TST: remove redundant strict=True parameter (GH23057)

Author: dcreekp

pandas/tests/arithmetic/conftest.py

@@ -162,7 +162,7 @@ def box(request):
 @pytest.fixture(params=[pd.Index,
                         pd.Series,
                         pytest.param(pd.DataFrame,
-                                     marks=pytest.mark.xfail(strict=True))],
+                                     marks=pytest.mark.xfail)],
                 ids=id_func)
 def box_df_fail(request):
     """
@@ -175,7 +175,7 @@ def box_df_fail(request):
                         (pd.Series, False),
                         (pd.DataFrame, False),
                         pytest.param((pd.DataFrame, True),
-                                     marks=pytest.mark.xfail(strict=True))],
+                                     marks=pytest.mark.xfail)],
                 ids=id_func)
 def box_transpose_fail(request):
     """

pandas/tests/arithmetic/test_numeric.py

@@ -407,7 +407,7 @@ class TestMultiplicationDivision(object):
         pytest.param(pd.Index,
                      marks=pytest.mark.xfail(reason="Index.__div__ always "
                                                     "raises",
-                                             raises=TypeError, strict=True)),
+                                             raises=TypeError)),
         pd.Series,
         pd.DataFrame
     ], ids=lambda x: x.__name__)

pandas/tests/arithmetic/test_object.py

@@ -92,7 +92,7 @@ def test_add_extension_scalar(self, other, box, op):
     @pytest.mark.parametrize('box', [
         pytest.param(pd.Index,
                      marks=pytest.mark.xfail(reason="Does not mask nulls",
-                                             strict=True, raises=TypeError)),
+                                             raises=TypeError)),
         pd.Series,
         pd.DataFrame
     ], ids=lambda x: x.__name__)
@@ -109,7 +109,7 @@ def test_objarr_add_str(self, box):
     @pytest.mark.parametrize('box', [
         pytest.param(pd.Index,
                      marks=pytest.mark.xfail(reason="Does not mask nulls",
-                                             strict=True, raises=TypeError)),
+                                             raises=TypeError)),
         pd.Series,
         pd.DataFrame
     ], ids=lambda x: x.__name__)

pandas/tests/arrays/categorical/test_constructors.py

@@ -538,8 +538,7 @@ def test_construction_with_ordered(self):
         cat = Categorical([0, 1, 2], ordered=True)
         assert cat.ordered
 
-    @pytest.mark.xfail(reason="Imaginary values not supported in Categorical",
-                       strict=True)
+    @pytest.mark.xfail(reason="Imaginary values not supported in Categorical")
     def test_constructor_imaginary(self):
         values = [1, 2, 3 + 1j]
         c1 = Categorical(values)

pandas/tests/arrays/sparse/test_array.py

@@ -488,7 +488,7 @@ def test_astype_all(self, any_real_dtype):
             SparseArray(np.array([0, 1], dtype='datetime64[ns]'),
                         dtype=SparseDtype('datetime64[ns]',
                                           pd.Timestamp('1970'))),
-            marks=[pytest.mark.xfail(reason="NumPy-7619", strict=True)],
+            marks=[pytest.mark.xfail(reason="NumPy-7619")],
         ),
         (SparseArray([0, 1, 10]), str,
          SparseArray(['0', '1', '10'], dtype=SparseDtype(str, '0'))),

pandas/tests/extension/base/ops.py

@@ -72,8 +72,7 @@ def test_arith_series_with_scalar(self, data, all_arithmetic_operators):
         s = pd.Series(data)
         self.check_opname(s, op_name, s.iloc[0], exc=self.series_scalar_exc)
 
-    @pytest.mark.xfail(run=False, reason="_reduce needs implementation",
-                       strict=True)
+    @pytest.mark.xfail(run=False, reason="_reduce needs implementation")
     def test_arith_frame_with_scalar(self, data, all_arithmetic_operators):
         # frame & scalar
         op_name = all_arithmetic_operators

pandas/tests/extension/base/setitem.py

@@ -166,8 +166,7 @@ def test_setitem_frame_invalid_length(self, data):
         with pytest.raises(ValueError, match=xpr):
             df['B'] = data[:5]
 
-    @pytest.mark.xfail(reason="GH#20441: setitem on extension types.",
-                       strict=True)
+    @pytest.mark.xfail(reason="GH#20441: setitem on extension types.")
     def test_setitem_tuple_index(self, data):
         s = pd.Series(data[:2], index=[(0, 0), (0, 1)])
         expected = pd.Series(data.take([1, 1]), index=s.index)

pandas/tests/extension/json/test_json.py

@@ -148,7 +148,7 @@ def test_stack(self):
         rows since we consider `{}` NA, but `.astype(object)` doesn't.
         """
 
-    @pytest.mark.xfail(reason="dict for NA", strict=True)
+    @pytest.mark.xfail(reason="dict for NA")
     def test_unstack(self, data, index):
         # The base test has NaN for the expected NA value.
         # this matches otherwise

pandas/tests/extension/test_categorical.py

@@ -72,7 +72,7 @@ class TestDtype(base.BaseDtypeTests):
 
 
 class TestInterface(base.BaseInterfaceTests):
-    @pytest.mark.skip(reason="Memory usage doesn't match", strict=True)
+    @pytest.mark.skip(reason="Memory usage doesn't match")
     def test_memory_usage(self, data):
         # Is this deliberate?
         super(TestInterface, self).test_memory_usage(data)
@@ -87,9 +87,9 @@ class TestReshaping(base.BaseReshapingTests):
 
 
 class TestGetitem(base.BaseGetitemTests):
-    skip_take = pytest.mark.skip(reason="GH-20664.", strict=True)
+    skip_take = pytest.mark.skip(reason="GH-20664.")
 
-    @pytest.mark.skip(reason="Backwards compatibility", strict=True)
+    @pytest.mark.skip(reason="Backwards compatibility")
     def test_getitem_scalar(self, data):
         # CategoricalDtype.type isn't "correct" since it should
         # be a parent of the elements (object). But don't want
@@ -117,20 +117,19 @@ def test_take_non_na_fill_value(self, data_missing):
     def test_take_out_of_bounds_raises(self, data, allow_fill):
         return super().test_take_out_of_bounds_raises(data, allow_fill)
 
-    @pytest.mark.skip(reason="GH-20747. Unobserved categories.", strict=True)
+    @pytest.mark.skip(reason="GH-20747. Unobserved categories.")
     def test_take_series(self, data):
         super().test_take_series(data)
 
     @skip_take
     def test_reindex_non_na_fill_value(self, data_missing):
         super().test_reindex_non_na_fill_value(data_missing)
 
-    @pytest.mark.skip(reason="Categorical.take buggy", strict=True)
+    @pytest.mark.skip(reason="Categorical.take buggy")
     def test_take_empty(self, data, na_value, na_cmp):
         super().test_take_empty(data, na_value, na_cmp)
 
-    @pytest.mark.skip(reason="test not written correctly for categorical",
-                      strict=True)
+    @pytest.mark.skip(reason="test not written correctly for categorical")
     def test_reindex(self, data, na_value):
         super().test_reindex(data, na_value)
 
@@ -141,11 +140,11 @@ class TestSetitem(base.BaseSetitemTests):
 
 class TestMissing(base.BaseMissingTests):
 
-    @pytest.mark.skip(reason="Not implemented", strict=True)
+    @pytest.mark.skip(reason="Not implemented")
     def test_fillna_limit_pad(self, data_missing):
         super().test_fillna_limit_pad(data_missing)
 
-    @pytest.mark.skip(reason="Not implemented", strict=True)
+    @pytest.mark.skip(reason="Not implemented")
     def test_fillna_limit_backfill(self, data_missing):
         super().test_fillna_limit_backfill(data_missing)
 
@@ -155,7 +154,7 @@ class TestReduce(base.BaseNoReduceTests):
 
 
 class TestMethods(base.BaseMethodsTests):
-    @pytest.mark.skip(reason="Unobserved categories included", strict=True)
+    @pytest.mark.skip(reason="Unobserved categories included")
     def test_value_counts(self, all_data, dropna):
         return super().test_value_counts(all_data, dropna)
 
@@ -175,7 +174,7 @@ def test_combine_add(self, data_repeated):
         expected = pd.Series([a + val for a in list(orig_data1)])
         self.assert_series_equal(result, expected)
 
-    @pytest.mark.skip(reason="Not Applicable", strict=True)
+    @pytest.mark.skip(reason="Not Applicable")
     def test_fillna_length_mismatch(self, data_missing):
         super().test_fillna_length_mismatch(data_missing)
 

pandas/tests/frame/test_combine_concat.py

@@ -77,8 +77,7 @@ def test_concat_multiple_tzs(self):
         [
             '2015-01-01',
             pytest.param(pd.NaT, marks=pytest.mark.xfail(
-                reason='GH23037 incorrect dtype when concatenating',
-                strict=True))])
+                reason='GH23037 incorrect dtype when concatenating'))])
     def test_concat_tz_NaT(self, t1):
         # GH 22796
         # Concating tz-aware multicolumn DataFrames

pandas/tests/frame/test_duplicates.py

@@ -55,8 +55,7 @@ def test_duplicated_keep(keep, expected):
     tm.assert_series_equal(result, expected)
 
 
-@pytest.mark.xfail(reason="GH#21720; nan/None falsely considered equal",
-                   strict=True)
+@pytest.mark.xfail(reason="GH#21720; nan/None falsely considered equal")
 @pytest.mark.parametrize('keep, expected', [
     ('first', Series([False, False, True, False, True])),
     ('last', Series([True, True, False, False, False])),

pandas/tests/groupby/test_apply.py

@@ -60,8 +60,7 @@ def test_apply_trivial():
 
 @pytest.mark.xfail(reason="GH#20066; function passed into apply "
                           "returns a DataFrame with the same index "
-                          "as the one to create GroupBy object.",
-                   strict=True)
+                          "as the one to create GroupBy object.")
 def test_apply_trivial_fail():
     # GH 20066
     # trivial apply fails if the constant dataframe has the same index

pandas/tests/indexes/interval/test_astype.py

@@ -92,7 +92,7 @@ def test_subtype_integer(self, subtype_start, subtype_end):
                                              closed=index.closed)
         tm.assert_index_equal(result, expected)
 
-    @pytest.mark.xfail(reason='GH#15832', strict=True)
+    @pytest.mark.xfail(reason='GH#15832')
     def test_subtype_integer_errors(self):
         # int64 -> uint64 fails with negative values
         index = interval_range(-10, 10)
@@ -130,7 +130,7 @@ def test_subtype_integer(self, subtype):
         with pytest.raises(ValueError, match=msg):
             index.insert(0, np.nan).astype(dtype)
 
-    @pytest.mark.xfail(reason='GH#15832', strict=True)
+    @pytest.mark.xfail(reason='GH#15832')
     def test_subtype_integer_errors(self):
         # float64 -> uint64 fails with negative values
         index = interval_range(-10.0, 10.0)

pandas/tests/indexes/multi/test_missing.py

@@ -84,7 +84,7 @@ def test_nulls(idx):
         idx.isna()
 
 
-@pytest.mark.xfail(strict=True)
+@pytest.mark.xfail
 def test_hasnans_isnans(idx):
     # GH 11343, added tests for hasnans / isnans
     index = idx.copy()

pandas/tests/indexes/test_base.py

@@ -497,8 +497,7 @@ def test_constructor_overflow_int64(self):
             Index([np.iinfo(np.uint64).max - 1], dtype="int64")
 
     @pytest.mark.xfail(reason="see GH#21311: Index "
-                              "doesn't enforce dtype argument",
-                       strict=True)
+                              "doesn't enforce dtype argument")
     def test_constructor_cast(self):
         msg = "could not convert string to float"
         with pytest.raises(ValueError, match=msg):
@@ -1547,8 +1546,7 @@ def test_slice_float_locs(self):
         assert index2.slice_locs(8.5, 1.5) == (2, 6)
         assert index2.slice_locs(10.5, -1) == (0, n)
 
-    @pytest.mark.xfail(reason="Assertions were not correct - see GH#20915",
-                       strict=True)
+    @pytest.mark.xfail(reason="Assertions were not correct - see GH#20915")
     def test_slice_ints_with_floats_raises(self):
         # int slicing with floats
         # GH 4892, these are all TypeErrors

pandas/tests/io/formats/test_to_csv.py

@@ -358,7 +358,7 @@ def test_to_csv_string_array_ascii(self):
             with open(path, 'r') as f:
                 assert f.read() == expected_ascii
 
-    @pytest.mark.xfail(strict=True)
+    @pytest.mark.xfail
     def test_to_csv_string_array_utf8(self):
         # GH 10813
         str_array = [{'names': ['foo', 'bar']}, {'names': ['baz', 'qux']}]

pandas/tests/io/formats/test_to_html.py

@@ -220,7 +220,7 @@ def test_to_html_truncate_multi_index(self, datapath):
         expected = expected_html(datapath, 'truncate_multi_index')
         assert result == expected
 
-    @pytest.mark.xfail(reason='GH22887 TypeError', strict=True)
+    @pytest.mark.xfail(reason='GH22887 TypeError')
     def test_to_html_truncate_multi_index_sparse_off(self, datapath):
         arrays = [['bar', 'bar', 'baz', 'baz', 'foo', 'foo', 'qux', 'qux'],
                   ['one', 'two', 'one', 'two', 'one', 'two', 'one', 'two']]

pandas/tests/io/json/test_json_table_schema.py

@@ -498,7 +498,7 @@ class TestTableOrientReader(object):
         None,
         "idx",
         pytest.param("index",
-                     marks=pytest.mark.xfail(strict=True)),
+                     marks=pytest.mark.xfail),
         'level_0'])
     @pytest.mark.parametrize("vals", [
         {'ints': [1, 2, 3, 4]},
@@ -508,7 +508,7 @@ class TestTableOrientReader(object):
         {'ordered_cats': pd.Series(pd.Categorical(['a', 'b', 'c', 'c'],
                                                   ordered=True))},
         pytest.param({'floats': [1., 2., 3., 4.]},
-                     marks=pytest.mark.xfail(strict=True)),
+                     marks=pytest.mark.xfail),
         {'floats': [1.1, 2.2, 3.3, 4.4]},
         {'bools': [True, False, False, True]}])
     def test_read_json_table_orient(self, index_nm, vals, recwarn):
@@ -566,7 +566,7 @@ def test_multiindex(self, index_names):
         tm.assert_frame_equal(df, result)
 
     @pytest.mark.parametrize("strict_check", [
-        pytest.param(True, marks=pytest.mark.xfail(strict=True)),
+        pytest.param(True, marks=pytest.mark.xfail),
         False
     ])
     def test_empty_frame_roundtrip(self, strict_check):

pandas/tests/io/test_excel.py

@@ -2362,8 +2362,7 @@ def check_called(func):
     pytest.param('xlwt',
                  marks=pytest.mark.xfail(reason='xlwt does not support '
                                                 'openpyxl-compatible '
-                                                'style dicts',
-                                         strict=True)),
+                                                'style dicts')),
     'xlsxwriter',
     'openpyxl',
 ])

pandas/tests/io/test_parquet.py

@@ -201,8 +201,7 @@ def test_options_get_engine(fp, pa):
 
 
 @pytest.mark.xfail(is_platform_windows() or is_platform_mac(),
-                   reason="reading pa metadata failing on Windows/mac",
-                   strict=True)
+                   reason="reading pa metadata failing on Windows/mac")
 def test_cross_engine_pa_fp(df_cross_compat, pa, fp):
     # cross-compat with differing reading/writing engines
 

pandas/tests/plotting/test_frame.py

@@ -489,8 +489,7 @@ def test_subplots_timeseries_y_axis(self):
             testdata.plot(y="text")
 
     @pytest.mark.xfail(reason='not support for period, categorical, '
-                              'datetime_mixed_tz',
-                       strict=True)
+                              'datetime_mixed_tz')
     def test_subplots_timeseries_y_axis_not_supported(self):
         """
         This test will fail for:

pandas/tests/reshape/test_pivot.py

@@ -489,8 +489,7 @@ def test_pivot_with_list_like_values_nans(self, values, method):
         tm.assert_frame_equal(result, expected)
 
     @pytest.mark.xfail(reason='MultiIndexed unstack with tuple names fails'
-                              'with KeyError GH#19966',
-                       strict=True)
+                              'with KeyError GH#19966')
     @pytest.mark.parametrize('method', [True, False])
     def test_pivot_with_multiindex(self, method):
         # issue #17160
@@ -616,8 +615,7 @@ def test_margins_dtype(self):
         tm.assert_frame_equal(expected, result)
 
     @pytest.mark.xfail(reason='GH#17035 (len of floats is casted back to '
-                              'floats)',
-                       strict=True)
+                              'floats)')
     def test_margins_dtype_len(self):
         mi_val = list(product(['bar', 'foo'], ['one', 'two'])) + [('All', '')]
         mi = MultiIndex.from_tuples(mi_val, names=('A', 'B'))
@@ -1102,8 +1100,7 @@ def test_pivot_table_margins_name_with_aggfunc_list(self):
         tm.assert_frame_equal(table, expected)
 
     @pytest.mark.xfail(reason='GH#17035 (np.mean of ints is casted back to '
-                              'ints)',
-                       strict=True)
+                              'ints)')
     def test_categorical_margins(self, observed):
         # GH 10989
         df = pd.DataFrame({'x': np.arange(8),
@@ -1118,8 +1115,7 @@ def test_categorical_margins(self, observed):
         tm.assert_frame_equal(table, expected)
 
     @pytest.mark.xfail(reason='GH#17035 (np.mean of ints is casted back to '
-                              'ints)',
-                       strict=True)
+                              'ints)')
     def test_categorical_margins_category(self, observed):
         df = pd.DataFrame({'x': np.arange(8),
                            'y': np.arange(8) // 4,

pandas/tests/scalar/period/test_asfreq.py

@@ -34,8 +34,7 @@ def test_asfreq_near_zero_weekly(self):
         assert week2.asfreq('D', 'S') <= per2
 
     @pytest.mark.xfail(reason='GH#19643 period_helper asfreq functions fail '
-                              'to check for overflows',
-                       strict=True)
+                              'to check for overflows')
     def test_to_timestamp_out_of_bounds(self):
         # GH#19643, currently gives Timestamp('1754-08-30 22:43:41.128654848')
         per = Period('0001-01-01', freq='B')

pandas/tests/series/test_analytics.py

@@ -2140,7 +2140,7 @@ def test_value_counts_with_nan(self):
         "dtype",
         ["int_", "uint", "float_", "unicode_", "timedelta64[h]",
          pytest.param("datetime64[D]",
-                      marks=pytest.mark.xfail(reason="GH#7996", strict=True))]
+                      marks=pytest.mark.xfail(reason="GH#7996"))]
     )
     @pytest.mark.parametrize("is_ordered", [True, False])
     def test_drop_duplicates_categorical_non_bool(self, dtype, is_ordered):