def get_column_spec(
cls,
native_type: Optional[str],
source: utils.ColumnTypeSource = utils.ColumnTypeSource.GET_TABLE,
column_type_mappings: Tuple[
Tuple[
Pattern[str],
Union[TypeEngine, Callable[[Match[str]], TypeEngine]],
GenericDataType,
],
...,
] = column_type_mappings,
) -> Union[ColumnSpec, None]:
"""
Converts native database type to sqlalchemy column type.
:param native_type: Native database typee
:param source: Type coming from the database table or cursor description
:return: ColumnSpec object
"""
col_types = cls.get_sqla_column_type(
native_type, column_type_mappings=column_type_mappings
)
if col_types:
column_type, generic_type = col_types
# wrap temporal types in custom type that supports literal binding
# using datetimes
if generic_type == GenericDataType.TEMPORAL:
column_type = literal_dttm_type_factory(
type(column_type), cls, native_type or ""
)
is_dttm = generic_type == GenericDataType.TEMPORAL
return ColumnSpec(
sqla_type=column_type, generic_type=generic_type, is_dttm=is_dttm
)
return None
def test_literal_dttm_type_factory():
orig_type = DateTime()
new_type = literal_dttm_type_factory(
orig_type, PostgresEngineSpec, "TIMESTAMP", db_extra={}
)
assert type(new_type).__name__ == "TemporalWrapperType"
assert str(new_type) == str(orig_type)
