fixes

Signed-off-by: Anatoly Myachev <[email protected]>

modin/pandas/test/test_rolling.py

@@ -12,6 +12,7 @@
 # governing permissions and limitations under the License.
 
 import contextlib
+import warnings
 
 import numpy as np
 import pandas
@@ -147,7 +148,8 @@ def test_dataframe_agg(data, window, min_periods, axis):
         )
     with catch_rolling_numpy_callable_future_depr():
         pandas_res = pandas_rolled.aggregate(np.sum)
-    # TODO: with catch_rolling_numpy_callable_future_depr():
+    # FIXME: modin doesn't have warning for the case so we can't use
+    # `catch_rolling_numpy_callable_future_depr`.
     modin_res = modin_rolled.aggregate(np.sum)
     df_equals(pandas_res, modin_res)
     # TODO(https://github.com/modin-project/modin/issues/4260): Once pandas
@@ -156,7 +158,8 @@ def test_dataframe_agg(data, window, min_periods, axis):
     if axis != 1:
         with catch_rolling_numpy_callable_future_depr():
             pandas_res = pandas_rolled.aggregate([np.sum, np.mean])
-        # TODO: add with catch_rolling_numpy_callable_future_depr():
+        # FIXME: modin doesn't have warning for the case so we can't use
+        # `catch_rolling_numpy_callable_future_depr`.
         modin_res = modin_rolled.aggregate([np.sum, np.mean])
         df_equals(pandas_res, modin_res)
 
@@ -251,7 +254,8 @@ def test_dataframe_dt_index(axis, on, closed, window):
             pandas_rolled.apply(np.sum, raw=True),
         )
 
-        # TODO: add with catch_rolling_numpy_callable_future_depr():
+        # FIXME: modin doesn't have warning for the case so we can't use
+        # `catch_rolling_numpy_callable_future_depr`.
         modin_res = modin_rolled.aggregate(np.sum)
         with catch_rolling_numpy_callable_future_depr():
             pandas_res = pandas_rolled.aggregate(np.sum)
@@ -289,19 +293,28 @@ def test_series_rolling(data, window, min_periods, method, kwargs):
     modin_series, pandas_series = create_test_series(data)
     if window > len(pandas_series):
         window = len(pandas_series)
-    eval_general(
-        modin_series,
-        pandas_series,
-        lambda series: getattr(
-            series.rolling(
-                window=window,
-                min_periods=min_periods,
-                win_type=None,
-                center=True,
-            ),
-            method,
-        )(**kwargs),
-    )
+
+    # FIXME: modin doesn't have warning for the case so we can't use
+    # `catch_rolling_numpy_callable_future_depr`.
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore",
+            message=".*The provided callable.*pass .* instead.",
+            category=FutureWarning,
+        )
+        eval_general(
+            modin_series,
+            pandas_series,
+            lambda series: getattr(
+                series.rolling(
+                    window=window,
+                    min_periods=min_periods,
+                    win_type=None,
+                    center=True,
+                ),
+                method,
+            )(**kwargs),
+        )
 
 
 @pytest.mark.parametrize("data", test_data_values, ids=test_data_keys)
@@ -371,7 +384,15 @@ def test_series_dt_index(closed):
     df_equals(
         modin_rolled.apply(np.sum, raw=True), pandas_rolled.apply(np.sum, raw=True)
     )
-    df_equals(modin_rolled.aggregate(np.sum), pandas_rolled.aggregate(np.sum))
+    # FIXME: modin doesn't have warning for the case so we can't use
+    # `catch_rolling_numpy_callable_future_depr`.
+    with warnings.catch_warnings():
+        warnings.filterwarnings(
+            "ignore",
+            message=".*The provided callable.*pass .* instead.",
+            category=FutureWarning,
+        )
+        df_equals(modin_rolled.aggregate(np.sum), pandas_rolled.aggregate(np.sum))
     df_equals(modin_rolled.quantile(0.1), pandas_rolled.quantile(0.1))