Deprecate to/from_dask_dataframe APIs in dask-cudf (#15592)

The `to/from_dask_dataframe` APIs have been obsolete for a long time. It is always better to use `ddf.to_backend("cudf")` or `ddf.to_backend("pandas")` instead.

These APIs are also "dangerous" to use with dask-expr, because the same API names are still used to convert data to/from "legacy" Dask collections. Note that dask-expr also deprecated `to/from_dask_dataframe` in favor of `to/from_legacy_dataframe`, but the conflicting APIs still exist (for now).

Authors:
  - Richard (Rick) Zamora (https://github.com/rjzamora)

Approvers:
  - Charles Blackmon-Luca (https://github.com/charlesbluca)

URL: #15592

docs/dask_cudf/source/api.rst

@@ -13,12 +13,11 @@ Creating and storing DataFrames
 of DataFrames from a variety of storage formats. For on-disk data that
 are not supported directly in Dask-cuDF, we recommend using Dask's
 data reading facilities, followed by calling
-:func:`.from_dask_dataframe` to obtain a Dask-cuDF object.
+:meth:`*.to_backend("cudf")` to obtain a Dask-cuDF object.
 
 .. automodule:: dask_cudf
    :members:
       from_cudf,
-      from_dask_dataframe,
       from_delayed,
       read_csv,
       read_json,

python/dask_cudf/dask_cudf/core.py

@@ -55,9 +55,20 @@ def __repr__(self):
 
     @_dask_cudf_nvtx_annotate
     def to_dask_dataframe(self, **kwargs):
-        """Create a dask.dataframe object from a dask_cudf object"""
-        nullable = kwargs.get("nullable", False)
-        return self.map_partitions(M.to_pandas, nullable=nullable)
+        """Create a dask.dataframe object from a dask_cudf object
+
+        WARNING: This API is deprecated, and may not work properly
+        when query-planning is active. Please use `*.to_backend("pandas")`
+        to convert the underlying data to pandas.
+        """
+
+        warnings.warn(
+            "The `to_dask_dataframe` API is now deprecated. "
+            "Please use `*.to_backend('pandas')` instead.",
+            FutureWarning,
+        )
+
+        return self.to_backend("pandas", **kwargs)
 
 
 concat = dd.concat
@@ -733,6 +744,10 @@ def from_dask_dataframe(df):
     Convert a Dask :class:`dask.dataframe.DataFrame` to a Dask-cuDF
     one.
 
+    WARNING: This API is deprecated, and may not work properly
+    when query-planning is active. Please use `*.to_backend("cudf")`
+    to convert the underlying data to cudf.
+
     Parameters
     ----------
     df : dask.dataframe.DataFrame
@@ -742,7 +757,14 @@ def from_dask_dataframe(df):
     -------
     dask_cudf.DataFrame : A new Dask collection backed by cuDF objects
     """
-    return df.map_partitions(cudf.from_pandas)
+
+    warnings.warn(
+        "The `from_dask_dataframe` API is now deprecated. "
+        "Please use `*.to_backend('cudf')` instead.",
+        FutureWarning,
+    )
+
+    return df.to_backend("cudf")
 
 
 for name in (

python/dask_cudf/dask_cudf/expr/_collection.py

@@ -1,5 +1,6 @@
 # Copyright (c) 2024, NVIDIA CORPORATION.
 
+import warnings
 from functools import cached_property
 
 from dask_expr import (
@@ -22,9 +23,25 @@
 ##
 
 
-# VarMixin can be removed if cudf#15179 is addressed.
-# See: https://github.com/rapidsai/cudf/issues/15179
-class VarMixin:
+class CudfFrameBase(FrameBase):
+    def to_dask_dataframe(self, **kwargs):
+        """Create a dask.dataframe object from a dask_cudf object
+
+        WARNING: This API is deprecated, and may not work properly.
+        Please use `*.to_backend("pandas")` to convert the
+        underlying data to pandas.
+        """
+
+        warnings.warn(
+            "The `to_dask_dataframe` API is now deprecated. "
+            "Please use `*.to_backend('pandas')` instead.",
+            FutureWarning,
+        )
+
+        return self.to_backend("pandas", **kwargs)
+
+    # var can be removed if cudf#15179 is addressed.
+    # See: https://github.com/rapidsai/cudf/issues/15179
     def var(
         self,
         axis=0,
@@ -49,7 +66,7 @@ def var(
         )
 
 
-class DataFrame(VarMixin, DXDataFrame):
+class DataFrame(DXDataFrame, CudfFrameBase):
     @classmethod
     def from_dict(cls, *args, **kwargs):
         with config.set({"dataframe.backend": "cudf"}):
@@ -94,7 +111,7 @@ def read_text(*args, **kwargs):
         return from_legacy_dataframe(ddf)
 
 
-class Series(VarMixin, DXSeries):
+class Series(DXSeries, CudfFrameBase):
     def groupby(self, by, **kwargs):
         from dask_cudf.expr._groupby import SeriesGroupBy
 
@@ -113,7 +130,7 @@ def struct(self):
         return StructMethods(self)
 
 
-class Index(DXIndex):
+class Index(DXIndex, CudfFrameBase):
     pass  # Same as pandas (for now)
 
 

python/dask_cudf/dask_cudf/io/tests/test_parquet.py

@@ -113,7 +113,7 @@ def test_roundtrip_from_dask_none_index_false(tmpdir):
 @pytest.mark.parametrize("write_meta", [True, False])
 def test_roundtrip_from_dask_cudf(tmpdir, write_meta):
     tmpdir = str(tmpdir)
-    gddf = dask_cudf.from_dask_dataframe(ddf)
+    gddf = ddf.to_backend("cudf")
     gddf.to_parquet(tmpdir, write_metadata_file=write_meta)
 
     gddf2 = dask_cudf.read_parquet(tmpdir, calculate_divisions=True)

python/dask_cudf/dask_cudf/tests/test_core.py

@@ -32,6 +32,30 @@ def test_from_dict_backend_dispatch():
     dd.assert_eq(expect, ddf)
 
 
+def test_to_dask_dataframe_deprecated():
+    gdf = cudf.DataFrame({"a": range(100)})
+    ddf = dd.from_pandas(gdf, npartitions=2)
+    assert isinstance(ddf._meta, cudf.DataFrame)
+
+    with pytest.warns(FutureWarning, match="API is now deprecated"):
+        assert isinstance(
+            ddf.to_dask_dataframe()._meta,
+            pd.DataFrame,
+        )
+
+
+def test_from_dask_dataframe_deprecated():
+    gdf = pd.DataFrame({"a": range(100)})
+    ddf = dd.from_pandas(gdf, npartitions=2)
+    assert isinstance(ddf._meta, pd.DataFrame)
+
+    with pytest.warns(FutureWarning, match="API is now deprecated"):
+        assert isinstance(
+            dask_cudf.from_dask_dataframe(ddf)._meta,
+            cudf.DataFrame,
+        )
+
+
 def test_to_backend():
     np.random.seed(0)
     data = {

python/dask_cudf/dask_cudf/tests/test_groupby.py

@@ -562,9 +562,9 @@ def test_groupby_reset_index_string_name():
 def test_groupby_categorical_key():
     # See https://github.com/rapidsai/cudf/issues/4608
     df = dask.datasets.timeseries()
-    gddf = dask_cudf.from_dask_dataframe(df)
+    gddf = df.to_backend("cudf")
     gddf["name"] = gddf["name"].astype("category")
-    ddf = gddf.to_dask_dataframe()
+    ddf = gddf.to_backend("pandas")
 
     got = gddf.groupby("name", sort=True).agg(
         {"x": ["mean", "max"], "y": ["mean", "count"]}