fix: fix python format

.github/workflows/python.yml

@@ -57,7 +57,7 @@ jobs:
           workspaces: python
       - name: Install linting tools
         run: |
-          pip install ruff==0.4.1 maturin tensorflow tqdm ray[data] pyright datasets polars[pyarrow,pandas]
+          pip install ruff==0.11.2 maturin tensorflow tqdm ray[data] pyright datasets polars[pyarrow,pandas]
           pip install torch --index-url https://download.pytorch.org/whl/cpu
       - name: Lint Python
         run: |

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.4.1
+    rev: v0.11.2
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]

python/python/lance/__init__.py

@@ -159,8 +159,7 @@ def set_logger(
 
 def __warn_on_fork():
     warnings.warn(
-        "lance is not fork-safe. If you are using multiprocessing, "
-        "use spawn instead."
+        "lance is not fork-safe. If you are using multiprocessing, use spawn instead."
     )
 
 

python/python/lance/dependencies.py

@@ -191,43 +191,43 @@ def _might_be(cls: type, type_: str) -> bool:
 
 def _check_for_numpy(obj: Any, *, check_type: bool = True) -> bool:
     return _NUMPY_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "numpy"
+        cast("Hashable", type(obj) if check_type else obj), "numpy"
     )
 
 
 def _check_for_pandas(obj: Any, *, check_type: bool = True) -> bool:
     return _PANDAS_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "pandas"
+        cast("Hashable", type(obj) if check_type else obj), "pandas"
     )
 
 
 def _check_for_polars(obj: Any, *, check_type: bool = True) -> bool:
     return _POLARS_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "polars"
+        cast("Hashable", type(obj) if check_type else obj), "polars"
     )
 
 
 def _check_for_torch(obj: Any, *, check_type: bool = True) -> bool:
     return _TORCH_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "torch"
+        cast("Hashable", type(obj) if check_type else obj), "torch"
     )
 
 
 def _check_for_hugging_face(obj: Any, *, check_type: bool = True) -> bool:
     return _HUGGING_FACE_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "datasets"
+        cast("Hashable", type(obj) if check_type else obj), "datasets"
     )
 
 
 def _check_for_tensorflow(obj: Any, *, check_type: bool = True) -> bool:
     return _TENSORFLOW_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "tensorflow"
+        cast("Hashable", type(obj) if check_type else obj), "tensorflow"
     )
 
 
 def _check_for_ray(obj: Any, *, check_type: bool = True) -> bool:
     return _RAY_AVAILABLE and _might_be(
-        cast(Hashable, type(obj) if check_type else obj), "ray"
+        cast("Hashable", type(obj) if check_type else obj), "ray"
     )
 
 

python/python/lance/util.py

@@ -25,7 +25,7 @@ def _normalize_metric_type(metric_type: str) -> MetricType:
         normalized = "l2"
     if normalized not in {"l2", "dot", "cosine"}:
         raise ValueError(f"Invalid metric_type: {metric_type}")
-    return cast(MetricType, normalized)
+    return cast("MetricType", normalized)
 
 
 def sanitize_ts(ts: ts_types) -> datetime:

python/python/tests/test_scalar_index.py

@@ -222,9 +222,7 @@ def test_fixed_size_binary(tmp_path):
     ds.create_scalar_index("uuid", "BTREE")
 
     query = (
-        "uuid = arrow_cast("
-        "0x32333435323334353233343532333435, "
-        "'FixedSizeBinary(16)')"
+        "uuid = arrow_cast(0x32333435323334353233343532333435, 'FixedSizeBinary(16)')"
     )
     assert "MaterializeIndex" in ds.scanner(filter=query).explain_plan()