refactor(typing): Avoid more ignore[attr-defined] on Datetime

narwhals/_arrow/series_dt.py

@@ -9,7 +9,6 @@
 from narwhals._arrow.utils import floordiv_compat
 from narwhals._arrow.utils import lit
 from narwhals.utils import import_dtypes_module
-from narwhals.utils import isinstance_or_issubclass
 
 if TYPE_CHECKING:
     from typing_extensions import Self
@@ -52,7 +51,7 @@ def convert_time_zone(self: Self, time_zone: str) -> ArrowSeries:
     def timestamp(self: Self, time_unit: TimeUnit) -> ArrowSeries:
         ser: ArrowSeries = self._compliant_series
         dtypes = import_dtypes_module(ser._version)
-        if isinstance_or_issubclass(ser.dtype, dtypes.Datetime):
+        if isinstance(ser.dtype, dtypes.Datetime):
             unit = ser.dtype.time_unit
             s_cast = ser._native_series.cast(pa.int64())
             if unit == "ns":
@@ -86,7 +85,7 @@ def timestamp(self: Self, time_unit: TimeUnit) -> ArrowSeries:
             else:  # pragma: no cover
                 msg = f"unexpected time unit {unit}, please report an issue at https://github.com/narwhals-dev/narwhals"
                 raise AssertionError(msg)
-        elif isinstance_or_issubclass(ser.dtype, dtypes.Date):
+        elif isinstance(ser.dtype, dtypes.Date):
             time_s = pc.multiply(ser._native_series.cast(pa.int32()), 86400)
             if time_unit == "ns":
                 result = cast("ArrowChunkedArray", pc.multiply(time_s, 1_000_000_000))

narwhals/_dask/expr_dt.py

@@ -114,8 +114,8 @@ def func(s: dx.Series, time_unit: TimeUnit) -> dx.Series:
                 # Date is only supported in pandas dtypes if pyarrow-backed
                 s_cast = s.astype("Int32[pyarrow]")
                 result = calculate_timestamp_date(s_cast, time_unit)
-            elif dtype == dtypes.Datetime:
-                original_time_unit = dtype.time_unit  # type: ignore[attr-defined]
+            elif isinstance(dtype, dtypes.Datetime):
+                original_time_unit = dtype.time_unit
                 s_cast = (
                     s.astype("Int64[pyarrow]") if is_pyarrow_dtype else s.astype("int64")
                 )

narwhals/_pandas_like/series.py

@@ -656,7 +656,7 @@ def to_numpy(self: Self, dtype: Any = None, copy: bool | None = None) -> _1DArra
         # https://numpy.org/doc/stable/reference/generated/numpy.ndarray.__array__.html
         copy = copy or self._implementation is Implementation.CUDF
         dtypes = import_dtypes_module(self._version)
-        if self.dtype == dtypes.Datetime and self.dtype.time_zone is not None:  # type: ignore[attr-defined]
+        if isinstance(self.dtype, dtypes.Datetime) and self.dtype.time_zone is not None:
             s = self.dt.convert_time_zone("UTC").dt.replace_time_zone(None)._native_series
         else:
             s = self._native_series

narwhals/_pandas_like/series_dt.py

@@ -218,8 +218,8 @@ def timestamp(self: Self, time_unit: TimeUnit) -> PandasLikeSeries:
             # Date is only supported in pandas dtypes if pyarrow-backed
             s_cast = s.astype("Int32[pyarrow]")
             result = calculate_timestamp_date(s_cast, time_unit)
-        elif dtype == dtypes.Datetime:
-            original_time_unit = dtype.time_unit  # type: ignore[attr-defined]
+        elif isinstance(dtype, dtypes.Datetime):
+            original_time_unit = dtype.time_unit
             if (
                 self._compliant_series._implementation is Implementation.PANDAS
                 and self._compliant_series._backend_version < (2,)

narwhals/utils.py

@@ -1294,11 +1294,11 @@ def dtype_matches_time_unit_and_time_zone(
     dtype: DType, dtypes: DTypes, time_units: Set[TimeUnit], time_zones: Set[str | None]
 ) -> bool:
     return (
-        (dtype == dtypes.Datetime)
-        and (dtype.time_unit in time_units)  # type: ignore[attr-defined]
+        isinstance(dtype, dtypes.Datetime)
+        and (dtype.time_unit in time_units)
         and (
-            dtype.time_zone in time_zones  # type: ignore[attr-defined]
-            or ("*" in time_zones and dtype.time_zone is not None)  # type: ignore[attr-defined]
+            dtype.time_zone in time_zones
+            or ("*" in time_zones and dtype.time_zone is not None)
         )
     )
 

tests/expr_and_series/dt/convert_time_zone_test.py

@@ -42,7 +42,8 @@ def test_convert_time_zone(
     result = df.select(nw.col("a").dt.convert_time_zone("Asia/Kathmandu"))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone == "Asia/Kathmandu"  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone == "Asia/Kathmandu"
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M%z"))
     expected = {"a": ["2020-01-01T05:45+0545", "2020-01-02T05:45+0545"]}
     assert_equal_data(result_str, expected)
@@ -70,7 +71,8 @@ def test_convert_time_zone_series(
     result = df.select(df["a"].dt.convert_time_zone("Asia/Kathmandu"))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone == "Asia/Kathmandu"  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone == "Asia/Kathmandu"
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M%z"))
     expected = {"a": ["2020-01-01T05:45+0545", "2020-01-02T05:45+0545"]}
     assert_equal_data(result_str, expected)
@@ -105,7 +107,8 @@ def test_convert_time_zone_from_none(
     )
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone == "Asia/Kathmandu"  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone == "Asia/Kathmandu"
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M%z"))
     expected = {"a": ["2020-01-01T05:45+0545", "2020-01-02T05:45+0545"]}
     assert_equal_data(result_str, expected)

tests/expr_and_series/dt/replace_time_zone_test.py

@@ -40,7 +40,8 @@ def test_replace_time_zone(
     result = df.select(nw.col("a").dt.replace_time_zone("Asia/Kathmandu"))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone == "Asia/Kathmandu"  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone == "Asia/Kathmandu"
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M%z"))
     expected = {"a": ["2020-01-01T00:00+0545", "2020-01-02T00:00+0545"]}
     assert_equal_data(result_str, expected)
@@ -68,7 +69,8 @@ def test_replace_time_zone_none(
     result = df.select(nw.col("a").dt.replace_time_zone(None))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone is None  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone is None
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M"))
     expected = {"a": ["2020-01-01T00:00", "2020-01-02T00:00"]}
     assert_equal_data(result_str, expected)
@@ -95,7 +97,8 @@ def test_replace_time_zone_series(
     result = df.select(df["a"].dt.replace_time_zone("Asia/Kathmandu"))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone == "Asia/Kathmandu"  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone == "Asia/Kathmandu"
     result_str = result.select(nw.col("a").dt.to_string("%Y-%m-%dT%H:%M%z"))
     expected = {"a": ["2020-01-01T00:00+0545", "2020-01-02T00:00+0545"]}
     assert_equal_data(result_str, expected)
@@ -121,7 +124,8 @@ def test_replace_time_zone_none_series(
     result = df.select(df["a"].dt.replace_time_zone(None))
     result_dtype = result.collect_schema()["a"]
     assert result_dtype == nw.Datetime
-    assert result_dtype.time_zone is None  # type: ignore[attr-defined]
+    assert isinstance(result_dtype, nw.Datetime)
+    assert result_dtype.time_zone is None
     result_str = result.select(df["a"].dt.to_string("%Y-%m-%dT%H:%M"))
     expected = {"a": ["2020-01-01T00:00", "2020-01-02T00:00"]}
     assert_equal_data(result_str, expected)