Merge branch-24.12 into branch-25.02

python/cudf/cudf/_lib/copying.pyx

@@ -1,7 +1,5 @@
 # Copyright (c) 2020-2024, NVIDIA CORPORATION.
 
-import pickle
-
 from libcpp cimport bool
 import pylibcudf
 
@@ -358,24 +356,23 @@ class PackedColumns(Serializable):
         header["index-names"] = self.index_names
         header["metadata"] = self._metadata.tobytes()
         for name, dtype in self.column_dtypes.items():
-            dtype_header, dtype_frames = dtype.serialize()
+            dtype_header, dtype_frames = dtype.device_serialize()
             self.column_dtypes[name] = (
                 dtype_header,
                 (len(frames), len(frames) + len(dtype_frames)),
             )
             frames.extend(dtype_frames)
         header["column-dtypes"] = self.column_dtypes
-        header["type-serialized"] = pickle.dumps(type(self))
         return header, frames
 
     @classmethod
     def deserialize(cls, header, frames):
         column_dtypes = {}
         for name, dtype in header["column-dtypes"].items():
             dtype_header, (start, stop) = dtype
-            column_dtypes[name] = pickle.loads(
-                dtype_header["type-serialized"]
-            ).deserialize(dtype_header, frames[start:stop])
+            column_dtypes[name] = Serializable.device_deserialize(
+                dtype_header, frames[start:stop]
+            )
         return cls(
             plc.contiguous_split.pack(
                 plc.contiguous_split.unpack_from_memoryviews(

python/cudf/cudf/core/_base_index.py

@@ -2,7 +2,6 @@
 
 from __future__ import annotations
 
-import pickle
 import warnings
 from functools import cached_property
 from typing import TYPE_CHECKING, Any, Literal
@@ -330,13 +329,6 @@ def get_level_values(self, level):
         else:
             raise KeyError(f"Requested level with name {level} " "not found")
 
-    @classmethod
-    def deserialize(cls, header, frames):
-        # Dispatch deserialization to the appropriate index type in case
-        # deserialization is ever attempted with the base class directly.
-        idx_type = pickle.loads(header["type-serialized"])
-        return idx_type.deserialize(header, frames)
-
     @property
     def names(self):
         """

python/cudf/cudf/core/abc.py

@@ -1,8 +1,6 @@
 # Copyright (c) 2020-2024, NVIDIA CORPORATION.
 """Common abstract base classes for cudf."""
 
-import pickle
-
 import numpy
 
 import cudf
@@ -22,6 +20,14 @@ class Serializable:
     latter converts back from that representation into an equivalent object.
     """
 
+    # A mapping from class names to the classes themselves. This is used to
+    # reconstruct the correct class when deserializing an object.
+    _name_type_map: dict = {}
+
+    def __init_subclass__(cls, /, **kwargs):
+        super().__init_subclass__(**kwargs)
+        cls._name_type_map[cls.__name__] = cls
+
     def serialize(self):
         """Generate an equivalent serializable representation of an object.
 
@@ -98,7 +104,7 @@ def device_serialize(self):
             )
             for f in frames
         )
-        header["type-serialized"] = pickle.dumps(type(self))
+        header["type-serialized-name"] = type(self).__name__
         header["is-cuda"] = [
             hasattr(f, "__cuda_array_interface__") for f in frames
         ]
@@ -128,10 +134,10 @@ def device_deserialize(cls, header, frames):
 
         :meta private:
         """
-        typ = pickle.loads(header["type-serialized"])
+        typ = cls._name_type_map[header["type-serialized-name"]]
         frames = [
             cudf.core.buffer.as_buffer(f) if c else memoryview(f)
-            for c, f in zip(header["is-cuda"], frames)
+            for c, f in zip(header["is-cuda"], frames, strict=True)
         ]
         return typ.deserialize(header, frames)
 

python/cudf/cudf/core/buffer/buffer.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import math
-import pickle
 import weakref
 from types import SimpleNamespace
 from typing import TYPE_CHECKING, Any, Literal
@@ -432,8 +431,7 @@ def serialize(self) -> tuple[dict, list]:
             second element is a list containing single frame.
         """
         header: dict[str, Any] = {}
-        header["type-serialized"] = pickle.dumps(type(self))
-        header["owner-type-serialized"] = pickle.dumps(type(self._owner))
+        header["owner-type-serialized-name"] = type(self._owner).__name__
         header["frame_count"] = 1
         frames = [self]
         return header, frames
@@ -460,7 +458,9 @@ def deserialize(cls, header: dict, frames: list) -> Self:
         if isinstance(frame, cls):
             return frame  # The frame is already deserialized
 
-        owner_type: BufferOwner = pickle.loads(header["owner-type-serialized"])
+        owner_type: BufferOwner = Serializable._name_type_map[
+            header["owner-type-serialized-name"]
+        ]
         if hasattr(frame, "__cuda_array_interface__"):
             owner = owner_type.from_device_memory(frame, exposed=False)
         else:

python/cudf/cudf/core/buffer/spillable_buffer.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import collections.abc
-import pickle
 import time
 import weakref
 from threading import RLock
@@ -415,8 +414,7 @@ def serialize(self) -> tuple[dict, list]:
         header: dict[str, Any] = {}
         frames: list[Buffer | memoryview]
         with self._owner.lock:
-            header["type-serialized"] = pickle.dumps(self.__class__)
-            header["owner-type-serialized"] = pickle.dumps(type(self._owner))
+            header["owner-type-serialized-name"] = type(self._owner).__name__
             header["frame_count"] = 1
             if self.is_spilled:
                 frames = [self.memoryview()]

python/cudf/cudf/core/column/column.py

@@ -2,7 +2,6 @@
 
 from __future__ import annotations
 
-import pickle
 from collections import abc
 from collections.abc import MutableSequence, Sequence
 from functools import cached_property
@@ -1294,28 +1293,27 @@ def serialize(self) -> tuple[dict, list]:
 
         header: dict[Any, Any] = {}
         frames = []
-        header["type-serialized"] = pickle.dumps(type(self))
         try:
-            dtype, dtype_frames = self.dtype.serialize()
+            dtype, dtype_frames = self.dtype.device_serialize()
             header["dtype"] = dtype
             frames.extend(dtype_frames)
             header["dtype-is-cudf-serialized"] = True
         except AttributeError:
-            header["dtype"] = pickle.dumps(self.dtype)
+            header["dtype"] = self.dtype.str
             header["dtype-is-cudf-serialized"] = False
 
         if self.data is not None:
-            data_header, data_frames = self.data.serialize()
+            data_header, data_frames = self.data.device_serialize()
             header["data"] = data_header
             frames.extend(data_frames)
 
         if self.mask is not None:
-            mask_header, mask_frames = self.mask.serialize()
+            mask_header, mask_frames = self.mask.device_serialize()
             header["mask"] = mask_header
             frames.extend(mask_frames)
         if self.children:
             child_headers, child_frames = zip(
-                *(c.serialize() for c in self.children)
+                *(c.device_serialize() for c in self.children)
             )
             header["subheaders"] = list(child_headers)
             frames.extend(chain(*child_frames))
@@ -1327,8 +1325,7 @@ def serialize(self) -> tuple[dict, list]:
     def deserialize(cls, header: dict, frames: list) -> ColumnBase:
         def unpack(header, frames) -> tuple[Any, list]:
             count = header["frame_count"]
-            klass = pickle.loads(header["type-serialized"])
-            obj = klass.deserialize(header, frames[:count])
+            obj = cls.device_deserialize(header, frames[:count])
             return obj, frames[count:]
 
         assert header["frame_count"] == len(frames), (
@@ -1338,7 +1335,7 @@ def unpack(header, frames) -> tuple[Any, list]:
         if header["dtype-is-cudf-serialized"]:
             dtype, frames = unpack(header["dtype"], frames)
         else:
-            dtype = pickle.loads(header["dtype"])
+            dtype = np.dtype(header["dtype"])
         if "data" in header:
             data, frames = unpack(header["data"], frames)
         else:
@@ -2307,7 +2304,9 @@ def serialize_columns(columns: list[ColumnBase]) -> tuple[list[dict], list]:
     frames = []
 
     if len(columns) > 0:
-        header_columns = [c.serialize() for c in columns]
+        header_columns: list[tuple[dict, list]] = [
+            c.device_serialize() for c in columns
+        ]
         headers, column_frames = zip(*header_columns)
         for f in column_frames:
             frames.extend(f)
@@ -2324,7 +2323,7 @@ def deserialize_columns(headers: list[dict], frames: list) -> list[ColumnBase]:
 
     for meta in headers:
         col_frame_count = meta["frame_count"]
-        col_typ = pickle.loads(meta["type-serialized"])
+        col_typ = Serializable._name_type_map[meta["type-serialized-name"]]
         colobj = col_typ.deserialize(meta, frames[:col_frame_count])
         columns.append(colobj)
         # Advance frames

python/cudf/cudf/core/dataframe.py

@@ -7,7 +7,6 @@
 import itertools
 import numbers
 import os
-import pickle
 import re
 import sys
 import textwrap
@@ -50,7 +49,6 @@
 )
 from cudf.core import column, df_protocol, indexing_utils, reshape
 from cudf.core._compat import PANDAS_LT_300
-from cudf.core.abc import Serializable
 from cudf.core.buffer import acquire_spill_lock, as_buffer
 from cudf.core.column import (
     CategoricalColumn,
@@ -588,7 +586,7 @@ class _DataFrameiAtIndexer(_DataFrameIlocIndexer):
     pass
 
 
-class DataFrame(IndexedFrame, Serializable, GetAttrGetItemMixin):
+class DataFrame(IndexedFrame, GetAttrGetItemMixin):
     """
     A GPU Dataframe object.
 
@@ -1190,7 +1188,7 @@ def _constructor_expanddim(self):
     def serialize(self):
         header, frames = super().serialize()
 
-        header["index"], index_frames = self.index.serialize()
+        header["index"], index_frames = self.index.device_serialize()
         header["index_frame_count"] = len(index_frames)
         # For backwards compatibility with older versions of cuDF, index
         # columns are placed before data columns.
@@ -1205,8 +1203,7 @@ def deserialize(cls, header, frames):
             header, frames[header["index_frame_count"] :]
         )
 
-        idx_typ = pickle.loads(header["index"]["type-serialized"])
-        index = idx_typ.deserialize(header["index"], frames[:index_nframes])
+        index = cls.device_deserialize(header["index"], frames[:index_nframes])
         obj.index = index
 
         return obj