Apply code formatting with ruff

Copilot · franciscojavierarceo · Copilot · commit 79d67447277f · 2026-01-23T06:44:11.000Z
Co-authored-by: franciscojavierarceo &lt;4163062+franciscojavierarceo@users.noreply.github.com&gt;
diff --git a/sdk/python/feast/feature_store.py b/sdk/python/feast/feature_store.py
@@ -303,7 +303,9 @@ def list_all_feature_views(
         Returns:
             A list of feature views.
         """
-        return self._list_all_feature_views(allow_cache, tags=tags, skip_validation=skip_validation)
+        return self._list_all_feature_views(
+            allow_cache, tags=tags, skip_validation=skip_validation
+        )
 
     def list_feature_views(
         self, allow_cache: bool = False, tags: Optional[dict[str, str]] = None
@@ -1966,7 +1968,9 @@ def _get_feature_view_and_df_for_online_write(
     ):
         feature_view_dict = {
             fv_proto.name: fv_proto
-            for fv_proto in self.list_all_feature_views(allow_registry_cache, skip_validation=skip_validation)
+            for fv_proto in self.list_all_feature_views(
+                allow_registry_cache, skip_validation=skip_validation
+            )
         }
         try:
             feature_view = feature_view_dict[feature_view_name]
diff --git a/sdk/python/feast/infra/registry/proto_registry_utils.py b/sdk/python/feast/infra/registry/proto_registry_utils.py
@@ -244,7 +244,9 @@ def list_all_feature_views(
         return (
             list_feature_views(registry_proto, project, tags)
             + list_stream_feature_views(registry_proto, project, tags)
-            + list_on_demand_feature_views(registry_proto, project, tags, skip_udf=skip_udf)
+            + list_on_demand_feature_views(
+                registry_proto, project, tags, skip_udf=skip_udf
+            )
         )
     else:
         return _list_all_feature_views_cached(registry_proto, project, tags)
@@ -303,7 +305,9 @@ def list_on_demand_feature_views(
                 on_demand_feature_view.spec.tags, tags
             ):
                 on_demand_feature_views.append(
-                    OnDemandFeatureView.from_proto(on_demand_feature_view, skip_udf=skip_udf)
+                    OnDemandFeatureView.from_proto(
+                        on_demand_feature_view, skip_udf=skip_udf
+                    )
                 )
         return on_demand_feature_views
     else:
diff --git a/sdk/python/tests/unit/test_skip_validation.py b/sdk/python/tests/unit/test_skip_validation.py
@@ -20,7 +20,9 @@
 
 from feast.feature_store import FeatureStore
 from feast.on_demand_feature_view import PandasTransformation, PythonTransformation
-from feast.protos.feast.core.Transformation_pb2 import UserDefinedFunctionV2 as UserDefinedFunctionProto
+from feast.protos.feast.core.Transformation_pb2 import (
+    UserDefinedFunctionV2 as UserDefinedFunctionProto,
+)
 
 
 def test_apply_has_skip_feature_view_validation_parameter():
@@ -93,32 +95,33 @@ def test_push_async_has_skip_validation_parameter():
 
 def test_pandas_transformation_from_proto_with_skip_udf():
     """Test that PandasTransformation.from_proto works with skip_udf=True."""
-    
+
     # Create a UDF that would reference a non-existent module
     def udf_with_missing_module(df: pd.DataFrame) -> pd.DataFrame:
         # This would normally fail if a module is missing during deserialization
         import nonexistent_module  # noqa: F401
+
         return df
-    
+
     # Serialize the UDF
     serialized_udf = dill.dumps(udf_with_missing_module)
     udf_string = "import nonexistent_module\ndef udf(df): return df"
-    
+
     # Create proto
     udf_proto = UserDefinedFunctionProto(
         name="test_udf",
         body=serialized_udf,
         body_text=udf_string,
     )
-    
+
     # Test that skip_udf=True doesn't try to deserialize the UDF
     # This would normally fail with ModuleNotFoundError
     transformation = PandasTransformation.from_proto(udf_proto, skip_udf=True)
-    
+
     # Should get a dummy transformation with identity function
     assert transformation is not None
     assert transformation.udf_string == udf_string
-    
+
     # The dummy UDF should be callable and act as identity
     test_df = pd.DataFrame({"col1": [1, 2, 3]})
     result = transformation.udf(test_df)
@@ -127,32 +130,33 @@ def udf_with_missing_module(df: pd.DataFrame) -> pd.DataFrame:
 
 def test_python_transformation_from_proto_with_skip_udf():
     """Test that PythonTransformation.from_proto works with skip_udf=True."""
-    
+
     # Create a UDF that would reference a non-existent module
     def udf_with_missing_module(features_dict):
         # This would normally fail if a module is missing during deserialization
         import nonexistent_module  # noqa: F401
+
         return features_dict
-    
+
     # Serialize the UDF
     serialized_udf = dill.dumps(udf_with_missing_module)
     udf_string = "import nonexistent_module\ndef udf(d): return d"
-    
+
     # Create proto
     udf_proto = UserDefinedFunctionProto(
         name="test_udf",
         body=serialized_udf,
         body_text=udf_string,
     )
-    
+
     # Test that skip_udf=True doesn't try to deserialize the UDF
     # This would normally fail with ModuleNotFoundError
     transformation = PythonTransformation.from_proto(udf_proto, skip_udf=True)
-    
+
     # Should get a dummy transformation with identity function
     assert transformation is not None
     assert transformation.udf_string == udf_string
-    
+
     # The dummy UDF should be callable and act as identity
     test_dict = {"col1": 1}
     result = transformation.udf(test_dict)
@@ -212,4 +216,3 @@ def test_skip_validation_use_case_documentation():
     - Different teams manage training vs. serving infrastructure
     """
     pass  # This is a documentation test
-
