Fix: EA attribute specifying whether copy=False is ignored

pandas/tests/extension/base/missing.py

@@ -6,6 +6,8 @@
 
 
 class BaseMissingTests:
+    _supports_fillna_copy_false = True
+
     def test_isna(self, data_missing):
         expected = np.array([True, False])
 
@@ -193,3 +195,9 @@ def test_fillna_fill_other(self, data):
         expected = pd.DataFrame({"A": data, "B": [0.0] * len(result)})
 
         tm.assert_frame_equal(result, expected)
+
+    def test_fillna_readonly(self, data_missing):
+        fill_value = data_missing[1]
+        result = data_missing.fillna(fill_value, copy=False)
+        expected = data_missing.fillna(fill_value, copy=True)
+        tm.assert_extension_array_equal(result, expected)

pandas/tests/extension/test_numpy.py

@@ -169,6 +169,8 @@ def skip_numpy_object(dtype, request):
 
 
 class TestNumpyExtensionArray(base.ExtensionTests):
+    _supports_fillna_copy_false = False
+
     @pytest.mark.skip(reason="We don't register our dtype")
     # We don't want to register. This test should probably be split in two.
     def test_from_dtype(self, data):

pandas/tests/extension/test_sparse.py

@@ -237,21 +237,6 @@ def test_isna(self, data_missing):
     def test_fillna_no_op_returns_copy(self, data, request):
         super().test_fillna_no_op_returns_copy(data)
 
-    def test_fillna_readonly(self, data_missing):
-        # copy keyword is ignored by SparseArray.fillna
-        # -> copy=True vs False doesn't make a difference
-        data = data_missing.copy()
-        data._readonly = True
-
-        result = data.fillna(data_missing[1])
-        assert result[0] == data_missing[1]
-        tm.assert_extension_array_equal(data, data_missing)
-
-        # fillna(copy=False) is ignored -> so same result as above
-        result = data.fillna(data_missing[1], copy=False)
-        assert result[0] == data_missing[1]
-        tm.assert_extension_array_equal(data, data_missing)
-
     @pytest.mark.xfail(reason="Unsupported")
     def test_fillna_series(self, data_missing):
         # this one looks doable.