Revert "REF: remove unnecessary na_value fixture"

pandas/tests/extension/base/constructors.py

@@ -35,8 +35,7 @@ def test_series_constructor(self, data):
         if hasattr(result._mgr, "blocks"):
             assert isinstance(result2._mgr.blocks[0], EABackedBlock)
 
-    def test_series_constructor_no_data_with_index(self, dtype):
-        na_value = dtype.na_value
+    def test_series_constructor_no_data_with_index(self, dtype, na_value):
         result = pd.Series(index=[1, 2, 3], dtype=dtype)
         expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
         tm.assert_series_equal(result, expected)
@@ -46,8 +45,7 @@ def test_series_constructor_no_data_with_index(self, dtype):
         expected = pd.Series([], index=pd.Index([], dtype="object"), dtype=dtype)
         tm.assert_series_equal(result, expected)
 
-    def test_series_constructor_scalar_na_with_index(self, dtype):
-        na_value = dtype.na_value
+    def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
         result = pd.Series(na_value, index=[1, 2, 3], dtype=dtype)
         expected = pd.Series([na_value] * 3, index=[1, 2, 3], dtype=dtype)
         tm.assert_series_equal(result, expected)

pandas/tests/extension/base/getitem.py

@@ -148,8 +148,7 @@ def test_getitem_invalid(self, data):
         with pytest.raises(IndexError, match=msg):
             data[-ub - 1]
 
-    def test_getitem_scalar_na(self, data_missing, na_cmp):
-        na_value = data_missing.dtype.na_value
+    def test_getitem_scalar_na(self, data_missing, na_cmp, na_value):
         result = data_missing[0]
         assert na_cmp(result, na_value)
 
@@ -349,8 +348,7 @@ def test_take_sequence(self, data):
         assert result.iloc[1] == data[1]
         assert result.iloc[2] == data[3]
 
-    def test_take(self, data, na_cmp):
-        na_value = data.dtype.na_value
+    def test_take(self, data, na_value, na_cmp):
         result = data.take([0, -1])
         assert result.dtype == data.dtype
         assert result[0] == data[0]
@@ -363,8 +361,7 @@ def test_take(self, data, na_cmp):
         with pytest.raises(IndexError, match="out of bounds"):
             data.take([len(data) + 1])
 
-    def test_take_empty(self, data, na_cmp):
-        na_value = data.dtype.na_value
+    def test_take_empty(self, data, na_value, na_cmp):
         empty = data[:0]
 
         result = empty.take([-1], allow_fill=True)
@@ -396,8 +393,7 @@ def test_take_non_na_fill_value(self, data_missing):
         expected = arr.take([1, 1])
         tm.assert_extension_array_equal(result, expected)
 
-    def test_take_pandas_style_negative_raises(self, data):
-        na_value = data.dtype.na_value
+    def test_take_pandas_style_negative_raises(self, data, na_value):
         with pytest.raises(ValueError, match=""):
             data.take([0, -2], fill_value=na_value, allow_fill=True)
 
@@ -417,8 +413,7 @@ def test_take_series(self, data):
         )
         tm.assert_series_equal(result, expected)
 
-    def test_reindex(self, data):
-        na_value = data.dtype.na_value
+    def test_reindex(self, data, na_value):
         s = pd.Series(data)
         result = s.reindex([0, 1, 3])
         expected = pd.Series(data.take([0, 1, 3]), index=[0, 1, 3])

pandas/tests/extension/base/methods.py

@@ -121,7 +121,7 @@ def test_argsort_missing(self, data_missing_for_sorting):
         expected = pd.Series(np.array([1, -1, 0], dtype=np.intp))
         tm.assert_series_equal(result, expected)
 
-    def test_argmin_argmax(self, data_for_sorting, data_missing_for_sorting):
+    def test_argmin_argmax(self, data_for_sorting, data_missing_for_sorting, na_value):
         # GH 24382
         is_bool = data_for_sorting.dtype._is_boolean
 
@@ -154,10 +154,9 @@ def test_argmin_argmax_empty_array(self, method, data):
             getattr(data[:0], method)()
 
     @pytest.mark.parametrize("method", ["argmax", "argmin"])
-    def test_argmin_argmax_all_na(self, method, data):
+    def test_argmin_argmax_all_na(self, method, data, na_value):
         # all missing with skipna=True is the same as empty
         err_msg = "attempt to get"
-        na_value = data.dtype.na_value
         data_na = type(data)._from_sequence([na_value, na_value], dtype=data.dtype)
         with pytest.raises(ValueError, match=err_msg):
             getattr(data_na, method)()
@@ -556,8 +555,7 @@ def _test_searchsorted_bool_dtypes(self, data_for_sorting, as_series):
         sorter = np.array([1, 0])
         assert data_for_sorting.searchsorted(a, sorter=sorter) == 0
 
-    def test_where_series(self, data, as_frame):
-        na_value = data.dtype.na_value
+    def test_where_series(self, data, na_value, as_frame):
         assert data[0] != data[1]
         cls = type(data)
         a, b = data[:2]
@@ -684,8 +682,7 @@ def test_insert_invalid_loc(self, data):
             data.insert(1.5, data[0])
 
     @pytest.mark.parametrize("box", [pd.array, pd.Series, pd.DataFrame])
-    def test_equals(self, data, as_series, box):
-        na_value = data.dtype.na_value
+    def test_equals(self, data, na_value, as_series, box):
         data2 = type(data)._from_sequence([data[0]] * len(data), dtype=data.dtype)
         data_na = type(data)._from_sequence([na_value] * len(data), dtype=data.dtype)
 

pandas/tests/extension/base/reshaping.py

@@ -72,8 +72,7 @@ def test_concat_mixed_dtypes(self, data):
         expected = pd.concat([df1["A"].astype("object"), df2["A"].astype("object")])
         tm.assert_series_equal(result, expected)
 
-    def test_concat_columns(self, data):
-        na_value = data.dtype.na_value
+    def test_concat_columns(self, data, na_value):
         df1 = pd.DataFrame({"A": data[:3]})
         df2 = pd.DataFrame({"B": [1, 2, 3]})
 
@@ -97,9 +96,8 @@ def test_concat_columns(self, data):
         result = pd.concat([df1["A"], df2["B"]], axis=1)
         tm.assert_frame_equal(result, expected)
 
-    def test_concat_extension_arrays_copy_false(self, data):
+    def test_concat_extension_arrays_copy_false(self, data, na_value):
         # GH 20756
-        na_value = data.dtype.na_value
         df1 = pd.DataFrame({"A": data[:3]})
         df2 = pd.DataFrame({"B": data[3:7]})
         expected = pd.DataFrame(
@@ -124,8 +122,7 @@ def test_concat_with_reindex(self, data):
         )
         tm.assert_frame_equal(result, expected)
 
-    def test_align(self, data):
-        na_value = data.dtype.na_value
+    def test_align(self, data, na_value):
         a = data[:3]
         b = data[2:5]
         r1, r2 = pd.Series(a).align(pd.Series(b, index=[1, 2, 3]))
@@ -136,8 +133,7 @@ def test_align(self, data):
         tm.assert_series_equal(r1, e1)
         tm.assert_series_equal(r2, e2)
 
-    def test_align_frame(self, data):
-        na_value = data.dtype.na_value
+    def test_align_frame(self, data, na_value):
         a = data[:3]
         b = data[2:5]
         r1, r2 = pd.DataFrame({"A": a}).align(pd.DataFrame({"A": b}, index=[1, 2, 3]))
@@ -152,9 +148,8 @@ def test_align_frame(self, data):
         tm.assert_frame_equal(r1, e1)
         tm.assert_frame_equal(r2, e2)
 
-    def test_align_series_frame(self, data):
+    def test_align_series_frame(self, data, na_value):
         # https://github.com/pandas-dev/pandas/issues/20576
-        na_value = data.dtype.na_value
         ser = pd.Series(data, name="a")
         df = pd.DataFrame({"col": np.arange(len(ser) + 1)})
         r1, r2 = ser.align(df)
@@ -185,7 +180,7 @@ def test_set_frame_overwrite_object(self, data):
         df["A"] = data
         assert df.dtypes["A"] == data.dtype
 
-    def test_merge(self, data):
+    def test_merge(self, data, na_value):
         # GH-20743
         df1 = pd.DataFrame({"ext": data[:3], "int1": [1, 2, 3], "key": [0, 1, 2]})
         df2 = pd.DataFrame({"int2": [1, 2, 3, 4], "key": [0, 0, 1, 3]})
@@ -210,8 +205,7 @@ def test_merge(self, data):
                 "int2": [1, 2, 3, np.nan, 4],
                 "key": [0, 0, 1, 2, 3],
                 "ext": data._from_sequence(
-                    [data[0], data[0], data[1], data[2], data.dtype.na_value],
-                    dtype=data.dtype,
+                    [data[0], data[0], data[1], data[2], na_value], dtype=data.dtype
                 ),
             }
         )

pandas/tests/extension/base/setitem.py

@@ -359,8 +359,7 @@ def test_setitem_with_expansion_dataframe_column(self, data, full_indexer):
 
         tm.assert_frame_equal(result, expected)
 
-    def test_setitem_with_expansion_row(self, data):
-        na_value = data.dtype.na_value
+    def test_setitem_with_expansion_row(self, data, na_value):
         df = pd.DataFrame({"data": data[:1]})
 
         df.loc[1, "data"] = data[1]

pandas/tests/extension/conftest.py

@@ -118,6 +118,16 @@ def na_cmp():
     return operator.is_
 
 
+@pytest.fixture
+def na_value(dtype):
+    """
+    The scalar missing value for this type. Default dtype.na_value.
+
+    TODO: can be removed in 3.x (see https://github.com/pandas-dev/pandas/pull/54930)
+    """
+    return dtype.na_value
+
+
 @pytest.fixture
 def data_for_grouping():
     """

pandas/tests/extension/json/test_json.py

@@ -97,24 +97,24 @@ def test_from_dtype(self, data):
         super().test_from_dtype(data)
 
     @pytest.mark.xfail(reason="RecursionError, GH-33900")
-    def test_series_constructor_no_data_with_index(self, dtype):
+    def test_series_constructor_no_data_with_index(self, dtype, na_value):
         # RecursionError: maximum recursion depth exceeded in comparison
         rec_limit = sys.getrecursionlimit()
         try:
             # Limit to avoid stack overflow on Windows CI
             sys.setrecursionlimit(100)
-            super().test_series_constructor_no_data_with_index(dtype)
+            super().test_series_constructor_no_data_with_index(dtype, na_value)
         finally:
             sys.setrecursionlimit(rec_limit)
 
     @pytest.mark.xfail(reason="RecursionError, GH-33900")
-    def test_series_constructor_scalar_na_with_index(self, dtype):
+    def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
         # RecursionError: maximum recursion depth exceeded in comparison
         rec_limit = sys.getrecursionlimit()
         try:
             # Limit to avoid stack overflow on Windows CI
             sys.setrecursionlimit(100)
-            super().test_series_constructor_scalar_na_with_index(dtype)
+            super().test_series_constructor_scalar_na_with_index(dtype, na_value)
         finally:
             sys.setrecursionlimit(rec_limit)
 
@@ -214,19 +214,19 @@ def test_combine_first(self, data):
         super().test_combine_first(data)
 
     @pytest.mark.xfail(reason="broadcasting error")
-    def test_where_series(self, data):
+    def test_where_series(self, data, na_value):
         # Fails with
         # *** ValueError: operands could not be broadcast together
         # with shapes (4,) (4,) (0,)
-        super().test_where_series(data)
+        super().test_where_series(data, na_value)
 
     @pytest.mark.xfail(reason="Can't compare dicts.")
     def test_searchsorted(self, data_for_sorting):
         super().test_searchsorted(data_for_sorting)
 
     @pytest.mark.xfail(reason="Can't compare dicts.")
-    def test_equals(self, data, as_series):
-        super().test_equals(data, as_series)
+    def test_equals(self, data, na_value, as_series):
+        super().test_equals(data, na_value, as_series)
 
     @pytest.mark.skip("fill-value is interpreted as a dict of values")
     def test_fillna_copy_frame(self, data_missing):

pandas/tests/extension/test_arrow.py

@@ -503,7 +503,9 @@ def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna, reque
         super().test_reduce_series_numeric(data, all_numeric_reductions, skipna)
 
     @pytest.mark.parametrize("skipna", [True, False])
-    def test_reduce_series_boolean(self, data, all_boolean_reductions, skipna, request):
+    def test_reduce_series_boolean(
+        self, data, all_boolean_reductions, skipna, na_value, request
+    ):
         pa_dtype = data.dtype.pyarrow_dtype
         xfail_mark = pytest.mark.xfail(
             raises=TypeError,

pandas/tests/extension/test_sparse.py

@@ -149,29 +149,29 @@ def test_concat_mixed_dtypes(self, data):
     def test_stack(self, data, columns, future_stack):
         super().test_stack(data, columns, future_stack)
 
-    def test_concat_columns(self, data):
+    def test_concat_columns(self, data, na_value):
         self._check_unsupported(data)
-        super().test_concat_columns(data)
+        super().test_concat_columns(data, na_value)
 
-    def test_concat_extension_arrays_copy_false(self, data):
+    def test_concat_extension_arrays_copy_false(self, data, na_value):
         self._check_unsupported(data)
-        super().test_concat_extension_arrays_copy_false(data)
+        super().test_concat_extension_arrays_copy_false(data, na_value)
 
-    def test_align(self, data):
+    def test_align(self, data, na_value):
         self._check_unsupported(data)
-        super().test_align(data)
+        super().test_align(data, na_value)
 
-    def test_align_frame(self, data):
+    def test_align_frame(self, data, na_value):
         self._check_unsupported(data)
-        super().test_align_frame(data)
+        super().test_align_frame(data, na_value)
 
-    def test_align_series_frame(self, data):
+    def test_align_series_frame(self, data, na_value):
         self._check_unsupported(data)
-        super().test_align_series_frame(data)
+        super().test_align_series_frame(data, na_value)
 
-    def test_merge(self, data):
+    def test_merge(self, data, na_value):
         self._check_unsupported(data)
-        super().test_merge(data)
+        super().test_merge(data, na_value)
 
 
 class TestGetitem(BaseSparseTests, base.BaseGetitemTests):
@@ -183,9 +183,9 @@ def test_get(self, data):
             assert ser.get(4) == ser.iloc[2]
         assert ser.get(2) == ser.iloc[1]
 
-    def test_reindex(self, data):
+    def test_reindex(self, data, na_value):
         self._check_unsupported(data)
-        super().test_reindex(data)
+        super().test_reindex(data, na_value)
 
 
 class TestSetitem(BaseSparseTests, base.BaseSetitemTests):
@@ -285,7 +285,7 @@ def test_fillna_copy_series(self, data_missing, using_copy_on_write):
     def test_fillna_length_mismatch(self, data_missing):
         super().test_fillna_length_mismatch(data_missing)
 
-    def test_where_series(self, data):
+    def test_where_series(self, data, na_value):
         assert data[0] != data[1]
         cls = type(data)
         a, b = data[:2]
@@ -296,7 +296,6 @@ def test_where_series(self, data):
         result = ser.where(cond)
 
         new_dtype = SparseDtype("float", 0.0)
-        na_value = data.dtype.na_value
         expected = pd.Series(
             cls._from_sequence([a, a, na_value, na_value], dtype=new_dtype)
         )
@@ -320,15 +319,15 @@ def test_shift_0_periods(self, data):
         assert result._sparse_values[0] != result._sparse_values[1]
 
     @pytest.mark.parametrize("method", ["argmax", "argmin"])
-    def test_argmin_argmax_all_na(self, method, data):
+    def test_argmin_argmax_all_na(self, method, data, na_value):
         # overriding because Sparse[int64, 0] cannot handle na_value
         self._check_unsupported(data)
-        super().test_argmin_argmax_all_na(method, data)
+        super().test_argmin_argmax_all_na(method, data, na_value)
 
     @pytest.mark.parametrize("box", [pd.array, pd.Series, pd.DataFrame])
-    def test_equals(self, data, as_series, box):
+    def test_equals(self, data, na_value, as_series, box):
         self._check_unsupported(data)
-        super().test_equals(data, as_series, box)
+        super().test_equals(data, na_value, as_series, box)
 
     @pytest.mark.parametrize(
         "func, na_action, expected",