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fix: Fix STRING type handling in on-demand feature views by ntkathole · Pull Request #5669 · feast-dev/feast · GitHub

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fix: Fix STRING type handling in on-demand feature views #5669

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Merged
franciscojavierarceo merged 1 commit into from
Oct 15, 2025
+21 −14
Conversation 4 Commits 1 Checks 17 Files changed 2
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fix: Fix STRING type handling in on-demand feature views #5669

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10 changes: 10 additions & 0 deletions sdk/python/feast/type_map.py
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Original file line number Diff line number Diff line change
Expand Up @@ -172,6 +172,16 @@ def python_type_to_feast_value_type(
if type_name in type_map:
return type_map[type_name]

# Handle pandas "object" dtype by inspecting the actual value
if type_name == "object" and value is not None:
# Check the actual type of the value
actual_type = type(value).__name__.lower()
if actual_type == "str":
return ValueType.STRING
# If it's a different type wrapped in object, try to infer from the value
elif actual_type in type_map:
return type_map[actual_type]

if isinstance(value, np.ndarray) and str(value.dtype) in type_map:
item_type = type_map[str(value.dtype)]
return ValueType[item_type.name + "_LIST"]
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25 changes: 11 additions & 14 deletions sdk/python/tests/unit/infra/test_inference_unit_tests.py
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Original file line number Diff line number Diff line change
Expand Up @@ -96,29 +96,27 @@ def python_native_test_view(input_dict: dict[str, Any]) -> dict[str, Any]:

python_native_test_view.infer_features()


def test_on_demand_features_invalid_type_inference():
# Create Feature Views
date_request = RequestSource(
name="date_request",
schema=[Field(name="some_date", dtype=UnixTimestamp)],
)

@on_demand_feature_view(
sources=[date_request],
schema=[
Field(name="output", dtype=UnixTimestamp),
Field(name="object_output", dtype=String),
],
)
def invalid_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
def object_string_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
data = pd.DataFrame()
data["output"] = features_df["some_date"]
data["object_output"] = features_df["some_date"].astype(str)
return data

with pytest.raises(ValueError, match="Value with native type object"):
invalid_test_view.infer_features()
object_string_test_view.infer_features()


def test_on_demand_features_invalid_type_inference():

franciscojavierarceo Oct 15, 2025

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Choose a reason Spam Abuse Off Topic Outdated Duplicate Resolved Low Quality

if this is invalid, shouldn't it raise?

ntkathole Oct 15, 2025

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Choose a reason Spam Abuse Off Topic Outdated Duplicate Resolved Low Quality

it's a negative test.

ntkathole Oct 15, 2025

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Choose a reason Spam Abuse Off Topic Outdated Duplicate Resolved Low Quality

There is with pytest.raises() sections which catch exceptions raised when mode is mismatched or feature is missing

franciscojavierarceo Oct 15, 2025

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Choose a reason Spam Abuse Off Topic Outdated Duplicate Resolved Low Quality

ooh nice i see on line 138, thank you.
date_request = RequestSource(
name="date_request",
schema=[Field(name="some_date", dtype=UnixTimestamp)],
)

@on_demand_feature_view(
schema=[
Expand Down Expand Up @@ -184,14 +182,13 @@ def test_view(features_df: pd.DataFrame) -> pd.DataFrame:
Field(name="object_output", dtype=String),
],
)
def invalid_test_view(features_df: pd.DataFrame) -> pd.DataFrame:
def object_string_view(features_df: pd.DataFrame) -> pd.DataFrame:
data = pd.DataFrame()
data["output"] = features_df["some_date"]
data["object_output"] = features_df["some_date"].astype(str)
return data

with pytest.raises(ValueError, match="Value with native type object"):
invalid_test_view.infer_features()
object_string_view.infer_features()

@on_demand_feature_view(
sources=[date_request],
Expand Down
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