Pin Polars<1.43

.pre-commit-config.yaml

@@ -39,7 +39,7 @@ repos:
     hooks:
       - id: mypy
         additional_dependencies: [
-          "polars>=1.35,<1.39",
+          "polars>=1.35,<1.43",
           "numpy>=1.26",
           "pyarrow-stubs>=19.0",
           "pyarrow>=19.0.0,<24.0.0",  # https://github.com/rapidsai/cudf/issues/22229

ci/test_narwhals.sh

@@ -1,5 +1,5 @@
 #!/bin/bash
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 set -euo pipefail
@@ -122,6 +122,9 @@ PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 \
 # test_dtypes: narwhals' dtype mapping changed with polars 1.40 (reports Object where the test expects Int8).
 # test_namespace_len[polars[lazy]]: len() row count lost in zero-column streaming chunks
 #   (https://github.com/rapidsai/cudf/issues/21428).
+# test_explode_*[polars[lazy]-*]: polars 1.42 emits a DeprecationWarning when explode() is called
+#   without empty_as_null=True; narwhals 2.16.0 doesn't pass the kwarg yet, so filterwarnings=error
+#   turns this into a failure. Remove once narwhals is updated.
 TESTS_THAT_NEED_NARWHALS_FIX_FOR_CUDF_POLARS=" \
 test_dtypes or \
 test_namespace_len[polars[lazy]] or \
@@ -131,7 +134,8 @@ test_to_datetime_tz_aware[polars[lazy]-None] or \
 test_truncate[polars[lazy]-1ns-expected0] or \
 test_truncate_multiples[polars[lazy]-2ns-expected0] or \
 ((test_nested_structures and polars and lazy) and (value0 or value1 or value3 or value4 or value6 or value7)) or \
-(test_series_from_iterable and pandas) \
+(test_series_from_iterable and pandas) or \
+(test_explode and polars and lazy) \
 "
 
 rapids-logger "Run narwhals tests for cuDF Polars"

conda/environments/all_cuda-129_arch-aarch64.yaml

@@ -74,7 +74,7 @@ dependencies:
 - packaging
 - pandas>=3.0.0,<3.0.4a0
 - pandoc
-- polars>=1.35,<1.42
+- polars>=1.35,<1.43
 - pre-commit
 - pyarrow>=19.0.0,<24
 - pytables

conda/environments/all_cuda-129_arch-x86_64.yaml

@@ -74,7 +74,7 @@ dependencies:
 - packaging
 - pandas>=3.0.0,<3.0.4a0
 - pandoc
-- polars>=1.35,<1.42
+- polars>=1.35,<1.43
 - pre-commit
 - pyarrow>=19.0.0,<24
 - pytables

conda/environments/all_cuda-133_arch-aarch64.yaml

@@ -74,7 +74,7 @@ dependencies:
 - packaging
 - pandas>=3.0.0,<3.0.4a0
 - pandoc
-- polars>=1.35,<1.42
+- polars>=1.35,<1.43
 - pre-commit
 - pyarrow>=19.0.0,<24
 - pytables

conda/environments/all_cuda-133_arch-x86_64.yaml

@@ -74,7 +74,7 @@ dependencies:
 - packaging
 - pandas>=3.0.0,<3.0.4a0
 - pandoc
-- polars>=1.35,<1.42
+- polars>=1.35,<1.43
 - pre-commit
 - pyarrow>=19.0.0,<24
 - pytables

conda/recipes/cudf-polars/recipe.yaml

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION.
+# SPDX-FileCopyrightText: Copyright (c) 2018-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 schema_version: 1
 
@@ -38,7 +38,7 @@ requirements:
     - pylibcudf =${{ version }}
     - rapidsmpf =${{ minor_version }}
     - cudf-streaming =${{ version }}
-    - polars>=1.35,<1.42
+    - polars>=1.35,<1.43
     - packaging
     - ${{ pin_compatible("cuda-version", upper_bound="x", lower_bound="x") }}
     - if: cuda_major == "12"

dependencies.yaml

@@ -589,7 +589,7 @@ files:
   test_cudf_polars_compat:
     output: none
     matrix:
-      polars_compat_version: ["1.35", "1.36", "1.37", "1.38", "1.39", "1.40", "1.41"]
+      polars_compat_version: ["1.35", "1.36", "1.37", "1.38", "1.39", "1.40", "1.41", "1.42"]
     includes:
       - test_cudf_polars_compat
 channels:
@@ -967,7 +967,7 @@ dependencies:
           # 'nvidia-ml-py' provides the 'pynvml' module
           - &nvidia_ml_py nvidia-ml-py>=12
           - packaging
-          - polars>=1.35,<1.42
+          - polars>=1.35,<1.43
           - typing_extensions>=4.0.0
   run_cudf_polars_dask:
     common:
@@ -1741,5 +1741,9 @@ dependencies:
               polars_compat_version: "1.41"
             packages:
               - polars==1.41.*
+          - matrix:
+              polars_compat_version: "1.42"
+            packages:
+              - polars==1.42.*
           - matrix:
             packages:

python/cudf_polars/cudf_polars/containers/dataframe.py

@@ -73,7 +73,7 @@ def __init__(
         self.stream = stream
 
     def __arrow_c_array__(
-        self, requested_schema: None = None
+        self, requested_schema: object | None = None
     ) -> tuple[CapsuleType, CapsuleType]:
         return self.obj._to_schema(self.metadata), self.obj._to_host_array(
             stream=self.stream

python/cudf_polars/cudf_polars/dsl/expressions/boolean.py

@@ -65,6 +65,7 @@ class Name(IntEnum):
         IsNotNan = auto()
         IsNotNull = auto()
         IsNull = auto()
+        IsSorted = auto()
         IsUnique = auto()
         Not = auto()
 
@@ -100,6 +101,7 @@ def __init__(
             BooleanFunction.Name.IsDuplicated,
             BooleanFunction.Name.IsFirstDistinct,
             BooleanFunction.Name.IsLastDistinct,
+            BooleanFunction.Name.IsSorted,
             BooleanFunction.Name.IsUnique,
         )
         if self.name in {
@@ -409,6 +411,26 @@ def do_evaluate(
                 ),
                 dtype=self.dtype,
             )
+        elif self.name is BooleanFunction.Name.IsSorted:
+            (column,) = columns
+            (descending, nulls_last) = self.options
+            order = (
+                plc.types.Order.DESCENDING if descending else plc.types.Order.ASCENDING
+            )
+            null_order = (
+                plc.types.NullOrder.AFTER if nulls_last else plc.types.NullOrder.BEFORE
+            )
+            bool_result: bool = column.check_sorted(
+                order=order, null_order=null_order, stream=df.stream
+            )
+            return Column(
+                plc.Column.from_scalar(
+                    plc.Scalar.from_py(py_val=bool_result, stream=df.stream),
+                    1,
+                    stream=df.stream,
+                ),
+                dtype=self.dtype,
+            )
         elif self.name is BooleanFunction.Name.Not:
             (column,) = columns
             # Polars semantics:

python/cudf_polars/cudf_polars/dsl/translate.py

@@ -38,14 +38,15 @@
     POLARS_VERSION_LT_139,
     POLARS_VERSION_LT_140,
     POLARS_VERSION_LT_141,
+    POLARS_VERSION_LT_142,
 )
 
 if TYPE_CHECKING:
     from collections.abc import Generator
 
     from polars import GPUEngine
 
-    from cudf_polars.typing import NodeTraverser
+    from cudf_polars.typing import NodeTraverser, Slice as Zlice
 
 __all__ = ["Translator", "translate_named_expr"]
 
@@ -164,7 +165,7 @@ def translate_ir(self, *, n: int | None = None) -> ir.IR:
         # IR is versioned with major.minor, minor is bumped for backwards
         # compatible changes (e.g. adding new nodes), major is bumped for
         # incompatible changes (e.g. renaming nodes).
-        if (version := self.visitor.version()) >= (13, 1):
+        if (version := self.visitor.version()) >= (14, 4):
             e = NotImplementedError(
                 f"No support for polars IR {version=}"
             )  # pragma: no cover; no such version for now.
@@ -291,10 +292,16 @@ def _drop_dyn_pred_hints(
 ) -> expr.Expr | None:
     try:
         node = translator.visitor.view_expression(n)
-    except Exception as e:
+    except Exception as e:  # pragma: no cover
         if str(e) == "dynamic_pred":
             return None
-        raise  # pragma: no cover
+        raise
+    if (
+        not POLARS_VERSION_LT_142
+        and isinstance(node, plrs._expr_nodes.Function)
+        and node.function_data[0] == "dynamic_pred"
+    ):
+        return None
     if isinstance(node, plrs._expr_nodes.BinaryExpr) and node.op in (
         plrs._expr_nodes.Operator.And,
         plrs._expr_nodes.Operator.LogicalAnd,
@@ -410,6 +417,8 @@ def _(node: plrs._ir_nodes.Scan, translator: Translator, schema: Schema) -> ir.I
         raise NotImplementedError(
             "Iceberg format is not supported in cudf-polars. Furthermore, row-level deletions are not supported."
         )  # pragma: no cover
+    if not POLARS_VERSION_LT_142 and node.hive_parts is not None:
+        raise NotImplementedError("Hive-partitioned scans are not supported")
     config_options = translator.config_options
     parquet_options = config_options.parquet_options
 
@@ -657,7 +666,17 @@ def _(node: plrs._ir_nodes.Sort, translator: Translator, schema: Schema) -> ir.I
     order, null_order = sorting.sort_order(
         descending, nulls_last=nulls_last, num_keys=len(by)
     )
-    return ir.Sort(schema, by, order, null_order, stable, node.slice, inp)
+    # TODO: use the DynamicPred hint from node.slice (offset, length,
+    # dynamic_pred_id). dynamic_pred_id is an int (u128 UUID) matching a
+    # DynamicPred Function node in an upstream scan. The sort actor could
+    # set a threshold predicate on it (e.g. col < max_seen) to prune rows
+    # at the source.
+    if not POLARS_VERSION_LT_142 and node.slice is not None:
+        offset, length, *_ = node.slice
+        zlice: Zlice | None = (offset, length)
+    else:
+        zlice = node.slice
+    return ir.Sort(schema, by, order, null_order, stable, zlice, inp)
 
 
 @_translate_ir.register

python/cudf_polars/cudf_polars/testing/inject_gpu_engine.py

@@ -151,7 +151,7 @@ def pytest_report_header(config: pytest.Config) -> str:
     "tests/unit/io/test_iceberg.py::test_scan_iceberg_nested_column_cast_deletion_rename": "Iceberg column_mapping (schema evolution) not yet implemented in cudf-polars",
     "tests/unit/io/test_iceberg.py::test_scan_iceberg_parquet_prefilter_with_column_mapping": "Iceberg column_mapping (schema evolution) not yet implemented in cudf-polars",
     "tests/unit/io/test_iceberg.py::test_fill_missing_fields_with_identity_partition_values_nested": "Iceberg partition column injection not yet implemented in cudf-polars",
-    "tests/unit/io/test_iceberg.py::test_scan_iceberg_fast_count": "Iceberg support not yet implemented in cudf-polars",
+    "tests/unit/io/test_iceberg.py::test_scan_iceberg_fast_count[native]": "Iceberg fast count from metadata not yet supported in cudf-polars",
     "tests/unit/io/test_iceberg.py::test_iceberg_filter_bool_26474": "Iceberg support not yet implemented in cudf-polars",
     "tests/unit/io/test_io_plugin.py::test_defer_validate_false": "cudf-polars always validates the IO source schema, so validate_schema=False dtype mismatches are unsupported on GPU",
     "tests/unit/io/test_io_plugin.py::test_datetime_io_predicate_pushdown_21790": "cudf-polars validates the IO source schema exactly and does not coerce datetime time units (us vs ns)",
@@ -248,6 +248,7 @@ def pytest_report_header(config: pytest.Config) -> str:
     "tests/unit/sql/test_cast.py::test_cast_errors[values2-values::int1-conversion from `i64` to `i8` failed]": "Casting that raises not supported on GPU",
     "tests/unit/sql/test_cast.py::test_cast_errors[values5-values::int4-conversion from `str` to `i32` failed]": "Cast raises, but error user receives is wrong",
     "tests/unit/lazyframe/test_predicates.py::test_predicate_pushdown_split_pushable": "Casting that raises not supported on GPU",
+    "tests/unit/lazyframe/test_predicates.py::test_filter_contradiction_fallible_error_handling": "Casting that raises not supported on GPU",
     "tests/unit/sql/test_miscellaneous.py::test_read_csv": "Incorrect handling of missing_is_null in read_csv",
     "tests/unit/lazyframe/test_cse.py::test_cse_predicate_self_join[False]": "Debug output on stderr doesn't match, see https://github.com/rapidsai/cudf/issues/22967",
     "tests/unit/lazyframe/test_cse.py::test_cse_predicate_self_join[True]": "Debug output on stderr doesn't match, see https://github.com/rapidsai/cudf/issues/22967",
@@ -344,6 +345,12 @@ def pytest_report_header(config: pytest.Config) -> str:
     "tests/unit/io/test_scan.py::test_scan_metrics[False-parquet]": "Checks to IO metric logs specific to Polars CPU",
     "tests/unit/io/test_scan.py::test_scan_metrics[False-csv]": "Checks to IO metric logs specific to Polars CPU",
     "tests/unit/io/test_scan.py::test_scan_metrics[False-ndjson]": "Checks to IO metric logs specific to Polars CPU",
+    # polars 1.42 updated these tests to also assert deprecated_call and strict=True ShapeError
+    # in the same test function. The SPMD engine fails on the strict=True collect() inside a
+    # pytest.raises block because the DeprecationWarning from how='horizontal' propagates differently
+    # across engines. Skip both runs rather than xfail (which would XPASS on in-memory).
+    "tests/unit/lazyframe/test_predicates.py::test_hconcat_predicate": "polars 1.42: test uses deprecated how='horizontal' with strict=True in ways that behave differently across GPU engines",
+    "tests/unit/functions/test_union.py::test_union_lazyframe_horizontal": "polars 1.42: test uses deprecated how='horizontal' with strict=True in ways that behave differently across GPU engines",
 }
 
 

python/cudf_polars/cudf_polars/utils/versions.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES.
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 """Version utilities so that cudf_polars supports a range of polars versions."""
@@ -18,6 +18,7 @@
 POLARS_VERSION_LT_139 = POLARS_VERSION < parse("1.39.0")
 POLARS_VERSION_LT_140 = POLARS_VERSION < parse("1.40.0")
 POLARS_VERSION_LT_141 = POLARS_VERSION < parse("1.41.0")
+POLARS_VERSION_LT_142 = POLARS_VERSION < parse("1.42.0")
 
 
 def _ensure_polars_version() -> None:

python/cudf_polars/pyproject.toml

@@ -25,7 +25,7 @@ dependencies = [
     "cudf-streaming==26.8.*,>=0.0.0a0",
     "nvidia-ml-py>=12",
     "packaging",
-    "polars>=1.35,<1.42",
+    "polars>=1.35,<1.43",
     "pylibcudf==26.8.*,>=0.0.0a0",
     "rapidsmpf==26.8.*,>=0.0.0a0",
     "typing_extensions>=4.0.0",

python/cudf_polars/tests/dsl/test_serialization.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES.
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 from __future__ import annotations
@@ -16,6 +16,7 @@
 from cudf_polars.utils.versions import (
     POLARS_VERSION_LT_138,
     POLARS_VERSION_LT_141,
+    POLARS_VERSION_LT_142,
 )
 
 
@@ -57,6 +58,9 @@ def test_from_polars_all_names(function):
     if POLARS_VERSION_LT_141 and function == BooleanFunction:
         # 'HasNulls' and 'IsEmpty' were added to polars' BooleanFunction in 1.41.
         cudf_polars_names_set = cudf_polars_names_set - {"HasNulls", "IsEmpty"}
+    if POLARS_VERSION_LT_142 and function == BooleanFunction:
+        # 'IsSorted' was added to polars' BooleanFunction in 1.42.
+        cudf_polars_names_set = cudf_polars_names_set - {"IsSorted"}
     assert polars_names_set == cudf_polars_names_set
     names = function.Name
     if function == StructFunction:
@@ -71,6 +75,8 @@ def test_from_polars_all_names(function):
             BooleanFunction.Name.HasNulls,
             BooleanFunction.Name.IsEmpty,
         }
+    if POLARS_VERSION_LT_142 and function == BooleanFunction:
+        names = set(names) - {BooleanFunction.Name.IsSorted}
     for name in names:
         attr = getattr(polars_function, name.name)
         assert function.Name.from_polars(attr) == name

python/cudf_polars/tests/expressions/test_booleanfunction.py

@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES.
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 from __future__ import annotations
 
@@ -12,6 +12,7 @@
     assert_gpu_result_equal,
     assert_ir_translation_raises,
 )
+from cudf_polars.utils.versions import POLARS_VERSION_LT_142
 
 if TYPE_CHECKING:
     from collections.abc import Callable
@@ -294,6 +295,35 @@ def test_boolean_not_with_integers(engine: pl.GPUEngine, dtype, col):
     assert_gpu_result_equal(q, engine=engine)
 
 
+@pytest.mark.skipif(
+    POLARS_VERSION_LT_142, reason="IsSorted BooleanFunction was added in polars 1.42"
+)
+@pytest.mark.parametrize("descending", [False, True])
+@pytest.mark.parametrize("nulls_last", [False, True])
+def test_boolean_is_sorted(
+    engine: pl.GPUEngine, *, descending: bool, nulls_last: bool, has_nulls: bool
+) -> None:
+    values: list[int | None] = [1, 2, 3, 4, 5]
+    if has_nulls:
+        values[2] = None
+
+    ldf = pl.LazyFrame(
+        {
+            "asc": pl.Series(values, dtype=pl.Int64()),
+            "desc": pl.Series(list(reversed(values)), dtype=pl.Int64()),
+            "unsorted": pl.Series([3, 1, None, 4, 2], dtype=pl.Int64()),
+        }
+    )
+
+    q = ldf.select(
+        pl.col("asc").is_sorted(descending=descending, nulls_last=nulls_last),
+        pl.col("desc").is_sorted(descending=descending, nulls_last=nulls_last),
+        pl.col("unsorted").is_sorted(descending=descending, nulls_last=nulls_last),
+    )
+
+    assert_gpu_result_equal(q, engine=engine)
+
+
 @pytest.mark.parametrize(
     "expr",
     [