REF: remove need to override get_indexer_non_unique in DatetimeIndexOpsMixin

pandas/_libs/index.pyx

@@ -441,6 +441,10 @@ cdef class DatetimeEngine(Int64Engine):
         except KeyError:
             raise KeyError(val)
 
+    def get_indexer_non_unique(self, targets):
+        # we may get datetime64[ns] or timedelta64[ns], cast these to int64
+        return super().get_indexer_non_unique(targets.view("i8"))
+
     def get_indexer(self, values):
         self._ensure_mapping_populated()
         if values.dtype != self._get_box_dtype():

pandas/core/indexes/base.py

@@ -13,7 +13,7 @@
 from pandas._libs.tslibs import OutOfBoundsDatetime, Timestamp
 from pandas._libs.tslibs.period import IncompatibleFrequency
 from pandas._libs.tslibs.timezones import tz_compare
-from pandas._typing import Label
+from pandas._typing import DtypeObj, Label
 from pandas.compat import set_function_name
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import Appender, Substitution, cache_readonly, doc
@@ -4626,6 +4626,10 @@ def get_indexer_non_unique(self, target):
         if pself is not self or ptarget is not target:
             return pself.get_indexer_non_unique(ptarget)
 
+        if not self._is_comparable_dtype(target.dtype):
+            no_matches = -1 * np.ones(self.shape, dtype=np.intp)
+            return no_matches, no_matches
+
         if is_categorical_dtype(target.dtype):
             tgt_values = np.asarray(target)
         else:
@@ -4651,16 +4655,33 @@ def get_indexer_for(self, target, **kwargs):
         indexer, _ = self.get_indexer_non_unique(target, **kwargs)
         return indexer
 
-    def _maybe_promote(self, other):
-        # A hack, but it works
+    def _maybe_promote(self, other: "Index"):
+        """
+        When dealing with an object-dtype Index and a non-object Index, see
+        if we can upcast the object-dtype one to improve performance.
+        """
 
         if self.inferred_type == "date" and isinstance(other, ABCDatetimeIndex):
             return type(other)(self), other
+        elif self.inferred_type == "timedelta" and isinstance(other, ABCTimedeltaIndex):
+            # TODO: we dont have tests that get here
+            return type(other)(self), other
         elif self.inferred_type == "boolean":
             if not is_object_dtype(self.dtype):
                 return self.astype("object"), other.astype("object")
+
+        if not is_object_dtype(self.dtype) and is_object_dtype(other.dtype):
+            # Reverse op so we dont need to re-implement on the subclasses
+            other, self = other._maybe_promote(self)
+
         return self, other
 
+    def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
+        """
+        Can we compare values of the given dtype to our own?
+        """
+        return True
+
     def groupby(self, values) -> PrettyDict[Hashable, np.ndarray]:
         """
         Group the index labels by a given array of values.

pandas/core/indexes/datetimelike.py

@@ -8,14 +8,13 @@
 
 from pandas._libs import NaT, iNaT, join as libjoin, lib
 from pandas._libs.tslibs import timezones
-from pandas._typing import DtypeObj, Label
+from pandas._typing import Label
 from pandas.compat.numpy import function as nv
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import Appender, cache_readonly, doc
 
 from pandas.core.dtypes.common import (
     ensure_int64,
-    ensure_platform_int,
     is_bool_dtype,
     is_dtype_equal,
     is_integer,
@@ -31,7 +30,7 @@
 from pandas.core.arrays.datetimelike import DatetimeLikeArrayMixin
 from pandas.core.base import IndexOpsMixin
 import pandas.core.indexes.base as ibase
-from pandas.core.indexes.base import Index, _index_shared_docs, ensure_index
+from pandas.core.indexes.base import Index, _index_shared_docs
 from pandas.core.indexes.extension import (
     ExtensionIndex,
     inherit_names,
@@ -99,12 +98,6 @@ class DatetimeIndexOpsMixin(ExtensionIndex):
     def is_all_dates(self) -> bool:
         return True
 
-    def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
-        """
-        Can we compare values of the given dtype to our own?
-        """
-        raise AbstractMethodError(self)
-
     # ------------------------------------------------------------------------
     # Abstract data attributes
 
@@ -430,21 +423,6 @@ def _partial_date_slice(
             # try to find the dates
             return (lhs_mask & rhs_mask).nonzero()[0]
 
-    @Appender(Index.get_indexer_non_unique.__doc__)
-    def get_indexer_non_unique(self, target):
-        target = ensure_index(target)
-        pself, ptarget = self._maybe_promote(target)
-        if pself is not self or ptarget is not target:
-            return pself.get_indexer_non_unique(ptarget)
-
-        if not self._is_comparable_dtype(target.dtype):
-            no_matches = -1 * np.ones(self.shape, dtype=np.intp)
-            return no_matches, no_matches
-
-        tgt_values = target.asi8
-        indexer, missing = self._engine.get_indexer_non_unique(tgt_values)
-        return ensure_platform_int(indexer), missing
-
     # --------------------------------------------------------------------
 
     __add__ = make_wrapped_arith_op("__add__")

pandas/core/indexes/datetimes.py

@@ -538,11 +538,6 @@ def _validate_partial_date_slice(self, reso: str):
             # _parsed_string_to_bounds allows it.
             raise KeyError
 
-    def _maybe_promote(self, other):
-        if other.inferred_type == "date":
-            other = DatetimeIndex(other)
-        return self, other
-
     def get_loc(self, key, method=None, tolerance=None):
         """
         Get integer location for requested label

pandas/core/indexes/timedeltas.py

@@ -197,11 +197,6 @@ def astype(self, dtype, copy=True):
             return Index(result.astype("i8"), name=self.name)
         return DatetimeIndexOpsMixin.astype(self, dtype, copy=copy)
 
-    def _maybe_promote(self, other):
-        if other.inferred_type == "timedelta":
-            other = TimedeltaIndex(other)
-        return self, other
-
     def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
         """
         Can we compare values of the given dtype to our own?