BUG: pd.unique(Index) now returns Index as Index.unique

doc/source/whatsnew/v3.0.0.rst

@@ -383,6 +383,7 @@ Other
 ^^^^^
 - Bug in :class:`DataFrame` when passing a ``dict`` with a NA scalar and ``columns`` that would always return ``np.nan`` (:issue:`57205`)
 - Bug in :func:`tseries.api.guess_datetime_format` would fail to infer time format when "%Y" == "%H%M" (:issue:`57452`)
+- Bug in :func:`unique` on :class:`Index` not always returning :class:`Index` (:issue:`57043`)
 - Bug in :meth:`DataFrame.sort_index` when passing ``axis="columns"`` and ``ignore_index=True`` and ``ascending=False`` not returning a :class:`RangeIndex` columns (:issue:`57293`)
 - Bug in :meth:`DataFrame.where` where using a non-bool type array in the function would return a ``ValueError`` instead of a ``TypeError`` (:issue:`56330`)
 - Bug in Dataframe Interchange Protocol implementation was returning incorrect results for data buffers' associated dtype, for string and datetime columns (:issue:`54781`)

pandas/core/algorithms.py

@@ -439,6 +439,10 @@ def unique_with_mask(values, mask: npt.NDArray[np.bool_] | None = None):
         # Dispatch to extension dtype's unique.
         return values.unique()
 
+    if isinstance(values, ABCIndex):
+        # Dispatch to Index's unique.
+        return values.unique()
+
     original = values
     hashtable, values = _get_hashtable_algo(values)
 

pandas/tests/test_algos.py

@@ -570,6 +570,13 @@ def test_object_refcount_bug(self):
         for i in range(1000):
             len(algos.unique(lst))
 
+    def test_index_returned(self, index):
+        # GH#57043
+        index = index.repeat(2)
+        result = algos.unique(index)
+        expected = index.unique()
+        tm.assert_index_equal(result, expected, exact=True)
+
     def test_on_index_object(self):
         mindex = MultiIndex.from_arrays(
             [np.arange(5).repeat(5), np.tile(np.arange(5), 5)]
@@ -579,7 +586,7 @@ def test_on_index_object(self):
 
         mindex = mindex.repeat(2)
 
-        result = pd.unique(mindex)
+        result = pd.unique(mindex).values
         result.sort()
 
         tm.assert_almost_equal(result, expected)
@@ -639,7 +646,7 @@ def test_datetime64_dtype_array_returned(self):
             ]
         )
         result = algos.unique(dt_index)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_index_equal(result, to_datetime(expected))
         assert result.dtype == expected.dtype
 
         s = Series(dt_index)
@@ -670,7 +677,7 @@ def test_timedelta64_dtype_array_returned(self):
 
         td_index = to_timedelta([31200, 45678, 31200, 10000, 45678])
         result = algos.unique(td_index)
-        tm.assert_numpy_array_equal(result, expected)
+        tm.assert_index_equal(result, to_timedelta(expected))
         assert result.dtype == expected.dtype
 
         s = Series(td_index)