fix: OnDemandFeatureView type inference for array types

[alexmirrington]

What and Why

OnDemandFeatureView.feature_transformation.infer_features should be able to infer features from python types for all supported feast data types, for all transformation backends. This PR passes values to python_type_to_feast_value_type so that list types can be inferred correctly.

Tests

• Unit tests passing in CI for all Python versions on my fork.
• Tested against a local project by patching PandasTransformation.infer_features, e.g.

from feast.transformation.pandas_transformation import PandasTransformation

def __patched_infer_features(
    self, random_input: dict[str, list[Any]]
) -> list[Field]:
    df = pd.DataFrame.from_dict(random_input)
    output_df: pd.DataFrame = self.transform(df)
    return [
        Field(
            name=f,
            dtype=from_value_type(
                python_type_to_feast_value_type(
                    f, value=output_df[f].tolist()[0], type_name=str(dt)
                )
            ),
        )
        for f, dt in zip(output_df.columns, output_df.dtypes)
    ]

PandasTransformation.infer_features = __patched_infer_features

Note to reviewers If you can point me to where I could add some feature repository tests to catch any regressions in the future that would be great 🙏

Fixes

Fixes #4308