TST: de-special-case test_EA_types

pandas/tests/extension/base/io.py

@@ -5,11 +5,31 @@
 
 import pandas as pd
 import pandas._testing as tm
+from pandas.core.arrays import ExtensionArray
 
 
 class BaseParsingTests:
     @pytest.mark.parametrize("engine", ["c", "python"])
-    def test_EA_types(self, engine, data):
+    def test_EA_types(self, engine, data, request):
+        if isinstance(data.dtype, pd.CategoricalDtype):
+            # in parsers.pyx _convert_with_dtype there is special-casing for
+            #  Categorical that pre-empts _from_sequence_of_strings
+            pass
+        elif isinstance(data.dtype, pd.core.dtypes.dtypes.NumpyEADtype):
+            # These get unwrapped internally so are treated as numpy dtypes
+            #  in the parsers.pyx code
+            pass
+        elif (
+            type(data)._from_sequence_of_strings.__func__
+            is ExtensionArray._from_sequence_of_strings.__func__
+        ):
+            # i.e. the EA hasn't overridden _from_sequence_of_strings
+            mark = pytest.mark.xfail(
+                reason="_from_sequence_of_strings not implemented",
+                raises=NotImplementedError,
+            )
+            request.node.add_marker(mark)
+
         df = pd.DataFrame({"with_dtype": pd.Series(data, dtype=str(data.dtype))})
         csv_output = df.to_csv(index=False, na_rep=np.nan)
         result = pd.read_csv(

pandas/tests/extension/test_datetime.py

@@ -113,12 +113,6 @@ def test_map(self, data, na_action):
         result = data.map(lambda x: x, na_action=na_action)
         tm.assert_extension_array_equal(result, data)
 
-    @pytest.mark.parametrize("engine", ["c", "python"])
-    def test_EA_types(self, engine, data):
-        expected_msg = r".*must implement _from_sequence_of_strings.*"
-        with pytest.raises(NotImplementedError, match=expected_msg):
-            super().test_EA_types(engine, data)
-
     def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):
         if op_name in ["median", "mean", "std"]:
             alt = ser.astype("int64")

pandas/tests/extension/test_interval.py

@@ -90,12 +90,6 @@ def _supports_reduction(self, ser: pd.Series, op_name: str) -> bool:
     def test_fillna_length_mismatch(self, data_missing):
         super().test_fillna_length_mismatch(data_missing)
 
-    @pytest.mark.parametrize("engine", ["c", "python"])
-    def test_EA_types(self, engine, data):
-        expected_msg = r".*must implement _from_sequence_of_strings.*"
-        with pytest.raises(NotImplementedError, match=expected_msg):
-            super().test_EA_types(engine, data)
-
 
 # TODO: either belongs in tests.arrays.interval or move into base tests.
 def test_fillna_non_scalar_raises(data_missing):

pandas/tests/extension/test_sparse.py

@@ -446,11 +446,7 @@ def test_array_repr(self, data, size):
 
 
 class TestParsing(BaseSparseTests, base.BaseParsingTests):
-    @pytest.mark.parametrize("engine", ["c", "python"])
-    def test_EA_types(self, engine, data):
-        expected_msg = r".*must implement _from_sequence_of_strings.*"
-        with pytest.raises(NotImplementedError, match=expected_msg):
-            super().test_EA_types(engine, data)
+    pass
 
 
 class TestNoNumericAccumulations(base.BaseAccumulateTests):