CLN: remove unnecessary check needs_i8_conversion if Index subclass…

… does not support `any` or `all` (#58006)

* cln-remove-unnecessary-check-needs_i8_conversion

* fix tests

* remove the check self.dtype.kind, fix tests

* Update pandas/core/indexes/base.py

Co-authored-by: Matthew Roeschke <[email protected]>

* combine two branches in test_logical_compat

* correct test_logical_compat

* correct test_logical_compat

* correct test_logical_compat

* roll back the check for datetime64 in test_logical_compat

* replace reduction with operation to unify err msg

* delete unused line

---------

Co-authored-by: Matthew Roeschke <[email protected]>

pandas/core/arrays/arrow/array.py

@@ -1697,7 +1697,7 @@ def pyarrow_meth(data, skip_nulls, **kwargs):
         except (AttributeError, NotImplementedError, TypeError) as err:
             msg = (
                 f"'{type(self).__name__}' with dtype {self.dtype} "
-                f"does not support reduction '{name}' with pyarrow "
+                f"does not support operation '{name}' with pyarrow "
                 f"version {pa.__version__}. '{name}' may be supported by "
                 f"upgrading pyarrow."
             )

pandas/core/arrays/base.py

@@ -1886,7 +1886,7 @@ def _reduce(
 
         Raises
         ------
-        TypeError : subclass does not define reductions
+        TypeError : subclass does not define operations
 
         Examples
         --------
@@ -1897,7 +1897,7 @@ def _reduce(
         if meth is None:
             raise TypeError(
                 f"'{type(self).__name__}' with dtype {self.dtype} "
-                f"does not support reduction '{name}'"
+                f"does not support operation '{name}'"
             )
         result = meth(skipna=skipna, **kwargs)
         if keepdims:

pandas/core/arrays/datetimelike.py

@@ -1662,7 +1662,7 @@ def _groupby_op(
         if dtype.kind == "M":
             # Adding/multiplying datetimes is not valid
             if how in ["any", "all", "sum", "prod", "cumsum", "cumprod", "var", "skew"]:
-                raise TypeError(f"datetime64 type does not support operation: '{how}'")
+                raise TypeError(f"datetime64 type does not support operation '{how}'")
 
         elif isinstance(dtype, PeriodDtype):
             # Adding/multiplying Periods is not valid

pandas/core/indexes/base.py

@@ -176,7 +176,6 @@
 )
 from pandas.core.missing import clean_reindex_fill_method
 from pandas.core.ops import get_op_result_name
-from pandas.core.ops.invalid import make_invalid_op
 from pandas.core.sorting import (
     ensure_key_mapped,
     get_group_index_sorter,
@@ -6942,14 +6941,8 @@ def _maybe_disable_logical_methods(self, opname: str_t) -> None:
         """
         raise if this Index subclass does not support any or all.
         """
-        if (
-            isinstance(self, ABCMultiIndex)
-            # TODO(3.0): PeriodArray and DatetimeArray any/all will raise,
-            #  so checking needs_i8_conversion will be unnecessary
-            or (needs_i8_conversion(self.dtype) and self.dtype.kind != "m")
-        ):
-            # This call will raise
-            make_invalid_op(opname)(self)
+        if isinstance(self, ABCMultiIndex):
+            raise TypeError(f"cannot perform {opname} with {type(self).__name__}")
 
     @Appender(IndexOpsMixin.argmin.__doc__)
     def argmin(self, axis=None, skipna: bool = True, *args, **kwargs) -> int:

pandas/core/nanops.py

@@ -520,7 +520,7 @@ def nanany(
 
     if values.dtype.kind == "M":
         # GH#34479
-        raise TypeError("datetime64 type does not support operation: 'any'")
+        raise TypeError("datetime64 type does not support operation 'any'")
 
     values, _ = _get_values(values, skipna, fill_value=False, mask=mask)
 
@@ -576,7 +576,7 @@ def nanall(
 
     if values.dtype.kind == "M":
         # GH#34479
-        raise TypeError("datetime64 type does not support operation: 'all'")
+        raise TypeError("datetime64 type does not support operation 'all'")
 
     values, _ = _get_values(values, skipna, fill_value=True, mask=mask)
 

pandas/tests/apply/test_frame_apply.py

@@ -1209,7 +1209,7 @@ def test_agg_multiple_mixed_raises():
     )
 
     # sorted index
-    msg = "does not support reduction"
+    msg = "does not support operation"
     with pytest.raises(TypeError, match=msg):
         mdf.agg(["min", "sum"])
 
@@ -1309,15 +1309,15 @@ def test_nuiscance_columns():
     )
     tm.assert_frame_equal(result, expected)
 
-    msg = "does not support reduction"
+    msg = "does not support operation"
     with pytest.raises(TypeError, match=msg):
         df.agg("sum")
 
     result = df[["A", "B", "C"]].agg("sum")
     expected = Series([6, 6.0, "foobarbaz"], index=["A", "B", "C"])
     tm.assert_series_equal(result, expected)
 
-    msg = "does not support reduction"
+    msg = "does not support operation"
     with pytest.raises(TypeError, match=msg):
         df.agg(["sum"])
 

pandas/tests/arrays/categorical/test_operators.py

@@ -374,14 +374,14 @@ def test_numeric_like_ops(self):
         # min/max)
         s = df["value_group"]
         for op in ["kurt", "skew", "var", "std", "mean", "sum", "median"]:
-            msg = f"does not support reduction '{op}'"
+            msg = f"does not support operation '{op}'"
             with pytest.raises(TypeError, match=msg):
                 getattr(s, op)(numeric_only=False)
 
     def test_numeric_like_ops_series(self):
         # numpy ops
         s = Series(Categorical([1, 2, 3, 4]))
-        with pytest.raises(TypeError, match="does not support reduction 'sum'"):
+        with pytest.raises(TypeError, match="does not support operation 'sum'"):
             np.sum(s)
 
     @pytest.mark.parametrize(

pandas/tests/arrays/test_datetimelike.py

@@ -247,7 +247,7 @@ def test_scalar_from_string(self, arr1d):
         assert result == arr1d[0]
 
     def test_reduce_invalid(self, arr1d):
-        msg = "does not support reduction 'not a method'"
+        msg = "does not support operation 'not a method'"
         with pytest.raises(TypeError, match=msg):
             arr1d._reduce("not a method")
 

pandas/tests/extension/base/groupby.py

@@ -165,7 +165,7 @@ def test_in_numeric_groupby(self, data_for_grouping):
                     # period
                     "does not support sum operations",
                     # datetime
-                    "does not support operation: 'sum'",
+                    "does not support operation 'sum'",
                     # all others
                     re.escape(f"agg function failed [how->sum,dtype->{dtype}"),
                 ]

pandas/tests/extension/base/reduce.py

@@ -86,7 +86,7 @@ def test_reduce_series_boolean(self, data, all_boolean_reductions, skipna):
             # TODO: the message being checked here isn't actually checking anything
             msg = (
                 "[Cc]annot perform|Categorical is not ordered for operation|"
-                "does not support reduction|"
+                "does not support operation|"
             )
 
             with pytest.raises(TypeError, match=msg):
@@ -105,7 +105,7 @@ def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):
             # TODO: the message being checked here isn't actually checking anything
             msg = (
                 "[Cc]annot perform|Categorical is not ordered for operation|"
-                "does not support reduction|"
+                "does not support operation|"
             )
 
             with pytest.raises(TypeError, match=msg):

pandas/tests/extension/test_datetime.py

@@ -104,7 +104,7 @@ def _supports_reduction(self, obj, op_name: str) -> bool:
     @pytest.mark.parametrize("skipna", [True, False])
     def test_reduce_series_boolean(self, data, all_boolean_reductions, skipna):
         meth = all_boolean_reductions
-        msg = f"datetime64 type does not support operation: '{meth}'"
+        msg = f"datetime64 type does not support operation '{meth}'"
         with pytest.raises(TypeError, match=msg):
             super().test_reduce_series_boolean(data, all_boolean_reductions, skipna)
 

pandas/tests/frame/test_reductions.py

@@ -975,7 +975,7 @@ def test_sum_mixed_datetime(self):
         df = DataFrame({"A": date_range("2000", periods=4), "B": [1, 2, 3, 4]}).reindex(
             [2, 3, 4]
         )
-        with pytest.raises(TypeError, match="does not support reduction 'sum'"):
+        with pytest.raises(TypeError, match="does not support operation 'sum'"):
             df.sum()
 
     def test_mean_corner(self, float_frame, float_string_frame):
@@ -1381,7 +1381,7 @@ def test_any_datetime(self):
         ]
         df = DataFrame({"A": float_data, "B": datetime_data})
 
-        msg = "datetime64 type does not support operation: 'any'"
+        msg = "datetime64 type does not support operation 'any'"
         with pytest.raises(TypeError, match=msg):
             df.any(axis=1)
 
@@ -1466,18 +1466,18 @@ def test_any_all_np_func(self, func, data, expected):
 
         if any(isinstance(x, CategoricalDtype) for x in data.dtypes):
             with pytest.raises(
-                TypeError, match="dtype category does not support reduction"
+                TypeError, match=".* dtype category does not support operation"
             ):
                 func(data)
 
             # method version
             with pytest.raises(
-                TypeError, match="dtype category does not support reduction"
+                TypeError, match=".* dtype category does not support operation"
             ):
                 getattr(DataFrame(data), func.__name__)(axis=None)
         if data.dtypes.apply(lambda x: x.kind == "M").any():
             # GH#34479
-            msg = "datetime64 type does not support operation: '(any|all)'"
+            msg = "datetime64 type does not support operation '(any|all)'"
             with pytest.raises(TypeError, match=msg):
                 func(data)
 
@@ -1734,19 +1734,19 @@ def test_any_all_categorical_dtype_nuisance_column(self, all_boolean_reductions)
         df = ser.to_frame()
 
         # Double-check the Series behavior is to raise
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             getattr(ser, all_boolean_reductions)()
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             getattr(np, all_boolean_reductions)(ser)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             getattr(df, all_boolean_reductions)(bool_only=False)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             getattr(df, all_boolean_reductions)(bool_only=None)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             getattr(np, all_boolean_reductions)(df, axis=0)
 
     def test_median_categorical_dtype_nuisance_column(self):
@@ -1755,22 +1755,22 @@ def test_median_categorical_dtype_nuisance_column(self):
         ser = df["A"]
 
         # Double-check the Series behavior is to raise
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             ser.median()
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             df.median(numeric_only=False)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             df.median()
 
         # same thing, but with an additional non-categorical column
         df["B"] = df["A"].astype(int)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             df.median(numeric_only=False)
 
-        with pytest.raises(TypeError, match="does not support reduction"):
+        with pytest.raises(TypeError, match="does not support operation"):
             df.median()
 
         # TODO: np.median(df, axis=0) gives np.array([2.0, 2.0]) instead
@@ -1964,7 +1964,7 @@ def test_minmax_extensionarray(method, numeric_only):
 def test_frame_mixed_numeric_object_with_timestamp(ts_value):
     # GH 13912
     df = DataFrame({"a": [1], "b": [1.1], "c": ["foo"], "d": [ts_value]})
-    with pytest.raises(TypeError, match="does not support reduction"):
+    with pytest.raises(TypeError, match="does not support operation"):
         df.sum()
 
 

pandas/tests/groupby/test_groupby.py

@@ -671,7 +671,7 @@ def test_raises_on_nuisance(df):
     df = df.loc[:, ["A", "C", "D"]]
     df["E"] = datetime.now()
     grouped = df.groupby("A")
-    msg = "datetime64 type does not support operation: 'sum'"
+    msg = "datetime64 type does not support operation 'sum'"
     with pytest.raises(TypeError, match=msg):
         grouped.agg("sum")
     with pytest.raises(TypeError, match=msg):
@@ -1794,7 +1794,7 @@ def get_categorical_invalid_expected():
             else:
                 msg = "category type does not support"
             if op == "skew":
-                msg = "|".join([msg, "does not support reduction 'skew'"])
+                msg = "|".join([msg, "does not support operation 'skew'"])
             with pytest.raises(TypeError, match=msg):
                 get_result()