test: Add cudf_constructor to conftest (#797)

narwhals/_pandas_like/series.py

@@ -221,18 +221,9 @@ def is_in(self, other: Any) -> PandasLikeSeries:
         return self._from_native_series(res)
 
     def arg_true(self) -> PandasLikeSeries:
-        import numpy as np  # ignore-banned-import
-
         ser = self._native_series
-        res = np.flatnonzero(ser)
-        return self._from_native_series(
-            native_series_from_iterable(
-                res,
-                name=self.name,
-                index=range(len(res)),
-                implementation=self._implementation,
-            )
-        )
+        result = ser.__class__(range(len(ser)), name=ser.name, index=ser.index).loc[ser]
+        return self._from_native_series(result)
 
     # Binary comparisons
 

narwhals/_pandas_like/utils.py

@@ -197,6 +197,10 @@ def set_axis(
     implementation: Implementation,
     backend_version: tuple[int, ...],
 ) -> T:
+    if implementation is Implementation.CUDF:  # pragma: no cover
+        obj = obj.copy(deep=False)  # type: ignore[attr-defined]
+        obj.index = index  # type: ignore[attr-defined]
+        return obj
     if implementation is Implementation.PANDAS and backend_version < (
         1,
     ):  # pragma: no cover
@@ -210,7 +214,7 @@ def set_axis(
         kwargs["copy"] = False
     else:  # pragma: no cover
         pass
-    return obj.set_axis(index, axis=0, **kwargs)  # type: ignore[no-any-return, attr-defined]
+    return obj.set_axis(index, axis=0, **kwargs)  # type: ignore[attr-defined, no-any-return]
 
 
 def translate_dtype(column: Any) -> DType:

narwhals/expr.py

@@ -1114,8 +1114,8 @@ def arg_true(self) -> Self:
 
             >>> func(df_pd)
                a
-            0  1
-            1  2
+            1  1
+            2  2
             >>> func(df_pl)
             shape: (2, 1)
             ┌─────┐

narwhals/series.py

@@ -766,8 +766,8 @@ def arg_true(self) -> Self:
             We can then pass either pandas or Polars to `func`:
 
             >>> func(s_pd)
-            0    1
-            1    2
+            1    1
+            2    2
             Name: a, dtype: int64
             >>> func(s_pl)  # doctest: +NORMALIZE_WHITESPACE
             shape: (2,)

requirements-dev.txt

@@ -1,6 +1,6 @@
 covdefaults
 pandas
-polars[timezones]
+polars
 pre-commit
 pyarrow
 pytest

tests/conftest.py

@@ -7,6 +7,7 @@
 import pyarrow as pa
 import pytest
 
+from narwhals.dependencies import get_cudf
 from narwhals.dependencies import get_dask_dataframe
 from narwhals.dependencies import get_modin
 from narwhals.typing import IntoDataFrame
@@ -17,6 +18,8 @@
     import modin.pandas  # noqa: F401
 with contextlib.suppress(ImportError):
     import dask.dataframe  # noqa: F401
+with contextlib.suppress(ImportError):
+    import cudf  # noqa: F401
 
 
 def pytest_addoption(parser: Any) -> None:
@@ -56,6 +59,11 @@ def modin_constructor(obj: Any) -> IntoDataFrame:  # pragma: no cover
     return mpd.DataFrame(pd.DataFrame(obj)).convert_dtypes(dtype_backend="pyarrow")  # type: ignore[no-any-return]
 
 
+def cudf_constructor(obj: Any) -> IntoDataFrame:  # pragma: no cover
+    cudf = get_cudf()
+    return cudf.DataFrame(obj)  # type: ignore[no-any-return]
+
+
 def polars_eager_constructor(obj: Any) -> IntoDataFrame:
     return pl.DataFrame(obj)
 
@@ -87,7 +95,8 @@ def pyarrow_table_constructor(obj: Any) -> IntoDataFrame:
 
 if get_modin() is not None:  # pragma: no cover
     eager_constructors.append(modin_constructor)
-# TODO(unassigned): when Dask gets better support, remove the "False and" part
+if get_cudf() is not None:
+    eager_constructors.append(cudf_constructor)  # pragma: no cover
 if get_dask_dataframe() is not None:  # pragma: no cover
     lazy_constructors.append(dask_lazy_constructor)  # type: ignore  # noqa: PGH003