How to use the feast.value_type.ValueType function in feast

for item in value
                    ]
                )
            )

    # Handle scalar types below
    else:
        if pd.isnull(value):
            return ProtoValue()
        elif feast_value_type == ValueType.INT32:
            return ProtoValue(int32_val=int(value))
        elif feast_value_type == ValueType.INT64:
            return ProtoValue(int64_val=int(value))
        elif feast_value_type == ValueType.FLOAT:
            return ProtoValue(float_val=float(value))
        elif feast_value_type == ValueType.DOUBLE:
            assert type(value) is float or np.float64
            return ProtoValue(double_val=value)
        elif feast_value_type == ValueType.STRING:
            return ProtoValue(string_val=str(value))
        elif feast_value_type == ValueType.BYTES:
            assert type(value) is bytes
            return ProtoValue(bytes_val=value)
        elif feast_value_type == ValueType.BOOL:
            assert type(value) is bool
            return ProtoValue(bool_val=value)

    raise Exception(f"Unsupported data type: ${str(type(value))}")

)

    # Handle scalar types below
    else:
        if pd.isnull(value):
            return ProtoValue()
        elif feast_value_type == ValueType.INT32:
            return ProtoValue(int32_val=int(value))
        elif feast_value_type == ValueType.INT64:
            return ProtoValue(int64_val=int(value))
        elif feast_value_type == ValueType.FLOAT:
            return ProtoValue(float_val=float(value))
        elif feast_value_type == ValueType.DOUBLE:
            assert type(value) is float or np.float64
            return ProtoValue(double_val=value)
        elif feast_value_type == ValueType.STRING:
            return ProtoValue(string_val=str(value))
        elif feast_value_type == ValueType.BYTES:
            assert type(value) is bytes
            return ProtoValue(bytes_val=value)
        elif feast_value_type == ValueType.BOOL:
            assert type(value) is bool
            return ProtoValue(bool_val=value)

    raise Exception(f"Unsupported data type: ${str(type(value))}")

val=[
                        item
                        if type(item) in [np.bytes_, bytes]
                        else _type_err(item, np.bytes_)
                        for item in value
                    ]
                )
            )

    # Handle scalar types below
    else:
        if pd.isnull(value):
            return ProtoValue()
        elif feast_value_type == ValueType.INT32:
            return ProtoValue(int32_val=int(value))
        elif feast_value_type == ValueType.INT64:
            return ProtoValue(int64_val=int(value))
        elif feast_value_type == ValueType.FLOAT:
            return ProtoValue(float_val=float(value))
        elif feast_value_type == ValueType.DOUBLE:
            assert type(value) is float or np.float64
            return ProtoValue(double_val=value)
        elif feast_value_type == ValueType.STRING:
            return ProtoValue(string_val=str(value))
        elif feast_value_type == ValueType.BYTES:
            assert type(value) is bytes
            return ProtoValue(bytes_val=value)
        elif feast_value_type == ValueType.BOOL:
            assert type(value) is bool
            return ProtoValue(bool_val=value)

    raise Exception(f"Unsupported data type: ${str(type(value))}")

"""

    type_name = type(value).__name__

    type_map = {
        "int": ValueType.INT64,
        "str": ValueType.STRING,
        "float": ValueType.DOUBLE,
        "bytes": ValueType.BYTES,
        "float64": ValueType.DOUBLE,
        "float32": ValueType.FLOAT,
        "int64": ValueType.INT64,
        "uint64": ValueType.INT64,
        "int32": ValueType.INT32,
        "uint32": ValueType.INT32,
        "uint8": ValueType.INT32,
        "int8": ValueType.INT32,
        "bool": ValueType.BOOL,
        "timedelta": ValueType.INT64,
        "datetime64[ns]": ValueType.INT64,
        "datetime64[ns, tz]": ValueType.INT64,
        "category": ValueType.STRING,
    }

    if type_name in type_map:
        return type_map[type_name]

    if type_name == "ndarray":
        if recurse:

            # Convert to list type
            list_items = pd.core.series.Series(value)

def from_proto(cls, entity_proto: EntityProto):
        """
        Creates a Feast Entity object from its Protocol Buffer representation

        Args:
            entity_proto: EntitySpec protobuf object

        Returns:
            Entity object
        """
        return cls(name=entity_proto.name, dtype=ValueType(entity_proto.value_type))

)
            )

        if feast_value_type == ValueType.BOOL_LIST:
            return ProtoValue(
                bool_list_val=BoolList(
                    val=[
                        item
                        if type(item) in [np.bool_, bool]
                        else _type_err(item, np.bool_)
                        for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.BYTES_LIST:
            return ProtoValue(
                bytes_list_val=BytesList(
                    val=[
                        item
                        if type(item) in [np.bytes_, bytes]
                        else _type_err(item, np.bytes_)
                        for item in value
                    ]
                )
            )

    # Handle scalar types below
    else:
        if pd.isnull(value):
            return ProtoValue()
        elif feast_value_type == ValueType.INT32:

for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.INT32_LIST:
            return ProtoValue(
                int32_list_val=Int32List(
                    val=[
                        item if type(item) is np.int32 else _type_err(item, np.int32)
                        for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.INT64_LIST:
            return ProtoValue(
                int64_list_val=Int64List(
                    val=[
                        item
                        if type(item) in [np.int64, np.int32]
                        else _type_err(item, np.int64)
                        for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.STRING_LIST:
            return ProtoValue(
                string_list_val=StringList(
                    val=[
                        item

# Detect list type and handle separately
    if "list" in feast_value_type.name.lower():

        if feast_value_type == ValueType.FLOAT_LIST:
            return ProtoValue(
                float_list_val=FloatList(
                    val=[
                        item
                        if type(item) in [np.float32, np.float64]
                        else _type_err(item, np.float32)
                        for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.DOUBLE_LIST:
            return ProtoValue(
                double_list_val=DoubleList(
                    val=[
                        item
                        if type(item) in [np.float64, np.float32]
                        else _type_err(item, np.float64)
                        for item in value
                    ]
                )
            )

        if feast_value_type == ValueType.INT32_LIST:
            return ProtoValue(
                int32_list_val=Int32List(
                    val=[
                        item if type(item) is np.int32 else _type_err(item, np.int32)

return ProtoValue(
                bytes_list_val=BytesList(
                    val=[
                        item
                        if type(item) in [np.bytes_, bytes]
                        else _type_err(item, np.bytes_)
                        for item in value
                    ]
                )
            )

    # Handle scalar types below
    else:
        if pd.isnull(value):
            return ProtoValue()
        elif feast_value_type == ValueType.INT32:
            return ProtoValue(int32_val=int(value))
        elif feast_value_type == ValueType.INT64:
            return ProtoValue(int64_val=int(value))
        elif feast_value_type == ValueType.FLOAT:
            return ProtoValue(float_val=float(value))
        elif feast_value_type == ValueType.DOUBLE:
            assert type(value) is float or np.float64
            return ProtoValue(double_val=value)
        elif feast_value_type == ValueType.STRING:
            return ProtoValue(string_val=str(value))
        elif feast_value_type == ValueType.BYTES:
            assert type(value) is bytes
            return ProtoValue(bytes_val=value)
        elif feast_value_type == ValueType.BOOL:
            assert type(value) is bool
            return ProtoValue(bool_val=value)

def __init__(self, name: str, dtype: ValueType):
        self._name = name
        if not isinstance(dtype, ValueType):
            raise ValueError("dtype is not a valid ValueType")
        self._dtype = dtype