updated tests

Signed-off-by: Francisco Javier Arceo <franciscojavierarceo@users.noreply.github.com>
feast-dev · franciscojavierarceo · Mar 25, 2024 · Mar 17, 2024 · Mar 17, 2024 · Mar 18, 2024
commit 5a1db096e95b9cee533147f78e693a36ec253ffb
@@ -285,6 +285,14 @@ def from_proto(cls, on_demand_feature_view_proto: OnDemandFeatureViewProto):
             transformation = OnDemandSubstraitTransformation.from_proto(
                 on_demand_feature_view_proto.spec.feature_transformation.on_demand_substrait_transformation
             )
+        elif (
+            hasattr(on_demand_feature_view_proto.spec, "user_defined_function")
+            and on_demand_feature_view_proto.spec.feature_transformation.user_defined_function.body_text
+            == ""
+        ):
+            transformation = OnDemandPandasTransformation.from_proto(
+                on_demand_feature_view_proto.spec.user_defined_function
+            )
         else:
             raise Exception("At least one transformation type needs to be provided")
 

@@ -133,3 +133,65 @@ def test_hash():
         on_demand_feature_view_5.feature_transformation
         == on_demand_feature_view_5.transformation
     )
+
+
+@pytest.mark.filterwarnings("ignore:udf and udf_string parameters are deprecated")
+def test_from_proto_backwards_compatable_udf():
+    file_source = FileSource(name="my-file-source", path="test.parquet")
+    feature_view = FeatureView(
+        name="my-feature-view",
+        entities=[],
+        schema=[
+            Field(name="feature1", dtype=Float32),
+            Field(name="feature2", dtype=Float32),
+        ],
+        source=file_source,
+    )
+    sources = [feature_view]
+    on_demand_feature_view = OnDemandFeatureView(
+        name="my-on-demand-feature-view",
+        sources=sources,
+        schema=[
+            Field(name="output1", dtype=Float32),
+            Field(name="output2", dtype=Float32),
+        ],
+        transformation=OnDemandPandasTransformation(
+            udf=udf1, udf_string="udf1 source code"
+        ),
+    )
+
+    # We need a proto with the "udf1 source code" in the user_defined_function.body_text
+    # and to populate it in feature_transformation
+    proto = on_demand_feature_view.to_proto()
+    assert (
+        on_demand_feature_view.transformation.udf_string
+        == proto.spec.feature_transformation.user_defined_function.body_text
+    )
+    # Because of the current set of code this is just confirming it is empty
+    assert proto.spec.user_defined_function.body_text == ""
+    assert proto.spec.user_defined_function.body == b""
+    assert proto.spec.user_defined_function.name == ""
+
+    # Assuming we pull it from the registry we set it to the feature_transformation proto values
+    proto.spec.user_defined_function.name = (
+        proto.spec.feature_transformation.user_defined_function.name
+    )
+    proto.spec.user_defined_function.body = (
+        proto.spec.feature_transformation.user_defined_function.body
+    )
+    proto.spec.user_defined_function.body_text = (
+        proto.spec.feature_transformation.user_defined_function.body_text
+    )
+
+    # And now we're going to null the feature_transformation proto object before reserializing the entire proto
+    # proto.spec.user_defined_function.body_text = on_demand_feature_view.transformation.udf_string
+    proto.spec.feature_transformation.user_defined_function.name = ""
+    proto.spec.feature_transformation.user_defined_function.body = b""
+    proto.spec.feature_transformation.user_defined_function.body_text = ""
+
+    # And now we expect the to get the same object back under feature_transformation
+    reserialized_proto = OnDemandFeatureView.from_proto(proto)
+    assert (
+        reserialized_proto.feature_transformation.udf_string
+        == on_demand_feature_view.feature_transformation.udf_string
+    )