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Bump tempora from 5.1.0 to 5.2.1 (#1977)
* Bump tempora from 5.1.0 to 5.2.1 Bumps [tempora](https://github.com/jaraco/tempora) from 5.1.0 to 5.2.1. - [Release notes](https://github.com/jaraco/tempora/releases) - [Changelog](https://github.com/jaraco/tempora/blob/main/CHANGES.rst) - [Commits](https://github.com/jaraco/tempora/compare/v5.1.0...v5.2.1) --- updated-dependencies: - dependency-name: tempora dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> * Update tempora==5.2.1 --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: JonnyWong16 <9099342+JonnyWong16@users.noreply.github.com> [skip ci]
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@ -1,110 +1,119 @@
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"""Stubs for more_itertools.recipes"""
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from __future__ import annotations
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from typing import (
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Any,
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Callable,
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Iterable,
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Iterator,
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List,
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Optional,
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overload,
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Sequence,
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Tuple,
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Type,
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TypeVar,
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Union,
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)
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from typing_extensions import overload, Type
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# Type and type variable definitions
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_T = TypeVar('_T')
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_U = TypeVar('_U')
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def take(n: int, iterable: Iterable[_T]) -> List[_T]: ...
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def take(n: int, iterable: Iterable[_T]) -> list[_T]: ...
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def tabulate(
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function: Callable[[int], _T], start: int = ...
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) -> Iterator[_T]: ...
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def tail(n: int, iterable: Iterable[_T]) -> Iterator[_T]: ...
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def consume(iterator: Iterable[object], n: Optional[int] = ...) -> None: ...
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def consume(iterator: Iterable[object], n: int | None = ...) -> None: ...
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@overload
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def nth(iterable: Iterable[_T], n: int) -> Optional[_T]: ...
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def nth(iterable: Iterable[_T], n: int) -> _T | None: ...
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@overload
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def nth(iterable: Iterable[_T], n: int, default: _U) -> Union[_T, _U]: ...
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def nth(iterable: Iterable[_T], n: int, default: _U) -> _T | _U: ...
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def all_equal(iterable: Iterable[object]) -> bool: ...
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def quantify(
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iterable: Iterable[_T], pred: Callable[[_T], bool] = ...
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) -> int: ...
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def pad_none(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
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def padnone(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
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def pad_none(iterable: Iterable[_T]) -> Iterator[_T | None]: ...
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def padnone(iterable: Iterable[_T]) -> Iterator[_T | None]: ...
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def ncycles(iterable: Iterable[_T], n: int) -> Iterator[_T]: ...
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def dotproduct(vec1: Iterable[object], vec2: Iterable[object]) -> object: ...
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def flatten(listOfLists: Iterable[Iterable[_T]]) -> Iterator[_T]: ...
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def repeatfunc(
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func: Callable[..., _U], times: Optional[int] = ..., *args: Any
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func: Callable[..., _U], times: int | None = ..., *args: Any
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) -> Iterator[_U]: ...
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def pairwise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T]]: ...
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def pairwise(iterable: Iterable[_T]) -> Iterator[tuple[_T, _T]]: ...
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def grouper(
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iterable: Iterable[_T],
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n: int,
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incomplete: str = ...,
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fillvalue: _U = ...,
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) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
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) -> Iterator[tuple[_T | _U, ...]]: ...
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def roundrobin(*iterables: Iterable[_T]) -> Iterator[_T]: ...
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def partition(
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pred: Optional[Callable[[_T], object]], iterable: Iterable[_T]
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) -> Tuple[Iterator[_T], Iterator[_T]]: ...
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def powerset(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ...
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pred: Callable[[_T], object] | None, iterable: Iterable[_T]
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) -> tuple[Iterator[_T], Iterator[_T]]: ...
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def powerset(iterable: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
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def unique_everseen(
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iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
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iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
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) -> Iterator[_T]: ...
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def unique_justseen(
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iterable: Iterable[_T], key: Optional[Callable[[_T], object]] = ...
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iterable: Iterable[_T], key: Callable[[_T], object] | None = ...
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) -> Iterator[_T]: ...
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@overload
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def iter_except(
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func: Callable[[], _T],
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exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
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exception: Type[BaseException] | tuple[Type[BaseException], ...],
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first: None = ...,
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) -> Iterator[_T]: ...
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@overload
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def iter_except(
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func: Callable[[], _T],
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exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
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exception: Type[BaseException] | tuple[Type[BaseException], ...],
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first: Callable[[], _U],
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) -> Iterator[Union[_T, _U]]: ...
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) -> Iterator[_T | _U]: ...
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@overload
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def first_true(
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iterable: Iterable[_T], *, pred: Optional[Callable[[_T], object]] = ...
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) -> Optional[_T]: ...
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iterable: Iterable[_T], *, pred: Callable[[_T], object] | None = ...
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) -> _T | None: ...
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@overload
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def first_true(
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iterable: Iterable[_T],
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default: _U,
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pred: Optional[Callable[[_T], object]] = ...,
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) -> Union[_T, _U]: ...
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pred: Callable[[_T], object] | None = ...,
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) -> _T | _U: ...
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def random_product(
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*args: Iterable[_T], repeat: int = ...
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) -> Tuple[_T, ...]: ...
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) -> tuple[_T, ...]: ...
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def random_permutation(
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iterable: Iterable[_T], r: Optional[int] = ...
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) -> Tuple[_T, ...]: ...
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def random_combination(iterable: Iterable[_T], r: int) -> Tuple[_T, ...]: ...
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iterable: Iterable[_T], r: int | None = ...
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) -> tuple[_T, ...]: ...
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def random_combination(iterable: Iterable[_T], r: int) -> tuple[_T, ...]: ...
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def random_combination_with_replacement(
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iterable: Iterable[_T], r: int
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) -> Tuple[_T, ...]: ...
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) -> tuple[_T, ...]: ...
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def nth_combination(
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iterable: Iterable[_T], r: int, index: int
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) -> Tuple[_T, ...]: ...
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def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[Union[_T, _U]]: ...
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) -> tuple[_T, ...]: ...
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def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[_T | _U]: ...
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def convolve(signal: Iterable[_T], kernel: Iterable[_T]) -> Iterator[_T]: ...
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def before_and_after(
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predicate: Callable[[_T], bool], it: Iterable[_T]
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) -> Tuple[Iterator[_T], Iterator[_T]]: ...
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def triplewise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T, _T]]: ...
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) -> tuple[Iterator[_T], Iterator[_T]]: ...
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def triplewise(iterable: Iterable[_T]) -> Iterator[tuple[_T, _T, _T]]: ...
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def sliding_window(
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iterable: Iterable[_T], n: int
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) -> Iterator[Tuple[_T, ...]]: ...
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def subslices(iterable: Iterable[_T]) -> Iterator[List[_T]]: ...
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def polynomial_from_roots(roots: Sequence[int]) -> List[int]: ...
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) -> Iterator[tuple[_T, ...]]: ...
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def subslices(iterable: Iterable[_T]) -> Iterator[list[_T]]: ...
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def polynomial_from_roots(roots: Sequence[int]) -> list[int]: ...
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def iter_index(
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iterable: Iterable[object],
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value: Any,
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start: int | None = ...,
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) -> Iterator[int]: ...
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def sieve(n: int) -> Iterator[int]: ...
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def batched(
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iterable: Iterable[_T],
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n: int,
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) -> Iterator[List[_T]]: ...
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) -> Iterator[list[_T]]: ...
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def transpose(
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it: Iterable[Iterable[_T]],
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) -> tuple[Iterator[_T], ...]: ...
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def matmul(m1: Sequence[_T], m2: Sequence[_T]) -> Iterator[list[_T]]: ...
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def factor(n: int) -> Iterator[int]: ...
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