Address issue #5490 - wider usage of pretty_callable for callable expressions

[theodore-ando]

Fixes #5490
Uses pretty_callable for formatting Callable expressions that would otherwise be formatted with complex Args/VarArgs.

Avoids pretty_callable for things that would be formatted with only positional args such as Callable[[X, ..., Y], Z]

[github-actions]

Diff from mypy_primer, showing the effect of this PR on open source code:

pyinstrument (https://github.com/joerick/pyinstrument)
- pyinstrument/vendor/decorator.py:295: error: Incompatible types in assignment (expression has type "Callable[[Any, Any, VarArg(Any), KwArg(Any)], Any]", variable has type "Callable[[_GeneratorContextManagerBase[Generator[Any, None, None]], Callable[..., Generator[Any, None, None]], tuple[Any, ...], dict[str, Any]], None]")  [assignment]
+ pyinstrument/vendor/decorator.py:295: error: Incompatible types in assignment (expression has type "def __init__(self: Any, g: Any, *a: Any, **k: Any) -> Any", variable has type "Callable[[_GeneratorContextManagerBase[Generator[Any, None, None]], Callable[..., Generator[Any, None, None]], tuple[Any, ...], dict[str, Any]], None]")  [assignment]
- pyinstrument/vendor/decorator.py:301: error: Incompatible types in assignment (expression has type "Callable[[Any, Any, VarArg(Any), KwArg(Any)], Any]", variable has type "Callable[[_GeneratorContextManagerBase[Generator[Any, None, None]], Callable[..., Generator[Any, None, None]], tuple[Any, ...], dict[str, Any]], None]")  [assignment]
+ pyinstrument/vendor/decorator.py:301: error: Incompatible types in assignment (expression has type "def __init__(self: Any, g: Any, *a: Any, **k: Any) -> Any", variable has type "Callable[[_GeneratorContextManagerBase[Generator[Any, None, None]], Callable[..., Generator[Any, None, None]], tuple[Any, ...], dict[str, Any]], None]")  [assignment]

hydpy (https://github.com/hydpy-dev/hydpy)
- hydpy/auxs/statstools.py:1689: note:     def fmin(func: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., full_output: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> ndarray[tuple[int], dtype[float64]]
+ hydpy/auxs/statstools.py:1689: note:     def fmin(func: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., full_output: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> ndarray[tuple[int], dtype[float64]]
- hydpy/auxs/statstools.py:1689: note:     def fmin(func: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., full_output: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., *, retall: Literal[True] | numpy.bool[Literal[True]] | Literal[1], callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], list[ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]] | ndarray[tuple[int], dtype[float64]]]]
+ hydpy/auxs/statstools.py:1689: note:     def fmin(func: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., full_output: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., *, retall: Literal[True] | numpy.bool[Literal[True]] | Literal[1], callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], list[ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]] | ndarray[tuple[int], dtype[float64]]]]
- hydpy/auxs/statstools.py:1689: note:     def fmin(func: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., *, full_output: Literal[True] | numpy.bool[Literal[True]] | Literal[1], disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], int, int, Literal[0, 1, 2, 3, 4]]
+ hydpy/auxs/statstools.py:1689: note:     def fmin(func: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., *, full_output: Literal[True] | numpy.bool[Literal[True]] | Literal[1], disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[False] | numpy.bool[Literal[False]] | Literal[0] = ..., callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], int, int, Literal[0, 1, 2, 3, 4]]
- hydpy/auxs/statstools.py:1689: note:     def fmin(func: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., *, full_output: Literal[True] | numpy.bool[Literal[True]] | Literal[1], disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[True] | numpy.bool[Literal[True]] | Literal[1], callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], int, int, Literal[0, 1, 2, 3, 4], list[ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]] | ndarray[tuple[int], dtype[float64]]]]
+ hydpy/auxs/statstools.py:1689: note:     def fmin(func: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., xtol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., ftol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] = ..., maxiter: int | None = ..., maxfun: int | None = ..., *, full_output: Literal[True] | numpy.bool[Literal[True]] | Literal[1], disp: Literal[0, 1, 2, 3] | builtins.bool | numpy.bool[builtins.bool] = ..., retall: Literal[True] | numpy.bool[Literal[True]] | Literal[1], callback: Callable[[ndarray[tuple[int], dtype[float64]]], None] | None = ..., initial_simplex: _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ...) -> tuple[ndarray[tuple[int], dtype[float64]], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], int, int, Literal[0, 1, 2, 3, 4], list[ndarray[tuple[int], dtype[signedinteger[_32Bit | _64Bit]]] | ndarray[tuple[int], dtype[float64]]]]

spark (https://github.com/apache/spark)
- python/pyspark/pandas/frame.py:3187: error: No overload variant of "apply" of "DataFrame" matches argument types "Callable[[VarArg(Any), KwArg(Any)], Any]", "int", "Sequence[Any]", "dict[str, Any]"  [call-overload]
+ python/pyspark/pandas/frame.py:3187: error: No overload variant of "apply" of "DataFrame" matches argument types "def (*args: Any, **kwargs: Any) -> Any", "int", "Sequence[Any]", "dict[str, Any]"  [call-overload]
- python/pyspark/pandas/frame.py:3205: error: No overload variant of "apply" of "DataFrame" matches argument types "Callable[[VarArg(Any), KwArg(Any)], Any]", "int", "Sequence[Any]", "dict[str, Any]"  [call-overload]
+ python/pyspark/pandas/frame.py:3205: error: No overload variant of "apply" of "DataFrame" matches argument types "def (*args: Any, **kwargs: Any) -> Any", "int", "Sequence[Any]", "dict[str, Any]"  [call-overload]

prefect (https://github.com/PrefectHQ/prefect)
- src/prefect/utilities/pydantic.py:193: error: Incompatible types in assignment (expression has type "Callable[[type[M], KwArg(Any)], M]", variable has type overloaded function)  [assignment]
+ src/prefect/utilities/pydantic.py:193: error: Incompatible types in assignment (expression has type "def __new__(cls: type[M], **kwargs: Any) -> M", variable has type overloaded function)  [assignment]
- src/prefect/_internal/compatibility/deprecated.py:147: note: "_Wrapped[[object], None, [T, VarArg(Any), KwArg(Any)], None].__call__" has type "Callable[[Arg(T, 'self'), VarArg(Any), KwArg(Any)], None]"
+ src/prefect/_internal/compatibility/deprecated.py:147: note: "_Wrapped[[object], None, [T, VarArg(Any), KwArg(Any)], None].__call__" has type "def __call__(self: T, *args: Any, **kwargs: Any) -> None"
- src/prefect/utilities/asyncutils.py:361: note: "_Wrapped[P, Coroutine[Any, Any, Any], [VarArg(Any), DefaultNamedArg(Optional[bool], '_sync'), KwArg(Any)], Coroutine[Any, Any, Any]].__call__" has type "Callable[[VarArg(Any), DefaultNamedArg(Optional[bool], '_sync'), KwArg(Any)], Coroutine[Any, Any, Any]]"
+ src/prefect/utilities/asyncutils.py:361: note: "_Wrapped[P, Coroutine[Any, Any, Any], [VarArg(Any), DefaultNamedArg(Optional[bool], '_sync'), KwArg(Any)], Coroutine[Any, Any, Any]].__call__" has type "def __call__(*args: Any, _sync: Optional[bool] = ..., **kwargs: Any) -> Coroutine[Any, Any, Any]"
- src/prefect/task_runners.py:404: error: Argument 1 to "submit" of "Executor" has incompatible type "Callable[[Callable[_P, _T], **_P], _T]"; expected "Callable[[Callable[[Task[P, R], Optional[UUID], Optional[TaskRun], Optional[dict[str, Any]], Union[PrefectFuture[Any], Any, Iterable[Union[PrefectFuture[Any], Any]], None], Literal['state', 'result'], Optional[dict[str, set[RunInput]]], Optional[dict[str, Any]]], Union[R, State[Any], None]], KwArg(Any)], Union[Any, State[Any], None]]"  [arg-type]
+ src/prefect/task_runners.py:404: error: Argument 1 to "submit" of "Executor" has incompatible type "Callable[[Callable[_P, _T], **_P], _T]"; expected "def (Callable[[Task[P, R], Optional[UUID], Optional[TaskRun], Optional[dict[str, Any]], Union[PrefectFuture[Any], Any, Iterable[Union[PrefectFuture[Any], Any]], None], Literal['state', 'result'], Optional[dict[str, set[RunInput]]], Optional[dict[str, Any]]], Union[R, State[Any], None]], /, **Any) -> Union[Any, State[Any], None]"  [arg-type]
- src/prefect/cli/shell.py:105: error: Incompatible types in assignment (expression has type "list[Any]", variable has type "Callable[[object, VarArg(object), DefaultNamedArg(Union[bool, Union[tuple[type[BaseException], BaseException, Optional[TracebackType]], tuple[None, None, None]], BaseException, None], 'exc_info'), DefaultNamedArg(bool, 'stack_info'), DefaultNamedArg(int, 'stacklevel'), DefaultNamedArg(Optional[Mapping[str, object]], 'extra')], None]")  [assignment]
+ src/prefect/cli/shell.py:105: error: Incompatible types in assignment (expression has type "list[Any]", variable has type "def info(self, msg: object, *args: object, exc_info: Union[bool, Union[tuple[type[BaseException], BaseException, Optional[TracebackType]], tuple[None, None, None]], BaseException, None] = ..., stack_info: bool = ..., stacklevel: int = ..., extra: Optional[Mapping[str, object]] = ...) -> None")  [assignment]

pydantic (https://github.com/pydantic/pydantic)
- pydantic/_internal/_decorators.py:201: error: Incompatible return value type (got "Callable[[VarArg(Any), KwArg(Any)], ReturnType] | Any | property", expected "PydanticDescriptorProxy[ReturnType]")  [return-value]
+ pydantic/_internal/_decorators.py:201: error: Incompatible return value type (got "def (*Any, **Any) -> ReturnType | Any | property", expected "PydanticDescriptorProxy[ReturnType]")  [return-value]
- pydantic/_internal/_generate_schema.py:614: error: Argument 1 to "partial" has incompatible type "Callable[[Callable[[Any], Any], Mapping[str, Any], DefaultNamedArg(str | None, 'ref'), DefaultNamedArg(Mapping[str, Any] | None, 'json_schema_input_schema'), DefaultNamedArg(dict[str, Any] | None, 'metadata'), DefaultNamedArg(SimpleSerSchema | PlainSerializerFunctionSerSchema | WrapSerializerFunctionSerSchema | FormatSerSchema | ToStringSerSchema | ModelSerSchema | None, 'serialization')], AfterValidatorFunctionSchema]"; expected "Callable[..., WrapValidatorFunctionSchema]"  [arg-type]
+ pydantic/_internal/_generate_schema.py:614: error: Argument 1 to "partial" has incompatible type "def no_info_after_validator_function(function: Callable[[Any], Any], schema: Mapping[str, Any], *, ref: str | None = ..., json_schema_input_schema: Mapping[str, Any] | None = ..., metadata: dict[str, Any] | None = ..., serialization: SimpleSerSchema | PlainSerializerFunctionSerSchema | WrapSerializerFunctionSerSchema | FormatSerSchema | ToStringSerSchema | ModelSerSchema | None = ...) -> AfterValidatorFunctionSchema"; expected "Callable[..., WrapValidatorFunctionSchema]"  [arg-type]
- pydantic/_internal/_model_construction.py:307: error: Incompatible types in assignment (expression has type "Callable[[Any], bool]", base class "ABCMeta" defined the type as "Callable[[Arg(Any, 'instance')], bool]")  [assignment]
+ pydantic/_internal/_model_construction.py:307: error: Incompatible types in assignment (expression has type "Callable[[Any], bool]", base class "ABCMeta" defined the type as "def __instancecheck__(cls, instance: Any) -> bool")  [assignment]
- pydantic/_internal/_model_construction.py:308: error: Incompatible types in assignment (expression has type "Callable[[type], bool]", base class "ABCMeta" defined the type as "Callable[[Arg(type, 'subclass')], bool]")  [assignment]
+ pydantic/_internal/_model_construction.py:308: error: Incompatible types in assignment (expression has type "Callable[[type], bool]", base class "ABCMeta" defined the type as "def __subclasscheck__(cls, subclass: type) -> bool")  [assignment]
- pydantic/main.py:260: error: "Callable[[BaseModel, KwArg(Any)], None]" has no attribute "__pydantic_base_init__"  [attr-defined]
+ pydantic/main.py:260: error: "def __init__(BaseModel, /, **data: Any) -> None" has no attribute "__pydantic_base_init__"  [attr-defined]
- pydantic/root_model.py:70: error: "Callable[[RootModel[RootModelRootType], RootModelRootType, KwArg(Any)], None]" has no attribute "__pydantic_base_init__"  [attr-defined]
+ pydantic/root_model.py:70: error: "def __init__(RootModel[RootModelRootType], /, root: RootModelRootType = ..., **data: Any) -> None" has no attribute "__pydantic_base_init__"  [attr-defined]
- pydantic/_internal/_validate_call.py:126: error: Incompatible types in assignment (expression has type "Callable[[Arg(Any, 'input'), DefaultNamedArg(bool | None, 'strict'), DefaultNamedArg(Literal['allow', 'forbid', 'ignore'] | None, 'extra'), DefaultNamedArg(bool | None, 'from_attributes'), DefaultNamedArg(Any | None, 'context'), DefaultNamedArg(Any | None, 'self_instance'), DefaultNamedArg(Literal['off', 'on', 'trailing-strings'] | bool, 'allow_partial'), DefaultNamedArg(bool | None, 'by_alias'), DefaultNamedArg(bool | None, 'by_name')], Any]", variable has type "Callable[[Arg(Awaitable[Any], 'aw')], Coroutine[Any, Any, None]]")  [assignment]
+ pydantic/_internal/_validate_call.py:126: error: Incompatible types in assignment (expression has type "def validate_python(self, input: Any, *, strict: bool | None = ..., extra: Literal['allow', 'forbid', 'ignore'] | None = ..., from_attributes: bool | None = ..., context: Any | None = ..., self_instance: Any | None = ..., allow_partial: Literal['off', 'on', 'trailing-strings'] | bool = ..., by_alias: bool | None = ..., by_name: bool | None = ...) -> Any", variable has type "def return_val_wrapper(aw: Awaitable[Any]) -> Coroutine[Any, Any, None]")  [assignment]

colour (https://github.com/colour-science/colour)
- colour/temperature/krystek1985.py:115: note:     def [_Float1DT: ndarray[tuple[int], dtype[float64]]] minimize(fun: Callable[[_Float1DT, VarArg(Any), KwArg(Any)], _Float1DT], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], args: tuple[object, ...] = ..., method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None = ..., jac: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | Literal['2-point', '3-point', 'cs'] | Literal[False] | numpy.bool[Literal[False]] | Literal[0] | None = ..., hess: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: Callable[[ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
+ colour/temperature/krystek1985.py:115: note:     def [_Float1DT: ndarray[tuple[int], dtype[float64]]] minimize(fun: def (_Float1DT, /, *Any, **Any) -> _Float1DT, x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], args: tuple[object, ...] = ..., method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None = ..., jac: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Literal['2-point', '3-point', 'cs'] | Literal[False] | numpy.bool[Literal[False]] | Literal[0] | None = ..., hess: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: def (ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
- colour/temperature/krystek1985.py:115: note:     def minimize(fun: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None = ..., jac: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | Literal['2-point', '3-point', 'cs'] | Literal[False] | numpy.bool[Literal[False]] | Literal[0] | None = ..., hess: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: Callable[[ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
+ colour/temperature/krystek1985.py:115: note:     def minimize(fun: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None = ..., jac: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Literal['2-point', '3-point', 'cs'] | Literal[False] | numpy.bool[Literal[False]] | Literal[0] | None = ..., hess: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: def (ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
- colour/temperature/krystek1985.py:115: note:     def minimize(fun: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...], method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None, jac: Literal[True] | numpy.bool[Literal[True]] | Literal[1], hess: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: Callable[[ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
+ colour/temperature/krystek1985.py:115: note:     def minimize(fun: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...], method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None, jac: Literal[True] | numpy.bool[Literal[True]] | Literal[1], hess: def (ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: def (ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], /, *Any, **Any) -> _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult
- colour/temperature/krystek1985.py:115: note:     def minimize(fun: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]], x0: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]], args: tuple[object, ...] = ..., method: Literal['Nelder-Mead', 'nelder-mead', 'Powell', 'powell', 'CG', 'cg', 'BFGS', 'bfgs', 'Newton-CG', 'newton-cg', 'L-BFGS-B', 'l-bfgs-b', 'TNC', 'tnc', 'COBYLA', 'cobyla', 'COBYQA', 'cobyqa', 'SLSQP', 'slsqp', 'Trust-Constr', 'trust-constr', 'Dogleg', 'dogleg', 'Trust-NCG', 'trust-ncg', 'Trust-Exact', 'trust-exact', 'Trust-Krylov', 'trust-krylov'] | _MinimizeMethodFun | None = ..., *, jac: Literal[True] | numpy.bool[Literal[True]] | Literal[1], hess: Callable[[ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[_CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]]] | Literal['2-point', '3-point', 'cs'] | HessianUpdateStrategy | None = ..., hessp: Callable[[ndarray[tuple[int], dtype[float64]], ndarray[tuple[int], dtype[float64]], VarArg(Any), KwArg(Any)], _CanArrayND[floating[Any] | integer[Any] | numpy.bool[builtins.bool]] | Sequence[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool]]] | None = ..., bounds: Sequence[tuple[float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None, float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None]] | Bounds[tuple[Any, ...], float64] | None = ..., constraints: LinearConstraint | NonlinearConstraint | _ConstraintDict | Sequence[LinearConstraint | NonlinearConstraint | _ConstraintDict] = ..., tol: float | floating[Any] | integer[Any] | numpy.bool[builtins.bool] | None = ..., callback: _CallbackResult | _CallbackVector | None = ..., options: _MinimizeOptions | None = ...) -> OptimizeResult

... (truncated 59 lines) ...

Tanjun (https://github.com/FasterSpeeding/Tanjun)
- tanjun/commands/slash.py:268: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:268: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:268: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:268: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:377: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:377: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:377: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:377: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1277: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1277: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1277: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1277: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1331: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1331: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1331: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1331: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1525: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1525: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1525: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1525: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1543: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1543: error: Type argument "_SlashCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:1543: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "Callable[[MessageContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/slash.py:1543: error: Type argument "_SlashCallbackSigT" of "MessageCommand" must be a subtype of "def (MessageContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/slash.py:3222: error: Incompatible types in assignment (expression has type "Callable[[AutocompleteContext, float, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]] | None", variable has type "Callable[[AutocompleteContext, str, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]] | None")  [assignment]
- tanjun/commands/slash.py:3225: error: Incompatible types in assignment (expression has type "Callable[[AutocompleteContext, int, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]] | None", variable has type "Callable[[AutocompleteContext, str, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]] | None")  [assignment]
+ tanjun/commands/slash.py:3222: error: Incompatible types in assignment (expression has type "def (AutocompleteContext, float, /, *Any, **Any) -> Coroutine[Any, Any, None] | None", variable has type "def (AutocompleteContext, str, /, *Any, **Any) -> Coroutine[Any, Any, None] | None")  [assignment]
+ tanjun/commands/slash.py:3225: error: Incompatible types in assignment (expression has type "def (AutocompleteContext, int, /, *Any, **Any) -> Coroutine[Any, Any, None] | None", variable has type "def (AutocompleteContext, str, /, *Any, **Any) -> Coroutine[Any, Any, None] | None")  [assignment]
- tanjun/commands/slash.py:3235: error: Argument 1 to "call_with_async_di" of "Context" has incompatible type "Callable[[AutocompleteContext, str, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"; expected "Callable[..., Coroutine[Any, Any, Never] | Never]"  [arg-type]
+ tanjun/commands/slash.py:3235: error: Argument 1 to "call_with_async_di" of "Context" has incompatible type "def (AutocompleteContext, str, /, *Any, **Any) -> Coroutine[Any, Any, None]"; expected "Callable[..., Coroutine[Any, Any, Never] | Never]"  [arg-type]
- tanjun/commands/message.py:78: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:78: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:78: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:78: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:105: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:105: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:105: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:105: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:128: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:128: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:128: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:128: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:162: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:162: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:162: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:162: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:199: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:199: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:199: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:199: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:209: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:209: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:209: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:209: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:395: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:395: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:395: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "Callable[[SlashContext, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:395: error: Type argument "_MessageCallbackSigT" of "SlashCommand" must be a subtype of "def (SlashContext, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]
- tanjun/commands/message.py:406: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "Callable[[MenuContext, Any, VarArg(Any), KwArg(Any)], Coroutine[Any, Any, None]]"  [type-var]
+ tanjun/commands/message.py:406: error: Type argument "_MessageCallbackSigT" of "MenuCommand" must be a subtype of "def (MenuContext, Any, /, *Any, **Any) -> Coroutine[Any, Any, None]"  [type-var]

... (truncated 139 lines) ...```

[theodore-ando]

cc @JukkaL for #5490