feat: Validate schema members against polars DataType usage

dataframely/_base_schema.py

@@ -162,6 +162,19 @@ def __new__(
                     f"Did you forget to add parentheses?"
                 )
 
+            # Check for pl.DataType instance or type (e.g., pl.String() or pl.String instead of dy.String())
+            if isinstance(value, pl.DataType) or (
+                isinstance(value, type) and issubclass(value, pl.DataType)
+            ):
+                value_type = "instance" if isinstance(value, pl.DataType) else "type"
+                example = (
+                    "pl.String()" if isinstance(value, pl.DataType) else "pl.String"
+                )
+                raise TypeError(
+                    f"Schema member '{attr}' is a polars DataType {value_type}. "
+                    f"Use dataframely column types (e.g., dy.String()) instead of polars types (e.g., {example})."
+                )
+
         return cls
 
     if not TYPE_CHECKING:

tests/schema/test_base.py

@@ -125,3 +125,19 @@ def test_user_error_column_type_not_instance() -> None:
         class MySchemaWithColumnTypeNotInstance(dy.Schema):
             a = dy.Int32(nullable=False, primary_key=True)
             b = dy.Float64  # User error: Forgot parentheses!
+
+
+def test_user_error_polars_datatype_instance() -> None:
+    with pytest.raises(TypeError, match="polars DataType instance"):
+
+        class MySchemaWithPolarsDataTypeInstance(dy.Schema):
+            a = dy.Int32(nullable=False)
+            b = pl.String()  # User error: Used pl.String() instead of dy.String()
+
+
+def test_user_error_polars_datatype_type() -> None:
+    with pytest.raises(TypeError, match="polars DataType type"):
+
+        class MySchemaWithPolarsDataTypeType(dy.Schema):
+            a = dy.Int32(nullable=False)
+            b = pl.String  # User error: Used pl.String instead of dy.String()