creating function for create_test_df_in_defined_mode

Signed-off-by: arunjose696 <arunjose696@gmail.com>

modin/tests/pandas/native_df_mode/utils.py

@@ -10,6 +10,7 @@
 # the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
 # ANY KIND, either express or implied. See the License for the specific language
 # governing permissions and limitations under the License.
+
 from modin.config import Engine
 from modin.config.pubsub import context
 from modin.tests.pandas.utils import (
@@ -25,16 +26,14 @@ def create_test_df_in_defined_mode(
     *args, post_fn=None, backend=None, df_mode=None, **kwargs
 ):
     with context(NativeDataframeMode=df_mode):
-        return create_test_dfs(
-            *args, post_fn=None, backend=None, df_mode=None, **kwargs
-        )
+        return create_test_dfs(*args, post_fn=post_fn, backend=backend, **kwargs)
 
 
 def create_test_series_in_defined_mode(
     vals, sort=False, backend=None, df_mode=None, **kwargs
 ):
     with context(NativeDataframeMode=df_mode):
-        return create_test_series(vals, sort=False, backend=None, **kwargs)
+        return create_test_series(vals, sort=sort, backend=backend, **kwargs)
 
 
 def eval_general_interop(

modin/tests/pandas/utils.py

@@ -43,7 +43,6 @@
     Engine,
     MinColumnPartitionSize,
     MinRowPartitionSize,
-    NativeDataframeMode,
     NPartitions,
     RangePartitioning,
     TestDatasetSize,
@@ -1088,11 +1087,7 @@ def eval_io_from_str(csv_str: str, unique_filename: str, **kwargs):
 
 
 def create_test_dfs(
-    *args,
-    post_fn=None,
-    backend=None,
-    df_mode=None,
-    **kwargs,
+    *args, post_fn=None, backend=None, **kwargs
 ) -> tuple[pd.DataFrame, pandas.DataFrame]:
     if post_fn is None:
         post_fn = lambda df: (  # noqa: E731
@@ -1102,24 +1097,14 @@ def create_test_dfs(
         post_fn = lambda df: post_fn(df).convert_dtypes(  # noqa: E731
             dtype_backend=backend
         )
-    if df_mode:
-        actual_df_mode = NativeDataframeMode().get()
-        NativeDataframeMode().put(df_mode)
-    test_dfs = tuple(
+    return tuple(
         map(post_fn, [pd.DataFrame(*args, **kwargs), pandas.DataFrame(*args, **kwargs)])
     )
-    if df_mode:
-        NativeDataframeMode().put(actual_df_mode)
-
-    return test_dfs
 
 
 def create_test_series(
-    vals, sort=False, backend=None, df_mode=None, **kwargs
+    vals, sort=False, backend=None, **kwargs
 ) -> tuple[pd.Series, pandas.Series]:
-    if df_mode:
-        actual_df_mode = NativeDataframeMode().get()
-        NativeDataframeMode().put(df_mode)
     if isinstance(vals, dict):
         modin_series = pd.Series(vals[next(iter(vals.keys()))], **kwargs)
         pandas_series = pandas.Series(vals[next(iter(vals.keys()))], **kwargs)
@@ -1133,8 +1118,6 @@ def create_test_series(
     if backend is not None:
         modin_series = modin_series.convert_dtypes(dtype_backend=backend)
         pandas_series = pandas_series.convert_dtypes(dtype_backend=backend)
-    if df_mode:
-        NativeDataframeMode().put(actual_df_mode)
     return modin_series, pandas_series