BUG/REG: multiindex nested tuples with duplicates

pandas/core/indexes/multi.py

@@ -2643,7 +2643,8 @@ def _maybe_to_slice(loc):
             mask[loc] = True
             return mask
 
-        if not isinstance(key, tuple):
+        if not isinstance(key, (tuple, list)):
+            # not including list here breaks some indexing, xref #30892
             loc = self._get_level_indexer(key, level=0)
             return _maybe_to_slice(loc)
 

pandas/core/indexing.py

@@ -28,6 +28,7 @@
     length_of_indexer,
 )
 from pandas.core.indexes.api import Index
+from pandas.core.indexes.base import InvalidIndexError
 
 # "null slice"
 _NS = slice(None, None)
@@ -606,7 +607,7 @@ def _get_setitem_indexer(self, key):
         if isinstance(ax, ABCMultiIndex) and self.name != "iloc":
             try:
                 return ax.get_loc(key)
-            except (TypeError, KeyError):
+            except (TypeError, KeyError, InvalidIndexError):
                 # TypeError e.g. passed a bool
                 pass
 

pandas/tests/indexes/multi/test_indexing.py

@@ -396,7 +396,7 @@ def test_get_loc_missing_nan():
         idx.get_loc(3)
     with pytest.raises(KeyError, match=r"^nan$"):
         idx.get_loc(np.nan)
-    with pytest.raises(TypeError, match=r"'\[nan\]' is an invalid key"):
+    with pytest.raises(TypeError, match="unhashable type: 'list'"):
         # listlike/non-hashable raises TypeError
         idx.get_loc([np.nan])
 

pandas/tests/indexing/multiindex/test_multiindex.py

@@ -92,3 +92,22 @@ def test_contains(self):
         assert tx[0] in idx
         assert "element_not_exit" not in idx
         assert "0 day 09:30:00" in idx
+
+    def test_nested_tuples_duplicates(self):
+        # GH#30892
+
+        dti = pd.to_datetime(["20190101", "20190101", "20190102"])
+        idx = pd.Index(["a", "a", "c"])
+        mi = pd.MultiIndex.from_arrays([dti, idx], names=["index1", "index2"])
+
+        df = pd.DataFrame({"c1": [1, 2, 3], "c2": [np.nan, np.nan, np.nan]}, index=mi)
+
+        expected = pd.DataFrame({"c1": df["c1"], "c2": [1.0, 1.0, np.nan]}, index=mi)
+
+        df2 = df.copy(deep=True)
+        df2.loc[(dti[0], "a"), "c2"] = 1.0
+        tm.assert_frame_equal(df2, expected)
+
+        df3 = df.copy(deep=True)
+        df3.loc[[(dti[0], "a")], "c2"] = 1.0
+        tm.assert_frame_equal(df3, expected)