BUG: Remove special-casing for date objects in DatetimeIndex indexing (GH#62158)

pandas/core/indexes/base.py

@@ -39,7 +39,6 @@
     no_default,
 )
 from pandas._libs.tslibs import (
-    OutOfBoundsDatetime,
     Timestamp,
     tz_compare,
 )
@@ -6204,11 +6203,6 @@ def _maybe_downcast_for_indexing(self, other: Index) -> tuple[Index, Index]:
                 # standardize on UTC
                 return self.tz_convert("UTC"), other.tz_convert("UTC")
 
-        elif self.inferred_type == "date" and isinstance(other, ABCDatetimeIndex):
-            try:
-                return type(other)(self), other
-            except OutOfBoundsDatetime:
-                return self, other
         elif self.inferred_type == "timedelta" and isinstance(other, ABCTimedeltaIndex):
             # TODO: we dont have tests that get here
             return type(other)(self), other

pandas/core/indexes/datetimes.py

@@ -629,7 +629,13 @@ def get_loc(self, key):
     def _maybe_cast_slice_bound(self, label, side: str):
         # GH#42855 handle date here instead of get_slice_bound
         if isinstance(label, dt.date) and not isinstance(label, dt.datetime):
-            # Pandas supports slicing with dates, treated as datetimes at midnight.
+            warnings.warn(
+                "Indexing/slicing with datetime.date is deprecated and will be removed "
+                "in a future version of pandas. Please convert to pd.Timestamp or "
+                "datetime64[ns] before indexing.",
+                FutureWarning,
+                stacklevel=2,
+            )
             # https://github.com/pandas-dev/pandas/issues/31501
             label = Timestamp(label).to_pydatetime()
 

pandas/tests/frame/indexing/test_indexing.py

@@ -1880,6 +1880,17 @@ def test_add_new_column_infer_string():
     tm.assert_frame_equal(df, expected)
 
 
+def test_datetime_indexer_consistency_pyarrow_date32():
+    # GH#62158
+    ser = Series(["2016-01-01"], dtype="date32[pyarrow]")
+    ser3 = ser.astype("datetime64[ns]")
+    dti = Index(ser3)
+    # All should be consistent
+    assert dti.get_loc(ser[0]) == 0
+    tm.assert_numpy_array_equal(dti.get_indexer(ser.values), [0])
+    tm.assert_numpy_array_equal(dti.get_indexer(ser.values.astype(object)), [0])
+
+
 class TestSetitemValidation:
     # This is adapted from pandas/tests/arrays/masked/test_indexing.py
     def _check_setitem_invalid(self, df, invalid, indexer):

pandas/tests/frame/methods/test_asfreq.py

@@ -190,7 +190,7 @@ def test_asfreq_with_date_object_index(self, frame_or_series):
         ts = frame_or_series(np.random.default_rng(2).standard_normal(20), index=rng)
 
         ts2 = ts.copy()
-        ts2.index = [x.date() for x in ts2.index]
+        ts2.index = to_datetime([x.date() for x in ts2.index])
 
         result = ts2.asfreq("4h", method="ffill")
         expected = ts.asfreq("4h", method="ffill")

pandas/tests/indexes/datetimes/test_indexing.py

@@ -562,17 +562,22 @@ def test_get_indexer(self):
             idx.get_indexer(idx[[0]], method="nearest", tolerance="foo")
 
     @pytest.mark.parametrize(
-        "target",
+        "target, expected",
         [
-            [date(2020, 1, 1), Timestamp("2020-01-02")],
-            [Timestamp("2020-01-01"), date(2020, 1, 2)],
+            (
+                [date(2020, 1, 1), Timestamp("2020-01-02")],
+                np.array([-1, 1], dtype=np.intp),
+            ),
+            (
+                [Timestamp("2020-01-01"), Timestamp(date(2020, 1, 2))],
+                np.array([0, 1], dtype=np.intp),
+            ),
         ],
     )
-    def test_get_indexer_mixed_dtypes(self, target):
+    def test_get_indexer_mixed_dtypes(self, target, expected):
         # https://github.com/pandas-dev/pandas/issues/33741
         values = DatetimeIndex([Timestamp("2020-01-01"), Timestamp("2020-01-02")])
         result = values.get_indexer(target)
-        expected = np.array([0, 1], dtype=np.intp)
         tm.assert_numpy_array_equal(result, expected)
 
     @pytest.mark.parametrize(

pandas/tests/series/test_arithmetic.py

@@ -763,7 +763,8 @@ def test_align_date_objects_with_datetimeindex(self):
 
         ts_slice = ts[5:]
         ts2 = ts_slice.copy()
-        ts2.index = [x.date() for x in ts2.index]
+        # Explicitly convert date objects to Timestamps for alignment
+        ts2.index = [pd.Timestamp(x.date()) for x in ts2.index]
 
         result = ts + ts2
         result2 = ts2 + ts