grid_overrides=grid_overrides,
     )
 
-    for index_name in index_names:
-        dim_unique = np.unique(index_headers[index_name])
-        dims.append(Dimension(coords=dim_unique, name=index_name))
+    dimensions = []
+    for dim_name in horizontal_dimensions:
+        dim_unique = np.unique(headers_subset[dim_name])
+        dimensions.append(Dimension(coords=dim_unique, name=dim_name))
 
     sample_labels = segy_file.sample_labels / 1000  # normalize
 
     if all(sample_labels.astype("int64") == sample_labels):
         sample_labels = sample_labels.astype("int64")
 
-    sample_dim = Dimension(coords=sample_labels, name="sample")
-
-    dims.append(sample_dim)
+    vertical_dim = Dimension(coords=sample_labels, name=template.trace_domain)
+    dimensions.append(vertical_dim)
 
     if return_headers:
-        return dims, chunksize, index_headers
+        return dimensions, chunksize, headers_subset
 
-    return dims, chunksize
+    return dimensions, chunksize
 
 
 def find_trailing_ones_index(dim_blocks: tuple[int, ...]) -> int:
diff --git a/tests/integration/test_segy_import_export.py b/tests/integration/test_segy_import_export.py
index ecea8d1d2..d9d612435 100644
--- a/tests/integration/test_segy_import_export.py
+++ b/tests/integration/test_segy_import_export.py
@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import json
 import os
 from typing import TYPE_CHECKING
 
@@ -9,13 +10,21 @@
 import numpy as np
 import numpy.testing as npt
 import pytest
+import xarray as xr
 from segy import SegyFile
+from segy.standards import get_segy_standard
+from tests.integration.testing_helpers import customize_segy_specs
+from tests.integration.testing_helpers import get_inline_header_values
+from tests.integration.testing_helpers import get_values
+from tests.integration.testing_helpers import validate_variable
 
 from mdio import MDIOReader
 from mdio import mdio_to_segy
-from mdio.converters import segy_to_mdio
 from mdio.converters.exceptions import GridTraceSparsityError
+from mdio.converters.segy import segy_to_mdio
 from mdio.core import Dimension
+from mdio.core.storage_location import StorageLocation
+from mdio.schemas.v1.templates.template_registry import TemplateRegistry
 from mdio.segy.compat import mdio_segy_spec
 from mdio.segy.geometry import StreamerShotGeometryType
 
@@ -247,20 +256,30 @@ def test_import_6d_segy(  # noqa: PLR0913
 
 
 @pytest.mark.dependency
-@pytest.mark.parametrize("index_bytes", [(17, 13)])
-@pytest.mark.parametrize("index_names", [("inline", "crossline")])
-def test_3d_import(
+@pytest.mark.parametrize("index_bytes", [(17, 13, 81, 85)])
+@pytest.mark.parametrize("index_names", [("inline", "crossline", "cdp_x", "cdp_y")])
+@pytest.mark.parametrize("index_types", [("int32", "int32", "int32", "int32")])
+def test_3d_import_v1(
     segy_input: Path,
     zarr_tmp: Path,
     index_bytes: tuple[int, ...],
     index_names: tuple[str, ...],
+    index_types: tuple[str, ...],
 ) -> None:
     """Test importing a SEG-Y file to MDIO."""
-    segy_to_mdio(
-        segy_path=segy_input.__str__(),
-        mdio_path_or_buffer=zarr_tmp.__str__(),
+    segy_spec = get_segy_standard(1.0)
+    segy_spec = customize_segy_specs(
+        segy_spec=segy_spec,
         index_bytes=index_bytes,
         index_names=index_names,
+        index_types=index_types,
+    )
+
+    segy_to_mdio(
+        segy_spec=segy_spec,
+        mdio_template=TemplateRegistry().get("PostStack3DTime"),
+        input_location=StorageLocation(segy_input.__str__()),
+        output_location=StorageLocation(zarr_tmp.__str__()),
         overwrite=True,
     )
 
@@ -269,55 +288,120 @@ def test_3d_import(
 class TestReader:
     """Test reader functionality."""
 
-    def test_meta_read(self, zarr_tmp: Path) -> None:
+    def test_meta_dataset_read(self, zarr_tmp: Path) -> None:
+        """Metadata reading tests."""
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+        expected_attrs = {
+            "apiVersion": "1.0.0a1",
+            "createdOn": "2025-08-06 16:21:54.747880+00:00",
+            "name": "PostStack3DTime",
+        }
+        actual_attrs_json = ds.attrs
+        # compare one by one due to ever changing createdOn. For it, we only check existence
+        for key, value in expected_attrs.items():
+            assert key in actual_attrs_json
+            if key == "createdOn":
+                assert actual_attrs_json[key] is not None
+            else:
+                assert actual_attrs_json[key] == value
+
+    def test_meta_variable_read(self, zarr_tmp: Path) -> None:
         """Metadata reading tests."""
-        mdio = MDIOReader(zarr_tmp.__str__())
-        assert mdio.binary_header["samples_per_trace"] == 1501
-        assert mdio.binary_header["sample_interval"] == 2000
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+        expected_attrs = {
+            "count": 97354860,
+            "sum": -8594.551666259766,
+            "sum_squares": 40571291.6875,
+            "min": -8.375323295593262,
+            "max": 0.0,
+            "histogram": {"counts": [], "bin_centers": []},
+        }
+        actual_attrs_json = json.loads(ds["amplitude"].attrs["statsV1"])
+        assert actual_attrs_json == expected_attrs
 
     def test_grid(self, zarr_tmp: Path) -> None:
-        """Grid reading tests."""
-        mdio = MDIOReader(zarr_tmp.__str__())
-        grid = mdio.grid
+        """Test validating MDIO variables."""
+        # Load Xarray dataset from the MDIO file
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+
+        # Note: in order to create the dataset we used the Time template, so the
+        # sample dimension is called "time"
+
+        # Validate the dimension coordinate variables
+        validate_variable(ds, "inline", (345,), ["inline"], np.int32, range(1, 346), get_values)
+        validate_variable(
+            ds, "crossline", (188,), ["crossline"], np.int32, range(1, 189), get_values
+        )
+        validate_variable(ds, "time", (1501,), ["time"], np.int32, range(0, 3002, 2), get_values)
 
-        assert grid.select_dim("inline") == Dimension(range(1, 346), "inline")
-        assert grid.select_dim("crossline") == Dimension(range(1, 189), "crossline")
-        assert grid.select_dim("sample") == Dimension(range(0, 3002, 2), "sample")
+        # Validate the non-dimensional coordinate variables
+        validate_variable(ds, "cdp_x", (345, 188), ["inline", "crossline"], np.float64, None, None)
+        validate_variable(ds, "cdp_y", (345, 188), ["inline", "crossline"], np.float64, None, None)
 
-    def test_get_data(self, zarr_tmp: Path) -> None:
-        """Data retrieval tests."""
-        mdio = MDIOReader(zarr_tmp.__str__())
+        # Validate the headers
+        # We have a subset of headers since we used customize_segy_specs() providing the values only
+        # for "inline", "crossline", "cdp_x", "cdp_y"
+        data_type = np.dtype(
+            [("inline", "<i4"), ("crossline", "<i4"), ("cdp_x", "<i4"), ("cdp_y", "<i4")]
+        )
+        validate_variable(
+            ds,
+            "headers",
+            (345, 188),
+            ["inline", "crossline"],
+            data_type,
+            range(1, 346),
+            get_inline_header_values,
+        )
 
-        assert mdio.shape == (345, 188, 1501)
-        assert mdio[0, :, :].shape == (188, 1501)
-        assert mdio[:, 0, :].shape == (345, 1501)
-        assert mdio[:, :, 0].shape == (345, 188)
+        # Validate the trace mask
+        validate_variable(
+            ds, "trace_mask", (345, 188), ["inline", "crossline"], np.bool, None, None
+        )
+
+        # validate the amplitude data
+        validate_variable(
+            ds,
+            "amplitude",
+            (345, 188, 1501),
+            ["inline", "crossline", "time"],
+            np.float32,
+            None,
+            None,
+        )
 
     def test_inline(self, zarr_tmp: Path) -> None:
         """Read and compare every 75 inlines' mean and std. dev."""
-        mdio = MDIOReader(zarr_tmp.__str__())
-
-        inlines = mdio[::75, :, :]
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+        inlines = ds["amplitude"][::75, :, :]
         mean, std = inlines.mean(), inlines.std()
-
         npt.assert_allclose([mean, std], [1.0555277e-04, 6.0027051e-01])
 
     def test_crossline(self, zarr_tmp: Path) -> None:
         """Read and compare every 75 crosslines' mean and std. dev."""
-        mdio = MDIOReader(zarr_tmp.__str__())
-
-        xlines = mdio[:, ::75, :]
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+        xlines = ds["amplitude"][:, ::75, :]
         mean, std = xlines.mean(), xlines.std()
 
         npt.assert_allclose([mean, std], [-5.0329847e-05, 5.9406823e-01])
 
     def test_zslice(self, zarr_tmp: Path) -> None:
         """Read and compare every 225 z-slices' mean and std. dev."""
-        mdio = MDIOReader(zarr_tmp.__str__())
-
-        slices = mdio[:, :, ::225]
+        path = zarr_tmp.__str__()
+        # path = "/tmp/pytest-of-vscode/my-mdio/mdio0"
+        ds = xr.open_dataset(path, engine="zarr")
+        slices = ds["amplitude"][:, :, ::225]
         mean, std = slices.mean(), slices.std()
-
         npt.assert_allclose([mean, std], [0.005236923, 0.61279935])
 
 
diff --git a/tests/integration/testing_helpers.py b/tests/integration/testing_helpers.py
new file mode 100644
index 000000000..4df6bdad0
--- /dev/null
+++ b/tests/integration/testing_helpers.py
@@ -0,0 +1,69 @@
+"""This module provides testing helpers for integration testing."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numpy as np
+from segy.schema import HeaderField
+from segy.schema import SegySpec
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
+    import xarray as xr
+
+
+def customize_segy_specs(
+    segy_spec: SegySpec,
+    index_bytes: tuple[int, ...] | None = None,
+    index_names: tuple[int, ...] | None = None,
+    index_types: tuple[int, ...] | None = None,
+) -> SegySpec:
+    """Customize SEG-Y specifications with user-defined index fields."""
+    if not index_bytes:
+        # No customization
+        return segy_spec
+
+    index_names = index_names or [f"dim_{i}" for i in range(len(index_bytes))]
+    index_types = index_types or ["int32"] * len(index_bytes)
+
+    if not (len(index_names) == len(index_bytes) == len(index_types)):
+        err = "All index fields must have the same length."
+        raise ValueError(err)
+
+    # Index the dataset using a spec that interprets the user provided index headers.
+    index_fields = []
+    for name, byte, format_ in zip(index_names, index_bytes, index_types, strict=True):
+        index_fields.append(HeaderField(name=name, byte=byte, format=format_))
+
+    return segy_spec.customize(trace_header_fields=index_fields)
+
+
+def get_values(arr: xr.DataArray) -> np.ndarray:
+    """Extract actual values from an Xarray DataArray."""
+    return arr.values
+
+
+def get_inline_header_values(dataset: xr.Dataset) -> np.ndarray:
+    """Extract a specific header value from an Xarray DataArray."""
+    return dataset["inline"].values
+
+
+def validate_variable(  # noqa PLR0913
+    dataset: xr.Dataset,
+    name: str,
+    shape: list[int],
+    dims: list[str],
+    data_type: np.dtype,
+    expected_values: range | None,
+    actual_value_generator: Callable,
+) -> None:
+    """Validate the properties of a variable in an Xarray dataset."""
+    arr = dataset[name]
+    assert shape == arr.shape
+    assert set(dims) == set(arr.dims)
+    assert data_type == arr.dtype
+    if expected_values is not None and actual_value_generator is not None:
+        actual_values = actual_value_generator(arr)
+        assert np.array_equal(expected_values, actual_values)
diff --git a/tests/integration/v1/test_segy_to_mdio_v1.py b/tests/integration/v1/test_segy_to_mdio_v1.py
new file mode 100644
index 000000000..e44af6cb2
--- /dev/null
+++ b/tests/integration/v1/test_segy_to_mdio_v1.py
@@ -0,0 +1,354 @@
+"""End to end testing for SEG-Y to MDIO conversion v1."""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import numcodecs
+import numpy as np
+import pytest
+import xarray as xr
+import zarr
+from segy.standards import get_segy_standard
+from zarr.core.chunk_key_encodings import V2ChunkKeyEncoding
+
+from mdio.converters.segy import segy_to_mdio
+from mdio.converters.type_converter import to_numpy_dtype
+from mdio.core.storage_location import StorageLocation
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.templates.template_registry import TemplateRegistry
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
+
+def _slice_three_values(dims: tuple[int], values_from_start: bool) -> tuple[slice, ...]:
+    if values_from_start:
+        slices = tuple([slice(0, 3) for _ in range(len(dims))])
+    else:
+        slices = tuple([slice(-3, None) for _ in range(len(dims))])
+    return slices
+
+
+def _get_actual_value(arr: xr.DataArray) -> np.ndarray:
+    return arr.values[_slice_three_values(arr.shape, values_from_start=True)]
+
+
+def _validate_variable(  # noqa PLR0913
+    dataset: xr.Dataset,
+    name: str,
+    shape: list[int],
+    dims: list[str],
+    data_type: np.dtype,
+    expected_values: range | None,
+    actual_func: Callable,
+) -> None:
+    arr = dataset[name]
+    assert shape == arr.shape
+    assert set(dims) == set(arr.dims)
+    assert data_type == arr.dtype
+    # Validate first/last values
+    # actual_values = d.values[_slice_three_values(shape, values_from_start)]
+    actual_values = actual_func(arr)
+    assert np.array_equal(expected_values, actual_values)
+
+
+def test_segy_to_mdio_v1__f3() -> None:
+    """Test the SEG-Y to MDIO conversion for the f3 equinor/segyio dataset."""
+    # The f3 dataset comes from
+    # equinor/segyio (https://github.com/equinor/segyio) project (GNU LGPL license)
+    # wget https://github.com/equinor/segyio/blob/main/test-data/f3.sgy
+
+    pref_path = "/DATA/equinor-segyio/f3.sgy"
+    mdio_path = f"{pref_path}_mdio_v1"
+
+    segy_to_mdio(
+        segy_spec=get_segy_standard(1.0),
+        mdio_template=TemplateRegistry().get("PostStack3DTime"),
+        input_location=StorageLocation(pref_path),
+        output_location=StorageLocation(mdio_path),
+        overwrite=True,
+    )
+
+    # Load Xarray dataset from the MDIO file
+    ds = xr.open_dataset(mdio_path, engine="zarr")
+
+    # Tests "inline" variable
+    expected = np.array([111, 112, 113])
+    _validate_variable(ds, "inline", (23,), ["inline"], np.int32, expected, _get_actual_value)
+
+    # Tests "crossline" variable
+    expected = np.array([875, 876, 877])
+    _validate_variable(ds, "crossline", (18,), ["crossline"], np.int32, expected, _get_actual_value)
+
+    # Tests "time" variable
+    expected = np.array([0, 4, 8])
+    _validate_variable(ds, "time", (75,), ["time"], np.int64, expected, _get_actual_value)
+
+    # Tests "cdp_x" variable
+    expected = np.array(
+        [[6201972, 6202222, 6202472], [6201965, 6202215, 6202465], [6201958, 6202208, 6202458]]
+    )
+    _validate_variable(
+        ds, "cdp_x", (23, 18), ["inline", "crossline"], np.int32, expected, _get_actual_value
+    )
+
+    # Tests "cdp_y" variable
+    expected = np.array(
+        [
+            [60742329, 60742336, 60742343],
+            [60742579, 60742586, 60742593],
+            [60742828, 60742835, 60742842],
+        ]
+    )
+    _validate_variable(
+        ds, "cdp_y", (23, 18), ["inline", "crossline"], np.int32, expected, _get_actual_value
+    )
+
+    # Tests "headers" variable
+    data_type = np.dtype(
+        [
+            ("trace_seq_num_line", "<i4"),
+            ("trace_seq_num_reel", "<i4"),
+            ("orig_field_record_num", "<i4"),
+            ("trace_num_orig_record", "<i4"),
+            ("energy_source_point_num", "<i4"),
+            ("ensemble_num", "<i4"),
+            ("trace_num_ensemble", "<i4"),
+            ("trace_id_code", "<i2"),
+            ("vertically_summed_traces", "<i2"),
+            ("horizontally_stacked_traces", "<i2"),
+            ("data_use", "<i2"),
+            ("source_to_receiver_distance", "<i4"),
+            ("receiver_group_elevation", "<i4"),
+            ("source_surface_elevation", "<i4"),
+            ("source_depth_below_surface", "<i4"),
+            ("receiver_datum_elevation", "<i4"),
+            ("source_datum_elevation", "<i4"),
+            ("source_water_depth", "<i4"),
+            ("receiver_water_depth", "<i4"),
+            ("elevation_depth_scalar", "<i2"),
+            ("coordinate_scalar", "<i2"),
+            ("source_coord_x", "<i4"),
+            ("source_coord_y", "<i4"),
+            ("group_coord_x", "<i4"),
+            ("group_coord_y", "<i4"),
+            ("coordinate_unit", "<i2"),
+            ("weathering_velocity", "<i2"),
+            ("subweathering_velocity", "<i2"),
+            ("source_uphole_time", "<i2"),
+            ("group_uphole_time", "<i2"),
+            ("source_static_correction", "<i2"),
+            ("receiver_static_correction", "<i2"),
+            ("total_static_applied", "<i2"),
+            ("lag_time_a", "<i2"),
+            ("lag_time_b", "<i2"),
+            ("delay_recording_time", "<i2"),
+            ("mute_time_start", "<i2"),
+            ("mute_time_end", "<i2"),
+            ("samples_per_trace", "<i2"),
+            ("sample_interval", "<i2"),
+            ("instrument_gain_type", "<i2"),
+            ("instrument_gain_const", "<i2"),
+            ("instrument_gain_initial", "<i2"),
+            ("correlated_data", "<i2"),
+            ("sweep_freq_start", "<i2"),
+            ("sweep_freq_end", "<i2"),
+            ("sweep_length", "<i2"),
+            ("sweep_type", "<i2"),
+            ("sweep_taper_start", "<i2"),
+            ("sweep_taper_end", "<i2"),
+            ("taper_type", "<i2"),
+            ("alias_filter_freq", "<i2"),
+            ("alias_filter_slope", "<i2"),
+            ("notch_filter_freq", "<i2"),
+            ("notch_filter_slope", "<i2"),
+            ("low_cut_freq", "<i2"),
+            ("high_cut_freq", "<i2"),
+            ("low_cut_slope", "<i2"),
+            ("high_cut_slope", "<i2"),
+            ("year_recorded", "<i2"),
+            ("day_of_year", "<i2"),
+            ("hour_of_day", "<i2"),
+            ("minute_of_hour", "<i2"),
+            ("second_of_minute", "<i2"),
+            ("time_basis_code", "<i2"),
+            ("trace_weighting_factor", "<i2"),
+            ("group_num_roll_switch", "<i2"),
+            ("group_num_first_trace", "<i2"),
+            ("group_num_last_trace", "<i2"),
+            ("gap_size", "<i2"),
+            ("taper_overtravel", "<i2"),
+            ("cdp_x", "<i4"),
+            ("cdp_y", "<i4"),
+            ("inline", "<i4"),
+            ("crossline", "<i4"),
+            ("shot_point", "<i4"),
+            ("shot_point_scalar", "<i2"),
+            ("trace_value_unit", "<i2"),
+            ("transduction_const_mantissa", "<i4"),
+            ("transduction_const_exponent", "<i2"),
+            ("transduction_unit", "<i2"),
+            ("device_trace_id", "<i2"),
+            ("times_scalar", "<i2"),
+            ("source_type_orientation", "<i2"),
+            ("source_energy_dir_mantissa", "<i4"),
+            ("source_energy_dir_exponent", "<i2"),
+            ("source_measurement_mantissa", "<i4"),
+            ("source_measurement_exponent", "<i2"),
+            ("source_measurement_unit", "<i2"),
+        ]
+    )
+    expected = np.array(
+        [
+            [6201972, 6202222, 6202472],
+            [6201965, 6202215, 6202465],
+            [6201958, 6202208, 6202458],
+        ],
+        dtype=np.int32,
+    )
+
+    def get_actual_headers(arr: xr.DataArray) -> np.ndarray:
+        cdp_x_headers = arr.values["cdp_x"]
+        return cdp_x_headers[_slice_three_values(arr.shape, values_from_start=True)]
+
+    _validate_variable(
+        ds, "headers", (23, 18), ["inline", "crossline"], data_type, expected, get_actual_headers
+    )
+
+    # Tests "trace_mask" variable
+    expected = np.array([[True, True, True], [True, True, True], [True, True, True]])
+    _validate_variable(
+        ds, "trace_mask", (23, 18), ["inline", "crossline"], np.bool, expected, _get_actual_value
+    )
+
+    # Tests "amplitude" variable
+    expected = np.array(
+        [
+            [[487.0, -1104.0, -1456.0], [-129.0, -1728.0, 445.0], [-1443.0, 741.0, 1458.0]],
+            [[2464.0, 3220.0, 1362.0], [686.0, 530.0, -282.0], [3599.0, 2486.0, 433.0]],
+            [[4018.0, 5159.0, 2087.0], [-81.0, -3039.0, -1850.0], [2898.0, 1060.0, -121.0]],
+        ]
+    )
+
+    def get_actual_amplitudes(arr: xr.DataArray) -> np.ndarray:
+        return arr.values[_slice_three_values(arr.shape, values_from_start=False)]
+
+    _validate_variable(
+        ds,
+        "amplitude",
+        (23, 18, 75),
+        ["inline", "crossline", "time"],
+        np.float32,
+        expected,
+        get_actual_amplitudes,
+    )
+
+
+@pytest.mark.skip(reason="Bug reproducer for the issue 582")
+def test_bug_reproducer_structured_xr_to_zar() -> None:
+    """Bug reproducer for the issue https://github.com/TGSAI/mdio-python/issues/582.
+
+    Will be removed in the when the bug is fixed
+    """
+    shape = (4, 4, 2)
+    dim_names = ["inline", "crossline", "depth"]
+    chunks = (2, 2, 2)
+    # Pretend that we created a pydantic model from a template
+    structured_type = StructuredType(
+        fields=[
+            StructuredField(name="cdp_x", format=ScalarType.INT32),
+            StructuredField(name="cdp_y", format=ScalarType.INT32),
+            StructuredField(name="elevation", format=ScalarType.FLOAT16),
+            StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
+        ]
+    )
+
+    xr_dataset = xr.Dataset()
+
+    # Add traces to the dataset, shape = (4, 4, 2) of floats
+    traces_zarr = zarr.zeros(shape=shape, dtype=np.float32, zarr_format=2)
+    traces_xr = xr.DataArray(traces_zarr, dims=dim_names)
+    traces_xr.encoding = {
+        "_FillValue": np.nan,
+        "chunks": chunks,
+        "chunk_key_encoding": V2ChunkKeyEncoding(separator="/").to_dict(),
+        "compressor": numcodecs.Blosc(cname="zstd", clevel=5, shuffle=1, blocksize=0),
+    }
+    xr_dataset["traces"] = traces_xr
+
+    # Add headers to the dataset, shape = (4, 4) of structured type
+    data_type = to_numpy_dtype(structured_type)
+
+    # Validate the conversion
+    assert data_type == np.dtype(
+        [("cdp_x", "<i4"), ("cdp_y", "<i4"), ("elevation", "<f2"), ("some_scalar", "<f2")]
+    )
+    fill_value = np.zeros((), dtype=data_type)
+    headers_zarr = zarr.zeros(shape=shape[:-1], dtype=data_type, zarr_format=2)
+    headers_xr = xr.DataArray(headers_zarr, dims=dim_names[:-1])
+    headers_xr.encoding = {
+        "_FillValue": fill_value,
+        "chunks": chunks[:-1],
+        "chunk_key_encoding": V2ChunkKeyEncoding(separator="/").to_dict(),
+        "compressor": numcodecs.Blosc(cname="zstd", clevel=5, shuffle=1, blocksize=0),
+    }
+    xr_dataset["headers"] = headers_xr
+
+    # See _populate_dims_coords_and_write_to_zarr()
+    # The compute=True because we would also write to Zarr the coord values here
+    xr_dataset.to_zarr(
+        store="/tmp/reproducer_xr.zarr",  # noqa: S108
+        mode="w",
+        write_empty_chunks=False,
+        zarr_format=2,
+        compute=True,
+    )
+
+    # In _populate_trace_mask_and_write_to_zarr
+    # We do another write of "trace_mask" to the same Zarr store and remove it
+    # from the dataset
+
+    # ----------------------------------------------
+    # Now will will do parallel write of the data and the headers
+    # see blocked_io.to_zarr -> trace_worker
+
+    not_null = np.array(
+        [
+            [True, False, False, False],
+            [False, True, False, False],
+            [False, False, True, False],
+            [False, False, False, True],
+        ]
+    )
+    hdr = (11, 22, -33.0, 44.0)
+    headers = np.array([hdr, hdr, hdr, hdr], dtype=data_type)
+    trace = np.array(
+        [[100.0, 200.0], [300.0, 400.0], [500.0, 600.0], [700.0, 800.0]], dtype=np.float32
+    )
+
+    # Here is one iteration of it:
+    ds_to_write = xr_dataset[["traces", "headers"]]
+    # We do not have any coords to reset
+    # ds_to_write = ds_to_write.reset_coords()
+
+    ds_to_write["headers"].data[not_null] = headers
+    ds_to_write["headers"].data[~not_null] = 0
+    ds_to_write["traces"].data[not_null] = trace
+
+    region = {
+        "inline": slice(0, 2, None),
+        "crossline": slice(0, 2, None),
+        "depth": slice(0, 2, None),
+    }
+
+    sub_dataset = ds_to_write.isel(region)
+    sub_dataset.to_zarr(
+        store="/tmp/reproducer_xr.zarr",  # noqa: S108
+        region=region,
+        mode="r+",
+        write_empty_chunks=False,
+        zarr_format=2,
+    )
diff --git a/tests/unit/test_compat.py b/tests/unit/test_compat.py
deleted file mode 100644
index e1c950de3..000000000
--- a/tests/unit/test_compat.py
+++ /dev/null
@@ -1,106 +0,0 @@
-"""Test MDIO compatibility with older versions."""
-
-from pathlib import Path
-
-import numpy as np
-import pytest
-import zarr
-from segy import SegyFile
-from segy.factory import SegyFactory
-from segy.standards import get_segy_standard
-
-from mdio import mdio_to_segy
-from mdio import segy_to_mdio
-
-# Constants
-MDIO_VERSIONS = ["0.7.4", "0.8.3"]
-SEGY_REVISIONS = [0.0, 0.1, 1.0, 1.1]
-INLINES = (10, 10, 11, 11)
-CROSSLINES = (100, 101, 100, 101)
-INDEX_BYTES = (189, 193)
-API_VERSION_KEY = "api_version"
-BINARY_HEADER_KEY = "binary_header"
-CHUNKED_TRACE_HEADERS_KEY = "chunked_012_trace_headers"
-
-
-def update_mdio_for_version_0_7_4(root_group: zarr.Group) -> None:
-    """Update MDIO metadata to mimic version 0.7.4."""
-    # Update binary header revision keys
-    meta_group = root_group.require_group("metadata")
-    bin_hdr = meta_group.attrs[BINARY_HEADER_KEY]
-    bin_hdr["SEGYRevision"] = bin_hdr.pop("segy_revision_major")
-    bin_hdr["SEGYRevisionMinor"] = bin_hdr.pop("segy_revision_minor")
-    meta_group.attrs[BINARY_HEADER_KEY] = bin_hdr
-
-    # Remove trace headers past field 232 (pre-0.8 schema)
-    orig_hdr = meta_group[CHUNKED_TRACE_HEADERS_KEY]
-    new_dtype = np.dtype(orig_hdr.dtype.descr[:-1])
-    meta_group.create_array(
-        name=CHUNKED_TRACE_HEADERS_KEY,
-        shape=orig_hdr.shape,
-        dtype=new_dtype,
-        chunks=orig_hdr.chunks,
-        chunk_key_encoding={"name": "v2", "separator": "/"},
-        overwrite=True,
-    )
-    zarr.consolidate_metadata(meta_group.store)
-
-
-@pytest.mark.parametrize("mdio_version", MDIO_VERSIONS)
-@pytest.mark.parametrize("segy_revision", SEGY_REVISIONS)
-def test_revision_encode_decode(mdio_version: str, segy_revision: float, tmp_path: Path) -> None:
-    """Test binary header major/minor revision roundtrip.
-
-    After introducting TGSAI/segy, we changed the header names. Now we use
-    aliasing and MDIO has a dummy schema. The handling is slightly different
-    for SEG-Y revision major/minor numbers. Testing to ensure they're
-    (de)serialized correctly.
-    """
-    rev1_spec = get_segy_standard(1.0)
-    segy_filename = tmp_path / "segy_input.sgy"
-    mdio_output_filename = tmp_path / "output.mdio"
-    roundtrip_sgy_filename = tmp_path / "roundtrip_output.sgy"
-
-    # Make a rev1 segy
-    factory = SegyFactory(rev1_spec, sample_interval=1000, samples_per_trace=5)
-
-    # We will replace the values in revision fields with these
-    minor, major = np.modf(segy_revision)
-    major, minor = int(major), int(minor * 10)
-    revision_code = (major << 8) | minor
-
-    # Make fake tiny 3D dataset
-    txt_buffer = factory.create_textual_header()
-
-    header = factory.create_trace_header_template(len(INLINES))
-    data = factory.create_trace_sample_template(len(INLINES))
-    header["inline"] = INLINES
-    header["crossline"] = CROSSLINES
-    data[:] = np.arange(len(INLINES))[:, None]
-    trace_buffer = factory.create_traces(header, data)
-
-    # Update revision during bin hdr creation
-    bin_hdr_buffer = factory.create_binary_header(update={"segy_revision": revision_code})
-    with segy_filename.open(mode="wb") as fp:
-        fp.write(txt_buffer)
-        fp.write(bin_hdr_buffer)
-        fp.write(trace_buffer)
-
-    # Convert SEG-Y to MDIO
-    segy_to_mdio(str(segy_filename), str(mdio_output_filename), index_bytes=INDEX_BYTES)
-
-    # Modify MDIO for specific versions
-    root = zarr.open_group(mdio_output_filename, mode="r+")
-    root.attrs[API_VERSION_KEY] = mdio_version
-    if mdio_version == "0.7.4":
-        update_mdio_for_version_0_7_4(root)
-
-    # Convert MDIO back to SEG-Y
-    mdio_to_segy(str(mdio_output_filename), str(roundtrip_sgy_filename))
-
-    # Assert binary headers and revisions match
-    orig = SegyFile(segy_filename, spec=rev1_spec)
-    rt = SegyFile(roundtrip_sgy_filename, spec=rev1_spec)
-    assert orig.binary_header["segy_revision_major"] == major
-    assert orig.binary_header["segy_revision_minor"] == minor
-    assert orig.binary_header == rt.binary_header
diff --git a/tests/unit/v1/converters/test_type_converter.py b/tests/unit/v1/converters/test_type_converter.py
new file mode 100644
index 000000000..31d72f157
--- /dev/null
+++ b/tests/unit/v1/converters/test_type_converter.py
@@ -0,0 +1,95 @@
+"""Unit tests for the type converter module."""
+
+import pytest
+from numpy import dtype as np_dtype
+
+from mdio.converters.type_converter import to_numpy_dtype
+from mdio.converters.type_converter import to_scalar_type
+from mdio.converters.type_converter import to_structured_type
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+
+
+@pytest.fixture
+def supported_scalar_types_map() -> tuple[ScalarType, str]:
+    """Supported scalar types and their numpy equivalents."""
+    return (
+        (ScalarType.INT8, "int8"),
+        (ScalarType.INT16, "int16"),
+        (ScalarType.INT32, "int32"),
+        (ScalarType.INT64, "int64"),
+        (ScalarType.UINT8, "uint8"),
+        (ScalarType.UINT16, "uint16"),
+        (ScalarType.UINT32, "uint32"),
+        (ScalarType.UINT64, "uint64"),
+        (ScalarType.FLOAT32, "float32"),
+        (ScalarType.FLOAT64, "float64"),
+        (ScalarType.COMPLEX64, "complex64"),
+        (ScalarType.COMPLEX128, "complex128"),
+        (ScalarType.BOOL, "bool"),
+    )
+
+
+@pytest.fixture
+def a_structured_type() -> StructuredType:
+    """Sample structured type.
+
+    Returns a structured type.
+    """
+    return StructuredType(
+        fields=[
+            StructuredField(name="x", format=ScalarType.FLOAT64),
+            StructuredField(name="y", format=ScalarType.FLOAT64),
+            StructuredField(name="z", format=ScalarType.FLOAT64),
+            StructuredField(name="id", format=ScalarType.INT32),
+            StructuredField(name="valid", format=ScalarType.BOOL),
+        ]
+    )
+
+
+def test_to_numpy_dtype(
+    supported_scalar_types_map: tuple[ScalarType, str], a_structured_type: StructuredType
+) -> None:
+    """Comprehensive test for to_numpy_dtype function."""
+    # Test 0: invalid input
+    err = "Expected ScalarType or StructuredType, got 'str'"
+    with pytest.raises(ValueError, match=err):
+        to_numpy_dtype("parameter of invalid type")
+
+    # Test 1: ScalarType cases - all supported scalar types
+    for scalar_type, expected_numpy_type in supported_scalar_types_map:
+        result = to_numpy_dtype(scalar_type)
+        expected = np_dtype(expected_numpy_type)
+        assert result == expected
+        assert isinstance(result, np_dtype)
+        assert result.name == expected.name
+
+    # Test 2: StructuredType with multiple fields
+    result_multi = to_numpy_dtype(a_structured_type)
+    expected_multi = np_dtype(
+        [("x", "float64"), ("y", "float64"), ("z", "float64"), ("id", "int32"), ("valid", "bool")]
+    )
+
+    assert result_multi == expected_multi
+    assert isinstance(result_multi, np_dtype)
+    assert len(result_multi.names) == 5
+    assert set(result_multi.names) == {"x", "y", "z", "id", "valid"}
+
+
+def test_to_scalar_type(supported_scalar_types_map: tuple[ScalarType, str]) -> None:
+    """Test for to_scalar_type function."""
+    for expected_mdio_type, numpy_type in supported_scalar_types_map:
+        result = to_scalar_type(np_dtype(numpy_type))
+        assert result == expected_mdio_type
+
+
+def test_to_structured_type(a_structured_type: StructuredType) -> None:
+    """Test for to_structured_type function."""
+    dtype = np_dtype(
+        [("x", "float64"), ("y", "float64"), ("z", "float64"), ("id", "int32"), ("valid", "bool")]
+    )
+    assert a_structured_type == to_structured_type(dtype)
+
+    dtype = np_dtype([("x", "<f8"), ("y", "<f8"), ("z", "<f8"), ("id", "<i4"), ("valid", "?")])
+    assert a_structured_type == to_structured_type(dtype)
diff --git a/tests/unit/v1/core/test_indexing.py b/tests/unit/v1/core/test_indexing.py
new file mode 100644
index 000000000..5c52e555f
--- /dev/null
+++ b/tests/unit/v1/core/test_indexing.py
@@ -0,0 +1,128 @@
+"""Unit tests for the type converter module."""
+
+import numpy as np
+from xarray import DataArray as xr_DataArray
+from xarray import Dataset as xr_Dataset
+
+from mdio.core.indexing import ChunkIterator
+
+
+def test_chunk_iterator_returning_dict() -> None:
+    """Test the ChunkIterator class."""
+    dims = ["inline", "crossline", "depth"]
+    chunks = (3, 4, 5)
+
+    shape = (6, 12, 20)
+    iter1 = ChunkIterator(shape=shape, chunks=chunks, dim_names=dims)
+    assert iter1.arr_shape == shape
+    assert iter1.dims == dims
+    assert iter1.len_chunks == chunks
+    assert iter1.dim_chunks == (2, 3, 4)
+    assert iter1.num_chunks == 24
+
+    shape = (5, 11, 19)
+    iter2 = ChunkIterator(shape=shape, chunks=chunks, dim_names=dims)
+    assert iter2.dim_chunks == (2, 3, 4)
+    assert iter2.num_chunks == 24
+
+    # Its purpose is to confirm that all slices are created of the same size,
+    # even if the last slice should have been smaller.
+    for _ in range(13):  # element index 12
+        region = iter1.__next__()
+    assert region == {
+        "inline": slice(3, 6, None),
+        "crossline": slice(0, 4, None),
+        "depth": slice(0, 5, None),
+    }
+
+    for _ in range(13):  # element index 12
+        region = iter2.__next__()
+    assert region == {
+        "inline": slice(3, 6, None),
+        "crossline": slice(0, 4, None),
+        "depth": slice(0, 5, None),
+    }
+
+
+def test_chunk_iterator_returning_tuple() -> None:
+    """Test the ChunkIterator class."""
+    chunks = (3, 4, 5)
+
+    shape = (6, 12, 20)
+    iter1 = ChunkIterator(shape=shape, chunks=chunks)
+    assert iter1.arr_shape == shape
+    assert iter1.dims is None
+    assert iter1.len_chunks == chunks
+    assert iter1.dim_chunks == (2, 3, 4)
+    assert iter1.num_chunks == 24
+
+    shape = (5, 11, 19)
+    iter2 = ChunkIterator(shape=shape, chunks=chunks)
+    assert iter2.dim_chunks == (2, 3, 4)
+    assert iter2.num_chunks == 24
+
+    # Its purpose is to confirm that all slices are created of the same size,
+    # even if the last slice should have been smaller.
+    for _ in range(13):  # element index 12
+        region = iter1.__next__()
+    assert region == (slice(3, 6, None), slice(0, 4, None), slice(0, 5, None))
+
+    for _ in range(13):  # element index 12
+        region = iter2.__next__()
+    assert region == (slice(3, 6, None), slice(0, 4, None), slice(0, 5, None))
+
+
+def val(shape: tuple[int, int, int], i: int, j: int, k: int) -> int:
+    """Calculate the linear index in a 3D array."""
+    return i * (shape[1] * shape[2]) + j * shape[2] + k
+
+
+def mock_trace_worker(
+    shape: tuple[int, int, int], region: dict[str, slice], dataset: xr_Dataset, grid_map: np.array
+) -> None:
+    """Mock trace worker function.
+
+    Note:
+        Xarray, Zarr, and NumPy automatically truncates the slice to the valid bounds of the array
+        (see the test above, where the last chunk is always of the same size)
+        and does not raise an error. However, if one attempts to access an element at an index
+        that is out of bounds, you will get an IndexError
+    """
+    # We used a 2D selection with 2D index_slices
+    assert grid_map.shape == (3, 4, 20)
+    # We used a 3D selection with isel()
+    assert tuple(dataset.dims[d] for d in region) == (3, 4, 5)
+
+    dimension_names = list(dataset.dims)
+
+    slice0 = region[dimension_names[0]]
+    slice1 = region[dimension_names[1]]
+    slice2 = region[dimension_names[2]]
+    for ii, i in enumerate(range(slice0.start, min(slice0.stop, shape[0]))):
+        for jj, j in enumerate(range(slice1.start, min(slice1.stop, shape[1]))):
+            for kk, k in enumerate(range(slice2.start, min(slice2.stop, shape[2]))):
+                # Validate that we've got the sample indexing right
+                assert dataset["amplitude"].values[ii, jj, kk] == val(shape, i, j, k)
+                # NOTE: grid_map is 2D, so we need to use k for the depth dimension
+                assert dataset["amplitude"].values[ii, jj, kk] == grid_map[ii, jj, k]
+
+
+def test_chunk_iterator_with_dataset() -> None:
+    """Test the ChunkIterator with a dataset."""
+    shape = (6, 12, 20)
+    dims = ["inline", "crossline", "depth"]
+    chunks = (3, 4, 5)
+
+    data3 = np.arange(shape[0] * shape[1] * shape[2]).reshape(shape)
+    amplitude = xr_DataArray(data3, dims=dims, name="amplitude")
+    ds = xr_Dataset({"amplitude": amplitude})
+
+    chunk_iter = ChunkIterator(shape, chunks, dims)
+    for region in chunk_iter:
+        # If one needs both a dict and a tuple of slices,
+        # one can use the following line an example to strip dim names out
+        index_slices = tuple(region[key] for key in dims[:-1])
+        # The .isel() method takes keyword arguments, region, where each keyword corresponds
+        # to a dimension name and the value is an integer, a slice object (our case),
+        # or an array-like object
+        mock_trace_worker(shape, region, ds.isel(region), amplitude[index_slices])
diff --git a/tests/unit/v1/core/test_storage_location.py b/tests/unit/v1/core/test_storage_location.py
new file mode 100644
index 000000000..4f18e93a7
--- /dev/null
+++ b/tests/unit/v1/core/test_storage_location.py
@@ -0,0 +1,132 @@
+"""Unit tests for StorageLocation class."""
+
+import tempfile
+from pathlib import Path
+from unittest.mock import MagicMock
+from unittest.mock import Mock
+from unittest.mock import patch
+
+import pytest
+
+from mdio.core.storage_location import StorageLocation
+
+
+class TestStorageLocation:
+    """Test cases for StorageLocation class."""
+
+    @patch("fsspec.filesystem")
+    def test_exists(self, mock_filesystem: MagicMock, capsys: pytest.CaptureFixture[str]) -> None:
+        """Test the exists() method of StorageLocation."""
+        # Test exists() returns True when file exists.
+        mock_fs = Mock()
+        mock_fs.exists.return_value = True
+        mock_filesystem.return_value = mock_fs
+        location = StorageLocation("/test/existing/file")
+        result = location.exists()
+        assert result is True
+        mock_fs.exists.assert_called_once()
+
+        # Test exists() returns False when file does not exist.
+        mock_fs = Mock()
+        mock_fs.exists.return_value = False
+        mock_filesystem.return_value = mock_fs
+        location = StorageLocation("/test/nonexistent/file")
+        result = location.exists()
+        assert result is False
+        mock_fs.exists.assert_called_once()
+
+        # Test exists() handles exceptions gracefully.
+        mock_fs = Mock()
+        mock_fs.exists.side_effect = Exception("Connection failed")
+        mock_filesystem.return_value = mock_fs
+        location = StorageLocation("s3://bucket/file")
+        result = location.exists()
+        assert result is False
+        captured = capsys.readouterr()
+        assert "Error checking existence of s3://bucket/file: Connection failed" in captured.out
+
+    def test_representations(self) -> None:
+        """Test string and developer representations of StorageLocation."""
+        # Test string representation of StorageLocation.
+        location = StorageLocation("/test/path")
+        assert str(location) == "/test/path"
+
+        # Test developer representation of StorageLocation.
+
+        uri = "s3://my-bucket/file.segy"
+        options = {"region": "us-west-2"}
+        location = StorageLocation(uri=uri, options=options)
+        expected = (
+            "StorageLocation(uri='s3://my-bucket/file.segy', options={'region': 'us-west-2'})"
+        )
+        assert repr(location) == expected
+
+    def test_from_path(self) -> None:
+        """Test from_path class method."""
+        # Test with string path.
+        path_str = "/home/user/data.segy"
+        location = StorageLocation(path_str)
+        # Should resolve to absolute path
+        expected_path = str(Path(path_str).resolve())
+        assert location.uri == expected_path
+        assert location.options == {}
+
+        # Test with path uri path.
+        location = StorageLocation(f"file://{path_str}")
+        # Should resolve to absolute path
+        expected_path = str(Path(path_str).resolve())
+        assert location.uri == expected_path
+        assert location.options == {}
+
+        # Test with real local file operations.
+        # Create a temporary file for testing
+        with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+            temp_path = Path(temp_file.name)
+            temp_file.write(b"test content")
+        try:
+            # Test with real local file
+            location = StorageLocation(str(temp_path))
+            # Should exist
+            assert location.exists() is True
+            # Should have correct URI
+            assert location.uri == str(temp_path.resolve())
+        finally:
+            # Clean up
+            temp_path.unlink()
+            # Now should not exist
+            assert location.exists() is False
+
+    def test_from_cloud(self) -> None:
+        """Test class for cloud storage URIs."""
+        # Test from_s3 without options.
+        s3_uri = "s3://bucket/file"
+        location = StorageLocation(s3_uri)
+        assert location.uri == s3_uri
+        assert location.options == {}
+
+        # Test from_s3 with valid S3 URI.
+        s3_uri = "s3://my-bucket/path/to/file.segy"
+        options = {"region": "us-west-2", "aws_access_key_id": "key123"}
+        location = StorageLocation(s3_uri, options=options)
+        assert location.uri == s3_uri
+        assert location.options == options
+
+    def test_options_immutability(self) -> None:
+        """Test that options property returns a defensive copy."""
+        original_options = {"region": "us-east-1", "timeout": 30}
+        location = StorageLocation(uri="s3://bucket/file", options=original_options)
+
+        # Get options through property
+        returned_options = location.options
+
+        # Verify it's equal to original
+        assert returned_options == original_options
+
+        # Modify the returned dict
+        returned_options["new_key"] = "new_value"
+        returned_options["timeout"] = 60
+
+        # Original should be unchanged
+        assert location.options == original_options
+        assert "new_key" not in location.options
+        assert location.options["timeout"] == 30
diff --git a/tests/unit/v1/helpers.py b/tests/unit/v1/helpers.py
index f9d209690..ca0383d09 100644
--- a/tests/unit/v1/helpers.py
+++ b/tests/unit/v1/helpers.py
@@ -185,13 +185,13 @@ def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
     )
     # Add coordinates
     ds.add_coordinate(
-        "cdp-x",
+        "cdp_x",
         dimensions=["inline", "crossline"],
         data_type=ScalarType.FLOAT32,
         metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
     )
     ds.add_coordinate(
-        "cdp-y",
+        "cdp_y",
         dimensions=["inline", "crossline"],
         data_type=ScalarType.FLOAT32,
         metadata_info=[AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.METER))],
@@ -203,7 +203,7 @@ def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT32,
         compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
+        coordinates=["cdp_x", "cdp_y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -228,7 +228,7 @@ def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
         name="velocity",
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT16,
-        coordinates=["cdp-x", "cdp-y"],
+        coordinates=["cdp_x", "cdp_y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -245,7 +245,7 @@ def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT32,
         compressor=Blosc(algorithm="zstd"),
-        coordinates=["cdp-x", "cdp-y"],
+        coordinates=["cdp_x", "cdp_y"],
         metadata_info=[
             ChunkGridMetadata(
                 chunk_grid=RegularChunkGrid(
@@ -258,11 +258,11 @@ def make_seismic_poststack_3d_acceptance_dataset(dataset_name: str) -> Dataset:
     ds.add_variable(
         name="image_headers",
         dimensions=["inline", "crossline"],
-        coordinates=["cdp-x", "cdp-y"],
+        coordinates=["cdp_x", "cdp_y"],
         data_type=StructuredType(
             fields=[
-                StructuredField(name="cdp-x", format=ScalarType.INT32),
-                StructuredField(name="cdp-y", format=ScalarType.INT32),
+                StructuredField(name="cdp_x", format=ScalarType.INT32),
+                StructuredField(name="cdp_y", format=ScalarType.INT32),
                 StructuredField(name="elevation", format=ScalarType.FLOAT16),
                 StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
             ]
diff --git a/tests/unit/v1/templates/conftest.py b/tests/unit/v1/templates/conftest.py
new file mode 100644
index 000000000..1a3e5e097
--- /dev/null
+++ b/tests/unit/v1/templates/conftest.py
@@ -0,0 +1,21 @@
+"""Unit tests for the conftest module in the templates directory."""
+
+# conftest.py
+import pytest
+
+from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredField
+from mdio.schemas.dtype import StructuredType
+
+
+@pytest.fixture(scope="session")
+def structured_headers() -> StructuredType:
+    """Fixture to provide structured headers for testing."""
+    return StructuredType(
+        fields=[
+            StructuredField(name="cdp_x", format=ScalarType.INT32),
+            StructuredField(name="cdp_y", format=ScalarType.INT32),
+            StructuredField(name="elevation", format=ScalarType.FLOAT16),
+            StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
+        ]
+    )
diff --git a/tests/unit/v1/templates/test_seismic_2d_poststack.py b/tests/unit/v1/templates/test_seismic_2d_poststack.py
index 79f795854..89b5d0655 100644
--- a/tests/unit/v1/templates/test_seismic_2d_poststack.py
+++ b/tests/unit/v1/templates/test_seismic_2d_poststack.py
@@ -4,6 +4,8 @@
 
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.templates.seismic_2d_poststack import Seismic2DPostStackTemplate
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
@@ -15,6 +17,70 @@
 _UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
 
 
+def _validate_coordinates_headers_trace_mask(
+    dataset: Dataset, headers: StructuredType, domain: str
+) -> None:
+    """Validate the coordinate, headers, trace_mask variables in the dataset."""
+    # Verify variables
+    # 2 dim coords + 2 non-dim coords + 1 data + 1 trace mask + 1 headers = 6 variables
+    assert len(dataset.variables) == 7
+
+    # Verify trace headers
+    validate_variable(
+        dataset,
+        name="headers",
+        dims=[("cdp", 2048)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=headers,
+    )
+
+    validate_variable(
+        dataset,
+        name="trace_mask",
+        dims=[("cdp", 2048)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=ScalarType.BOOL,
+    )
+
+    # Verify dimension coordinate variables
+    inline = validate_variable(
+        dataset,
+        name="cdp",
+        dims=[("cdp", 2048)],
+        coords=["cdp"],
+        dtype=ScalarType.INT32,
+    )
+    assert inline.metadata is None
+
+    domain = validate_variable(
+        dataset,
+        name=domain,
+        dims=[(domain, 4096)],
+        coords=[domain],
+        dtype=ScalarType.INT32,
+    )
+    assert domain.metadata is None
+
+    # Verify non-dimension coordinate variables
+    cdp_x = validate_variable(
+        dataset,
+        name="cdp_x",
+        dims=[("cdp", 2048)],
+        coords=["cdp_x"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    cdp_y = validate_variable(
+        dataset,
+        name="cdp_y",
+        dims=[("cdp", 2048)],
+        coords=["cdp_y"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+
 class TestSeismic2DPostStackTemplate:
     """Unit tests for Seismic2DPostStackTemplate."""
 
@@ -26,14 +92,13 @@ def test_configuration_depth(self) -> None:
         assert t._trace_domain == "depth"
         assert t._coord_dim_names == ["cdp"]
         assert t._dim_names == ["cdp", "depth"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
-        assert t._var_name == "StackedAmplitude"
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [1024, 1024]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         # Verify dataset attributes
         attrs = t._load_dataset_attributes()
@@ -43,6 +108,8 @@ def test_configuration_depth(self) -> None:
             "processingStage": "post-stack",
         }
 
+        assert t.trace_variable_name == "amplitude"
+
     def test_configuration_time(self) -> None:
         """Test configuration of Seismic2DPostStackTemplate with time domain."""
         t = Seismic2DPostStackTemplate("time")
@@ -51,35 +118,44 @@ def test_configuration_time(self) -> None:
         assert t._trace_domain == "time"
         assert t._coord_dim_names == ["cdp"]
         assert t._dim_names == ["cdp", "time"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
-        assert t._var_name == "StackedAmplitude"
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [1024, 1024]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
+
+        # Verify dataset attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
+            "surveyDimensionality": "2D",
+            "ensembleType": "line",
+            "processingStage": "post-stack",
+        }
+        assert t.trace_variable_name == "amplitude"
 
     def test_domain_case_handling(self) -> None:
         """Test that domain parameter handles different cases correctly."""
         # Test uppercase
         t1 = Seismic2DPostStackTemplate("ELEVATION")
         assert t1._trace_domain == "elevation"
-        assert t1.get_name() == "PostStack2DElevation"
+        assert t1.name == "PostStack2DElevation"
 
         # Test mixed case
         t2 = Seismic2DPostStackTemplate("elevatioN")
         assert t2._trace_domain == "elevation"
-        assert t2.get_name() == "PostStack2DElevation"
+        assert t2.name == "PostStack2DElevation"
 
-    def test_build_dataset_depth(self) -> None:
+    def test_build_dataset_depth(self, structured_headers: StructuredType) -> None:
         """Test building a complete 2D depth dataset."""
         t = Seismic2DPostStackTemplate("depth")
 
         dataset = t.build_dataset(
             "Seismic 2D Depth Line 001",
             sizes=[2048, 4096],
-            coord_units=[_UNIT_METER, _UNIT_METER],  # Both coordinates and depth in meters
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         # Verify dataset metadata
@@ -88,48 +164,29 @@ def test_build_dataset_depth(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "line"
         assert dataset.metadata.attributes["processingStage"] == "post-stack"
 
-        # 2 coordinate variables + 1 data variable = 5 variables
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        cdp_x = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("cdp", 2048)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        cdp_y = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("cdp", 2048)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "depth")
 
         # Verify seismic variable
         seismic = validate_variable(
             dataset,
-            name="StackedAmplitude",
+            name="amplitude",
             dims=[("cdp", 2048), ("depth", 4096)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(seismic.metadata.chunk_grid, RegularChunkGrid)
         assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1024, 1024]
         assert seismic.metadata.stats_v1 is None
 
-    def test_build_dataset_time(self) -> None:
+    def test_build_dataset_time(self, structured_headers: StructuredType) -> None:
         """Test building a complete 2D time dataset."""
         t = Seismic2DPostStackTemplate("time")
 
         dataset = t.build_dataset(
             "Seismic 2D Time Line 001",
             sizes=[2048, 4096],
-            coord_units=[_UNIT_METER, _UNIT_METER],  # Coordinates in meters, time in seconds
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         # Verify dataset metadata
@@ -138,34 +195,14 @@ def test_build_dataset_time(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "line"
         assert dataset.metadata.attributes["processingStage"] == "post-stack"
 
-        # Verify variables count
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        v = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("cdp", 2048)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert v.metadata.units_v1.length == LengthUnitEnum.METER
-
-        v = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("cdp", 2048)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert v.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "time")
 
         # Verify seismic variable
         v = validate_variable(
             dataset,
-            name="StackedAmplitude",
+            name="amplitude",
             dims=[("cdp", 2048), ("time", 4096)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(v.metadata.chunk_grid, RegularChunkGrid)
@@ -182,11 +219,10 @@ def test_time_vs_depth_comparison(self) -> None:
         assert depth_template._trace_domain == "depth"
 
         # Different names
-        assert time_template.get_name() == "PostStack2DTime"
-        assert depth_template.get_name() == "PostStack2DDepth"
+        assert time_template.name == "PostStack2DTime"
+        assert depth_template.name == "PostStack2DDepth"
 
         # Same other attributes
         assert time_template._coord_dim_names == depth_template._coord_dim_names
         assert time_template._coord_names == depth_template._coord_names
-        assert time_template._var_name == depth_template._var_name
         assert time_template._var_chunk_shape == depth_template._var_chunk_shape
diff --git a/tests/unit/v1/templates/test_seismic_3d_poststack.py b/tests/unit/v1/templates/test_seismic_3d_poststack.py
index 3e205b0ae..8f4c1ad0e 100644
--- a/tests/unit/v1/templates/test_seismic_3d_poststack.py
+++ b/tests/unit/v1/templates/test_seismic_3d_poststack.py
@@ -5,6 +5,8 @@
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
@@ -16,6 +18,79 @@
 _UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
 
 
+def _validate_coordinates_headers_trace_mask(
+    dataset: Dataset, headers: StructuredType, domain: str
+) -> None:
+    """Validate the coordinate, headers, trace_mask variables in the dataset."""
+    # Verify variables
+    # 3 dim coords + 2 non-dim coords + 1 data + 1 trace mask + 1 headers = 7 variables
+    assert len(dataset.variables) == 8
+
+    # Verify trace headers
+    validate_variable(
+        dataset,
+        name="headers",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=headers,
+    )
+
+    validate_variable(
+        dataset,
+        name="trace_mask",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=ScalarType.BOOL,
+    )
+
+    # Verify dimension coordinate variables
+    inline = validate_variable(
+        dataset,
+        name="inline",
+        dims=[("inline", 256)],
+        coords=["inline"],
+        dtype=ScalarType.INT32,
+    )
+    assert inline.metadata is None
+
+    crossline = validate_variable(
+        dataset,
+        name="crossline",
+        dims=[("crossline", 512)],
+        coords=["crossline"],
+        dtype=ScalarType.INT32,
+    )
+    assert crossline.metadata is None
+
+    domain = validate_variable(
+        dataset,
+        name=domain,
+        dims=[(domain, 1024)],
+        coords=[domain],
+        dtype=ScalarType.INT32,
+    )
+    assert domain.metadata is None
+
+    # Verify non-dimension coordinate variables
+    cdp_x = validate_variable(
+        dataset,
+        name="cdp_x",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp_x"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    cdp_y = validate_variable(
+        dataset,
+        name="cdp_y",
+        dims=[("inline", 256), ("crossline", 512)],
+        coords=["cdp_y"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+
 class TestSeismic3DPostStackTemplate:
     """Unit tests for Seismic3DPostStackTemplate."""
 
@@ -27,21 +102,22 @@ def test_configuration_depth(self) -> None:
         assert t._trace_domain == "depth"  # Domain should be lowercased
         assert t._coord_dim_names == ["inline", "crossline"]
         assert t._dim_names == ["inline", "crossline", "depth"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [128, 128, 128]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
-        assert t._load_dataset_attributes().attributes == {
+        # Verify dataset attributes
+        attrs = t._load_dataset_attributes()
+        assert attrs.attributes == {
             "surveyDimensionality": "3D",
             "ensembleType": "line",
             "processingStage": "post-stack",
         }
-
-        assert t.get_name() == "PostStack3DDepth"
+        assert t.trace_variable_name == "amplitude"
 
     def test_configuration_time(self) -> None:
         """Unit tests for Seismic3DPostStackTemplate with time domain."""
@@ -51,13 +127,13 @@ def test_configuration_time(self) -> None:
         assert t._trace_domain == "time"  # Domain should be lowercased
         assert t._coord_dim_names == ["inline", "crossline"]
         assert t._dim_names == ["inline", "crossline", "time"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [128, 128, 128]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         assert t._load_dataset_attributes().attributes == {
             "surveyDimensionality": "3D",
@@ -65,27 +141,30 @@ def test_configuration_time(self) -> None:
             "processingStage": "post-stack",
         }
 
-        assert t.get_name() == "PostStack3DTime"
+        assert t.name == "PostStack3DTime"
 
     def test_domain_case_handling(self) -> None:
         """Test that domain parameter handles different cases correctly."""
         # Test uppercase
         t1 = Seismic3DPostStackTemplate("ELEVATION")
         assert t1._trace_domain == "elevation"
-        assert t1.get_name() == "PostStack3DElevation"
+        assert t1.name == "PostStack3DElevation"
 
         # Test mixed case
         t2 = Seismic3DPostStackTemplate("elevatioN")
         assert t2._trace_domain == "elevation"
-        assert t2.get_name() == "PostStack3DElevation"
+        assert t2.name == "PostStack3DElevation"
 
-    def test_build_dataset_depth(self) -> None:
+    def test_build_dataset_depth(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPostStackTemplate build with depth domain."""
         t = Seismic3DPostStackTemplate(domain="depth")
 
-        assert t.get_name() == "PostStack3DDepth"
+        assert t.name == "PostStack3DDepth"
         dataset = t.build_dataset(
-            "Seismic 3D", sizes=[256, 512, 1024], coord_units=[_UNIT_METER, _UNIT_METER]
+            "Seismic 3D",
+            sizes=[256, 512, 1024],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "Seismic 3D"
@@ -93,35 +172,14 @@ def test_build_dataset_depth(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "line"
         assert dataset.metadata.attributes["processingStage"] == "post-stack"
 
-        # Verify variables
-        # 2 coordinate variables + 1 data variables = 3 variables
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        cdp_x = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("inline", 256), ("crossline", 512)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        cdp_y = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("inline", 256), ("crossline", 512)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "depth")
 
         # Verify seismic variable
         seismic = validate_variable(
             dataset,
-            name="StackedAmplitude",
+            name="amplitude",
             dims=[("inline", 256), ("crossline", 512), ("depth", 1024)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(seismic.compressor, Blosc)
@@ -130,13 +188,16 @@ def test_build_dataset_depth(self) -> None:
         assert seismic.metadata.chunk_grid.configuration.chunk_shape == [128, 128, 128]
         assert seismic.metadata.stats_v1 is None
 
-    def test_build_dataset_time(self) -> None:
+    def test_build_dataset_time(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPostStackTimeTemplate build with time domain."""
         t = Seismic3DPostStackTemplate(domain="time")
 
-        assert t.get_name() == "PostStack3DTime"
+        assert t.name == "PostStack3DTime"
         dataset = t.build_dataset(
-            "Seismic 3D", sizes=[256, 512, 1024], coord_units=[_UNIT_METER, _UNIT_METER]
+            "Seismic 3D",
+            sizes=[256, 512, 1024],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "Seismic 3D"
@@ -144,35 +205,14 @@ def test_build_dataset_time(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "line"
         assert dataset.metadata.attributes["processingStage"] == "post-stack"
 
-        # Verify variables
-        # 2 coordinate variables + 1 data variables = 3 variables
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        cdp_x = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("inline", 256), ("crossline", 512)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        cdp_y = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("inline", 256), ("crossline", 512)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "time")
 
         # Verify seismic variable
         seismic = validate_variable(
             dataset,
-            name="StackedAmplitude",
+            name="amplitude",
             dims=[("inline", 256), ("crossline", 512), ("time", 1024)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(seismic.compressor, Blosc)
diff --git a/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py b/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
index 4f936940e..07af31837 100644
--- a/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
+++ b/tests/unit/v1/templates/test_seismic_3d_prestack_cdp.py
@@ -5,6 +5,8 @@
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.templates.seismic_3d_prestack_cdp import Seismic3DPreStackCDPTemplate
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
@@ -16,6 +18,88 @@
 _UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
 
 
+def validate_coordinates_headers_trace_mask(
+    dataset: Dataset, headers: StructuredType, domain: str
+) -> None:
+    """A helper method to validate coordinates, headers, and trace mask."""
+    # Verify variables
+    # 4 dim coords + 2 non-dim coords + 1 data + 1 trace mask + 1 headers = 8 variables
+    assert len(dataset.variables) == 9
+
+    # Verify trace headers
+    validate_variable(
+        dataset,
+        name="headers",
+        dims=[("inline", 512), ("crossline", 768), ("offset", 36)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=headers,
+    )
+
+    validate_variable(
+        dataset,
+        name="trace_mask",
+        dims=[("inline", 512), ("crossline", 768), ("offset", 36)],
+        coords=["cdp_x", "cdp_y"],
+        dtype=ScalarType.BOOL,
+    )
+
+    # Verify dimension coordinate variables
+    inline = validate_variable(
+        dataset,
+        name="inline",
+        dims=[("inline", 512)],
+        coords=["inline"],
+        dtype=ScalarType.INT32,
+    )
+    assert inline.metadata is None
+
+    crossline = validate_variable(
+        dataset,
+        name="crossline",
+        dims=[("crossline", 768)],
+        coords=["crossline"],
+        dtype=ScalarType.INT32,
+    )
+    assert crossline.metadata is None
+
+    crossline = validate_variable(
+        dataset,
+        name="offset",
+        dims=[("offset", 36)],
+        coords=["offset"],
+        dtype=ScalarType.INT32,
+    )
+    assert crossline.metadata is None
+
+    domain = validate_variable(
+        dataset,
+        name=domain,
+        dims=[(domain, 1536)],
+        coords=[domain],
+        dtype=ScalarType.INT32,
+    )
+    assert domain.metadata is None
+
+    # Verify non-dimension coordinate variables
+    cdp_x = validate_variable(
+        dataset,
+        name="cdp_x",
+        dims=[("inline", 512), ("crossline", 768), ("offset", 36)],
+        coords=["cdp_x"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    cdp_y = validate_variable(
+        dataset,
+        name="cdp_y",
+        dims=[("inline", 512), ("crossline", 768), ("offset", 36)],
+        coords=["cdp_y"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+
 class TestSeismic3DPreStackCDPTemplate:
     """Unit tests for Seismic3DPreStackCDPTemplate."""
 
@@ -25,16 +109,15 @@ def test_configuration_depth(self) -> None:
 
         # Template attributes for prestack CDP
         assert t._trace_domain == "depth"
-        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._coord_dim_names == ["inline", "crossline", "offset"]
         assert t._dim_names == ["inline", "crossline", "offset", "depth"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
-        assert t._var_name == "AmplitudeCDP"
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [1, 1, 512, 4096]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         # Verify prestack CDP attributes
         attrs = t._load_dataset_attributes()
@@ -43,8 +126,7 @@ def test_configuration_depth(self) -> None:
             "ensembleType": "cdp",
             "processingStage": "pre-stack",
         }
-
-        assert t.get_name() == "PreStackCdpGathers3DDepth"
+        assert t.trace_variable_name == "amplitude"
 
     def test_configuration_time(self) -> None:
         """Unit tests for Seismic3DPreStackCDPTemplate."""
@@ -52,16 +134,15 @@ def test_configuration_time(self) -> None:
 
         # Template attributes for prestack CDP
         assert t._trace_domain == "time"
-        assert t._coord_dim_names == ["inline", "crossline"]
+        assert t._coord_dim_names == ["inline", "crossline", "offset"]
         assert t._dim_names == ["inline", "crossline", "offset", "time"]
-        assert t._coord_names == ["cdp-x", "cdp-y"]
-        assert t._var_name == "AmplitudeCDP"
+        assert t._coord_names == ["cdp_x", "cdp_y"]
         assert t._var_chunk_shape == [1, 1, 512, 4096]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         # Verify prestack CDP attributes
         attrs = t._load_dataset_attributes()
@@ -71,29 +152,30 @@ def test_configuration_time(self) -> None:
             "processingStage": "pre-stack",
         }
 
-        assert t.get_name() == "PreStackCdpGathers3DTime"
+        assert t.name == "PreStackCdpGathers3DTime"
 
     def test_domain_case_handling(self) -> None:
         """Test that domain parameter handles different cases correctly."""
         # Test uppercase
         t1 = Seismic3DPreStackCDPTemplate("ELEVATION")
         assert t1._trace_domain == "elevation"
-        assert t1.get_name() == "PreStackCdpGathers3DElevation"
+        assert t1.name == "PreStackCdpGathers3DElevation"
 
         # Test mixed case
         t2 = Seismic3DPreStackCDPTemplate("elevatioN")
         assert t2._trace_domain == "elevation"
-        assert t2.get_name() == "PreStackCdpGathers3DElevation"
+        assert t2.name == "PreStackCdpGathers3DElevation"
 
-    def test_build_dataset_depth(self) -> None:
+    def test_build_dataset_depth(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPreStackCDPDepthTemplate build with depth domain."""
         t = Seismic3DPreStackCDPTemplate(domain="depth")
 
-        assert t.get_name() == "PreStackCdpGathers3DDepth"
+        assert t.name == "PreStackCdpGathers3DDepth"
         dataset = t.build_dataset(
             "North Sea 3D Prestack Depth",
             sizes=[512, 768, 36, 1536],
-            coord_units=[_UNIT_METER, _UNIT_METER],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "North Sea 3D Prestack Depth"
@@ -101,35 +183,14 @@ def test_build_dataset_depth(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "cdp"
         assert dataset.metadata.attributes["processingStage"] == "pre-stack"
 
-        # Verify variables
-        # 2 coordinate variables + 1 data variable = 3 variables
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        cdp_x = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("inline", 512), ("crossline", 768)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        cdp_y = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("inline", 512), ("crossline", 768)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+        validate_coordinates_headers_trace_mask(dataset, structured_headers, "depth")
 
         # Verify seismic variable (prestack depth data)
         seismic = validate_variable(
             dataset,
-            name="AmplitudeCDP",
+            name="amplitude",
             dims=[("inline", 512), ("crossline", 768), ("offset", 36), ("depth", 1536)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(seismic.compressor, Blosc)
@@ -138,15 +199,16 @@ def test_build_dataset_depth(self) -> None:
         assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
         assert seismic.metadata.stats_v1 is None
 
-    def test_build_dataset_time(self) -> None:
+    def test_build_dataset_time(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPreStackCDPTimeTemplate build with time domain."""
         t = Seismic3DPreStackCDPTemplate(domain="time")
 
-        assert t.get_name() == "PreStackCdpGathers3DTime"
+        assert t.name == "PreStackCdpGathers3DTime"
         dataset = t.build_dataset(
             "Santos Basin 3D Prestack",
             sizes=[512, 768, 36, 1536],
-            coord_units=[_UNIT_METER, _UNIT_METER],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "Santos Basin 3D Prestack"
@@ -154,35 +216,14 @@ def test_build_dataset_time(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "cdp"
         assert dataset.metadata.attributes["processingStage"] == "pre-stack"
 
-        # Verify variables
-        # 2 coordinate variables + 1 data variable = 3 variables
-        assert len(dataset.variables) == 3
-
-        # Verify coordinate variables
-        cdp_x = validate_variable(
-            dataset,
-            name="cdp-x",
-            dims=[("inline", 512), ("crossline", 768)],
-            coords=["cdp-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        cdp_y = validate_variable(
-            dataset,
-            name="cdp-y",
-            dims=[("inline", 512), ("crossline", 768)],
-            coords=["cdp-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
+        validate_coordinates_headers_trace_mask(dataset, structured_headers, "time")
 
         # Verify seismic variable (prestack time data)
         seismic = validate_variable(
             dataset,
-            name="AmplitudeCDP",
+            name="amplitude",
             dims=[("inline", 512), ("crossline", 768), ("offset", 36), ("time", 1536)],
-            coords=["cdp-x", "cdp-y"],
+            coords=["cdp_x", "cdp_y"],
             dtype=ScalarType.FLOAT32,
         )
         assert isinstance(seismic.compressor, Blosc)
diff --git a/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py b/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
index eea66cf6b..5d4b51c29 100644
--- a/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
+++ b/tests/unit/v1/templates/test_seismic_3d_prestack_shot.py
@@ -5,6 +5,8 @@
 from mdio.schemas.chunk_grid import RegularChunkGrid
 from mdio.schemas.compressors import Blosc
 from mdio.schemas.dtype import ScalarType
+from mdio.schemas.dtype import StructuredType
+from mdio.schemas.v1.dataset import Dataset
 from mdio.schemas.v1.templates.seismic_3d_prestack_shot import Seismic3DPreStackShotTemplate
 from mdio.schemas.v1.units import AllUnits
 from mdio.schemas.v1.units import LengthUnitEnum
@@ -16,6 +18,114 @@
 _UNIT_SECOND = AllUnits(units_v1=TimeUnitModel(time=TimeUnitEnum.SECOND))
 
 
+def _validate_coordinates_headers_trace_mask(
+    dataset: Dataset, headers: StructuredType, domain: str
+) -> None:
+    """Validate the coordinate, headers, trace_mask variables in the dataset."""
+    # Verify variables
+    # 4 dim coords + 5 non-dim coords + 1 data + 1 trace mask + 1 headers = 12 variables
+    assert len(dataset.variables) == 12
+
+    # Verify trace headers
+    validate_variable(
+        dataset,
+        name="headers",
+        dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+        coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
+        dtype=headers,
+    )
+
+    validate_variable(
+        dataset,
+        name="trace_mask",
+        dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+        coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
+        dtype=ScalarType.BOOL,
+    )
+
+    # Verify dimension coordinate variables
+    inline = validate_variable(
+        dataset,
+        name="shot_point",
+        dims=[("shot_point", 256)],
+        coords=["shot_point"],
+        dtype=ScalarType.INT32,
+    )
+    assert inline.metadata is None
+
+    crossline = validate_variable(
+        dataset,
+        name="cable",
+        dims=[("cable", 512)],
+        coords=["cable"],
+        dtype=ScalarType.INT32,
+    )
+    assert crossline.metadata is None
+
+    crossline = validate_variable(
+        dataset,
+        name="channel",
+        dims=[("channel", 24)],
+        coords=["channel"],
+        dtype=ScalarType.INT32,
+    )
+    assert crossline.metadata is None
+
+    domain = validate_variable(
+        dataset,
+        name=domain,
+        dims=[(domain, 2048)],
+        coords=[domain],
+        dtype=ScalarType.INT32,
+    )
+    assert domain.metadata is None
+
+    # Verify non-dimension coordinate variables
+    validate_variable(
+        dataset,
+        name="gun",
+        dims=[("shot_point", 256)],
+        coords=["gun"],
+        dtype=ScalarType.UINT8,
+    )
+
+    shot_x = validate_variable(
+        dataset,
+        name="shot-x",
+        dims=[("shot_point", 256)],
+        coords=["shot-x"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert shot_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    shot_y = validate_variable(
+        dataset,
+        name="shot-y",
+        dims=[("shot_point", 256)],
+        coords=["shot-y"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert shot_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+    receiver_x = validate_variable(
+        dataset,
+        name="receiver-x",
+        dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+        coords=["receiver-x"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert receiver_x.metadata.units_v1.length == LengthUnitEnum.METER
+
+    receiver_y = validate_variable(
+        dataset,
+        name="receiver-y",
+        dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
+        coords=["receiver-y"],
+        dtype=ScalarType.FLOAT64,
+    )
+    assert receiver_y.metadata.units_v1.length == LengthUnitEnum.METER
+
+
 class TestSeismic3DPreStackShotTemplate:
     """Unit tests for Seismic3DPreStackShotTemplate."""
 
@@ -25,16 +135,15 @@ def test_configuration_depth(self) -> None:
 
         # Template attributes for prestack shot
         assert t._trace_domain == "depth"
-        assert t._coord_dim_names == []
+        assert t._coord_dim_names == ["shot_point", "cable", "channel"]
         assert t._dim_names == ["shot_point", "cable", "channel", "depth"]
         assert t._coord_names == ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
-        assert t._var_name == "AmplitudeShot"
         assert t._var_chunk_shape == [1, 1, 512, 4096]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         # Verify prestack shot attributes
         attrs = t._load_dataset_attributes()
@@ -43,8 +152,7 @@ def test_configuration_depth(self) -> None:
             "ensembleType": "shot",
             "processingStage": "pre-stack",
         }
-
-        assert t.get_name() == "PreStackShotGathers3DDepth"
+        assert t.trace_variable_name == "amplitude"
 
     def test_configuration_time(self) -> None:
         """Unit tests for Seismic3DPreStackShotTemplate in time domain."""
@@ -52,16 +160,15 @@ def test_configuration_time(self) -> None:
 
         # Template attributes for prestack shot
         assert t._trace_domain == "time"
-        assert t._coord_dim_names == []
+        assert t._coord_dim_names == ["shot_point", "cable", "channel"]
         assert t._dim_names == ["shot_point", "cable", "channel", "time"]
         assert t._coord_names == ["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"]
-        assert t._var_name == "AmplitudeShot"
         assert t._var_chunk_shape == [1, 1, 512, 4096]
 
         # Variables instantiated when build_dataset() is called
         assert t._builder is None
         assert t._dim_sizes == []
-        assert t._coord_units == []
+        assert t._horizontal_coord_unit is None
 
         # Verify prestack shot attributes
         attrs = t._load_dataset_attributes()
@@ -71,29 +178,30 @@ def test_configuration_time(self) -> None:
             "processingStage": "pre-stack",
         }
 
-        assert t.get_name() == "PreStackShotGathers3DTime"
+        assert t.name == "PreStackShotGathers3DTime"
 
     def test_domain_case_handling(self) -> None:
         """Test that domain parameter handles different cases correctly."""
         # Test uppercase
         t1 = Seismic3DPreStackShotTemplate("ELEVATION")
         assert t1._trace_domain == "elevation"
-        assert t1.get_name() == "PreStackShotGathers3DElevation"
+        assert t1.name == "PreStackShotGathers3DElevation"
 
         # Test mixed case
         t2 = Seismic3DPreStackShotTemplate("elevatioN")
         assert t2._trace_domain == "elevation"
-        assert t2.get_name() == "PreStackShotGathers3DElevation"
+        assert t2.name == "PreStackShotGathers3DElevation"
 
-    def test_build_dataset_depth(self) -> None:
+    def test_build_dataset_depth(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPreStackShotTemplate build in depth domain."""
         t = Seismic3DPreStackShotTemplate(domain="depth")
 
-        assert t.get_name() == "PreStackShotGathers3DDepth"
+        assert t.name == "PreStackShotGathers3DDepth"
         dataset = t.build_dataset(
             "Gulf of Mexico 3D Shot Depth",
             sizes=[256, 512, 24, 2048],
-            coord_units=[_UNIT_METER, _UNIT_METER],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "Gulf of Mexico 3D Shot Depth"
@@ -101,59 +209,12 @@ def test_build_dataset_depth(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "shot"
         assert dataset.metadata.attributes["processingStage"] == "pre-stack"
 
-        # Verify variables (including dimension variables)
-        # 5 coordinate variables + 1 data variable = 6 variables
-        assert len(dataset.variables) == 6
-
-        # Verify coordinate variables
-        validate_variable(
-            dataset,
-            name="gun",
-            dims=[("shot_point", 256)],
-            coords=["gun"],
-            dtype=ScalarType.UINT8,
-        )
-
-        shot_x = validate_variable(
-            dataset,
-            name="shot-x",
-            dims=[("shot_point", 256)],
-            coords=["shot-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert shot_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        shot_y = validate_variable(
-            dataset,
-            name="shot-y",
-            dims=[("shot_point", 256)],
-            coords=["shot-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert shot_y.metadata.units_v1.length == LengthUnitEnum.METER
-
-        receiver_x = validate_variable(
-            dataset,
-            name="receiver-x",
-            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
-            coords=["receiver-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert receiver_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        receiver_y = validate_variable(
-            dataset,
-            name="receiver-y",
-            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
-            coords=["receiver-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert receiver_y.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "depth")
 
         # Verify seismic variable (prestack shot depth data)
         seismic = validate_variable(
             dataset,
-            name="AmplitudeShot",
+            name="amplitude",
             dims=[("shot_point", 256), ("cable", 512), ("channel", 24), ("depth", 2048)],
             coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
             dtype=ScalarType.FLOAT32,
@@ -164,15 +225,16 @@ def test_build_dataset_depth(self) -> None:
         assert seismic.metadata.chunk_grid.configuration.chunk_shape == [1, 1, 512, 4096]
         assert seismic.metadata.stats_v1 is None
 
-    def test_build_dataset_time(self) -> None:
+    def test_build_dataset_time(self, structured_headers: StructuredType) -> None:
         """Unit tests for Seismic3DPreStackShotTemplate build in time domain."""
         t = Seismic3DPreStackShotTemplate(domain="time")
 
-        assert t.get_name() == "PreStackShotGathers3DTime"
+        assert t.name == "PreStackShotGathers3DTime"
         dataset = t.build_dataset(
             "North Sea 3D Shot Time",
             sizes=[256, 512, 24, 2048],
-            coord_units=[_UNIT_METER, _UNIT_METER],
+            horizontal_coord_unit=_UNIT_METER,
+            headers=structured_headers,
         )
 
         assert dataset.metadata.name == "North Sea 3D Shot Time"
@@ -180,59 +242,12 @@ def test_build_dataset_time(self) -> None:
         assert dataset.metadata.attributes["ensembleType"] == "shot"
         assert dataset.metadata.attributes["processingStage"] == "pre-stack"
 
-        # Verify variables (including dimension variables)
-        # 5 coordinate variables + 1 data variable = 6 variables
-        assert len(dataset.variables) == 6
-
-        # Verify coordinate variables
-        validate_variable(
-            dataset,
-            name="gun",
-            dims=[("shot_point", 256)],
-            coords=["gun"],
-            dtype=ScalarType.UINT8,
-        )
-
-        shot_x = validate_variable(
-            dataset,
-            name="shot-x",
-            dims=[("shot_point", 256)],
-            coords=["shot-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert shot_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        shot_y = validate_variable(
-            dataset,
-            name="shot-y",
-            dims=[("shot_point", 256)],
-            coords=["shot-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert shot_y.metadata.units_v1.length == LengthUnitEnum.METER
-
-        receiver_x = validate_variable(
-            dataset,
-            name="receiver-x",
-            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
-            coords=["receiver-x"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert receiver_x.metadata.units_v1.length == LengthUnitEnum.METER
-
-        receiver_y = validate_variable(
-            dataset,
-            name="receiver-y",
-            dims=[("shot_point", 256), ("cable", 512), ("channel", 24)],
-            coords=["receiver-y"],
-            dtype=ScalarType.FLOAT64,
-        )
-        assert receiver_y.metadata.units_v1.length == LengthUnitEnum.METER
+        _validate_coordinates_headers_trace_mask(dataset, structured_headers, "time")
 
         # Verify seismic variable (prestack shot time data)
         seismic = validate_variable(
             dataset,
-            name="AmplitudeShot",
+            name="amplitude",
             dims=[("shot_point", 256), ("cable", 512), ("channel", 24), ("time", 2048)],
             coords=["gun", "shot-x", "shot-y", "receiver-x", "receiver-y"],
             dtype=ScalarType.FLOAT32,
diff --git a/tests/unit/v1/templates/test_seismic_templates.py b/tests/unit/v1/templates/test_seismic_templates.py
index 46d2245a2..c0b487099 100644
--- a/tests/unit/v1/templates/test_seismic_templates.py
+++ b/tests/unit/v1/templates/test_seismic_templates.py
@@ -1,6 +1,10 @@
 """Unit tests for concrete seismic dataset template implementations."""
 
 # Import all concrete template classes
+from tests.unit.v1.helpers import validate_variable
+from tests.unit.v1.templates.test_seismic_2d_poststack import _UNIT_METER
+
+from mdio.schemas.dtype import ScalarType
 from mdio.schemas.v1.templates.abstract_dataset_template import AbstractDatasetTemplate
 from mdio.schemas.v1.templates.seismic_2d_poststack import Seismic2DPostStackTemplate
 from mdio.schemas.v1.templates.seismic_3d_poststack import Seismic3DPostStackTemplate
@@ -11,31 +15,64 @@
 class TestSeismicTemplates:
     """Test cases for Seismic2DPostStackTemplate."""
 
+    def test_custom_data_variable_name(self) -> None:
+        """Test get_data_variable_name with custom names."""
+
+        # Define a template with a custom data variable name 'velocity'
+        class Velocity2DPostStackTemplate(Seismic2DPostStackTemplate):
+            def __init__(self, domain: str):
+                super().__init__(domain=domain)
+
+            @property
+            def _trace_variable_name(self) -> str:
+                return "velocity"
+
+            @property
+            def _name(self) -> str:
+                return f"Velocity2D{self._trace_domain.capitalize()}"
+
+        t = Velocity2DPostStackTemplate("depth")
+        assert t.name == "Velocity2DDepth"
+        assert t.trace_variable_name == "velocity"
+
+        dataset = t.build_dataset(
+            "Velocity 2D Depth Line 001", sizes=[2048, 4096], horizontal_coord_unit=_UNIT_METER
+        )
+
+        # Verify velocity variable
+        validate_variable(
+            dataset,
+            name="velocity",
+            dims=[("cdp", 2048), ("depth", 4096)],
+            coords=["cdp_x", "cdp_y"],
+            dtype=ScalarType.FLOAT32,
+        )
+
     def test_get_name_time(self) -> None:
         """Test get_name with domain."""
         time_template = Seismic2DPostStackTemplate("time")
         dpth_template = Seismic2DPostStackTemplate("depth")
 
-        assert time_template.get_name() == "PostStack2DTime"
-        assert dpth_template.get_name() == "PostStack2DDepth"
+        assert time_template.name == "PostStack2DTime"
+        assert dpth_template.name == "PostStack2DDepth"
 
         time_template = Seismic3DPostStackTemplate("time")
         dpth_template = Seismic3DPostStackTemplate("depth")
 
-        assert time_template.get_name() == "PostStack3DTime"
-        assert dpth_template.get_name() == "PostStack3DDepth"
+        assert time_template.name == "PostStack3DTime"
+        assert dpth_template.name == "PostStack3DDepth"
 
         time_template = Seismic3DPreStackCDPTemplate("time")
         dpth_template = Seismic3DPreStackCDPTemplate("depth")
 
-        assert time_template.get_name() == "PreStackCdpGathers3DTime"
-        assert dpth_template.get_name() == "PreStackCdpGathers3DDepth"
+        assert time_template.name == "PreStackCdpGathers3DTime"
+        assert dpth_template.name == "PreStackCdpGathers3DDepth"
 
         time_template = Seismic3DPreStackShotTemplate("time")
         dpth_template = Seismic3DPreStackShotTemplate("depth")
 
-        assert time_template.get_name() == "PreStackShotGathers3DTime"
-        assert dpth_template.get_name() == "PreStackShotGathers3DDepth"
+        assert time_template.name == "PreStackShotGathers3DTime"
+        assert dpth_template.name == "PreStackShotGathers3DDepth"
 
     def test_all_templates_inherit_from_abstract(self) -> None:
         """Test that all concrete templates inherit from AbstractDatasetTemplate."""
@@ -52,8 +89,13 @@ def test_all_templates_inherit_from_abstract(self) -> None:
 
         for template in templates:
             assert isinstance(template, AbstractDatasetTemplate)
-            assert hasattr(template, "get_name")
+            # That each template has the required properties and methods
+            assert hasattr(template, "name")
+            assert hasattr(template, "trace_variable_name")
+            assert hasattr(template, "trace_domain")
+            assert hasattr(template, "dimension_names")
+            assert hasattr(template, "coordinate_names")
             assert hasattr(template, "build_dataset")
 
-        names = [template.get_name() for template in templates]
+        names = [template.name for template in templates]
         assert len(names) == len(set(names)), f"Duplicate template names found: {names}"
diff --git a/tests/unit/v1/templates/test_template_registry.py b/tests/unit/v1/templates/test_template_registry.py
index a40f5021c..e8c61fe6a 100644
--- a/tests/unit/v1/templates/test_template_registry.py
+++ b/tests/unit/v1/templates/test_template_registry.py
@@ -21,7 +21,8 @@ def __init__(self, name: str):
         super().__init__()
         self.template_name = name
 
-    def _get_name(self) -> str:
+    @property
+    def _name(self) -> str:
         return self.template_name
 
     def _load_dataset_attributes(self) -> None:
diff --git a/tests/unit/v1/test_dataset_builder_add_coordinate.py b/tests/unit/v1/test_dataset_builder_add_coordinate.py
index 9d5f123b5..5ad4c70c0 100644
--- a/tests/unit/v1/test_dataset_builder_add_coordinate.py
+++ b/tests/unit/v1/test_dataset_builder_add_coordinate.py
@@ -38,9 +38,9 @@ def test_add_coordinate() -> None:
     with pytest.raises(ValueError, match="'name' must be a non-empty string"):
         builder.add_coordinate("", dimensions=["speed"], data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("cdp-x", dimensions=None, data_type=ScalarType.FLOAT32)
+        builder.add_coordinate("cdp_x", dimensions=None, data_type=ScalarType.FLOAT32)
     with pytest.raises(ValueError, match="'dimensions' must be a non-empty list"):
-        builder.add_coordinate("cdp-x", dimensions=[], data_type=ScalarType.FLOAT32)
+        builder.add_coordinate("cdp_x", dimensions=[], data_type=ScalarType.FLOAT32)
 
     # Add a variable using non-existent dimensions
     msg = "Pre-existing dimension named 'xline' is not found"
@@ -51,14 +51,14 @@ def test_add_coordinate() -> None:
 
     # Validate state transition
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        "cdp_x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
     )
     validate_builder(builder, _BuilderState.HAS_COORDINATES, n_dims=2, n_coords=1, n_var=1)
     validate_variable(
         builder,
-        name="cdp-x",
+        name="cdp_x",
         dims=[("inline", 100), ("crossline", 200)],
-        coords=["cdp-x"],
+        coords=["cdp_x"],
         dtype=ScalarType.FLOAT32,
     )
 
@@ -66,7 +66,7 @@ def test_add_coordinate() -> None:
     msg = "Adding coordinate with the same name twice is not allowed"
     with pytest.raises(ValueError, match=msg):
         builder.add_coordinate(
-            "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+            "cdp_x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
         )
 
 
diff --git a/tests/unit/v1/test_dataset_builder_add_variable.py b/tests/unit/v1/test_dataset_builder_add_variable.py
index 2db85f3ca..9bcb97ff1 100644
--- a/tests/unit/v1/test_dataset_builder_add_variable.py
+++ b/tests/unit/v1/test_dataset_builder_add_variable.py
@@ -115,17 +115,17 @@ def test_add_variable_with_coords() -> None:
 
     # Add non-dim coordinates (e.g., 2D coordinates)
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        "cdp_x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
     )
     builder.add_coordinate(
-        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
+        "cdp_y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT32
     )
 
     # Add a variable with pre-defined dimension and non-dimension coordinates
     builder.add_variable(
         "ampl2",
         dimensions=["inline", "crossline", "depth"],
-        coordinates=["inline", "crossline", "cdp-x", "cdp-y"],
+        coordinates=["inline", "crossline", "cdp_x", "cdp_y"],
         data_type=ScalarType.FLOAT32,
     )
     validate_builder(builder, _BuilderState.HAS_VARIABLES, n_dims=3, n_coords=4, n_var=6)
@@ -133,7 +133,7 @@ def test_add_variable_with_coords() -> None:
         builder,
         "ampl2",
         dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-        coords=["inline", "crossline", "cdp-x", "cdp-y"],
+        coords=["inline", "crossline", "cdp_x", "cdp_y"],
         dtype=ScalarType.FLOAT32,
     )
 
@@ -186,10 +186,10 @@ def test_add_variable_full_parameters() -> None:
     builder.add_coordinate("depth", dimensions=["depth"], data_type=ScalarType.UINT32)
     # Add coordinates before we can add a data variable
     builder.add_coordinate(
-        "cdp-x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+        "cdp_x", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
     )
     builder.add_coordinate(
-        "cdp-y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
+        "cdp_y", dimensions=["inline", "crossline"], data_type=ScalarType.FLOAT64
     )
 
     # Add data variable with full parameters
@@ -199,7 +199,7 @@ def test_add_variable_full_parameters() -> None:
         dimensions=["inline", "crossline", "depth"],
         data_type=ScalarType.FLOAT32,
         compressor=Blosc(algorithm="zstd"),
-        coordinates=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coordinates=["inline", "crossline", "depth", "cdp_x", "cdp_y"],
         metadata_info=[
             AllUnits(units_v1=LengthUnitModel(length=LengthUnitEnum.FOOT)),
             UserAttributes(attributes={"MGA": 51, "UnitSystem": "Imperial"}),
@@ -223,7 +223,7 @@ def test_add_variable_full_parameters() -> None:
         builder,
         "ampl",
         dims=[("inline", 100), ("crossline", 200), ("depth", 300)],
-        coords=["inline", "crossline", "depth", "cdp-x", "cdp-y"],
+        coords=["inline", "crossline", "depth", "cdp_x", "cdp_y"],
         dtype=ScalarType.FLOAT32,
     )
     assert v.long_name == "Amplitude (dimensionless)"
diff --git a/tests/unit/v1/test_dataset_builder_build.py b/tests/unit/v1/test_dataset_builder_build.py
index 43b87fb5f..a5d817e1f 100644
--- a/tests/unit/v1/test_dataset_builder_build.py
+++ b/tests/unit/v1/test_dataset_builder_build.py
@@ -78,18 +78,18 @@ def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR09
     # Verify coordinate variables
     cdp_x = validate_variable(
         dataset,
-        name="cdp-x",
+        name="cdp_x",
         dims=[("inline", 256), ("crossline", 512)],
-        coords=["cdp-x"],
+        coords=["cdp_x"],
         dtype=ScalarType.FLOAT32,
     )
     assert cdp_x.metadata.units_v1.length == LengthUnitEnum.METER
 
     cdp_y = validate_variable(
         dataset,
-        name="cdp-y",
+        name="cdp_y",
         dims=[("inline", 256), ("crossline", 512)],
-        coords=["cdp-y"],
+        coords=["cdp_y"],
         dtype=ScalarType.FLOAT32,
     )
     assert cdp_y.metadata.units_v1.length == LengthUnitEnum.METER
@@ -99,7 +99,7 @@ def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR09
         dataset,
         name="image",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
-        coords=["cdp-x", "cdp-y"],
+        coords=["cdp_x", "cdp_y"],
         dtype=ScalarType.FLOAT32,
     )
     assert image.metadata.units_v1 is None  # No units defined for image
@@ -111,7 +111,7 @@ def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR09
         dataset,
         name="velocity",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
-        coords=["cdp-x", "cdp-y"],
+        coords=["cdp_x", "cdp_y"],
         dtype=ScalarType.FLOAT16,
     )
     assert velocity.compressor is None
@@ -122,7 +122,7 @@ def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR09
         dataset,
         name="image_inline",
         dims=[("inline", 256), ("crossline", 512), ("depth", 384)],
-        coords=["cdp-x", "cdp-y"],
+        coords=["cdp_x", "cdp_y"],
         dtype=ScalarType.FLOAT32,
     )
     assert image_inline.long_name == "inline optimized version of 3d_stack"
@@ -133,17 +133,17 @@ def test_build_seismic_poststack_3d_acceptance_dataset() -> None:  # noqa: PLR09
     headers = next(v for v in dataset.variables if v.name == "image_headers")
     assert isinstance(headers.data_type, StructuredType)
     assert len(headers.data_type.fields) == 4
-    assert headers.data_type.fields[0].name == "cdp-x"
+    assert headers.data_type.fields[0].name == "cdp_x"
 
     headers = validate_variable(
         dataset,
         name="image_headers",
         dims=[("inline", 256), ("crossline", 512)],
-        coords=["cdp-x", "cdp-y"],
+        coords=["cdp_x", "cdp_y"],
         dtype=StructuredType(
             fields=[
-                StructuredField(name="cdp-x", format=ScalarType.INT32),
-                StructuredField(name="cdp-y", format=ScalarType.INT32),
+                StructuredField(name="cdp_x", format=ScalarType.INT32),
+                StructuredField(name="cdp_y", format=ScalarType.INT32),
                 StructuredField(name="elevation", format=ScalarType.FLOAT16),
                 StructuredField(name="some_scalar", format=ScalarType.FLOAT16),
             ]
diff --git a/tests/unit/v1/test_dataset_serializer.py b/tests/unit/v1/test_dataset_serializer.py
index 9db2deee1..4ad2040e3 100644
--- a/tests/unit/v1/test_dataset_serializer.py
+++ b/tests/unit/v1/test_dataset_serializer.py
@@ -28,11 +28,9 @@
 from mdio.schemas.v1.dataset_serializer import _get_coord_names
 from mdio.schemas.v1.dataset_serializer import _get_dimension_names
 from mdio.schemas.v1.dataset_serializer import _get_fill_value
-from mdio.schemas.v1.dataset_serializer import _get_np_datatype
 from mdio.schemas.v1.dataset_serializer import _get_zarr_chunks
 from mdio.schemas.v1.dataset_serializer import _get_zarr_shape
 from mdio.schemas.v1.dataset_serializer import to_xarray_dataset
-from mdio.schemas.v1.dataset_serializer import to_zarr
 from mdio.schemas.v1.variable import Coordinate
 from mdio.schemas.v1.variable import Variable
 
@@ -56,7 +54,7 @@
 from mdio.schemas.compressors import ZFPMode as mdio_ZFPMode
 
 
-def test__get_all_named_dimensions() -> None:
+def test_get_all_named_dimensions() -> None:
     """Test _get_all_named_dimensions function."""
     dim1 = NamedDimension(name="inline", size=100)
     dim2 = NamedDimension(name="crossline", size=200)
@@ -85,7 +83,7 @@ def test__get_all_named_dimensions() -> None:
     assert set(all_dims) == {"inline", "crossline", "depth"}
 
 
-def test__get_dimension_names() -> None:
+def test_get_dimension_names() -> None:
     """Test _get_dimension_names function with various dimension types."""
     dim1 = NamedDimension(name="inline", size=100)
     dim2 = NamedDimension(name="crossline", size=200)
@@ -110,7 +108,7 @@ def test__get_dimension_names() -> None:
     # NOTE: mixing NamedDimension and string dimensions is not allowed by the Variable schema
 
 
-def test__get_coord_names() -> None:
+def test_get_coord_names() -> None:
     """Comprehensive test for _get_coord_names function covering all scenarios."""
     dim1 = NamedDimension(name="inline", size=100)
     dim2 = NamedDimension(name="crossline", size=200)
@@ -140,57 +138,7 @@ def test__get_coord_names() -> None:
     # Variable schema
 
 
-def test__get_np_datatype() -> None:
-    """Comprehensive test for _get_np_datatype function."""
-    # Test 1: ScalarType cases - all supported scalar types
-    scalar_type_tests = [
-        (ScalarType.FLOAT32, "float32"),
-        (ScalarType.FLOAT64, "float64"),
-        (ScalarType.INT8, "int8"),
-        (ScalarType.INT16, "int16"),
-        (ScalarType.INT32, "int32"),
-        (ScalarType.INT64, "int64"),
-        (ScalarType.UINT8, "uint8"),
-        (ScalarType.UINT16, "uint16"),
-        (ScalarType.UINT32, "uint32"),
-        (ScalarType.UINT64, "uint64"),
-        (ScalarType.COMPLEX64, "complex64"),
-        (ScalarType.COMPLEX128, "complex128"),
-        (ScalarType.BOOL, "bool"),
-    ]
-    err = "Expected ScalarType or StructuredType, got 'str'"
-    with pytest.raises(ValueError, match=err):
-        _get_np_datatype("parameter of invalid type")
-
-    for scalar_type, expected_numpy_type in scalar_type_tests:
-        result = _get_np_datatype(scalar_type)
-        expected = np_dtype(expected_numpy_type)
-
-        assert result == expected
-        assert isinstance(result, np_dtype)
-        assert result.name == expected.name
-
-    # Test 2: StructuredType with multiple fields
-    multi_fields = [
-        StructuredField(name="x", format=ScalarType.FLOAT64),
-        StructuredField(name="y", format=ScalarType.FLOAT64),
-        StructuredField(name="z", format=ScalarType.FLOAT64),
-        StructuredField(name="id", format=ScalarType.INT32),
-        StructuredField(name="valid", format=ScalarType.BOOL),
-    ]
-    structured_multi = StructuredType(fields=multi_fields)
-    result_multi = _get_np_datatype(structured_multi)
-    expected_multi = np_dtype(
-        [("x", "float64"), ("y", "float64"), ("z", "float64"), ("id", "int32"), ("valid", "bool")]
-    )
-
-    assert result_multi == expected_multi
-    assert isinstance(result_multi, np_dtype)
-    assert len(result_multi.names) == 5
-    assert set(result_multi.names) == {"x", "y", "z", "id", "valid"}
-
-
-def test__get_zarr_shape() -> None:
+def test_get_zarr_shape() -> None:
     """Test for _get_zarr_shape function."""
     d1 = NamedDimension(name="inline", size=100)
     d2 = NamedDimension(name="crossline", size=200)
@@ -215,7 +163,7 @@ def test__get_zarr_shape() -> None:
     assert _get_zarr_shape(v2, all_named_dims) == (100, 200, 300)
 
 
-def test__get_zarr_chunks() -> None:
+def test_get_zarr_chunks() -> None:
     """Test for _get_zarr_chunks function."""
     d1 = NamedDimension(name="inline", size=100)
     d2 = NamedDimension(name="crossline", size=200)
@@ -241,7 +189,7 @@ def test__get_zarr_chunks() -> None:
     assert _get_zarr_chunks(v, all_named_dims=[d1, d2, d3]) == (100, 200, 300)
 
 
-def test__get_fill_value() -> None:
+def test_get_fill_value() -> None:
     """Test for _get_fill_value function."""
     # Test 1: ScalarType cases - should return values from fill_value_map
     scalar_types = [
@@ -282,8 +230,8 @@ def test__get_fill_value() -> None:
         assert np_isnan(val.imag)
 
     # Test 2: StructuredType
-    f1 = StructuredField(name="cdp-x", format=ScalarType.INT32)
-    f2 = StructuredField(name="cdp-y", format=ScalarType.INT32)
+    f1 = StructuredField(name="cdp_x", format=ScalarType.INT32)
+    f2 = StructuredField(name="cdp_y", format=ScalarType.INT32)
     f3 = StructuredField(name="elevation", format=ScalarType.FLOAT16)
     f4 = StructuredField(name="some_scalar", format=ScalarType.FLOAT16)
     structured_type = StructuredType(fields=[f1, f2, f3, f4])
@@ -291,7 +239,7 @@ def test__get_fill_value() -> None:
     expected = np_array(
         (0, 0, 0.0, 0.0),
         dtype=np_dtype(
-            [("cdp-x", "<i4"), ("cdp-y", "<i4"), ("elevation", "<f2"), ("some_scalar", "<f2")]
+            [("cdp_x", "<i4"), ("cdp_y", "<i4"), ("elevation", "<f2"), ("some_scalar", "<f2")]
         ),
     )
     result = _get_fill_value(structured_type)
@@ -310,7 +258,7 @@ def test__get_fill_value() -> None:
     assert result_none_input is None
 
 
-def test__convert_compressor() -> None:
+def test_convert_compressor() -> None:
     """Simple test for _convert_compressor function covering basic scenarios."""
     # Test 1: None input - should return None
     result_none = _convert_compressor(None)
@@ -393,7 +341,7 @@ def test_to_xarray_dataset(tmp_path: Path) -> None:
     xr_ds = to_xarray_dataset(dataset)
 
     file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
-    to_zarr(xr_ds, file_path, mode="w")
+    xr_ds.to_zarr(store=file_path, mode="w", zarr_format=2, compute=False)
 
 
 def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path: Path) -> None:
@@ -403,14 +351,17 @@ def test_seismic_poststack_3d_acceptance_to_xarray_dataset(tmp_path: Path) -> No
     xr_ds = to_xarray_dataset(dataset)
 
     file_path = output_path(tmp_path, f"{xr_ds.attrs['name']}", debugging=False)
-    to_zarr(xr_ds, file_path, mode="w")
+    xr_ds.to_zarr(store=file_path, mode="w", zarr_format=2, compute=False)
+
 
+@pytest.mark.skip(reason="Bug reproducer for the issue 582")
+def test_buf_reproducer_dask_to_zarr(tmp_path: Path) -> None:
+    """Bug reproducer for the issue https://github.com/TGSAI/mdio-python/issues/582."""
+    # TODO(Dmitriy Repin): Remove this test after the bug is fixed
+    # https://github.com/TGSAI/mdio-python/issues/582
 
-@pytest.mark.skip(reason="Issues serializing dask arrays of structured types to dask.")
-def test_to_zarr_dask(tmp_path: Path) -> None:
-    """Test writing XArray dataset with data as dask array to Zarr."""
     # Create a data type and the fill value
-    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype = np_dtype([("inline", "int32"), ("cdp_x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)
 
     # Use '_FillValue' instead of 'fill_value'
@@ -437,7 +388,7 @@ def test_to_zarr_from_zarr_zeros_1(tmp_path: Path) -> None:
     Set encoding in as DataArray attributes
     """
     # Create a data type and the fill value
-    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype = np_dtype([("inline", "int32"), ("cdp_x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)
 
     # Use '_FillValue' instead of 'fill_value'
@@ -463,7 +414,7 @@ def test_to_zarr_from_zarr_zeros_2(tmp_path: Path) -> None:
     Set encoding in the to_zar method
     """
     # Create a data type and the fill value
-    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype = np_dtype([("inline", "int32"), ("cdp_x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)
 
     # Use '_FillValue' instead of 'fill_value'
@@ -487,7 +438,7 @@ def test_to_zarr_from_zarr_zeros_2(tmp_path: Path) -> None:
 def test_to_zarr_from_np(tmp_path: Path) -> None:
     """Test writing XArray dataset with data as NumPy array to Zarr."""
     # Create a data type and the fill value
-    dtype = np_dtype([("inline", "int32"), ("cdp-x", "float64")])
+    dtype = np_dtype([("inline", "int32"), ("cdp_x", "float64")])
     dtype_fill_value = np_zeros((), dtype=dtype)
 
     # Use '_FillValue' instead of 'fill_value'
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index 9ecc1d26f..9bb4ff529 100644
--- a/uv.lock
+++ b/uv.lock
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