chore(typing): fix [type-arg]

Author: dangotbanned

narwhals/_arrow/series.py

@@ -381,10 +381,12 @@ def __narwhals_series__(self: Self) -> Self:
     def __getitem__(self: Self, idx: int) -> Any: ...
 
     @overload
-    def __getitem__(self: Self, idx: slice | Sequence[int] | pa.ChunkedArray) -> Self: ...
+    def __getitem__(
+        self: Self, idx: slice | Sequence[int] | ArrowChunkedArray
+    ) -> Self: ...
 
     def __getitem__(
-        self: Self, idx: int | slice | Sequence[int] | pa.ChunkedArray
+        self: Self, idx: int | slice | Sequence[int] | ArrowChunkedArray
     ) -> Any | Self:
         if isinstance(idx, int):
             return maybe_extract_py_scalar(
@@ -690,7 +692,7 @@ def to_frame(self: Self) -> ArrowDataFrame:
             validate_column_names=False,
         )
 
-    def to_pandas(self: Self) -> pd.Series:
+    def to_pandas(self: Self) -> pd.Series[Any]:
         import pandas as pd  # ignore-banned-import()
 
         return pd.Series(self._native_series, name=self.name)  # pyright: ignore[reportArgumentType, reportCallIssue]

narwhals/_arrow/series_str.py

@@ -2,6 +2,7 @@
 
 import string
 from typing import TYPE_CHECKING
+from typing import Any
 
 import pyarrow.compute as pc
 
@@ -75,7 +76,7 @@ def to_datetime(self: Self, format: str | None) -> ArrowSeries:  # noqa: A002
         native = self._compliant_series._native_series
         format = parse_datetime_format(native) if format is None else format
         strptime: Incomplete = pc.strptime
-        timestamp_array: pa.Array[pa.TimestampScalar] = strptime(
+        timestamp_array: pa.Array[pa.TimestampScalar[Any, Any]] = strptime(
             native, format=format, unit="us"
         )
         return self._compliant_series._from_native_series(timestamp_array)

narwhals/_expression_parsing.py

@@ -467,7 +467,7 @@ def infer_kind(obj: IntoExpr | _1DArray | object, *, str_as_lit: bool) -> ExprKi
 
 
 def apply_n_ary_operation(
-    plx: CompliantNamespace,
+    plx: CompliantNamespace[Any, Any],
     function: Any,
     *comparands: IntoExpr,
     str_as_lit: bool,

narwhals/_pandas_like/dataframe.py

@@ -57,7 +57,7 @@
 from narwhals.typing import CompliantDataFrame
 from narwhals.typing import CompliantLazyFrame
 
-CLASSICAL_NUMPY_DTYPES: frozenset[np.dtype] = frozenset(
+CLASSICAL_NUMPY_DTYPES: frozenset[np.dtype[Any]] = frozenset(
     [
         np.dtype("float64"),
         np.dtype("float32"),

narwhals/_pandas_like/series.py

@@ -681,7 +681,7 @@ def to_numpy(self: Self, dtype: Any = None, copy: bool | None = None) -> _1DArra
             )
         return s.to_numpy(dtype=dtype, copy=copy)
 
-    def to_pandas(self: Self) -> pd.Series:
+    def to_pandas(self: Self) -> pd.Series[Any]:
         if self._implementation is Implementation.PANDAS:
             return self._native_series
         elif self._implementation is Implementation.CUDF:  # pragma: no cover

narwhals/_pandas_like/utils.py

@@ -698,7 +698,7 @@ def int_dtype_mapper(dtype: Any) -> str:
 
 
 def convert_str_slice_to_int_slice(
-    str_slice: slice, columns: pd.Index
+    str_slice: slice, columns: pd.Index[str]
 ) -> tuple[int | None, int | None, int | None]:
     # We can safely cast to int because we know that `columns` doesn't contain duplicates.
     start = (
@@ -716,8 +716,8 @@ def convert_str_slice_to_int_slice(
 
 
 def calculate_timestamp_datetime(
-    s: pd.Series, original_time_unit: str, time_unit: str
-) -> pd.Series:
+    s: pd.Series[int], original_time_unit: str, time_unit: str
+) -> pd.Series[int]:
     if original_time_unit == "ns":
         if time_unit == "ns":
             result = s
@@ -752,7 +752,7 @@ def calculate_timestamp_datetime(
     return result
 
 
-def calculate_timestamp_date(s: pd.Series, time_unit: str) -> pd.Series:
+def calculate_timestamp_date(s: pd.Series[int], time_unit: str) -> pd.Series[int]:
     s = s * 86_400  # number of seconds in a day
     if time_unit == "ns":
         result = s * 1_000_000_000
@@ -833,7 +833,7 @@ def pivot_table(
     return result
 
 
-def check_column_names_are_unique(columns: pd.Index) -> None:
+def check_column_names_are_unique(columns: pd.Index[str]) -> None:
     try:
         len_unique_columns = len(columns.drop_duplicates())
     except Exception:  # noqa: BLE001  # pragma: no cover

narwhals/dependencies.py

@@ -136,7 +136,7 @@ def is_pandas_series(ser: Any) -> TypeIs[pd.Series[Any]]:
     )
 
 
-def is_pandas_index(index: Any) -> TypeIs[pd.Index]:
+def is_pandas_index(index: Any) -> TypeIs[pd.Index[Any]]:
     """Check whether `index` is a pandas Index without importing pandas."""
     return ((pd := get_pandas()) is not None and isinstance(index, pd.Index)) or any(
         (mod := sys.modules.get(module_name, None)) is not None

narwhals/series.py

@@ -1409,7 +1409,7 @@ def to_numpy(self: Self) -> _1DArray:
         """
         return self._compliant_series.to_numpy()
 
-    def to_pandas(self: Self) -> pd.Series:
+    def to_pandas(self: Self) -> pd.Series[Any]:
         """Convert to pandas Series.
 
         Returns:

narwhals/translate.py

@@ -792,7 +792,7 @@ def get_native_namespace(
     | LazyFrame[Any]
     | Series[Any]
     | pd.DataFrame
-    | pd.Series
+    | pd.Series[Any]
     | pl.DataFrame
     | pl.LazyFrame
     | pl.Series

narwhals/utils.py

@@ -855,7 +855,7 @@ def _is_range_index(obj: Any, native_namespace: Any) -> TypeIs[pd.RangeIndex]:
 
 
 def _has_default_index(
-    native_frame_or_series: pd.Series | pd.DataFrame, native_namespace: Any
+    native_frame_or_series: pd.Series[Any] | pd.DataFrame, native_namespace: Any
 ) -> bool:
     index = native_frame_or_series.index
     return (