Remove workaround for large strings in arrow schema

Now libcudf supports interop from arrow large strings, no need for
the cast. While here, handle casting of nested lists as well.

python/cudf_polars/cudf_polars/dsl/ir.py

@@ -29,7 +29,7 @@
 
 import cudf_polars.dsl.expr as expr
 from cudf_polars.containers import DataFrame, NamedColumn
-from cudf_polars.utils import sorting
+from cudf_polars.utils import dtypes, sorting
 
 if TYPE_CHECKING:
     from collections.abc import MutableMapping
@@ -292,15 +292,10 @@ def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
         table = pdf.to_arrow()
         schema = table.schema
         for i, field in enumerate(schema):
-            # TODO: Nested types
-            if field.type == pa.large_string():
-                # TODO: goes away when libcudf supports large strings
-                schema = schema.set(i, pa.field(field.name, pa.string()))
-            elif isinstance(field.type, pa.LargeListType):
-                # TODO: goes away when libcudf supports large lists
-                schema = schema.set(
-                    i, pa.field(field.name, pa.list_(field.type.field(0)))
-                )
+            schema = schema.set(
+                i, pa.field(field.name, dtypes.downcast_arrow_lists(field.type))
+            )
+        # No-op if the schema is unchanged.
         table = table.cast(schema)
         df = DataFrame.from_table(
             plc.interop.from_arrow(table), list(self.schema.keys())

python/cudf_polars/cudf_polars/utils/dtypes.py

@@ -7,13 +7,42 @@
 
 from functools import cache
 
+import pyarrow as pa
 from typing_extensions import assert_never
 
 import polars as pl
 
 import cudf._lib.pylibcudf as plc
 
-__all__ = ["from_polars"]
+__all__ = ["from_polars", "downcast_arrow_lists"]
+
+
+def downcast_arrow_lists(typ: pa.DataType) -> pa.DataType:
+    """
+    Sanitize an arrow datatype from polars.
+
+    Parameters
+    ----------
+    typ
+        Arrow type to sanitize
+
+    Returns
+    -------
+    Sanitized arrow type
+
+    Notes
+    -----
+    As well as arrow ``ListType``s, polars can produce
+    ``LargeListType``s and ``FixedSizeListType``s, these are not
+    currently handled by libcudf, so we attempt to cast them all into
+    normal ``ListType``s on the arrow side before consuming the arrow
+    data.
+    """
+    if isinstance(typ, pa.LargeListType):
+        return pa.list_(downcast_arrow_lists(typ.value_type))
+    # We don't have to worry about diving into struct types for now
+    # since those are always NotImplemented before we get here.
+    return typ
 
 
 @cache

python/cudf_polars/tests/test_dataframescan.py

@@ -41,3 +41,22 @@ def test_scan_drop_nulls(subset, predicate_pushdown):
     assert_gpu_result_equal(
         q, collect_kwargs={"predicate_pushdown": predicate_pushdown}
     )
+
+
+def test_can_convert_lists():
+    df = pl.LazyFrame(
+        {
+            "a": pl.Series([[1, 2], [3]], dtype=pl.List(pl.Int8())),
+            "b": pl.Series([[1], [2]], dtype=pl.List(pl.UInt16())),
+            "c": pl.Series(
+                [
+                    [["1", "2", "3"], ["4", "567"]],
+                    [["8", "9"], []],
+                ],
+                dtype=pl.List(pl.List(pl.String())),
+            ),
+            "d": pl.Series([[[1, 2]], []], dtype=pl.List(pl.List(pl.UInt16()))),
+        }
+    )
+
+    assert_gpu_result_equal(df)