From c34c825789f962495125bcdb4862ab7cc1554397 Mon Sep 17 00:00:00 2001
From: George Sittas <giwrgos.sittas@gmail.com>
Date: Wed, 5 Mar 2025 22:38:32 +0200
Subject: [PATCH] Chore: improve python model blueprint example docs

---
 docs/concepts/models/python_models.md | 40 ++++++++++++++++++++++++++-
 1 file changed, 39 insertions(+), 1 deletion(-)

diff --git a/docs/concepts/models/python_models.md b/docs/concepts/models/python_models.md
index e838f4ae00..201cb60ec6 100644
--- a/docs/concepts/models/python_models.md
+++ b/docs/concepts/models/python_models.md
@@ -327,7 +327,45 @@ Note that arguments must be specified explicitly - variables cannot be accessed
 
 ## Python model blueprinting
 
-A Python model can also serve as a template for creating multiple models, or _blueprints_, by specifying a list of key-value dicts in the `blueprints` property. Please refer to the Python-based SQL model [documentation page](./sql_models.md#Python-model-blueprinting)) for more details.
+A Python model can also serve as a template for creating multiple models, or _blueprints_, by specifying a list of key-value dicts in the `blueprints` property. In order to achieve this, the model's name must be parameterized with a variable that exists in this mapping.
+
+For instance, the following model will result into two new models, each using the corresponding mapping in the `blueprints` property:
+
+```python linenums="1"
+import typing as t
+from datetime import datetime
+
+import pandas as pd
+from sqlmesh import ExecutionContext, model
+
+@model(
+    "@{customer}.some_table",
+    kind="FULL",
+    blueprints=[
+        {"customer": "customer1", "field_a": "x", "field_b": "y"},
+        {"customer": "customer2", "field_a": "z", "field_b": "w"},
+    ],
+    columns={
+        "field_a": "text",
+        "field_b": "text",
+        "customer": "text",
+    },
+)
+def entrypoint(
+    context: ExecutionContext,
+    start: datetime,
+    end: datetime,
+    execution_time: datetime,
+    **kwargs: t.Any,
+) -> pd.DataFrame:
+    return pd.DataFrame(
+        {
+            "field_a": [context.var("field_a")],
+            "field_b": [context.var("field_b")],
+            "customer": [context.var("customer")],
+        }
+    )
+```
 
 ## Examples
 ### Basic