chore: Reformat code

tests/system/data_sources/common_functions.py

@@ -12,19 +12,24 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+
 def null_not_null_assertions(df):
     """Standard assertions for null_not_null integration test.
     These tests use BigQuery as a set target with a mismatch of not null/nullable settings.
     All other engines are validated against BigQuery to check we get the correct status."""
     # Should be 4 columns in the Dataframe.
     assert len(df) == 4
-    match_columns = ['col_nn', 'col_nullable']
-    mismatch_columns = ['col_src_nn_trg_n', 'col_src_n_trg_nn']
-    for column_name, status in zip(df['source_column_name'], df['validation_status']):
+    match_columns = ["col_nn", "col_nullable"]
+    mismatch_columns = ["col_src_nn_trg_n", "col_src_n_trg_nn"]
+    for column_name, status in zip(df["source_column_name"], df["validation_status"]):
         assert column_name in (match_columns + mismatch_columns)
         if column_name in match_columns:
             # These columns are the same for all engines and should succeed.
-            assert status == 'success', f"Column: {column_name}, status: {status} != 'success'"
+            assert (
+                status == "success"
+            ), f"Column: {column_name}, status: {status} != 'success'"
         elif column_name in mismatch_columns:
             # These columns are the different for source and target engines and should fail.
-            assert status == 'fail', f"Column: {column_name}, status: {status} != 'fail'"
+            assert (
+                status == "fail"
+            ), f"Column: {column_name}, status: {status} != 'fail'"

third_party/ibis/ibis_teradata/datatypes.py

@@ -51,9 +51,7 @@ def __init__(self):
 
     @classmethod
     def _col_data_nullable(cls, col_data: dict) -> bool:
-        return bool(
-            col_data.get("Nullable", "Y ").startswith("Y")
-        )
+        return bool(col_data.get("Nullable", "Y ").startswith("Y"))
 
     @classmethod
     def to_ibis(cls, col_data):
@@ -92,12 +90,13 @@ def to_ibis_from_N(cls, col_data, return_ibis_type=True):
         )
         if return_ibis_type:
             # No precision or scale specified
-            if precision == -128 or scale ==-128:
+            if precision == -128 or scale == -128:
                 return dt.Decimal()
-            return dt.Decimal(precision, scale,
-                              nullable=cls._col_data_nullable(col_data))
+            return dt.Decimal(
+                precision, scale, nullable=cls._col_data_nullable(col_data)
+            )
 
-        if precision == -128 or scale ==-128:
+        if precision == -128 or scale == -128:
             return "DECIMAL"
 
         return "DECIMAL(%d, %d)" % (precision, scale)
@@ -113,8 +112,9 @@ def to_ibis_from_D(cls, col_data, return_ibis_type=True):
             )
         )
         if return_ibis_type:
-            return dt.Decimal(precision, scale,
-                              nullable=cls._col_data_nullable(col_data))
+            return dt.Decimal(
+                precision, scale, nullable=cls._col_data_nullable(col_data)
+            )
         value_type = "DECIMAL(%d, %d)" % (precision, scale)
         return value_type
 
@@ -165,7 +165,9 @@ def to_ibis_from_TS(cls, col_data, return_ibis_type=True):
     @classmethod
     def to_ibis_from_SZ(cls, col_data, return_ibis_type=True):
         if return_ibis_type:
-            return dt.timestamp(timezone="UTC", nullable=cls._col_data_nullable(col_data))
+            return dt.timestamp(
+                timezone="UTC", nullable=cls._col_data_nullable(col_data)
+            )
 
         return "TIMESTAMP"