Backport PR pandas-dev#58043: BUG: DataFrame slice selection treated as hashable in Python 3.12 pandas-dev#57500

Author: tehunter

doc/source/whatsnew/v2.3.4.rst

@@ -0,0 +1,21 @@
+.. _whatsnew_234:
+
+What's new in 2.3.4 (November XX, 2025)
+----------------------------------------
+
+These are the changes in pandas 2.3.3. See :ref:`release` for a full changelog
+including other versions of pandas.
+
+{{ header }}
+
+.. ---------------------------------------------------------------------------
+
+Bug fixes
+^^^^^^^^^
+- Bug in :meth:`DataFrame.__getitem__` returning modified columns when called with ``slice`` in Python 3.12 (:issue:`57500`)
+
+.. ---------------------------------------------------------------------------
+.. _whatsnew_234.contributors:
+
+Contributors
+~~~~~~~~~~~~

pandas/core/frame.py

@@ -4075,8 +4075,10 @@ def __getitem__(self, key):
         key = lib.item_from_zerodim(key)
         key = com.apply_if_callable(key, self)
 
-        if is_hashable(key) and not is_iterator(key):
+        if is_hashable(key) and not is_iterator(key) and not isinstance(key, slice):
             # is_iterator to exclude generator e.g. test_getitem_listlike
+            # As of Python 3.12, slice is hashable which breaks MultiIndex (GH#57500)
+
             # shortcut if the key is in columns
             is_mi = isinstance(self.columns, MultiIndex)
             # GH#45316 Return view if key is not duplicated

pandas/tests/frame/indexing/test_indexing.py

@@ -538,6 +538,16 @@ def test_loc_setitem_boolean_mask_allfalse(self):
         result.loc[result.b.isna(), "a"] = result.a.copy()
         tm.assert_frame_equal(result, df)
 
+    def test_getitem_slice_empty(self):
+        df = DataFrame([[1]], columns=MultiIndex.from_product([["A"], ["a"]]))
+        result = df[:]
+
+        expected = DataFrame([[1]], columns=MultiIndex.from_product([["A"], ["a"]]))
+
+        tm.assert_frame_equal(result, expected)
+        # Ensure df[:] returns a view of df, not the same object
+        assert result is not df
+
     def test_getitem_fancy_slice_integers_step(self):
         df = DataFrame(np.random.default_rng(2).standard_normal((10, 5)))