moved condition to maybe helper and added maybe downcast before comparison

Author: arthurlw

pandas/core/indexes/base.py

@@ -3673,14 +3673,7 @@ def get_indexer(
         method = clean_reindex_fill_method(method)
         orig_target = target
         target = self._maybe_cast_listlike_indexer(target)
-
-        from pandas.api.types import is_timedelta64_dtype
-
-        if target.dtype == "string[pyarrow]" and is_timedelta64_dtype(self.dtype):
-            from pandas.core.arrays.timedeltas import sequence_to_td64ns
-
-            data, freq = sequence_to_td64ns(target, copy=False, unit=None)
-            target = type(target)(data)
+        target, self = target._maybe_downcast_for_indexing(self)
 
         self._check_indexing_method(method, limit, tolerance)
 

pandas/core/indexes/datetimelike.py

@@ -415,7 +415,18 @@ def _maybe_cast_listlike_indexer(self, keyarr):
                 # TODO: com.asarray_tuplesafe shouldn't cast e.g. DatetimeArray
             else:
                 res = keyarr
-        return Index(res, dtype=res.dtype)
+
+        res_index = Index(res, dtype=res.dtype)
+
+        if isinstance(res, ExtensionArray):
+            from pandas.core.dtypes.common import is_timedelta64_dtype
+            from pandas.core.arrays.timedeltas import sequence_to_td64ns
+
+            if res_index.dtype == "string[pyarrow]" and is_timedelta64_dtype(self.dtype):
+                data, freq = sequence_to_td64ns(res_index, copy=False, unit=None)
+                res_index = type(res_index)(data)
+
+        return res_index
 
 
 class DatetimeTimedeltaMixin(DatetimeIndexOpsMixin, ABC):

pandas/core/indexes/datetimes.py

@@ -385,17 +385,6 @@ def _is_comparable_dtype(self, dtype: DtypeObj) -> bool:
             # If we have tz, we can compare to tzaware
             return isinstance(dtype, DatetimeTZDtype)
 
-        from pandas import ArrowDtype
-
-        if isinstance(dtype, ArrowDtype):
-            import pyarrow as pa
-
-            return (
-                pa.types.is_date32(dtype.pyarrow_dtype)
-                or pa.types.is_date64(dtype.pyarrow_dtype)
-                or pa.types.is_timestamp(dtype.pyarrow_dtype)
-            )
-
         # if we dont have tz, we can only compare to tznaive
         return lib.is_np_dtype(dtype, "M")