Remove dataframe protocol (#17909)

Follow-up to #17736

Authors:
  - Vyas Ramasubramani (https://github.com/vyasr)
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Matthew Roeschke (https://github.com/mroeschke)
  - GALI PREM SAGAR (https://github.com/galipremsagar)

URL: #17909

docs/cudf/source/user_guide/api_docs/general_functions.rst

@@ -26,7 +26,6 @@ Top-level conversions
    :toctree: api/
 
    to_numeric
-   from_dataframe
    from_dlpack
    from_pandas
 

python/cudf/cudf/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2018-2024, NVIDIA CORPORATION.
+# Copyright (c) 2018-2025, NVIDIA CORPORATION.
 
 # If libcudf was installed as a wheel, we must request it to load the library symbols.
 # Otherwise, we assume that the library was installed in a system path that ld can find.
@@ -36,7 +36,7 @@
 from cudf.api.types import dtype
 from cudf.core.algorithms import factorize, unique
 from cudf.core.cut import cut
-from cudf.core.dataframe import DataFrame, from_dataframe, from_pandas, merge
+from cudf.core.dataframe import DataFrame, from_pandas, merge
 from cudf.core.dtypes import (
     CategoricalDtype,
     Decimal32Dtype,

python/cudf/cudf/core/dataframe.py

@@ -27,7 +27,6 @@
 import pandas as pd
 import pyarrow as pa
 from nvtx import annotate
-from packaging import version
 from pandas.io.formats import console
 from pandas.io.formats.printing import pprint_thing
 from typing_extensions import Self, assert_never
@@ -48,7 +47,7 @@
     is_scalar,
     is_string_dtype,
 )
-from cudf.core import column, df_protocol, indexing_utils, reshape
+from cudf.core import column, indexing_utils, reshape
 from cudf.core._compat import PANDAS_LT_300
 from cudf.core.buffer import acquire_spill_lock, as_buffer
 from cudf.core.column import (
@@ -5564,16 +5563,6 @@ def from_pandas(cls, dataframe, nan_as_null=no_default):
             # Checks duplicate columns and sets column metadata
             df.columns = dataframe.columns
             return df
-        elif hasattr(dataframe, "__dataframe__"):
-            # TODO: Probably should be handled in the constructor as
-            # this isn't pandas specific
-            assert version.parse(cudf.__version__) < version.parse("25.04.00")
-            warnings.warn(
-                "Support for loading dataframes via the `__dataframe__` interchange "
-                "protocol is deprecated",
-                FutureWarning,
-            )
-            return from_dataframe(dataframe, allow_copy=True)
         else:
             raise TypeError(
                 f"Could not construct DataFrame from {type(dataframe)}"
@@ -7730,15 +7719,6 @@ def pct_change(
             periods=periods, freq=freq, **kwargs
         )
 
-    def __dataframe__(
-        self, nan_as_null: bool = False, allow_copy: bool = True
-    ):
-        assert version.parse(cudf.__version__) < version.parse("25.04.00")
-        warnings.warn("Using `__dataframe__` is deprecated", FutureWarning)
-        return df_protocol.__dataframe__(
-            self, nan_as_null=nan_as_null, allow_copy=allow_copy
-        )
-
     def nunique(self, axis=0, dropna: bool = True) -> Series:
         """
         Count number of distinct elements in specified axis.
@@ -8183,29 +8163,6 @@ def from_pylibcudf(cls, table: plc.Table, metadata: dict) -> Self:
         return df
 
 
-def from_dataframe(df, allow_copy: bool = False) -> DataFrame:
-    """
-    Build a :class:`DataFrame` from an object supporting the dataframe interchange protocol.
-
-    .. note::
-
-        If you have a ``pandas.DataFrame``, use :func:`from_pandas` instead.
-
-    Parameters
-    ----------
-    df : DataFrameXchg
-        Object supporting the interchange protocol, i.e. ``__dataframe__`` method.
-    allow_copy : bool, default: True
-        Whether to allow copying the memory to perform the conversion
-        (if false then zero-copy approach is requested).
-
-    Returns
-    -------
-    :class:`DataFrame`
-    """
-    return df_protocol.from_dataframe(df, allow_copy=allow_copy)
-
-
 def make_binop_func(op, postprocess=None):
     # This function is used to wrap binary operations in Frame with an
     # appropriate API for DataFrame as required for pandas compatibility. The