revised testing to resolve CI errors v2

Author: veljanin

pandas/tests/frame/methods/test_convert_dtypes.py

@@ -3,6 +3,8 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
+
 import pandas as pd
 import pandas._testing as tm
 
@@ -35,7 +37,7 @@ def test_convert_empty(self):
         empty_df = pd.DataFrame()
         tm.assert_frame_equal(empty_df, empty_df.convert_dtypes())
 
-    @tm.skip_if_no("pyarrow")
+    @td.skip_if_no("pyarrow")
     def test_convert_empty_categorical_to_pyarrow(self):
         # GH#59934
         df = pd.DataFrame(
@@ -51,11 +53,9 @@ def test_convert_empty_categorical_to_pyarrow(self):
         assert converted.A.dtype == "category", "Dtype in column A is not 'category'"
         assert converted.B.dtype == "category", "Dtype in column B is not 'category'"
         assert converted.A.cat.categories.empty, "Categories in column A are not empty"
-        assert converted.B.cat.categories.__contains__(
-            "B1"
-        ) and converted.B.cat.categories.__contains__(
-            "B2"
-        ), "Categories in column B doesn't contain adequate categories"
+        assert converted.B.cat.categories.isin(
+            ["B1", "B2"]
+        ).all(), "Categories in column B doesn't contain adequate categories"
 
     def test_convert_dtypes_retain_column_names(self):
         # GH#41435

pandas/tests/series/methods/test_convert_dtypes.py

@@ -4,6 +4,7 @@
 import pytest
 
 from pandas._libs import lib
+import pandas.util._test_decorators as td
 
 import pandas as pd
 import pandas._testing as tm
@@ -298,7 +299,7 @@ def test_convert_dtypes_pyarrow_null(self):
         expected = pd.Series([None, None], dtype=pd.ArrowDtype(pa.null()))
         tm.assert_series_equal(result, expected)
 
-    @tm.skip_if_no("pyarrow")
+    @td.skip_if_no("pyarrow")
     def test_convert_empty_categorical_to_pyarrow(self):
         # GH#59934
         ser1 = pd.Series(pd.Categorical([None] * 5))
@@ -311,8 +312,6 @@ def test_convert_empty_categorical_to_pyarrow(self):
 
         ser2 = pd.Series(pd.Categorical([None] * 5, categories=["S1", "S2"]))
         converted2 = ser2.convert_dtypes(dtype_backend="pyarrow")
-        assert converted2.cat.categories.__contains__(
-            "S1"
-        ) and converted2.cat.categories.__contains__(
-            "S2"
-        ), "Categories in ser2 doesn't contain adequate categories"
+        assert converted2.cat.categories.isin(
+            ["S1", "S2"]
+        ).all(), "Categories in ser2 doesn't contain adequate categories"