Ensure DataFrame column types are preserved during serialization

python/cudf/cudf/core/frame.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2020-2023, NVIDIA CORPORATION.
+# Copyright (c) 2020-2024, NVIDIA CORPORATION.
 
 from __future__ import annotations
 
@@ -99,9 +99,14 @@ def _has_nulls(self):
 
     @_cudf_nvtx_annotate
     def serialize(self):
+        # TODO: See if self._data can be serialized outright
         header = {
             "type-serialized": pickle.dumps(type(self)),
             "column_names": pickle.dumps(tuple(self._data.names)),
+            "column_rangeindex": pickle.dumps(self._data.rangeindex),
+            "column_multiindex": pickle.dumps(self._data.multiindex),
+            "column_label_dtype": pickle.dumps(self._data.label_dtype),
+            "column_level_names": pickle.dumps(self._data._level_names),
         }
         header["columns"], frames = serialize_columns(self._columns)
         return header, frames
@@ -112,7 +117,20 @@ def deserialize(cls, header, frames):
         cls_deserialize = pickle.loads(header["type-serialized"])
         column_names = pickle.loads(header["column_names"])
         columns = deserialize_columns(header["columns"], frames)
-        return cls_deserialize._from_data(dict(zip(column_names, columns)))
+        kwargs = {}
+        for metadata in [
+            "rangeindex",
+            "multiindex",
+            "label_dtype",
+            "level_names",
+        ]:
+            key = f"column_{metadata}"
+            if key in header:
+                kwargs[metadata] = pickle.loads(header[key])
+        col_accessor = ColumnAccessor(
+            data=dict(zip(column_names, columns)), **kwargs
+        )
+        return cls_deserialize._from_data(col_accessor)
 
     @classmethod
     @_cudf_nvtx_annotate

python/cudf/cudf/tests/test_serialize.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2018-2023, NVIDIA CORPORATION.
+# Copyright (c) 2018-2024, NVIDIA CORPORATION.
 
 import pickle
 
@@ -8,7 +8,6 @@
 import pytest
 
 import cudf
-from cudf.core._compat import PANDAS_GE_200
 from cudf.testing import _utils as utils
 from cudf.testing._utils import assert_eq
 
@@ -302,12 +301,9 @@ def test_serialize_string():
     "frames",
     [
         (cudf.Series([], dtype="str"), pd.Series([], dtype="str")),
-        pytest.param(
-            (cudf.DataFrame([]), pd.DataFrame([])),
-            marks=pytest.mark.xfail(
-                not PANDAS_GE_200, reason=".column returns Index[object]"
-            ),
-        ),
+        (cudf.DataFrame(), pd.DataFrame()),
+        (cudf.DataFrame([]), pd.DataFrame([])),
+        (cudf.DataFrame({}), pd.DataFrame({})),
         (cudf.DataFrame([1]).head(0), pd.DataFrame([1]).head(0)),
         (cudf.DataFrame({"a": []}), pd.DataFrame({"a": []})),
         (
@@ -401,3 +397,19 @@ def test_serialize_sliced_string():
 
     recreated = cudf.Series.deserialize(*sliced.serialize())
     assert_eq(recreated.to_pandas(nullable=True), pd_series)
+
+
+@pytest.mark.parametrize(
+    "columns",
+    [
+        cudf.RangeIndex(2),
+        cudf.Index([1, 2], dtype="int8"),
+        cudf.MultiIndex(
+            levels=[["a", "b"], [1, 2]], codes=[[0, 1], [0, 1]], names=["a", 0]
+        ),
+    ],
+)
+def test_serialize_column_types_preserved(columns):
+    expected = cudf.DataFrame([[10, 11]], columns=columns)
+    result = cudf.DataFrame.deserialize(*expected.serialize())
+    assert_eq(result, expected)