BUG: refactor _is_key_type_compatible and update test for MultiIndex datetime/date type checking (GH#55969)

Author: Roxicaro

pandas/core/indexes/multi.py

@@ -31,6 +31,7 @@
     lib,
 )
 from pandas._libs.hashtable import duplicated
+from pandas._libs.tslibs.timestamps import Timestamp
 from pandas._typing import (
     AnyAll,
     AnyArrayLike,
@@ -3611,25 +3612,34 @@ def maybe_mi_droplevels(indexer, levels):
 
     def _is_key_type_compatible(self, key, level):
         """
-        Return True if the key type is compatible with the type of the level's values.
+        Return True if the key is compatible with the type of the level's values.
         """
         if len(self.levels[level]) == 0:
             return True  # nothing to compare
-        level_type = type(self.levels[level][0])
 
-        # Same type → OK
-        if isinstance(key, level_type):
+        level_type = self.levels[level][0]
+
+        # Allow slices (used in partial indexing)
+        if isinstance(key, slice):
             return True
-        # Allow Python int for numpy integer types
-        if isinstance(level_type, np.integer) and isinstance(key, int):
+
+        # datetime/date/Timestamp compatibility
+        datetime_types = (datetime.date, np.datetime64, Timestamp)
+        if isinstance(level_type, datetime_types) and isinstance(
+            key, datetime_types + (str,)
+        ):
             return True
 
-        # Allow Python float for numpy float types
-        if isinstance(level_type, np.floating) and isinstance(key, float):
+        # numeric compatibility
+        if np.issubdtype(type(level_type), np.integer) and isinstance(key, int):
+            return True
+        if np.issubdtype(type(level_type), np.floating) and isinstance(
+            key, (int, float)
+        ):
             return True
 
-        # Allow subclasses of datetime.date for datetime levels
-        if isinstance(level_type, datetime.date) and isinstance(key, datetime.date):
+        # string compatibility
+        if isinstance(level_type, str) and isinstance(key, str):
             return True
 
         return False

pandas/tests/indexes/multi/test_datetime_indexing.py

@@ -1,4 +1,4 @@
-import datetime
+import datetime as dt
 
 import numpy as np
 import pytest
@@ -7,9 +7,20 @@
 
 
 def test_multiindex_date_npdatetime_mismatch_raises():
-    idx = pd.MultiIndex.from_product(
-        [[datetime.date(2023, 11, 1)], ["A"], ["C"]], names=["date", "t1", "t2"]
+    dates = [dt.date(2023, 11, 1), dt.date(2023, 11, 1), dt.date(2023, 11, 2)]
+    t1 = ["A", "B", "C"]
+    t2 = ["C", "D", "E"]
+    vals = [10, 20, 30]
+
+    df = pd.DataFrame(
+        data=np.array([dates, t1, t2, vals]).T, columns=["dates", "t1", "t2", "vals"]
     )
-    df = pd.DataFrame({"vals": [1]}, index=idx)
-    with pytest.raises(TypeError, match="Type mismatch"):
+    df.set_index(["dates", "t1", "t2"], inplace=True)
+
+    # Exact type match
+    result = df.loc[(dt.date(2023, 11, 1), "A", "C")]
+    assert result["vals"] == 10
+
+    # TypeError
+    with pytest.raises(KeyError):
         df.loc[(np.datetime64("2023-11-01"), "A", "C")]