TST: unnecessary check_stacklevel=False

pandas/tests/api/test_types.py

@@ -59,5 +59,5 @@ def test_types(self):
     def test_deprecated_from_api_types(self):
 
         for t in self.deprecated:
-            with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+            with tm.assert_produces_warning(FutureWarning):
                 getattr(types, t)(1)

pandas/tests/apply/test_frame_transform.py

@@ -206,7 +206,7 @@ def test_transform_bad_dtype(op, frame_or_series):
 
     # tshift is deprecated
     warn = None if op != "tshift" else FutureWarning
-    with tm.assert_produces_warning(warn, check_stacklevel=False):
+    with tm.assert_produces_warning(warn):
         with pytest.raises(ValueError, match=msg):
             obj.transform(op)
         with pytest.raises(ValueError, match=msg):

pandas/tests/dtypes/test_common.py

@@ -724,7 +724,7 @@ def test_astype_nansafe(val, typ):
 
     msg = "Cannot convert NaT values to integer"
     with pytest.raises(ValueError, match=msg):
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(FutureWarning):
             # datetimelike astype(int64) deprecated
             astype_nansafe(arr, dtype=typ)
 

pandas/tests/frame/indexing/test_indexing.py

@@ -295,7 +295,7 @@ def test_getitem_boolean(
         # we are producing a warning that since the passed boolean
         # key is not the same as the given index, we will reindex
         # not sure this is really necessary
-        with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(UserWarning):
             indexer_obj = indexer_obj.reindex(datetime_frame.index[::-1])
             subframe_obj = datetime_frame[indexer_obj]
             tm.assert_frame_equal(subframe_obj, subframe)

pandas/tests/frame/methods/test_join.py

@@ -227,7 +227,7 @@ def test_suppress_future_warning_with_sort_kw(sort_kw):
     if sort_kw is False:
         expected = expected.reindex(index=["c", "a", "b"])
 
-    with tm.assert_produces_warning(None, check_stacklevel=False):
+    with tm.assert_produces_warning(None):
         result = a.join([b, c], how="outer", sort=sort_kw)
     tm.assert_frame_equal(result, expected)
 

pandas/tests/frame/methods/test_sort_values.py

@@ -845,7 +845,7 @@ def test_sort_column_level_and_index_label(
         if len(levels) > 1:
             # Accessing multi-level columns that are not lexsorted raises a
             # performance warning
-            with tm.assert_produces_warning(PerformanceWarning, check_stacklevel=False):
+            with tm.assert_produces_warning(PerformanceWarning):
                 tm.assert_frame_equal(result, expected)
         else:
             tm.assert_frame_equal(result, expected)

pandas/tests/frame/test_reductions.py

@@ -669,7 +669,7 @@ def test_mode_sortwarning(self):
         df = DataFrame({"A": [np.nan, np.nan, "a", "a"]})
         expected = DataFrame({"A": ["a", np.nan]})
 
-        with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(UserWarning):
             result = df.mode(dropna=False)
             result = result.sort_values(by="A").reset_index(drop=True)
 

pandas/tests/indexes/test_any_index.py

@@ -33,7 +33,7 @@ def test_hash_error(index):
 
 def test_copy_dtype_deprecated(index):
     # GH#35853
-    with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
+    with tm.assert_produces_warning(FutureWarning):
         index.copy(dtype=object)
 
 

pandas/tests/indexing/test_indexing.py

@@ -96,7 +96,7 @@ def test_getitem_ndarray_3d(self, index, frame_or_series, indexer_sli):
 
         potential_errors = (IndexError, ValueError, NotImplementedError)
         with pytest.raises(potential_errors, match=msg):
-            with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+            with tm.assert_produces_warning(DeprecationWarning):
                 idxr[nd3]
 
     def test_setitem_ndarray_3d(self, index, frame_or_series, indexer_sli):

pandas/tests/io/test_compression.py

@@ -112,7 +112,7 @@ def test_compression_warning(compression_only):
     )
     with tm.ensure_clean() as path:
         with icom.get_handle(path, "w", compression=compression_only) as handles:
-            with tm.assert_produces_warning(RuntimeWarning, check_stacklevel=False):
+            with tm.assert_produces_warning(RuntimeWarning):
                 df.to_csv(handles.handle, compression=compression_only)
 
 

pandas/tests/reductions/test_reductions.py

@@ -1420,7 +1420,7 @@ def test_mode_sortwarning(self):
         expected = Series(["foo", np.nan])
         s = Series([1, "foo", "foo", np.nan, np.nan])
 
-        with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(UserWarning):
             result = s.mode(dropna=False)
             result = result.sort_values().reset_index(drop=True)
 

pandas/tests/scalar/timestamp/test_timestamp.py

@@ -507,7 +507,7 @@ def test_to_pydatetime_nonzero_nano(self):
         ts = Timestamp("2011-01-01 9:00:00.123456789")
 
         # Warn the user of data loss (nanoseconds).
-        with tm.assert_produces_warning(UserWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(UserWarning):
             expected = datetime(2011, 1, 1, 9, 0, 0, 123456)
             result = ts.to_pydatetime()
             assert result == expected
@@ -541,13 +541,13 @@ def test_to_datetime_bijective(self):
         # Ensure that converting to datetime and back only loses precision
         # by going from nanoseconds to microseconds.
         exp_warning = None if Timestamp.max.nanosecond == 0 else UserWarning
-        with tm.assert_produces_warning(exp_warning, check_stacklevel=False):
+        with tm.assert_produces_warning(exp_warning):
             pydt_max = Timestamp.max.to_pydatetime()
 
         assert Timestamp(pydt_max).value / 1000 == Timestamp.max.value / 1000
 
         exp_warning = None if Timestamp.min.nanosecond == 0 else UserWarning
-        with tm.assert_produces_warning(exp_warning, check_stacklevel=False):
+        with tm.assert_produces_warning(exp_warning):
             pydt_min = Timestamp.min.to_pydatetime()
 
         # The next assertion can be enabled once GH#39221 is merged

pandas/tests/series/methods/test_astype.py

@@ -91,7 +91,7 @@ def test_astype_empty_constructor_equality(self, dtype):
             "m",  # Generic timestamps raise a ValueError. Already tested.
         ):
             init_empty = Series([], dtype=dtype)
-            with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+            with tm.assert_produces_warning(DeprecationWarning):
                 as_type_empty = Series([]).astype(dtype)
             tm.assert_series_equal(init_empty, as_type_empty)
 

pandas/tests/series/methods/test_replace.py

@@ -266,7 +266,7 @@ def test_replace_with_empty_dictlike(self):
         s = pd.Series(list("abcd"))
         tm.assert_series_equal(s, s.replace({}))
 
-        with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(DeprecationWarning):
             empty_series = pd.Series([])
         tm.assert_series_equal(s, s.replace(empty_series))
 
@@ -457,6 +457,6 @@ def test_str_replace_regex_default_raises_warning(self, pattern):
         msg = r"The default value of regex will change from True to False"
         if len(pattern) == 1:
             msg += r".*single character regular expressions.*not.*literal strings"
-        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False) as w:
+        with tm.assert_produces_warning(FutureWarning) as w:
             s.str.replace(pattern, "")
             assert re.match(msg, str(w[0].message))

pandas/tests/series/test_subclass.py

@@ -35,7 +35,7 @@ def test_subclass_unstack(self):
         tm.assert_frame_equal(res, exp)
 
     def test_subclass_empty_repr(self):
-        with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=False):
+        with tm.assert_produces_warning(DeprecationWarning):
             sub_series = tm.SubclassedSeries()
         assert "SubclassedSeries" in repr(sub_series)
 

pandas/tests/tseries/offsets/test_offsets.py

@@ -194,7 +194,7 @@ def _check_offsetfunc_works(self, offset, funcname, dt, expected, normalize=Fals
             exp_warning = UserWarning
 
         # test nanosecond is preserved
-        with tm.assert_produces_warning(exp_warning, check_stacklevel=False):
+        with tm.assert_produces_warning(exp_warning):
             result = func(ts)
         assert isinstance(result, Timestamp)
         if normalize is False:
@@ -231,7 +231,7 @@ def _check_offsetfunc_works(self, offset, funcname, dt, expected, normalize=Fals
                 exp_warning = UserWarning
 
             # test nanosecond is preserved
-            with tm.assert_produces_warning(exp_warning, check_stacklevel=False):
+            with tm.assert_produces_warning(exp_warning):
                 result = func(ts)
             assert isinstance(result, Timestamp)
             if normalize is False: