REF: share DatetimeLikeIndex methods higher up

pandas/core/indexes/datetimelike.py

@@ -62,7 +62,6 @@
 from pandas.core.indexes.extension import (
     NDArrayBackedExtensionIndex,
     inherit_names,
-    make_wrapped_arith_op,
 )
 from pandas.core.tools.timedeltas import to_timedelta
 
@@ -98,7 +97,6 @@ class DatetimeIndexOpsMixin(NDArrayBackedExtensionIndex):
     hasnans = cache_readonly(
         DatetimeLikeArrayMixin._hasnans.fget  # type: ignore[attr-defined]
     )
-    _hasnans = hasnans  # for index / array -agnostic code
 
     @property
     def _is_all_dates(self) -> bool:
@@ -450,23 +448,6 @@ def _partial_date_slice(
     # --------------------------------------------------------------------
     # Arithmetic Methods
 
-    __add__ = make_wrapped_arith_op("__add__")
-    __sub__ = make_wrapped_arith_op("__sub__")
-    __radd__ = make_wrapped_arith_op("__radd__")
-    __rsub__ = make_wrapped_arith_op("__rsub__")
-    __pow__ = make_wrapped_arith_op("__pow__")
-    __rpow__ = make_wrapped_arith_op("__rpow__")
-    __mul__ = make_wrapped_arith_op("__mul__")
-    __rmul__ = make_wrapped_arith_op("__rmul__")
-    __floordiv__ = make_wrapped_arith_op("__floordiv__")
-    __rfloordiv__ = make_wrapped_arith_op("__rfloordiv__")
-    __mod__ = make_wrapped_arith_op("__mod__")
-    __rmod__ = make_wrapped_arith_op("__rmod__")
-    __divmod__ = make_wrapped_arith_op("__divmod__")
-    __rdivmod__ = make_wrapped_arith_op("__rdivmod__")
-    __truediv__ = make_wrapped_arith_op("__truediv__")
-    __rtruediv__ = make_wrapped_arith_op("__rtruediv__")
-
     def shift(self: _T, periods: int = 1, freq=None) -> _T:
         """
         Shift index by desired number of time frequency increments.

pandas/core/indexes/datetimes.py

@@ -116,16 +116,10 @@ def _new_DatetimeIndex(cls, d):
 @inherit_names(["is_normalized", "_resolution_obj"], DatetimeArray, cache=True)
 @inherit_names(
     [
-        "_bool_ops",
-        "_object_ops",
-        "_field_ops",
-        "_datetimelike_ops",
-        "_datetimelike_methods",
         "tz",
         "tzinfo",
         "dtype",
         "to_pydatetime",
-        "_has_same_tz",
         "_format_native_types",
         "date",
         "time",

pandas/core/indexes/extension.py

@@ -159,7 +159,7 @@ def wrapper(self, other):
     return wrapper
 
 
-def make_wrapped_arith_op(opname: str):
+def _make_wrapped_arith_op(opname: str):
     def method(self, other):
         if (
             isinstance(other, Index)
@@ -170,7 +170,16 @@ def method(self, other):
             # a chance to implement ops before we unwrap them.
             # See https://github.com/pandas-dev/pandas/issues/31109
             return NotImplemented
-        meth = getattr(self._data, opname)
+
+        try:
+            meth = getattr(self._data, opname)
+        except AttributeError as err:
+            # e.g. Categorical, IntervalArray
+            cls = type(self).__name__
+            raise TypeError(
+                f"cannot perform {opname} with this index type: {cls}"
+            ) from err
+
         result = meth(_maybe_unwrap_index(other))
         return _wrap_arithmetic_op(self, other, result)
 
@@ -267,6 +276,23 @@ def _simple_new(
     __le__ = _make_wrapped_comparison_op("__le__")
     __ge__ = _make_wrapped_comparison_op("__ge__")
 
+    __add__ = _make_wrapped_arith_op("__add__")
+    __sub__ = _make_wrapped_arith_op("__sub__")
+    __radd__ = _make_wrapped_arith_op("__radd__")
+    __rsub__ = _make_wrapped_arith_op("__rsub__")
+    __pow__ = _make_wrapped_arith_op("__pow__")
+    __rpow__ = _make_wrapped_arith_op("__rpow__")
+    __mul__ = _make_wrapped_arith_op("__mul__")
+    __rmul__ = _make_wrapped_arith_op("__rmul__")
+    __floordiv__ = _make_wrapped_arith_op("__floordiv__")
+    __rfloordiv__ = _make_wrapped_arith_op("__rfloordiv__")
+    __mod__ = _make_wrapped_arith_op("__mod__")
+    __rmod__ = _make_wrapped_arith_op("__rmod__")
+    __divmod__ = _make_wrapped_arith_op("__divmod__")
+    __rdivmod__ = _make_wrapped_arith_op("__rdivmod__")
+    __truediv__ = _make_wrapped_arith_op("__truediv__")
+    __rtruediv__ = _make_wrapped_arith_op("__rtruediv__")
+
     @property
     def _has_complex_internals(self) -> bool:
         # used to avoid libreduction code paths, which raise or require conversion

pandas/tests/indexes/common.py

@@ -166,11 +166,12 @@ def test_numeric_compat(self, simple_index):
             return
 
         typ = type(idx._data).__name__
+        cls = type(idx).__name__
         lmsg = "|".join(
             [
                 rf"unsupported operand type\(s\) for \*: '{typ}' and 'int'",
                 "cannot perform (__mul__|__truediv__|__floordiv__) with "
-                f"this index type: {typ}",
+                f"this index type: ({cls}|{typ})",
             ]
         )
         with pytest.raises(TypeError, match=lmsg):
@@ -179,7 +180,7 @@ def test_numeric_compat(self, simple_index):
             [
                 rf"unsupported operand type\(s\) for \*: 'int' and '{typ}'",
                 "cannot perform (__rmul__|__rtruediv__|__rfloordiv__) with "
-                f"this index type: {typ}",
+                f"this index type: ({cls}|{typ})",
             ]
         )
         with pytest.raises(TypeError, match=rmsg):

pandas/tests/indexes/datetimes/test_misc.py

@@ -16,6 +16,7 @@
     offsets,
 )
 import pandas._testing as tm
+from pandas.core.arrays import DatetimeArray
 
 
 class TestTimeSeries:
@@ -223,7 +224,7 @@ def test_datetimeindex_accessors(self):
             dti.name = "name"
 
             # non boolean accessors -> return Index
-            for accessor in DatetimeIndex._field_ops:
+            for accessor in DatetimeArray._field_ops:
                 if accessor in ["week", "weekofyear"]:
                     # GH#33595 Deprecate week and weekofyear
                     continue
@@ -233,7 +234,7 @@ def test_datetimeindex_accessors(self):
                 assert res.name == "name"
 
             # boolean accessors -> return array
-            for accessor in DatetimeIndex._bool_ops:
+            for accessor in DatetimeArray._bool_ops:
                 res = getattr(dti, accessor)
                 assert len(res) == 365
                 assert isinstance(res, np.ndarray)

pandas/tests/scalar/test_nat.py

@@ -38,7 +38,7 @@
 @pytest.mark.parametrize(
     "nat,idx",
     [
-        (Timestamp("NaT"), DatetimeIndex),
+        (Timestamp("NaT"), DatetimeArray),
         (Timedelta("NaT"), TimedeltaIndex),
         (Period("NaT", freq="M"), PeriodArray),
     ],
@@ -84,7 +84,7 @@ def test_nat_vector_field_access():
 
     ser = Series(idx)
 
-    for field in DatetimeIndex._field_ops:
+    for field in DatetimeArray._field_ops:
         # weekday is a property of DTI, but a method
         # on NaT/Timestamp for compat with datetime
         if field == "weekday":
@@ -97,7 +97,7 @@ def test_nat_vector_field_access():
         expected = [getattr(x, field) for x in idx]
         tm.assert_series_equal(result, Series(expected))
 
-    for field in DatetimeIndex._bool_ops:
+    for field in DatetimeArray._bool_ops:
         result = getattr(ser.dt, field)
         expected = [getattr(x, field) for x in idx]
         tm.assert_series_equal(result, Series(expected))

pandas/tests/series/accessors/test_dt_accessor.py

@@ -33,6 +33,7 @@
 )
 import pandas._testing as tm
 from pandas.core.arrays import (
+    DatetimeArray,
     PeriodArray,
     TimedeltaArray,
 )
@@ -47,7 +48,7 @@ def test_dt_namespace_accessor(self):
 
         ok_for_period = PeriodArray._datetimelike_ops
         ok_for_period_methods = ["strftime", "to_timestamp", "asfreq"]
-        ok_for_dt = DatetimeIndex._datetimelike_ops
+        ok_for_dt = DatetimeArray._datetimelike_ops
         ok_for_dt_methods = [
             "to_period",
             "to_pydatetime",