chore(typing): Widen _utils signatures

narwhals/_pandas_like/utils.py

@@ -572,7 +572,7 @@ def select_columns_by_name(
         # See https://github.com/narwhals-dev/narwhals/issues/1349#issuecomment-2470118122
         # for why we need this
         if error := check_columns_exist(
-            column_names,  # type: ignore[arg-type]
+            column_names,
             available=df.columns.tolist(),  # type: ignore[attr-defined]
         ):
             raise error
@@ -581,7 +581,7 @@ def select_columns_by_name(
         return df[column_names]  # type: ignore[index]
     except KeyError as e:
         if error := check_columns_exist(
-            column_names,  # type: ignore[arg-type]
+            column_names,
             available=df.columns.tolist(),  # type: ignore[attr-defined]
         ):
             raise error from e

narwhals/_utils.py

@@ -2,7 +2,7 @@
 
 import os
 import re
-from collections.abc import Container, Iterable, Iterator, Mapping, Sequence
+from collections.abc import Collection, Container, Iterable, Iterator, Mapping, Sequence
 from datetime import timezone
 from enum import Enum, auto
 from functools import lru_cache, wraps
@@ -1181,7 +1181,7 @@ def is_ordered_categorical(series: Series[Any]) -> bool:
 
 
 def generate_unique_token(
-    n_bytes: int, columns: Sequence[str]
+    n_bytes: int, columns: Container[str]
 ) -> str:  # pragma: no cover
     msg = (
         "Use `generate_temporary_column_name` instead. `generate_unique_token` is "
@@ -1191,7 +1191,7 @@ def generate_unique_token(
     return generate_temporary_column_name(n_bytes=n_bytes, columns=columns)
 
 
-def generate_temporary_column_name(n_bytes: int, columns: Sequence[str]) -> str:
+def generate_temporary_column_name(n_bytes: int, columns: Container[str]) -> str:
     """Generates a unique column name that is not present in the given list of columns.
 
     It relies on [python secrets token_hex](https://docs.python.org/3/library/secrets.html#secrets.token_hex)
@@ -1489,7 +1489,7 @@ def generate_repr(header: str, native_repr: str) -> str:
 
 
 def check_columns_exist(
-    subset: Sequence[str], /, *, available: Sequence[str]
+    subset: Collection[str], /, *, available: Collection[str]
 ) -> ColumnNotFoundError | None:
     if missing := set(subset).difference(available):
         return ColumnNotFoundError.from_missing_and_available_column_names(
@@ -1498,7 +1498,7 @@ def check_columns_exist(
     return None
 
 
-def check_column_names_are_unique(columns: Sequence[str]) -> None:
+def check_column_names_are_unique(columns: Collection[str]) -> None:
     len_unique_columns = len(set(columns))
     if len(columns) != len_unique_columns:
         from collections import Counter
@@ -1622,7 +1622,7 @@ def supports_arrow_c_stream(obj: Any) -> TypeIs[ArrowStreamExportable]:
 
 
 def _remap_full_join_keys(
-    left_on: Sequence[str], right_on: Sequence[str], suffix: str
+    left_on: Collection[str], right_on: Collection[str], suffix: str
 ) -> dict[str, str]:
     """Remap join keys to avoid collisions.
 

narwhals/exceptions.py

@@ -3,7 +3,7 @@
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from collections.abc import Iterable, Sequence
+    from collections.abc import Collection, Iterable
 
 
 class NarwhalsError(ValueError):
@@ -35,7 +35,7 @@ def __init__(self, message: str) -> None:
 
     @classmethod
     def from_missing_and_available_column_names(
-        cls, missing_columns: Iterable[str], available_columns: Sequence[str], /
+        cls, missing_columns: Iterable[str], available_columns: Collection[str], /
     ) -> ColumnNotFoundError:
         message = (
             f"The following columns were not found: {sorted(missing_columns)}"