fix: consistent to_numpy behaviour for tz-aware

narwhals/_pandas_like/series.py

@@ -511,34 +511,30 @@ def to_numpy(self, dtype: Any = None, copy: bool | None = None) -> Any:
         # the default is meant to be None, but pandas doesn't allow it?
         # https://numpy.org/doc/stable/reference/generated/numpy.ndarray.__array__.html
         copy = copy or self._implementation is Implementation.CUDF
+        if self.dtype == self._dtypes.Datetime and self.dtype.time_zone is not None:  # type: ignore[attr-defined]
+            s = self.dt.convert_time_zone("UTC").dt.replace_time_zone(None)._native_series
+        else:
+            s = self._native_series
 
-        has_missing = self._native_series.isna().any()
-        if (
-            has_missing
-            and str(self._native_series.dtype) in PANDAS_TO_NUMPY_DTYPE_MISSING
-        ):
+        has_missing = s.isna().any()
+        if has_missing and str(s.dtype) in PANDAS_TO_NUMPY_DTYPE_MISSING:
             if self._implementation is Implementation.PANDAS and self._backend_version < (
                 1,
             ):  # pragma: no cover
                 kwargs = {}
             else:
                 kwargs = {"na_value": float("nan")}
-            return self._native_series.to_numpy(
-                dtype=dtype
-                or PANDAS_TO_NUMPY_DTYPE_MISSING[str(self._native_series.dtype)],
+            return s.to_numpy(
+                dtype=dtype or PANDAS_TO_NUMPY_DTYPE_MISSING[str(s.dtype)],
                 copy=copy,
                 **kwargs,
             )
-        if (
-            not has_missing
-            and str(self._native_series.dtype) in PANDAS_TO_NUMPY_DTYPE_NO_MISSING
-        ):
-            return self._native_series.to_numpy(
-                dtype=dtype
-                or PANDAS_TO_NUMPY_DTYPE_NO_MISSING[str(self._native_series.dtype)],
+        if not has_missing and str(s.dtype) in PANDAS_TO_NUMPY_DTYPE_NO_MISSING:
+            return s.to_numpy(
+                dtype=dtype or PANDAS_TO_NUMPY_DTYPE_NO_MISSING[str(s.dtype)],
                 copy=copy,
             )
-        return self._native_series.to_numpy(dtype=dtype, copy=copy)
+        return s.to_numpy(dtype=dtype, copy=copy)
 
     def to_pandas(self) -> Any:
         if self._implementation is Implementation.PANDAS:

tests/conftest.py

@@ -3,7 +3,6 @@
 import contextlib
 from typing import TYPE_CHECKING
 from typing import Any
-from typing import Callable
 
 import pandas as pd
 import polars as pl
@@ -19,6 +18,7 @@
     from narwhals.typing import IntoDataFrame
     from narwhals.typing import IntoFrame
     from tests.utils import Constructor
+    from tests.utils import ConstructorEager
 
 with contextlib.suppress(ImportError):
     import modin.pandas  # noqa: F401
@@ -117,7 +117,7 @@ def pyarrow_table_constructor(obj: Any) -> IntoDataFrame:
 @pytest.fixture(params=eager_constructors)
 def constructor_eager(
     request: pytest.FixtureRequest,
-) -> Callable[[Any], IntoDataFrame]:
+) -> ConstructorEager:
     return request.param  # type: ignore[no-any-return]
 
 

tests/series_only/to_numpy_test.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from datetime import datetime
 from typing import TYPE_CHECKING
 
 import numpy as np
@@ -30,3 +31,21 @@ def test_to_numpy(
     assert s.shape == (3,)
 
     assert_array_equal(s.to_numpy(), np.array(data, dtype=float))
+
+
+def test_to_numpy_tz_aware(constructor_eager: ConstructorEager) -> None:
+    df = nw.from_native(
+        constructor_eager({"a": [datetime(2020, 1, 1), datetime(2020, 1, 2)]}),
+        eager_only=True,
+    )
+    df = df.select(nw.col("a").dt.replace_time_zone("Asia/Kathmandu"))
+    result = df["a"].to_numpy()
+    # for some reason, NumPy uses 'M' for datetimes
+    assert result.dtype.kind == "M"
+    assert (
+        result
+        == np.array(
+            ["2019-12-31T18:15:00.000000", "2020-01-01T18:15:00.000000"],
+            dtype=result.dtype,
+        )
+    ).all()