fix: Handle numpy ndarray in Array(String) materialization

sdk/python/feast/type_map.py

@@ -863,6 +863,40 @@ def _convert_list_values_to_proto(
             ]
         raise _type_err(sample, valid_types[0])
 
+    # Arrow/Athena may deserialize array columns as numpy.ndarray with
+    # object dtype instead of plain Python lists.  Normalise every value
+    # to a Python list so that protobuf constructors accept them, and
+    # replace None elements with a type-appropriate default (protobuf
+    # repeated fields do not accept None).
+    _LIST_NONE_DEFAULTS: Dict[ValueType, Any] = {
+        ValueType.STRING_LIST: "",
+        ValueType.BYTES_LIST: b"",
+        ValueType.INT32_LIST: 0,
+        ValueType.INT64_LIST: 0,
+        ValueType.FLOAT_LIST: 0.0,
+        ValueType.DOUBLE_LIST: 0.0,
+        ValueType.BOOL_LIST: False,
+        ValueType.UNIX_TIMESTAMP_LIST: NULL_TIMESTAMP_INT_VALUE,
+        ValueType.UUID_LIST: "",
+        ValueType.TIME_UUID_LIST: "",
+        ValueType.DECIMAL_LIST: "",
+    }
+    none_default = _LIST_NONE_DEFAULTS.get(feast_value_type)
+
+    def _sanitize(value: Any) -> Any:
+        """Convert ndarray to list and replace None elements."""
+        if isinstance(value, np.ndarray):
+            value = value.tolist()
+        if isinstance(value, list) and len(value) == 0:
+            return None
+        if none_default is not None and isinstance(value, list):
+            value = [none_default if v is None else v for v in value]
+        return value
+
+    values = [_sanitize(v) if v is not None else v for v in values]
+    if sample is not None:
+        sample = _sanitize(sample)
+
     # Validate item types using shared helper
     _validate_collection_item_types(sample, valid_types, feast_value_type)
 
@@ -875,7 +909,6 @@ def _convert_list_values_to_proto(
         return _convert_bool_collection_to_proto(values, field_name, proto_type)
 
     if feast_value_type in (ValueType.UUID_LIST, ValueType.TIME_UUID_LIST):
-        # uuid.UUID objects must be converted to str for StringList proto.
         return [
             (
                 ProtoValue(
@@ -888,7 +921,6 @@ def _convert_list_values_to_proto(
         ]
 
     if feast_value_type == ValueType.DECIMAL_LIST:
-        # decimal.Decimal objects must be converted to str for StringList proto.
         return [
             (
                 ProtoValue(

sdk/python/tests/unit/test_type_map.py

@@ -1953,3 +1953,68 @@ def test_non_empty_array_treated_as_null_unix_timestamp(self):
             "non-empty array in UNIX_TIMESTAMP scalar column should produce null"
         )
         assert result[1].unix_timestamp_val == int(ts.timestamp())
+
+
+class TestNdarrayListConversion:
+    """Regression tests for https://github.com/feast-dev/feast/issues/6325
+    Arrow/Athena deserializes Array(String) columns as numpy.ndarray with
+    object dtype instead of plain Python lists.  Ensure these are converted
+    to proto without raising ValueError or TypeError.
+    """
+
+    def test_ndarray_string_list_roundtrip(self):
+        """ndarray of strings converts to STRING_LIST proto and back."""
+        values = [np.array(["tag1", "tag2"], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.STRING_LIST)
+        converted = feast_value_type_to_python_type(protos[0])
+        assert converted == ["tag1", "tag2"]
+
+    def test_ndarray_string_list_with_none_elements(self):
+        """None elements inside an ndarray are replaced with empty string."""
+        values = [np.array(["tag1", None, "tag3"], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.STRING_LIST)
+        converted = feast_value_type_to_python_type(protos[0])
+        assert converted == ["tag1", "", "tag3"]
+
+    def test_ndarray_empty_string_list(self):
+        """An empty ndarray in a list column produces an empty ProtoValue (null)."""
+        from feast.protos.feast.types.Value_pb2 import Value as ProtoValue
+
+        values = [np.array([], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.STRING_LIST)
+        assert protos[0] == ProtoValue()
+
+    def test_ndarray_string_list_mixed_batch(self):
+        """Batch with populated ndarray, None, and empty ndarray."""
+        from feast.protos.feast.types.Value_pb2 import Value as ProtoValue
+
+        values = [
+            np.array(["a", "b"], dtype=object),
+            None,
+            np.array([], dtype=object),
+        ]
+        protos = python_values_to_proto_values(values, ValueType.STRING_LIST)
+        assert feast_value_type_to_python_type(protos[0]) == ["a", "b"]
+        assert protos[1] == ProtoValue()
+        assert protos[2] == ProtoValue()
+
+    def test_ndarray_int64_list_roundtrip(self):
+        """ndarray of ints converts to INT64_LIST proto and back."""
+        values = [np.array([1, 2, 3], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.INT64_LIST)
+        converted = feast_value_type_to_python_type(protos[0])
+        assert converted == [1, 2, 3]
+
+    def test_ndarray_double_list_with_none_elements(self):
+        """None elements in a DOUBLE_LIST ndarray are replaced with 0.0."""
+        values = [np.array([1.5, None, 3.5], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.DOUBLE_LIST)
+        converted = feast_value_type_to_python_type(protos[0])
+        assert converted == [1.5, 0.0, 3.5]
+
+    def test_ndarray_bool_list_roundtrip(self):
+        """ndarray of bools converts to BOOL_LIST proto and back."""
+        values = [np.array([True, False, True], dtype=object)]
+        protos = python_values_to_proto_values(values, ValueType.BOOL_LIST)
+        converted = feast_value_type_to_python_type(protos[0])
+        assert converted == [True, False, True]