BUG: fix test_arrow.py tests

Author: jbrockmendel

pandas/core/dtypes/common.py

@@ -1188,10 +1188,10 @@ def needs_i8_conversion(arr_or_dtype) -> bool:
     """
     if arr_or_dtype is None:
         return False
-    if isinstance(arr_or_dtype, (np.dtype, ExtensionDtype)):
-        # fastpath
-        dtype = arr_or_dtype
-        return dtype.kind in ["m", "M"] or dtype.type is Period
+    if isinstance(arr_or_dtype, np.dtype):
+        return arr_or_dtype.kind in ["m", "M"]
+    elif isinstance(arr_or_dtype, ExtensionDtype):
+        return isinstance(arr_or_dtype, (PeriodDtype, DatetimeTZDtype))
 
     try:
         dtype = get_dtype(arr_or_dtype)

pandas/core/dtypes/concat.py

@@ -27,7 +27,10 @@
     is_dtype_equal,
     is_sparse,
 )
-from pandas.core.dtypes.dtypes import ExtensionDtype
+from pandas.core.dtypes.dtypes import (
+    DatetimeTZDtype,
+    ExtensionDtype,
+)
 from pandas.core.dtypes.generic import (
     ABCCategoricalIndex,
     ABCExtensionArray,
@@ -103,10 +106,12 @@ def is_nonempty(x) -> bool:
         # ea_compat_axis see GH#39574
         to_concat = non_empties
 
+    dtypes = {obj.dtype for obj in to_concat}
     kinds = {obj.dtype.kind for obj in to_concat}
-    contains_datetime = any(kind in ["m", "M"] for kind in kinds) or any(
-        isinstance(obj, ABCExtensionArray) and obj.ndim > 1 for obj in to_concat
-    )
+    contains_datetime = any(
+        isinstance(dtype, (np.dtype, DatetimeTZDtype)) and dtype.kind in ["m", "M"]
+        for dtype in dtypes
+    ) or any(isinstance(obj, ABCExtensionArray) and obj.ndim > 1 for obj in to_concat)
 
     all_empty = not len(non_empties)
     single_dtype = len({x.dtype for x in to_concat}) == 1

pandas/core/internals/concat.py

@@ -29,7 +29,6 @@
 )
 from pandas.core.dtypes.common import (
     is_1d_only_ea_dtype,
-    is_datetime64tz_dtype,
     is_dtype_equal,
     is_scalar,
     needs_i8_conversion,
@@ -38,7 +37,10 @@
     cast_to_common_type,
     concat_compat,
 )
-from pandas.core.dtypes.dtypes import ExtensionDtype
+from pandas.core.dtypes.dtypes import (
+    DatetimeTZDtype,
+    ExtensionDtype,
+)
 from pandas.core.dtypes.missing import (
     is_valid_na_for_dtype,
     isna,
@@ -471,7 +473,8 @@ def get_reindexed_values(self, empty_dtype: DtypeObj, upcasted_na) -> ArrayLike:
                     if len(values) and values[0] is None:
                         fill_value = None
 
-                if is_datetime64tz_dtype(empty_dtype):
+                if isinstance(empty_dtype, DatetimeTZDtype):
+                    # NB: exclude e.g. pyarrow[dt64tz] dtypes
                     i8values = np.full(self.shape, fill_value.value)
                     return DatetimeArray(i8values, dtype=empty_dtype)
 

pandas/core/reshape/merge.py

@@ -50,7 +50,6 @@
     is_bool,
     is_bool_dtype,
     is_categorical_dtype,
-    is_datetime64tz_dtype,
     is_dtype_equal,
     is_extension_array_dtype,
     is_float_dtype,
@@ -62,6 +61,7 @@
     is_object_dtype,
     needs_i8_conversion,
 )
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
     ABCSeries,
@@ -1352,12 +1352,12 @@ def _maybe_coerce_merge_keys(self) -> None:
                 raise ValueError(msg)
             elif not needs_i8_conversion(lk.dtype) and needs_i8_conversion(rk.dtype):
                 raise ValueError(msg)
-            elif is_datetime64tz_dtype(lk.dtype) and not is_datetime64tz_dtype(
-                rk.dtype
+            elif isinstance(lk.dtype, DatetimeTZDtype) and not isinstance(
+                rk.dtype, DatetimeTZDtype
             ):
                 raise ValueError(msg)
-            elif not is_datetime64tz_dtype(lk.dtype) and is_datetime64tz_dtype(
-                rk.dtype
+            elif not isinstance(lk.dtype, DatetimeTZDtype) and isinstance(
+                rk.dtype, DatetimeTZDtype
             ):
                 raise ValueError(msg)
 
@@ -2283,9 +2283,10 @@ def _factorize_keys(
     rk = extract_array(rk, extract_numpy=True, extract_range=True)
     # TODO: if either is a RangeIndex, we can likely factorize more efficiently?
 
-    if is_datetime64tz_dtype(lk.dtype) and is_datetime64tz_dtype(rk.dtype):
+    if isinstance(lk.dtype, DatetimeTZDtype) and isinstance(rk.dtype, DatetimeTZDtype):
         # Extract the ndarray (UTC-localized) values
         # Note: we dont need the dtypes to match, as these can still be compared
+        # TODO(non-nano): need to make sure resolutions match
         lk = cast("DatetimeArray", lk)._ndarray
         rk = cast("DatetimeArray", rk)._ndarray
 

pandas/io/formats/format.py

@@ -68,7 +68,6 @@
     is_categorical_dtype,
     is_complex_dtype,
     is_datetime64_dtype,
-    is_datetime64tz_dtype,
     is_extension_array_dtype,
     is_float,
     is_float_dtype,
@@ -79,6 +78,7 @@
     is_scalar,
     is_timedelta64_dtype,
 )
+from pandas.core.dtypes.dtypes import DatetimeTZDtype
 from pandas.core.dtypes.missing import (
     isna,
     notna,
@@ -1290,7 +1290,7 @@ def format_array(
     fmt_klass: type[GenericArrayFormatter]
     if is_datetime64_dtype(values.dtype):
         fmt_klass = Datetime64Formatter
-    elif is_datetime64tz_dtype(values.dtype):
+    elif isinstance(values.dtype, DatetimeTZDtype):
         fmt_klass = Datetime64TZFormatter
     elif is_timedelta64_dtype(values.dtype):
         fmt_klass = Timedelta64Formatter

pandas/tests/extension/test_arrow.py

@@ -542,25 +542,13 @@ def test_groupby_extension_apply(
         self, data_for_grouping, groupby_apply_op, request
     ):
         pa_dtype = data_for_grouping.dtype.pyarrow_dtype
-        # TODO: Is there a better way to get the "object" ID for groupby_apply_op?
-        is_object = "object" in request.node.nodeid
         if pa.types.is_duration(pa_dtype):
             request.node.add_marker(
                 pytest.mark.xfail(
                     raises=pa.ArrowNotImplementedError,
                     reason=f"pyarrow doesn't support factorizing {pa_dtype}",
                 )
             )
-        elif pa.types.is_date(pa_dtype) or (
-            pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None
-        ):
-            if is_object:
-                request.node.add_marker(
-                    pytest.mark.xfail(
-                        raises=TypeError,
-                        reason="GH 47514: _concat_datetime expects axis arg.",
-                    )
-                )
         with tm.maybe_produces_warning(
             PerformanceWarning, pa_version_under7p0, check_stacklevel=False
         ):
@@ -691,70 +679,10 @@ def test_dropna_array(self, data_missing):
 
 
 class TestBasePrinting(base.BasePrintingTests):
-    def test_series_repr(self, data, request):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if (
-            pa.types.is_date(pa_dtype)
-            or pa.types.is_duration(pa_dtype)
-            or (pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None)
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=TypeError,
-                    reason="GH 47514: _concat_datetime expects axis arg.",
-                )
-            )
-        super().test_series_repr(data)
-
-    def test_dataframe_repr(self, data, request):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if (
-            pa.types.is_date(pa_dtype)
-            or pa.types.is_duration(pa_dtype)
-            or (pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None)
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=TypeError,
-                    reason="GH 47514: _concat_datetime expects axis arg.",
-                )
-            )
-        super().test_dataframe_repr(data)
+    pass
 
 
 class TestBaseReshaping(base.BaseReshapingTests):
-    @pytest.mark.parametrize("in_frame", [True, False])
-    def test_concat(self, data, in_frame, request):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if (
-            pa.types.is_date(pa_dtype)
-            or pa.types.is_duration(pa_dtype)
-            or (pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None)
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=TypeError,
-                    reason="GH 47514: _concat_datetime expects axis arg.",
-                )
-            )
-        super().test_concat(data, in_frame)
-
-    @pytest.mark.parametrize("in_frame", [True, False])
-    def test_concat_all_na_block(self, data_missing, in_frame, request):
-        pa_dtype = data_missing.dtype.pyarrow_dtype
-        if (
-            pa.types.is_date(pa_dtype)
-            or pa.types.is_duration(pa_dtype)
-            or (pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None)
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=TypeError,
-                    reason="GH 47514: _concat_datetime expects axis arg.",
-                )
-            )
-        super().test_concat_all_na_block(data_missing, in_frame)
-
     def test_concat_columns(self, data, na_value, request):
         tz = getattr(data.dtype.pyarrow_dtype, "tz", None)
         if pa_version_under2p0 and tz not in (None, "UTC"):
@@ -775,26 +703,6 @@ def test_concat_extension_arrays_copy_false(self, data, na_value, request):
             )
         super().test_concat_extension_arrays_copy_false(data, na_value)
 
-    def test_concat_with_reindex(self, data, request, using_array_manager):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if pa.types.is_duration(pa_dtype):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=TypeError,
-                    reason="GH 47514: _concat_datetime expects axis arg.",
-                )
-            )
-        elif pa.types.is_date(pa_dtype) or (
-            pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=AttributeError if not using_array_manager else TypeError,
-                    reason="GH 34986",
-                )
-            )
-        super().test_concat_with_reindex(data)
-
     def test_align(self, data, na_value, request):
         tz = getattr(data.dtype.pyarrow_dtype, "tz", None)
         if pa_version_under2p0 and tz not in (None, "UTC"):
@@ -835,32 +743,6 @@ def test_merge(self, data, na_value, request):
             )
         super().test_merge(data, na_value)
 
-    def test_merge_on_extension_array(self, data, request):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if pa.types.is_date(pa_dtype) or (
-            pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=AttributeError,
-                    reason="GH 34986",
-                )
-            )
-        super().test_merge_on_extension_array(data)
-
-    def test_merge_on_extension_array_duplicates(self, data, request):
-        pa_dtype = data.dtype.pyarrow_dtype
-        if pa.types.is_date(pa_dtype) or (
-            pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=AttributeError,
-                    reason="GH 34986",
-                )
-            )
-        super().test_merge_on_extension_array_duplicates(data)
-
     def test_ravel(self, data, request):
         tz = getattr(data.dtype.pyarrow_dtype, "tz", None)
         if pa_version_under2p0 and tz not in (None, "UTC"):
@@ -1194,17 +1076,7 @@ def test_diff(self, data, periods, request):
     @pytest.mark.parametrize("dropna", [True, False])
     def test_value_counts(self, all_data, dropna, request):
         pa_dtype = all_data.dtype.pyarrow_dtype
-        if (
-            pa.types.is_date(pa_dtype)
-            or (pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None)
-        ) and dropna:
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=NotImplementedError,  # tries casting to i8
-                    reason="GH 34986",
-                )
-            )
-        elif pa.types.is_duration(pa_dtype):
+        if pa.types.is_duration(pa_dtype):
             request.node.add_marker(
                 pytest.mark.xfail(
                     raises=pa.ArrowNotImplementedError,
@@ -1215,16 +1087,7 @@ def test_value_counts(self, all_data, dropna, request):
 
     def test_value_counts_with_normalize(self, data, request):
         pa_dtype = data.dtype.pyarrow_dtype
-        if pa.types.is_date(pa_dtype) or (
-            pa.types.is_timestamp(pa_dtype) and pa_dtype.tz is None
-        ):
-            request.node.add_marker(
-                pytest.mark.xfail(
-                    raises=NotImplementedError,  # tries casting to i8
-                    reason="GH 34986",
-                )
-            )
-        elif pa.types.is_duration(pa_dtype):
+        if pa.types.is_duration(pa_dtype):
             request.node.add_marker(
                 pytest.mark.xfail(
                     raises=pa.ArrowNotImplementedError,