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feat: Override the udf name when provided as input to an on demand transformation #5094

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Merged
franciscojavierarceo merged 5 commits into from
Feb 25, 2025
Merged

feat: Override the udf name when provided as input to an on demand transformation #5094

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2beaf6c
allow setting name w/ udf
blaketastic2 Feb 25, 2025
f885266
Merge branch 'feast-dev:master' into master
blaketastic2 Feb 25, 2025
92a8a58
refactor based on PR review
blaketastic2 Feb 25, 2025
61d3b2a
removed comments
blaketastic2 Feb 25, 2025
90fa9e0
pr comments
blaketastic2 Feb 25, 2025
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4 changes: 2 additions & 2 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -202,7 +202,7 @@ The list below contains the functionality that contributors are planning to deve
* [x] Python Client
* [x] [Python feature server](https://docs.feast.dev/reference/feature-servers/python-feature-server)
* [x] [Java feature server (alpha)](https://github.com/feast-dev/feast/blob/master/infra/charts/feast/README.md)
* [x] [Go feature server (alpha)](https://github.com/feast-dev/feast/blob/master/go/README.md)
* [x] [Go feature server (alpha)](https://docs.feast.dev/reference/feature-servers/go-feature-server)
* **Data Quality Management (See [RFC](https://docs.google.com/document/d/110F72d4NTv80p35wDSONxhhPBqWRwbZXG4f9mNEMd98/edit))**
* [x] Data profiling and validation (Great Expectations)
* **Feature Discovery and Governance**
Expand Down Expand Up @@ -249,4 +249,4 @@ Thanks goes to these incredible people:

<a href="https://github.com/feast-dev/feast/graphs/contributors">
<img src="https://contrib.rocks/image?repo=feast-dev/feast" />
</a>
</a>
4 changes: 3 additions & 1 deletion sdk/python/feast/on_demand_feature_view.py
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Expand Up @@ -722,6 +722,7 @@ def get_requested_odfvs(

def on_demand_feature_view(
*,
name: Optional[str] = None,
entities: Optional[List[Entity]] = None,
schema: list[Field],
sources: list[
Expand All @@ -742,6 +743,7 @@ def on_demand_feature_view(
Creates an OnDemandFeatureView object with the given user function as udf.

Args:
name (optional): The name of the on demand feature view. If not provided, the name will be the name of the user function.
entities (Optional): The list of names of entities that this feature view is associated with.
schema: The list of features in the output of the on demand feature view, after
the transformation has been applied.
Expand Down Expand Up @@ -791,7 +793,7 @@ def decorator(user_function):
transformation = SubstraitTransformation.from_ibis(user_function, sources)

on_demand_feature_view_obj = OnDemandFeatureView(
name=user_function.__name__,
name=name if name is not None else user_function.__name__,
sources=sources,
schema=schema,
feature_transformation=transformation,
Expand Down
63 changes: 63 additions & 0 deletions sdk/python/tests/unit/test_on_demand_feature_view.py
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Expand Up @@ -24,6 +24,7 @@
OnDemandFeatureView,
PandasTransformation,
PythonTransformation,
on_demand_feature_view,
)
from feast.types import Float32

Expand Down Expand Up @@ -356,3 +357,65 @@ def test_on_demand_feature_view_stored_writes():
assert transformed_output["output3"] is not None and isinstance(
transformed_output["output3"], datetime.datetime
)


def test_function_call_syntax():
CUSTOM_FUNCTION_NAME = "custom-function-name"
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]

def transform_features(features_df: pd.DataFrame) -> pd.DataFrame:
df = pd.DataFrame()
df["output1"] = features_df["feature1"]
df["output2"] = features_df["feature2"]
return df

odfv = on_demand_feature_view(
sources=sources,
schema=[
Field(name="output1", dtype=Float32),
Field(name="output2", dtype=Float32),
],
)(transform_features)

assert odfv.name == transform_features.__name__
assert isinstance(odfv, OnDemandFeatureView)

proto = odfv.to_proto()
assert proto.spec.name == transform_features.__name__

deserialized = OnDemandFeatureView.from_proto(proto)
assert deserialized.name == transform_features.__name__

def another_transform(features_df: pd.DataFrame) -> pd.DataFrame:
df = pd.DataFrame()
df["output1"] = features_df["feature1"]
df["output2"] = features_df["feature2"]
return df

odfv_custom = on_demand_feature_view(
name=CUSTOM_FUNCTION_NAME,
sources=sources,
schema=[
Field(name="output1", dtype=Float32),
Field(name="output2", dtype=Float32),
],
)(another_transform)

assert odfv_custom.name == CUSTOM_FUNCTION_NAME
assert isinstance(odfv_custom, OnDemandFeatureView)

proto = odfv_custom.to_proto()
assert proto.spec.name == CUSTOM_FUNCTION_NAME

deserialized = OnDemandFeatureView.from_proto(proto)
assert deserialized.name == CUSTOM_FUNCTION_NAME
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