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Avoid pylibcudf.interop.to_arrow in DataFrame.to_polars in cudf_polars #19198

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Merged
merged 3 commits into from
Jun 25, 2025
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Avoid pylibcudf.interop.to_arrow in DataFrame.to_polars in cudf_polars #19198

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90a7e9e
Use a _ObjectWithArrowMetadata wrapper to pass plc table to Polars
mroeschke Jun 18, 2025
5800c8a
Merge remote-tracking branch 'upstream/branch-25.08' into ref/cudf_po…
mroeschke Jun 18, 2025
a2dd6a5
Use CapsuleType from typing_extensions
mroeschke Jun 18, 2025
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20 changes: 17 additions & 3 deletions python/cudf_polars/cudf_polars/containers/dataframe.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@
if TYPE_CHECKING:
from collections.abc import Iterable, Mapping, Sequence, Set

from typing_extensions import Any, Self
from typing_extensions import Any, CapsuleType, Self

from cudf_polars.typing import ColumnOptions, DataFrameHeader, Slice

Expand All @@ -40,6 +40,20 @@ def _create_polars_column_metadata(
return plc.interop.ColumnMetadata(name=name, children_meta=children_meta)


# This is also defined in pylibcudf.interop
class _ObjectWithArrowMetadata:
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I think #18722 is the primary limitation that necessitates this workaround cc @vyasr

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Yes, exactly. Without this you lose the underlying struct fields. This solution is fine for now while we sort out #18722.

def __init__(
self, obj: plc.Table, metadata: list[plc.interop.ColumnMetadata]
) -> None:
self.obj = obj
self.metadata = metadata

def __arrow_c_array__(
self, requested_schema: None = None
) -> tuple[CapsuleType, CapsuleType]:
return self.obj._to_schema(self.metadata), self.obj._to_host_array()


# Pacify the type checker. DataFrame init asserts that all the columns
# have a string name, so let's narrow the type.
class NamedColumn(Column):
Expand Down Expand Up @@ -82,8 +96,8 @@ def to_polars(self) -> pl.DataFrame:
)
for name, col in zip(name_map, self.columns, strict=True)
]
table = plc.interop.to_arrow(self.table, metadata=metadata)
df: pl.DataFrame = pl.from_arrow(table)
table_with_metadata = _ObjectWithArrowMetadata(self.table, metadata)
df = pl.DataFrame(table_with_metadata)
return df.rename(name_map).with_columns(
pl.col(c.name).set_sorted(descending=c.order == plc.types.Order.DESCENDING)
if c.is_sorted
Expand Down