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From Samuel Freilich: In Python 2, the predicate parameter in itertools.ifilter and itertools.ifilterfalse can be None, indicating that true or false values should be retained (functionally equivalent to passing "bool" as the predicate). In Python 3, filter and itertools.filterfalse have the same behavior.
106 lines
4.1 KiB
Python
106 lines
4.1 KiB
Python
# Stubs for itertools
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# Based on https://docs.python.org/2/library/itertools.html
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from typing import (Iterator, TypeVar, Iterable, overload, Any, Callable, Tuple,
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Union, Sequence, Generic, Optional)
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_T = TypeVar('_T')
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_S = TypeVar('_S')
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def count(start: int = ...,
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step: int = ...) -> Iterator[int]: ... # more general types?
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def cycle(iterable: Iterable[_T]) -> Iterator[_T]: ...
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def repeat(object: _T, times: int = ...) -> Iterator[_T]: ...
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def accumulate(iterable: Iterable[_T]) -> Iterator[_T]: ...
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class chain(Iterator[_T], Generic[_T]):
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def __init__(self, *iterables: Iterable[_T]) -> None: ...
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def next(self) -> _T: ...
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def __iter__(self) -> Iterator[_T]: ...
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@staticmethod
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def from_iterable(iterable: Iterable[Iterable[_S]]) -> Iterator[_S]: ...
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def compress(data: Iterable[_T], selectors: Iterable[Any]) -> Iterator[_T]: ...
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def dropwhile(predicate: Callable[[_T], Any],
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iterable: Iterable[_T]) -> Iterator[_T]: ...
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def ifilter(predicate: Optional[Callable[[_T], Any]],
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iterable: Iterable[_T]) -> Iterator[_T]: ...
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def ifilterfalse(predicate: Optional[Callable[[_T], Any]],
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iterable: Iterable[_T]) -> Iterator[_T]: ...
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@overload
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def groupby(iterable: Iterable[_T]) -> Iterator[Tuple[_T, Iterator[_T]]]: ...
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@overload
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def groupby(iterable: Iterable[_T],
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key: Callable[[_T], _S]) -> Iterator[Tuple[_S, Iterator[_T]]]: ...
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@overload
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def islice(iterable: Iterable[_T], stop: int) -> Iterator[_T]: ...
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@overload
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def islice(iterable: Iterable[_T], start: int, stop: Optional[int],
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step: int = ...) -> Iterator[_T]: ...
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_T1 = TypeVar('_T1')
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_T2 = TypeVar('_T2')
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_T3 = TypeVar('_T3')
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_T4 = TypeVar('_T4')
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_T5 = TypeVar('_T5')
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_T6 = TypeVar('_T6')
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@overload
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def imap(func: Callable[[_T1], _S], iter1: Iterable[_T1]) -> Iterator[_S]: ...
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@overload
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def imap(func: Callable[[_T1, _T2], _S],
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iter1: Iterable[_T1],
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iter2: Iterable[_T2]) -> Iterator[_S]: ... # TODO more than two iterables
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def starmap(func: Any, iterable: Iterable[Any]) -> Iterator[Any]: ...
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def takewhile(predicate: Callable[[_T], Any],
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iterable: Iterable[_T]) -> Iterator[_T]: ...
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def tee(iterable: Iterable[Any], n: int = ...) -> Iterator[Any]: ...
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@overload
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def izip(iter1: Iterable[_T1]) -> Iterator[Tuple[_T1]]: ...
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@overload
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def izip(iter1: Iterable[_T1],
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iter2: Iterable[_T2]) -> Iterator[Tuple[_T1, _T2]]: ...
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@overload
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def izip(iter1: Iterable[_T1], iter2: Iterable[_T2],
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iter3: Iterable[_T3]) -> Iterator[Tuple[_T1, _T2, _T3]]: ...
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@overload
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def izip(iter1: Iterable[_T1], iter2: Iterable[_T2], iter3: Iterable[_T3],
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iter4: Iterable[_T4]) -> Iterator[Tuple[_T1, _T2,
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_T3, _T4]]: ...
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@overload
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def izip(iter1: Iterable[_T1], iter2: Iterable[_T2],
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iter3: Iterable[_T3], iter4: Iterable[_T4],
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iter5: Iterable[_T5]) -> Iterator[Tuple[_T1, _T2,
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_T3, _T4, _T5]]: ...
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@overload
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def izip(iter1: Iterable[_T1], iter2: Iterable[_T2],
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iter3: Iterable[_T3], iter4: Iterable[_T4],
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iter5: Iterable[_T5], iter6: Iterable[_T6]) -> Iterator[Tuple[_T1, _T2, _T3,
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_T4, _T5, _T6]]: ...
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@overload
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def izip(iter1: Iterable[Any], iter2: Iterable[Any],
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iter3: Iterable[Any], iter4: Iterable[Any],
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iter5: Iterable[Any], iter6: Iterable[Any],
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iter7: Iterable[Any], *iterables: Iterable[Any]) -> Iterator[Tuple[Any, ...]]: ...
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def izip_longest(*p: Iterable[Any],
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fillvalue: Any = ...) -> Iterator[Any]: ...
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# TODO: Return type should be Iterator[Tuple[..]], but unknown tuple shape.
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# Iterator[Sequence[_T]] loses this type information.
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def product(*p: Iterable[_T], repeat: int = ...) -> Iterator[Sequence[_T]]: ...
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def permutations(iterable: Iterable[_T],
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r: int = ...) -> Iterator[Sequence[_T]]: ...
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def combinations(iterable: Iterable[_T],
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r: int) -> Iterator[Sequence[_T]]: ...
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def combinations_with_replacement(iterable: Iterable[_T],
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r: int) -> Iterator[Sequence[_T]]: ...
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