Method from_proto

sdk/python/feast/field.py:148–191

Creates a Field object from a protobuf representation. Args: field_proto: FieldProto protobuf object

(cls, field_proto: FieldProto)

    @classmethod
    def from_proto(cls, field_proto: FieldProto):
        """
        Creates a Field object from a protobuf representation.

        Args:
            field_proto: FieldProto protobuf object
        """
        value_type = ValueType(field_proto.value_type)
        tags = dict(field_proto.tags)
        vector_search_metric = getattr(field_proto, "vector_search_metric", "")
        vector_index = getattr(field_proto, "vector_index", False)
        vector_length = getattr(field_proto, "vector_length", 0)

        # Reconstruct Struct type from persisted schema in tags
        from feast.types import Array

        internal_tags = {STRUCT_SCHEMA_TAG, NESTED_COLLECTION_INNER_TYPE_TAG}
        dtype: FeastType
        if value_type == ValueType.STRUCT and STRUCT_SCHEMA_TAG in tags:
            dtype = _deserialize_struct_schema(tags[STRUCT_SCHEMA_TAG])
            user_tags = {k: v for k, v in tags.items() if k not in internal_tags}
        elif value_type == ValueType.STRUCT_LIST and STRUCT_SCHEMA_TAG in tags:
            inner_struct = _deserialize_struct_schema(tags[STRUCT_SCHEMA_TAG])
            dtype = Array(inner_struct)
            user_tags = {k: v for k, v in tags.items() if k not in internal_tags}
        elif (
            value_type in (ValueType.VALUE_LIST, ValueType.VALUE_SET)
            and NESTED_COLLECTION_INNER_TYPE_TAG in tags
        ):
            dtype = _str_to_feast_type(tags[NESTED_COLLECTION_INNER_TYPE_TAG])
            user_tags = {k: v for k, v in tags.items() if k not in internal_tags}
        else:
            dtype = from_value_type(value_type=value_type)
            user_tags = {k: v for k, v in tags.items() if k not in internal_tags}

        return cls(
            name=field_proto.name,
            dtype=dtype,
            tags=user_tags,
            description=field_proto.description,
            vector_index=vector_index,
            vector_length=vector_length,
            vector_search_metric=vector_search_metric,
        )

    @classmethod
    def from_feature(cls, feature: Feature):