mirror of
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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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commit
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10 changed files with 367 additions and 403 deletions
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@ -4,6 +4,7 @@ import inspect
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import collections
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import types
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import itertools
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import warnings
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import more_itertools
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@ -266,11 +267,33 @@ def result_invoke(action):
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return wrap
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def call_aside(f, *args, **kwargs):
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def invoke(f, *args, **kwargs):
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"""
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Call a function for its side effect after initialization.
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>>> @call_aside
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The benefit of using the decorator instead of simply invoking a function
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after defining it is that it makes explicit the author's intent for the
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function to be called immediately. Whereas if one simply calls the
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function immediately, it's less obvious if that was intentional or
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incidental. It also avoids repeating the name - the two actions, defining
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the function and calling it immediately are modeled separately, but linked
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by the decorator construct.
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The benefit of having a function construct (opposed to just invoking some
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behavior inline) is to serve as a scope in which the behavior occurs. It
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avoids polluting the global namespace with local variables, provides an
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anchor on which to attach documentation (docstring), keeps the behavior
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logically separated (instead of conceptually separated or not separated at
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all), and provides potential to re-use the behavior for testing or other
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purposes.
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This function is named as a pithy way to communicate, "call this function
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primarily for its side effect", or "while defining this function, also
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take it aside and call it". It exists because there's no Python construct
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for "define and call" (nor should there be, as decorators serve this need
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just fine). The behavior happens immediately and synchronously.
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>>> @invoke
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... def func(): print("called")
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called
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>>> func()
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@ -278,7 +301,7 @@ def call_aside(f, *args, **kwargs):
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Use functools.partial to pass parameters to the initial call
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>>> @functools.partial(call_aside, name='bingo')
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>>> @functools.partial(invoke, name='bingo')
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... def func(name): print("called with", name)
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called with bingo
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"""
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@ -286,6 +309,14 @@ def call_aside(f, *args, **kwargs):
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return f
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def call_aside(*args, **kwargs):
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"""
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Deprecated name for invoke.
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"""
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warnings.warn("call_aside is deprecated, use invoke", DeprecationWarning)
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return invoke(*args, **kwargs)
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class Throttler:
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"""
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Rate-limit a function (or other callable)
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@ -3,4 +3,4 @@
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from .more import * # noqa
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from .recipes import * # noqa
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__version__ = '9.0.0'
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__version__ = '9.1.0'
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@ -68,6 +68,7 @@ __all__ = [
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'exactly_n',
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'filter_except',
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'first',
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'gray_product',
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'groupby_transform',
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'ichunked',
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'iequals',
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@ -658,6 +659,7 @@ def distinct_permutations(iterable, r=None):
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[(0, 1), (0, 2), (1, 0), (1, 2), (2, 0), (2, 1)]
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"""
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# Algorithm: https://w.wiki/Qai
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def _full(A):
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while True:
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@ -1301,7 +1303,7 @@ def split_at(iterable, pred, maxsplit=-1, keep_separator=False):
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[[0], [2], [4, 5, 6, 7, 8, 9]]
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By default, the delimiting items are not included in the output.
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The include them, set *keep_separator* to ``True``.
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To include them, set *keep_separator* to ``True``.
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>>> list(split_at('abcdcba', lambda x: x == 'b', keep_separator=True))
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[['a'], ['b'], ['c', 'd', 'c'], ['b'], ['a']]
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@ -1391,7 +1393,9 @@ def split_after(iterable, pred, maxsplit=-1):
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if pred(item) and buf:
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yield buf
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if maxsplit == 1:
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yield list(it)
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buf = list(it)
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if buf:
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yield buf
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return
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buf = []
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maxsplit -= 1
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@ -2914,6 +2918,7 @@ def make_decorator(wrapping_func, result_index=0):
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'7'
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"""
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# See https://sites.google.com/site/bbayles/index/decorator_factory for
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# notes on how this works.
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def decorator(*wrapping_args, **wrapping_kwargs):
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@ -3464,7 +3469,6 @@ def _sample_unweighted(iterable, k):
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next_index = k + floor(log(random()) / log(1 - W))
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for index, element in enumerate(iterable, k):
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if index == next_index:
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reservoir[randrange(k)] = element
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# The new W is the largest in a sample of k U(0, `old_W`) numbers
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@ -4284,7 +4288,6 @@ def minmax(iterable_or_value, *others, key=None, default=_marker):
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lo_key = hi_key = key(lo)
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for x, y in zip_longest(it, it, fillvalue=lo):
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x_key, y_key = key(x), key(y)
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if y_key < x_key:
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@ -4345,3 +4348,45 @@ def constrained_batches(
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if batch:
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yield tuple(batch)
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def gray_product(*iterables):
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"""Like :func:`itertools.product`, but return tuples in an order such
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that only one element in the generated tuple changes from one iteration
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to the next.
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>>> list(gray_product('AB','CD'))
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[('A', 'C'), ('B', 'C'), ('B', 'D'), ('A', 'D')]
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This function consumes all of the input iterables before producing output.
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If any of the input iterables have fewer than two items, ``ValueError``
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is raised.
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For information on the algorithm, see
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`this section <https://www-cs-faculty.stanford.edu/~knuth/fasc2a.ps.gz>`__
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of Donald Knuth's *The Art of Computer Programming*.
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"""
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all_iterables = tuple(tuple(x) for x in iterables)
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iterable_count = len(all_iterables)
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for iterable in all_iterables:
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if len(iterable) < 2:
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raise ValueError("each iterable must have two or more items")
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# This is based on "Algorithm H" from section 7.2.1.1, page 20.
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# a holds the indexes of the source iterables for the n-tuple to be yielded
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# f is the array of "focus pointers"
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# o is the array of "directions"
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a = [0] * iterable_count
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f = list(range(iterable_count + 1))
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o = [1] * iterable_count
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while True:
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yield tuple(all_iterables[i][a[i]] for i in range(iterable_count))
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j = f[0]
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f[0] = 0
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if j == iterable_count:
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break
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a[j] = a[j] + o[j]
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if a[j] == 0 or a[j] == len(all_iterables[j]) - 1:
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o[j] = -o[j]
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f[j] = f[j + 1]
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f[j + 1] = j + 1
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@ -1,26 +1,25 @@
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"""Stubs for more_itertools.more"""
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from __future__ import annotations
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from types import TracebackType
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from typing import (
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Any,
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Callable,
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Container,
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Dict,
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ContextManager,
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Generic,
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Hashable,
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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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Reversible,
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Sequence,
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Sized,
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Tuple,
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Union,
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Type,
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TypeVar,
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type_check_only,
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)
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from types import TracebackType
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from typing_extensions import ContextManager, Protocol, Type, overload
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from typing_extensions import Protocol
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# Type and type variable definitions
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_T = TypeVar('_T')
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@ -31,7 +30,7 @@ _V = TypeVar('_V')
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_W = TypeVar('_W')
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_T_co = TypeVar('_T_co', covariant=True)
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_GenFn = TypeVar('_GenFn', bound=Callable[..., Iterator[object]])
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_Raisable = Union[BaseException, 'Type[BaseException]']
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_Raisable = BaseException | Type[BaseException]
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@type_check_only
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class _SizedIterable(Protocol[_T_co], Sized, Iterable[_T_co]): ...
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@ -39,23 +38,25 @@ class _SizedIterable(Protocol[_T_co], Sized, Iterable[_T_co]): ...
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@type_check_only
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class _SizedReversible(Protocol[_T_co], Sized, Reversible[_T_co]): ...
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@type_check_only
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class _SupportsSlicing(Protocol[_T_co]):
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def __getitem__(self, __k: slice) -> _T_co: ...
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def chunked(
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iterable: Iterable[_T], n: Optional[int], strict: bool = ...
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) -> Iterator[List[_T]]: ...
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iterable: Iterable[_T], n: int | None, strict: bool = ...
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) -> Iterator[list[_T]]: ...
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@overload
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def first(iterable: Iterable[_T]) -> _T: ...
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@overload
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def first(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ...
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def first(iterable: Iterable[_T], default: _U) -> _T | _U: ...
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@overload
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def last(iterable: Iterable[_T]) -> _T: ...
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@overload
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def last(iterable: Iterable[_T], default: _U) -> Union[_T, _U]: ...
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def last(iterable: Iterable[_T], default: _U) -> _T | _U: ...
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@overload
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def nth_or_last(iterable: Iterable[_T], n: int) -> _T: ...
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@overload
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def nth_or_last(
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iterable: Iterable[_T], n: int, default: _U
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) -> Union[_T, _U]: ...
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def nth_or_last(iterable: Iterable[_T], n: int, default: _U) -> _T | _U: ...
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class peekable(Generic[_T], Iterator[_T]):
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def __init__(self, iterable: Iterable[_T]) -> None: ...
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@ -64,13 +65,13 @@ class peekable(Generic[_T], Iterator[_T]):
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@overload
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def peek(self) -> _T: ...
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@overload
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def peek(self, default: _U) -> Union[_T, _U]: ...
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def peek(self, default: _U) -> _T | _U: ...
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def prepend(self, *items: _T) -> None: ...
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def __next__(self) -> _T: ...
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@overload
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def __getitem__(self, index: int) -> _T: ...
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@overload
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def __getitem__(self, index: slice) -> List[_T]: ...
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def __getitem__(self, index: slice) -> list[_T]: ...
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def consumer(func: _GenFn) -> _GenFn: ...
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def ilen(iterable: Iterable[object]) -> int: ...
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@ -80,42 +81,42 @@ def with_iter(
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) -> Iterator[_T]: ...
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def one(
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iterable: Iterable[_T],
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too_short: Optional[_Raisable] = ...,
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too_long: Optional[_Raisable] = ...,
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too_short: _Raisable | None = ...,
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too_long: _Raisable | None = ...,
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) -> _T: ...
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def raise_(exception: _Raisable, *args: Any) -> None: ...
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def strictly_n(
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iterable: Iterable[_T],
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n: int,
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too_short: Optional[_GenFn] = ...,
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too_long: Optional[_GenFn] = ...,
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) -> List[_T]: ...
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too_short: _GenFn | None = ...,
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too_long: _GenFn | None = ...,
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) -> list[_T]: ...
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def distinct_permutations(
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iterable: Iterable[_T], r: Optional[int] = ...
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) -> Iterator[Tuple[_T, ...]]: ...
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iterable: Iterable[_T], r: int | None = ...
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) -> Iterator[tuple[_T, ...]]: ...
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def intersperse(
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e: _U, iterable: Iterable[_T], n: int = ...
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) -> Iterator[Union[_T, _U]]: ...
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def unique_to_each(*iterables: Iterable[_T]) -> List[List[_T]]: ...
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) -> Iterator[_T | _U]: ...
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def unique_to_each(*iterables: Iterable[_T]) -> list[list[_T]]: ...
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@overload
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def windowed(
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seq: Iterable[_T], n: int, *, step: int = ...
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) -> Iterator[Tuple[Optional[_T], ...]]: ...
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) -> Iterator[tuple[_T | None, ...]]: ...
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@overload
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def windowed(
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seq: Iterable[_T], n: int, fillvalue: _U, step: int = ...
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) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
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def substrings(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ...
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) -> Iterator[tuple[_T | _U, ...]]: ...
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def substrings(iterable: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
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def substrings_indexes(
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seq: Sequence[_T], reverse: bool = ...
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) -> Iterator[Tuple[Sequence[_T], int, int]]: ...
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) -> Iterator[tuple[Sequence[_T], int, int]]: ...
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class bucket(Generic[_T, _U], Container[_U]):
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def __init__(
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self,
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iterable: Iterable[_T],
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key: Callable[[_T], _U],
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validator: Optional[Callable[[object], object]] = ...,
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validator: Callable[[object], object] | None = ...,
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) -> None: ...
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def __contains__(self, value: object) -> bool: ...
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def __iter__(self) -> Iterator[_U]: ...
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|
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@ -123,109 +124,105 @@ class bucket(Generic[_T, _U], Container[_U]):
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def spy(
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iterable: Iterable[_T], n: int = ...
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) -> Tuple[List[_T], Iterator[_T]]: ...
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) -> tuple[list[_T], Iterator[_T]]: ...
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def interleave(*iterables: Iterable[_T]) -> Iterator[_T]: ...
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def interleave_longest(*iterables: Iterable[_T]) -> Iterator[_T]: ...
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def interleave_evenly(
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iterables: List[Iterable[_T]], lengths: Optional[List[int]] = ...
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iterables: list[Iterable[_T]], lengths: list[int] | None = ...
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) -> Iterator[_T]: ...
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def collapse(
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iterable: Iterable[Any],
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base_type: Optional[type] = ...,
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levels: Optional[int] = ...,
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base_type: type | None = ...,
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levels: int | None = ...,
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) -> Iterator[Any]: ...
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@overload
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def side_effect(
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func: Callable[[_T], object],
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iterable: Iterable[_T],
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chunk_size: None = ...,
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before: Optional[Callable[[], object]] = ...,
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after: Optional[Callable[[], object]] = ...,
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before: Callable[[], object] | None = ...,
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after: Callable[[], object] | None = ...,
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) -> Iterator[_T]: ...
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@overload
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def side_effect(
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func: Callable[[List[_T]], object],
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func: Callable[[list[_T]], object],
|
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iterable: Iterable[_T],
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chunk_size: int,
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before: Optional[Callable[[], object]] = ...,
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after: Optional[Callable[[], object]] = ...,
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before: Callable[[], object] | None = ...,
|
||||
after: Callable[[], object] | None = ...,
|
||||
) -> Iterator[_T]: ...
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def sliced(
|
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seq: Sequence[_T], n: int, strict: bool = ...
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||||
) -> Iterator[Sequence[_T]]: ...
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seq: _SupportsSlicing[_T], n: int, strict: bool = ...
|
||||
) -> Iterator[_T]: ...
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def split_at(
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iterable: Iterable[_T],
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pred: Callable[[_T], object],
|
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maxsplit: int = ...,
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||||
keep_separator: bool = ...,
|
||||
) -> Iterator[List[_T]]: ...
|
||||
) -> Iterator[list[_T]]: ...
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def split_before(
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iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ...
|
||||
) -> Iterator[List[_T]]: ...
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||||
) -> Iterator[list[_T]]: ...
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def split_after(
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iterable: Iterable[_T], pred: Callable[[_T], object], maxsplit: int = ...
|
||||
) -> Iterator[List[_T]]: ...
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||||
) -> Iterator[list[_T]]: ...
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def split_when(
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iterable: Iterable[_T],
|
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pred: Callable[[_T, _T], object],
|
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maxsplit: int = ...,
|
||||
) -> Iterator[List[_T]]: ...
|
||||
) -> Iterator[list[_T]]: ...
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def split_into(
|
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iterable: Iterable[_T], sizes: Iterable[Optional[int]]
|
||||
) -> Iterator[List[_T]]: ...
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iterable: Iterable[_T], sizes: Iterable[int | None]
|
||||
) -> Iterator[list[_T]]: ...
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@overload
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def padded(
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iterable: Iterable[_T],
|
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*,
|
||||
n: Optional[int] = ...,
|
||||
n: int | None = ...,
|
||||
next_multiple: bool = ...,
|
||||
) -> Iterator[Optional[_T]]: ...
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||||
) -> Iterator[_T | None]: ...
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@overload
|
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def padded(
|
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iterable: Iterable[_T],
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fillvalue: _U,
|
||||
n: Optional[int] = ...,
|
||||
n: int | None = ...,
|
||||
next_multiple: bool = ...,
|
||||
) -> Iterator[Union[_T, _U]]: ...
|
||||
) -> Iterator[_T | _U]: ...
|
||||
@overload
|
||||
def repeat_last(iterable: Iterable[_T]) -> Iterator[_T]: ...
|
||||
@overload
|
||||
def repeat_last(
|
||||
iterable: Iterable[_T], default: _U
|
||||
) -> Iterator[Union[_T, _U]]: ...
|
||||
def distribute(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ...
|
||||
def repeat_last(iterable: Iterable[_T], default: _U) -> Iterator[_T | _U]: ...
|
||||
def distribute(n: int, iterable: Iterable[_T]) -> list[Iterator[_T]]: ...
|
||||
@overload
|
||||
def stagger(
|
||||
iterable: Iterable[_T],
|
||||
offsets: _SizedIterable[int] = ...,
|
||||
longest: bool = ...,
|
||||
) -> Iterator[Tuple[Optional[_T], ...]]: ...
|
||||
) -> Iterator[tuple[_T | None, ...]]: ...
|
||||
@overload
|
||||
def stagger(
|
||||
iterable: Iterable[_T],
|
||||
offsets: _SizedIterable[int] = ...,
|
||||
longest: bool = ...,
|
||||
fillvalue: _U = ...,
|
||||
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
|
||||
) -> Iterator[tuple[_T | _U, ...]]: ...
|
||||
|
||||
class UnequalIterablesError(ValueError):
|
||||
def __init__(
|
||||
self, details: Optional[Tuple[int, int, int]] = ...
|
||||
) -> None: ...
|
||||
def __init__(self, details: tuple[int, int, int] | None = ...) -> None: ...
|
||||
|
||||
@overload
|
||||
def zip_equal(__iter1: Iterable[_T1]) -> Iterator[Tuple[_T1]]: ...
|
||||
def zip_equal(__iter1: Iterable[_T1]) -> Iterator[tuple[_T1]]: ...
|
||||
@overload
|
||||
def zip_equal(
|
||||
__iter1: Iterable[_T1], __iter2: Iterable[_T2]
|
||||
) -> Iterator[Tuple[_T1, _T2]]: ...
|
||||
) -> Iterator[tuple[_T1, _T2]]: ...
|
||||
@overload
|
||||
def zip_equal(
|
||||
__iter1: Iterable[_T],
|
||||
__iter2: Iterable[_T],
|
||||
__iter3: Iterable[_T],
|
||||
*iterables: Iterable[_T],
|
||||
) -> Iterator[Tuple[_T, ...]]: ...
|
||||
) -> Iterator[tuple[_T, ...]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T1],
|
||||
|
|
@ -233,7 +230,7 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: None = None,
|
||||
) -> Iterator[Tuple[Optional[_T1]]]: ...
|
||||
) -> Iterator[tuple[_T1 | None]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T1],
|
||||
|
|
@ -242,7 +239,7 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: None = None,
|
||||
) -> Iterator[Tuple[Optional[_T1], Optional[_T2]]]: ...
|
||||
) -> Iterator[tuple[_T1 | None, _T2 | None]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T],
|
||||
|
|
@ -252,7 +249,7 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: None = None,
|
||||
) -> Iterator[Tuple[Optional[_T], ...]]: ...
|
||||
) -> Iterator[tuple[_T | None, ...]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T1],
|
||||
|
|
@ -260,7 +257,7 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: _U,
|
||||
) -> Iterator[Tuple[Union[_T1, _U]]]: ...
|
||||
) -> Iterator[tuple[_T1 | _U]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T1],
|
||||
|
|
@ -269,7 +266,7 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: _U,
|
||||
) -> Iterator[Tuple[Union[_T1, _U], Union[_T2, _U]]]: ...
|
||||
) -> Iterator[tuple[_T1 | _U, _T2 | _U]]: ...
|
||||
@overload
|
||||
def zip_offset(
|
||||
__iter1: Iterable[_T],
|
||||
|
|
@ -279,82 +276,80 @@ def zip_offset(
|
|||
offsets: _SizedIterable[int],
|
||||
longest: bool = ...,
|
||||
fillvalue: _U,
|
||||
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
|
||||
) -> Iterator[tuple[_T | _U, ...]]: ...
|
||||
def sort_together(
|
||||
iterables: Iterable[Iterable[_T]],
|
||||
key_list: Iterable[int] = ...,
|
||||
key: Optional[Callable[..., Any]] = ...,
|
||||
key: Callable[..., Any] | None = ...,
|
||||
reverse: bool = ...,
|
||||
) -> List[Tuple[_T, ...]]: ...
|
||||
def unzip(iterable: Iterable[Sequence[_T]]) -> Tuple[Iterator[_T], ...]: ...
|
||||
def divide(n: int, iterable: Iterable[_T]) -> List[Iterator[_T]]: ...
|
||||
) -> list[tuple[_T, ...]]: ...
|
||||
def unzip(iterable: Iterable[Sequence[_T]]) -> tuple[Iterator[_T], ...]: ...
|
||||
def divide(n: int, iterable: Iterable[_T]) -> list[Iterator[_T]]: ...
|
||||
def always_iterable(
|
||||
obj: object,
|
||||
base_type: Union[
|
||||
type, Tuple[Union[type, Tuple[Any, ...]], ...], None
|
||||
] = ...,
|
||||
base_type: type | tuple[type | tuple[Any, ...], ...] | None = ...,
|
||||
) -> Iterator[Any]: ...
|
||||
def adjacent(
|
||||
predicate: Callable[[_T], bool],
|
||||
iterable: Iterable[_T],
|
||||
distance: int = ...,
|
||||
) -> Iterator[Tuple[bool, _T]]: ...
|
||||
) -> Iterator[tuple[bool, _T]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: None = None,
|
||||
valuefunc: None = None,
|
||||
reducefunc: None = None,
|
||||
) -> Iterator[Tuple[_T, Iterator[_T]]]: ...
|
||||
) -> Iterator[tuple[_T, Iterator[_T]]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: None,
|
||||
reducefunc: None,
|
||||
) -> Iterator[Tuple[_U, Iterator[_T]]]: ...
|
||||
) -> Iterator[tuple[_U, Iterator[_T]]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: None,
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: None,
|
||||
) -> Iterable[Tuple[_T, Iterable[_V]]]: ...
|
||||
) -> Iterable[tuple[_T, Iterable[_V]]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: None,
|
||||
) -> Iterable[Tuple[_U, Iterator[_V]]]: ...
|
||||
) -> Iterable[tuple[_U, Iterator[_V]]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: None,
|
||||
valuefunc: None,
|
||||
reducefunc: Callable[[Iterator[_T]], _W],
|
||||
) -> Iterable[Tuple[_T, _W]]: ...
|
||||
) -> Iterable[tuple[_T, _W]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: None,
|
||||
reducefunc: Callable[[Iterator[_T]], _W],
|
||||
) -> Iterable[Tuple[_U, _W]]: ...
|
||||
) -> Iterable[tuple[_U, _W]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: None,
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: Callable[[Iterable[_V]], _W],
|
||||
) -> Iterable[Tuple[_T, _W]]: ...
|
||||
) -> Iterable[tuple[_T, _W]]: ...
|
||||
@overload
|
||||
def groupby_transform(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: Callable[[Iterable[_V]], _W],
|
||||
) -> Iterable[Tuple[_U, _W]]: ...
|
||||
) -> Iterable[tuple[_U, _W]]: ...
|
||||
|
||||
class numeric_range(Generic[_T, _U], Sequence[_T], Hashable, Reversible[_T]):
|
||||
@overload
|
||||
|
|
@ -375,22 +370,22 @@ class numeric_range(Generic[_T, _U], Sequence[_T], Hashable, Reversible[_T]):
|
|||
def __len__(self) -> int: ...
|
||||
def __reduce__(
|
||||
self,
|
||||
) -> Tuple[Type[numeric_range[_T, _U]], Tuple[_T, _T, _U]]: ...
|
||||
) -> tuple[Type[numeric_range[_T, _U]], tuple[_T, _T, _U]]: ...
|
||||
def __repr__(self) -> str: ...
|
||||
def __reversed__(self) -> Iterator[_T]: ...
|
||||
def count(self, value: _T) -> int: ...
|
||||
def index(self, value: _T) -> int: ... # type: ignore
|
||||
|
||||
def count_cycle(
|
||||
iterable: Iterable[_T], n: Optional[int] = ...
|
||||
) -> Iterable[Tuple[int, _T]]: ...
|
||||
iterable: Iterable[_T], n: int | None = ...
|
||||
) -> Iterable[tuple[int, _T]]: ...
|
||||
def mark_ends(
|
||||
iterable: Iterable[_T],
|
||||
) -> Iterable[Tuple[bool, bool, _T]]: ...
|
||||
) -> Iterable[tuple[bool, bool, _T]]: ...
|
||||
def locate(
|
||||
iterable: Iterable[object],
|
||||
pred: Callable[..., Any] = ...,
|
||||
window_size: Optional[int] = ...,
|
||||
window_size: int | None = ...,
|
||||
) -> Iterator[int]: ...
|
||||
def lstrip(
|
||||
iterable: Iterable[_T], pred: Callable[[_T], object]
|
||||
|
|
@ -403,9 +398,7 @@ def strip(
|
|||
) -> Iterator[_T]: ...
|
||||
|
||||
class islice_extended(Generic[_T], Iterator[_T]):
|
||||
def __init__(
|
||||
self, iterable: Iterable[_T], *args: Optional[int]
|
||||
) -> None: ...
|
||||
def __init__(self, iterable: Iterable[_T], *args: int | None) -> None: ...
|
||||
def __iter__(self) -> islice_extended[_T]: ...
|
||||
def __next__(self) -> _T: ...
|
||||
def __getitem__(self, index: slice) -> islice_extended[_T]: ...
|
||||
|
|
@ -420,7 +413,7 @@ def difference(
|
|||
func: Callable[[_T, _T], _U] = ...,
|
||||
*,
|
||||
initial: None = ...,
|
||||
) -> Iterator[Union[_T, _U]]: ...
|
||||
) -> Iterator[_T | _U]: ...
|
||||
@overload
|
||||
def difference(
|
||||
iterable: Iterable[_T], func: Callable[[_T, _T], _U] = ..., *, initial: _U
|
||||
|
|
@ -436,7 +429,7 @@ class SequenceView(Generic[_T], Sequence[_T]):
|
|||
|
||||
class seekable(Generic[_T], Iterator[_T]):
|
||||
def __init__(
|
||||
self, iterable: Iterable[_T], maxlen: Optional[int] = ...
|
||||
self, iterable: Iterable[_T], maxlen: int | None = ...
|
||||
) -> None: ...
|
||||
def __iter__(self) -> seekable[_T]: ...
|
||||
def __next__(self) -> _T: ...
|
||||
|
|
@ -444,20 +437,20 @@ class seekable(Generic[_T], Iterator[_T]):
|
|||
@overload
|
||||
def peek(self) -> _T: ...
|
||||
@overload
|
||||
def peek(self, default: _U) -> Union[_T, _U]: ...
|
||||
def peek(self, default: _U) -> _T | _U: ...
|
||||
def elements(self) -> SequenceView[_T]: ...
|
||||
def seek(self, index: int) -> None: ...
|
||||
|
||||
class run_length:
|
||||
@staticmethod
|
||||
def encode(iterable: Iterable[_T]) -> Iterator[Tuple[_T, int]]: ...
|
||||
def encode(iterable: Iterable[_T]) -> Iterator[tuple[_T, int]]: ...
|
||||
@staticmethod
|
||||
def decode(iterable: Iterable[Tuple[_T, int]]) -> Iterator[_T]: ...
|
||||
def decode(iterable: Iterable[tuple[_T, int]]) -> Iterator[_T]: ...
|
||||
|
||||
def exactly_n(
|
||||
iterable: Iterable[_T], n: int, predicate: Callable[[_T], object] = ...
|
||||
) -> bool: ...
|
||||
def circular_shifts(iterable: Iterable[_T]) -> List[Tuple[_T, ...]]: ...
|
||||
def circular_shifts(iterable: Iterable[_T]) -> list[tuple[_T, ...]]: ...
|
||||
def make_decorator(
|
||||
wrapping_func: Callable[..., _U], result_index: int = ...
|
||||
) -> Callable[..., Callable[[Callable[..., Any]], Callable[..., _U]]]: ...
|
||||
|
|
@ -467,44 +460,44 @@ def map_reduce(
|
|||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: None = ...,
|
||||
reducefunc: None = ...,
|
||||
) -> Dict[_U, List[_T]]: ...
|
||||
) -> dict[_U, list[_T]]: ...
|
||||
@overload
|
||||
def map_reduce(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: None = ...,
|
||||
) -> Dict[_U, List[_V]]: ...
|
||||
) -> dict[_U, list[_V]]: ...
|
||||
@overload
|
||||
def map_reduce(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: None = ...,
|
||||
reducefunc: Callable[[List[_T]], _W] = ...,
|
||||
) -> Dict[_U, _W]: ...
|
||||
reducefunc: Callable[[list[_T]], _W] = ...,
|
||||
) -> dict[_U, _W]: ...
|
||||
@overload
|
||||
def map_reduce(
|
||||
iterable: Iterable[_T],
|
||||
keyfunc: Callable[[_T], _U],
|
||||
valuefunc: Callable[[_T], _V],
|
||||
reducefunc: Callable[[List[_V]], _W],
|
||||
) -> Dict[_U, _W]: ...
|
||||
reducefunc: Callable[[list[_V]], _W],
|
||||
) -> dict[_U, _W]: ...
|
||||
def rlocate(
|
||||
iterable: Iterable[_T],
|
||||
pred: Callable[..., object] = ...,
|
||||
window_size: Optional[int] = ...,
|
||||
window_size: int | None = ...,
|
||||
) -> Iterator[int]: ...
|
||||
def replace(
|
||||
iterable: Iterable[_T],
|
||||
pred: Callable[..., object],
|
||||
substitutes: Iterable[_U],
|
||||
count: Optional[int] = ...,
|
||||
count: int | None = ...,
|
||||
window_size: int = ...,
|
||||
) -> Iterator[Union[_T, _U]]: ...
|
||||
def partitions(iterable: Iterable[_T]) -> Iterator[List[List[_T]]]: ...
|
||||
) -> Iterator[_T | _U]: ...
|
||||
def partitions(iterable: Iterable[_T]) -> Iterator[list[list[_T]]]: ...
|
||||
def set_partitions(
|
||||
iterable: Iterable[_T], k: Optional[int] = ...
|
||||
) -> Iterator[List[List[_T]]]: ...
|
||||
iterable: Iterable[_T], k: int | None = ...
|
||||
) -> Iterator[list[list[_T]]]: ...
|
||||
|
||||
class time_limited(Generic[_T], Iterator[_T]):
|
||||
def __init__(
|
||||
|
|
@ -515,16 +508,16 @@ class time_limited(Generic[_T], Iterator[_T]):
|
|||
|
||||
@overload
|
||||
def only(
|
||||
iterable: Iterable[_T], *, too_long: Optional[_Raisable] = ...
|
||||
) -> Optional[_T]: ...
|
||||
iterable: Iterable[_T], *, too_long: _Raisable | None = ...
|
||||
) -> _T | None: ...
|
||||
@overload
|
||||
def only(
|
||||
iterable: Iterable[_T], default: _U, too_long: Optional[_Raisable] = ...
|
||||
) -> Union[_T, _U]: ...
|
||||
iterable: Iterable[_T], default: _U, too_long: _Raisable | None = ...
|
||||
) -> _T | _U: ...
|
||||
def ichunked(iterable: Iterable[_T], n: int) -> Iterator[Iterator[_T]]: ...
|
||||
def distinct_combinations(
|
||||
iterable: Iterable[_T], r: int
|
||||
) -> Iterator[Tuple[_T, ...]]: ...
|
||||
) -> Iterator[tuple[_T, ...]]: ...
|
||||
def filter_except(
|
||||
validator: Callable[[Any], object],
|
||||
iterable: Iterable[_T],
|
||||
|
|
@ -539,16 +532,16 @@ def map_if(
|
|||
iterable: Iterable[Any],
|
||||
pred: Callable[[Any], bool],
|
||||
func: Callable[[Any], Any],
|
||||
func_else: Optional[Callable[[Any], Any]] = ...,
|
||||
func_else: Callable[[Any], Any] | None = ...,
|
||||
) -> Iterator[Any]: ...
|
||||
def sample(
|
||||
iterable: Iterable[_T],
|
||||
k: int,
|
||||
weights: Optional[Iterable[float]] = ...,
|
||||
) -> List[_T]: ...
|
||||
weights: Iterable[float] | None = ...,
|
||||
) -> list[_T]: ...
|
||||
def is_sorted(
|
||||
iterable: Iterable[_T],
|
||||
key: Optional[Callable[[_T], _U]] = ...,
|
||||
key: Callable[[_T], _U] | None = ...,
|
||||
reverse: bool = False,
|
||||
strict: bool = False,
|
||||
) -> bool: ...
|
||||
|
|
@ -566,10 +559,10 @@ class callback_iter(Generic[_T], Iterator[_T]):
|
|||
def __enter__(self) -> callback_iter[_T]: ...
|
||||
def __exit__(
|
||||
self,
|
||||
exc_type: Optional[Type[BaseException]],
|
||||
exc_value: Optional[BaseException],
|
||||
traceback: Optional[TracebackType],
|
||||
) -> Optional[bool]: ...
|
||||
exc_type: Type[BaseException] | None,
|
||||
exc_value: BaseException | None,
|
||||
traceback: TracebackType | None,
|
||||
) -> bool | None: ...
|
||||
def __iter__(self) -> callback_iter[_T]: ...
|
||||
def __next__(self) -> _T: ...
|
||||
def _reader(self) -> Iterator[_T]: ...
|
||||
|
|
@ -580,15 +573,15 @@ class callback_iter(Generic[_T], Iterator[_T]):
|
|||
|
||||
def windowed_complete(
|
||||
iterable: Iterable[_T], n: int
|
||||
) -> Iterator[Tuple[_T, ...]]: ...
|
||||
) -> Iterator[tuple[_T, ...]]: ...
|
||||
def all_unique(
|
||||
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
|
||||
iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
|
||||
) -> bool: ...
|
||||
def nth_product(index: int, *args: Iterable[_T]) -> Tuple[_T, ...]: ...
|
||||
def nth_product(index: int, *args: Iterable[_T]) -> tuple[_T, ...]: ...
|
||||
def nth_permutation(
|
||||
iterable: Iterable[_T], r: int, index: int
|
||||
) -> Tuple[_T, ...]: ...
|
||||
def value_chain(*args: Union[_T, Iterable[_T]]) -> Iterable[_T]: ...
|
||||
) -> tuple[_T, ...]: ...
|
||||
def value_chain(*args: _T | Iterable[_T]) -> Iterable[_T]: ...
|
||||
def product_index(element: Iterable[_T], *args: Iterable[_T]) -> int: ...
|
||||
def combination_index(
|
||||
element: Iterable[_T], iterable: Iterable[_T]
|
||||
|
|
@ -603,22 +596,20 @@ class countable(Generic[_T], Iterator[_T]):
|
|||
def __iter__(self) -> countable[_T]: ...
|
||||
def __next__(self) -> _T: ...
|
||||
|
||||
def chunked_even(iterable: Iterable[_T], n: int) -> Iterator[List[_T]]: ...
|
||||
def chunked_even(iterable: Iterable[_T], n: int) -> Iterator[list[_T]]: ...
|
||||
def zip_broadcast(
|
||||
*objects: Union[_T, Iterable[_T]],
|
||||
scalar_types: Union[
|
||||
type, Tuple[Union[type, Tuple[Any, ...]], ...], None
|
||||
] = ...,
|
||||
*objects: _T | Iterable[_T],
|
||||
scalar_types: type | tuple[type | tuple[Any, ...], ...] | None = ...,
|
||||
strict: bool = ...,
|
||||
) -> Iterable[Tuple[_T, ...]]: ...
|
||||
) -> Iterable[tuple[_T, ...]]: ...
|
||||
def unique_in_window(
|
||||
iterable: Iterable[_T], n: int, key: Optional[Callable[[_T], _U]] = ...
|
||||
iterable: Iterable[_T], n: int, key: Callable[[_T], _U] | None = ...
|
||||
) -> Iterator[_T]: ...
|
||||
def duplicates_everseen(
|
||||
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
|
||||
iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
|
||||
) -> Iterator[_T]: ...
|
||||
def duplicates_justseen(
|
||||
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
|
||||
iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
|
||||
) -> Iterator[_T]: ...
|
||||
|
||||
class _SupportsLessThan(Protocol):
|
||||
|
|
@ -629,38 +620,38 @@ _SupportsLessThanT = TypeVar("_SupportsLessThanT", bound=_SupportsLessThan)
|
|||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: Iterable[_SupportsLessThanT], *, key: None = None
|
||||
) -> Tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
|
||||
) -> tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
|
||||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: Iterable[_T], *, key: Callable[[_T], _SupportsLessThan]
|
||||
) -> Tuple[_T, _T]: ...
|
||||
) -> tuple[_T, _T]: ...
|
||||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: Iterable[_SupportsLessThanT],
|
||||
*,
|
||||
key: None = None,
|
||||
default: _U,
|
||||
) -> Union[_U, Tuple[_SupportsLessThanT, _SupportsLessThanT]]: ...
|
||||
) -> _U | tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
|
||||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: Iterable[_T],
|
||||
*,
|
||||
key: Callable[[_T], _SupportsLessThan],
|
||||
default: _U,
|
||||
) -> Union[_U, Tuple[_T, _T]]: ...
|
||||
) -> _U | tuple[_T, _T]: ...
|
||||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: _SupportsLessThanT,
|
||||
__other: _SupportsLessThanT,
|
||||
*others: _SupportsLessThanT,
|
||||
) -> Tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
|
||||
) -> tuple[_SupportsLessThanT, _SupportsLessThanT]: ...
|
||||
@overload
|
||||
def minmax(
|
||||
iterable_or_value: _T,
|
||||
__other: _T,
|
||||
*others: _T,
|
||||
key: Callable[[_T], _SupportsLessThan],
|
||||
) -> Tuple[_T, _T]: ...
|
||||
) -> tuple[_T, _T]: ...
|
||||
def longest_common_prefix(
|
||||
iterables: Iterable[Iterable[_T]],
|
||||
) -> Iterator[_T]: ...
|
||||
|
|
@ -668,7 +659,8 @@ def iequals(*iterables: Iterable[object]) -> bool: ...
|
|||
def constrained_batches(
|
||||
iterable: Iterable[object],
|
||||
max_size: int,
|
||||
max_count: Optional[int] = ...,
|
||||
max_count: int | None = ...,
|
||||
get_len: Callable[[_T], object] = ...,
|
||||
strict: bool = ...,
|
||||
) -> Iterator[Tuple[_T]]: ...
|
||||
) -> Iterator[tuple[_T]]: ...
|
||||
def gray_product(*iterables: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
|
||||
|
|
|
|||
|
|
@ -9,6 +9,7 @@ Some backward-compatible usability improvements have been made.
|
|||
"""
|
||||
import math
|
||||
import operator
|
||||
import warnings
|
||||
|
||||
from collections import deque
|
||||
from collections.abc import Sized
|
||||
|
|
@ -21,12 +22,14 @@ from itertools import (
|
|||
cycle,
|
||||
groupby,
|
||||
islice,
|
||||
product,
|
||||
repeat,
|
||||
starmap,
|
||||
tee,
|
||||
zip_longest,
|
||||
)
|
||||
from random import randrange, sample, choice
|
||||
from sys import hexversion
|
||||
|
||||
__all__ = [
|
||||
'all_equal',
|
||||
|
|
@ -36,9 +39,12 @@ __all__ = [
|
|||
'convolve',
|
||||
'dotproduct',
|
||||
'first_true',
|
||||
'factor',
|
||||
'flatten',
|
||||
'grouper',
|
||||
'iter_except',
|
||||
'iter_index',
|
||||
'matmul',
|
||||
'ncycles',
|
||||
'nth',
|
||||
'nth_combination',
|
||||
|
|
@ -62,6 +68,7 @@ __all__ = [
|
|||
'tabulate',
|
||||
'tail',
|
||||
'take',
|
||||
'transpose',
|
||||
'triplewise',
|
||||
'unique_everseen',
|
||||
'unique_justseen',
|
||||
|
|
@ -808,6 +815,35 @@ def polynomial_from_roots(roots):
|
|||
]
|
||||
|
||||
|
||||
def iter_index(iterable, value, start=0):
|
||||
"""Yield the index of each place in *iterable* that *value* occurs,
|
||||
beginning with index *start*.
|
||||
|
||||
See :func:`locate` for a more general means of finding the indexes
|
||||
associated with particular values.
|
||||
|
||||
>>> list(iter_index('AABCADEAF', 'A'))
|
||||
[0, 1, 4, 7]
|
||||
"""
|
||||
try:
|
||||
seq_index = iterable.index
|
||||
except AttributeError:
|
||||
# Slow path for general iterables
|
||||
it = islice(iterable, start, None)
|
||||
for i, element in enumerate(it, start):
|
||||
if element is value or element == value:
|
||||
yield i
|
||||
else:
|
||||
# Fast path for sequences
|
||||
i = start - 1
|
||||
try:
|
||||
while True:
|
||||
i = seq_index(value, i + 1)
|
||||
yield i
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
|
||||
def sieve(n):
|
||||
"""Yield the primes less than n.
|
||||
|
||||
|
|
@ -815,13 +851,13 @@ def sieve(n):
|
|||
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29]
|
||||
"""
|
||||
isqrt = getattr(math, 'isqrt', lambda x: int(math.sqrt(x)))
|
||||
data = bytearray((0, 1)) * (n // 2)
|
||||
data[:3] = 0, 0, 0
|
||||
limit = isqrt(n) + 1
|
||||
data = bytearray([1]) * n
|
||||
data[:2] = 0, 0
|
||||
for p in compress(range(limit), data):
|
||||
data[p + p : n : p] = bytearray(len(range(p + p, n, p)))
|
||||
|
||||
return compress(count(), data)
|
||||
data[p * p : n : p + p] = bytes(len(range(p * p, n, p + p)))
|
||||
data[2] = 1
|
||||
return iter_index(data, 1) if n > 2 else iter([])
|
||||
|
||||
|
||||
def batched(iterable, n):
|
||||
|
|
@ -833,9 +869,62 @@ def batched(iterable, n):
|
|||
This recipe is from the ``itertools`` docs. This library also provides
|
||||
:func:`chunked`, which has a different implementation.
|
||||
"""
|
||||
if hexversion >= 0x30C00A0: # Python 3.12.0a0
|
||||
warnings.warn(
|
||||
(
|
||||
'batched will be removed in a future version of '
|
||||
'more-itertools. Use the standard library '
|
||||
'itertools.batched function instead'
|
||||
),
|
||||
DeprecationWarning,
|
||||
)
|
||||
|
||||
it = iter(iterable)
|
||||
while True:
|
||||
batch = list(islice(it, n))
|
||||
if not batch:
|
||||
break
|
||||
yield batch
|
||||
|
||||
|
||||
def transpose(it):
|
||||
"""Swap the rows and columns of the input.
|
||||
|
||||
>>> list(transpose([(1, 2, 3), (11, 22, 33)]))
|
||||
[(1, 11), (2, 22), (3, 33)]
|
||||
|
||||
The caller should ensure that the dimensions of the input are compatible.
|
||||
"""
|
||||
# TODO: when 3.9 goes end-of-life, add stric=True to this.
|
||||
return zip(*it)
|
||||
|
||||
|
||||
def matmul(m1, m2):
|
||||
"""Multiply two matrices.
|
||||
>>> list(matmul([(7, 5), (3, 5)], [(2, 5), (7, 9)]))
|
||||
[[49, 80], [41, 60]]
|
||||
|
||||
The caller should ensure that the dimensions of the input matrices are
|
||||
compatible with each other.
|
||||
"""
|
||||
n = len(m2[0])
|
||||
return batched(starmap(dotproduct, product(m1, transpose(m2))), n)
|
||||
|
||||
|
||||
def factor(n):
|
||||
"""Yield the prime factors of n.
|
||||
>>> list(factor(360))
|
||||
[2, 2, 2, 3, 3, 5]
|
||||
"""
|
||||
isqrt = getattr(math, 'isqrt', lambda x: int(math.sqrt(x)))
|
||||
for prime in sieve(isqrt(n) + 1):
|
||||
while True:
|
||||
quotient, remainder = divmod(n, prime)
|
||||
if remainder:
|
||||
break
|
||||
yield prime
|
||||
n = quotient
|
||||
if n == 1:
|
||||
return
|
||||
if n >= 2:
|
||||
yield n
|
||||
|
|
|
|||
|
|
@ -1,110 +1,119 @@
|
|||
"""Stubs for more_itertools.recipes"""
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import (
|
||||
Any,
|
||||
Callable,
|
||||
Iterable,
|
||||
Iterator,
|
||||
List,
|
||||
Optional,
|
||||
overload,
|
||||
Sequence,
|
||||
Tuple,
|
||||
Type,
|
||||
TypeVar,
|
||||
Union,
|
||||
)
|
||||
from typing_extensions import overload, Type
|
||||
|
||||
# Type and type variable definitions
|
||||
_T = TypeVar('_T')
|
||||
_U = TypeVar('_U')
|
||||
|
||||
def take(n: int, iterable: Iterable[_T]) -> List[_T]: ...
|
||||
def take(n: int, iterable: Iterable[_T]) -> list[_T]: ...
|
||||
def tabulate(
|
||||
function: Callable[[int], _T], start: int = ...
|
||||
) -> Iterator[_T]: ...
|
||||
def tail(n: int, iterable: Iterable[_T]) -> Iterator[_T]: ...
|
||||
def consume(iterator: Iterable[object], n: Optional[int] = ...) -> None: ...
|
||||
def consume(iterator: Iterable[object], n: int | None = ...) -> None: ...
|
||||
@overload
|
||||
def nth(iterable: Iterable[_T], n: int) -> Optional[_T]: ...
|
||||
def nth(iterable: Iterable[_T], n: int) -> _T | None: ...
|
||||
@overload
|
||||
def nth(iterable: Iterable[_T], n: int, default: _U) -> Union[_T, _U]: ...
|
||||
def nth(iterable: Iterable[_T], n: int, default: _U) -> _T | _U: ...
|
||||
def all_equal(iterable: Iterable[object]) -> bool: ...
|
||||
def quantify(
|
||||
iterable: Iterable[_T], pred: Callable[[_T], bool] = ...
|
||||
) -> int: ...
|
||||
def pad_none(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
|
||||
def padnone(iterable: Iterable[_T]) -> Iterator[Optional[_T]]: ...
|
||||
def pad_none(iterable: Iterable[_T]) -> Iterator[_T | None]: ...
|
||||
def padnone(iterable: Iterable[_T]) -> Iterator[_T | None]: ...
|
||||
def ncycles(iterable: Iterable[_T], n: int) -> Iterator[_T]: ...
|
||||
def dotproduct(vec1: Iterable[object], vec2: Iterable[object]) -> object: ...
|
||||
def flatten(listOfLists: Iterable[Iterable[_T]]) -> Iterator[_T]: ...
|
||||
def repeatfunc(
|
||||
func: Callable[..., _U], times: Optional[int] = ..., *args: Any
|
||||
func: Callable[..., _U], times: int | None = ..., *args: Any
|
||||
) -> Iterator[_U]: ...
|
||||
def pairwise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T]]: ...
|
||||
def pairwise(iterable: Iterable[_T]) -> Iterator[tuple[_T, _T]]: ...
|
||||
def grouper(
|
||||
iterable: Iterable[_T],
|
||||
n: int,
|
||||
incomplete: str = ...,
|
||||
fillvalue: _U = ...,
|
||||
) -> Iterator[Tuple[Union[_T, _U], ...]]: ...
|
||||
) -> Iterator[tuple[_T | _U, ...]]: ...
|
||||
def roundrobin(*iterables: Iterable[_T]) -> Iterator[_T]: ...
|
||||
def partition(
|
||||
pred: Optional[Callable[[_T], object]], iterable: Iterable[_T]
|
||||
) -> Tuple[Iterator[_T], Iterator[_T]]: ...
|
||||
def powerset(iterable: Iterable[_T]) -> Iterator[Tuple[_T, ...]]: ...
|
||||
pred: Callable[[_T], object] | None, iterable: Iterable[_T]
|
||||
) -> tuple[Iterator[_T], Iterator[_T]]: ...
|
||||
def powerset(iterable: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
|
||||
def unique_everseen(
|
||||
iterable: Iterable[_T], key: Optional[Callable[[_T], _U]] = ...
|
||||
iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
|
||||
) -> Iterator[_T]: ...
|
||||
def unique_justseen(
|
||||
iterable: Iterable[_T], key: Optional[Callable[[_T], object]] = ...
|
||||
iterable: Iterable[_T], key: Callable[[_T], object] | None = ...
|
||||
) -> Iterator[_T]: ...
|
||||
@overload
|
||||
def iter_except(
|
||||
func: Callable[[], _T],
|
||||
exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
|
||||
exception: Type[BaseException] | tuple[Type[BaseException], ...],
|
||||
first: None = ...,
|
||||
) -> Iterator[_T]: ...
|
||||
@overload
|
||||
def iter_except(
|
||||
func: Callable[[], _T],
|
||||
exception: Union[Type[BaseException], Tuple[Type[BaseException], ...]],
|
||||
exception: Type[BaseException] | tuple[Type[BaseException], ...],
|
||||
first: Callable[[], _U],
|
||||
) -> Iterator[Union[_T, _U]]: ...
|
||||
) -> Iterator[_T | _U]: ...
|
||||
@overload
|
||||
def first_true(
|
||||
iterable: Iterable[_T], *, pred: Optional[Callable[[_T], object]] = ...
|
||||
) -> Optional[_T]: ...
|
||||
iterable: Iterable[_T], *, pred: Callable[[_T], object] | None = ...
|
||||
) -> _T | None: ...
|
||||
@overload
|
||||
def first_true(
|
||||
iterable: Iterable[_T],
|
||||
default: _U,
|
||||
pred: Optional[Callable[[_T], object]] = ...,
|
||||
) -> Union[_T, _U]: ...
|
||||
pred: Callable[[_T], object] | None = ...,
|
||||
) -> _T | _U: ...
|
||||
def random_product(
|
||||
*args: Iterable[_T], repeat: int = ...
|
||||
) -> Tuple[_T, ...]: ...
|
||||
) -> tuple[_T, ...]: ...
|
||||
def random_permutation(
|
||||
iterable: Iterable[_T], r: Optional[int] = ...
|
||||
) -> Tuple[_T, ...]: ...
|
||||
def random_combination(iterable: Iterable[_T], r: int) -> Tuple[_T, ...]: ...
|
||||
iterable: Iterable[_T], r: int | None = ...
|
||||
) -> tuple[_T, ...]: ...
|
||||
def random_combination(iterable: Iterable[_T], r: int) -> tuple[_T, ...]: ...
|
||||
def random_combination_with_replacement(
|
||||
iterable: Iterable[_T], r: int
|
||||
) -> Tuple[_T, ...]: ...
|
||||
) -> tuple[_T, ...]: ...
|
||||
def nth_combination(
|
||||
iterable: Iterable[_T], r: int, index: int
|
||||
) -> Tuple[_T, ...]: ...
|
||||
def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[Union[_T, _U]]: ...
|
||||
) -> tuple[_T, ...]: ...
|
||||
def prepend(value: _T, iterator: Iterable[_U]) -> Iterator[_T | _U]: ...
|
||||
def convolve(signal: Iterable[_T], kernel: Iterable[_T]) -> Iterator[_T]: ...
|
||||
def before_and_after(
|
||||
predicate: Callable[[_T], bool], it: Iterable[_T]
|
||||
) -> Tuple[Iterator[_T], Iterator[_T]]: ...
|
||||
def triplewise(iterable: Iterable[_T]) -> Iterator[Tuple[_T, _T, _T]]: ...
|
||||
) -> tuple[Iterator[_T], Iterator[_T]]: ...
|
||||
def triplewise(iterable: Iterable[_T]) -> Iterator[tuple[_T, _T, _T]]: ...
|
||||
def sliding_window(
|
||||
iterable: Iterable[_T], n: int
|
||||
) -> Iterator[Tuple[_T, ...]]: ...
|
||||
def subslices(iterable: Iterable[_T]) -> Iterator[List[_T]]: ...
|
||||
def polynomial_from_roots(roots: Sequence[int]) -> List[int]: ...
|
||||
) -> Iterator[tuple[_T, ...]]: ...
|
||||
def subslices(iterable: Iterable[_T]) -> Iterator[list[_T]]: ...
|
||||
def polynomial_from_roots(roots: Sequence[int]) -> list[int]: ...
|
||||
def iter_index(
|
||||
iterable: Iterable[object],
|
||||
value: Any,
|
||||
start: int | None = ...,
|
||||
) -> Iterator[int]: ...
|
||||
def sieve(n: int) -> Iterator[int]: ...
|
||||
def batched(
|
||||
iterable: Iterable[_T],
|
||||
n: int,
|
||||
) -> Iterator[List[_T]]: ...
|
||||
) -> Iterator[list[_T]]: ...
|
||||
def transpose(
|
||||
it: Iterable[Iterable[_T]],
|
||||
) -> tuple[Iterator[_T], ...]: ...
|
||||
def matmul(m1: Sequence[_T], m2: Sequence[_T]) -> Iterator[list[_T]]: ...
|
||||
def factor(n: int) -> Iterator[int]: ...
|
||||
|
|
|
|||
|
|
@ -11,9 +11,6 @@ from typing import Union, Tuple, Iterable
|
|||
from typing import cast
|
||||
|
||||
|
||||
from jaraco.functools import once
|
||||
|
||||
|
||||
# some useful constants
|
||||
osc_per_year = 290_091_329_207_984_000
|
||||
"""
|
||||
|
|
@ -36,7 +33,7 @@ seconds_per_month = seconds_per_year / 12
|
|||
hours_per_month = hours_per_day * days_per_year / 12
|
||||
|
||||
|
||||
@once
|
||||
@functools.lru_cache()
|
||||
def _needs_year_help() -> bool:
|
||||
"""
|
||||
Some versions of Python render %Y with only three characters :(
|
||||
|
|
|
|||
|
|
@ -1,149 +0,0 @@
|
|||
import time
|
||||
import random
|
||||
import datetime
|
||||
from unittest import mock
|
||||
|
||||
import pytest
|
||||
import pytz
|
||||
import freezegun
|
||||
|
||||
from tempora import schedule
|
||||
|
||||
|
||||
do_nothing = type(None)
|
||||
|
||||
|
||||
def test_delayed_command_order():
|
||||
"""
|
||||
delayed commands should be sorted by delay time
|
||||
"""
|
||||
delays = [random.randint(0, 99) for x in range(5)]
|
||||
cmds = sorted(
|
||||
[schedule.DelayedCommand.after(delay, do_nothing) for delay in delays]
|
||||
)
|
||||
assert [c.delay.seconds for c in cmds] == sorted(delays)
|
||||
|
||||
|
||||
def test_periodic_command_delay():
|
||||
"A PeriodicCommand must have a positive, non-zero delay."
|
||||
with pytest.raises(ValueError) as exc_info:
|
||||
schedule.PeriodicCommand.after(0, None)
|
||||
assert str(exc_info.value) == test_periodic_command_delay.__doc__
|
||||
|
||||
|
||||
def test_periodic_command_fixed_delay():
|
||||
"""
|
||||
Test that we can construct a periodic command with a fixed initial
|
||||
delay.
|
||||
"""
|
||||
fd = schedule.PeriodicCommandFixedDelay.at_time(
|
||||
at=schedule.now(), delay=datetime.timedelta(seconds=2), target=lambda: None
|
||||
)
|
||||
assert fd.due() is True
|
||||
assert fd.next().due() is False
|
||||
|
||||
|
||||
class TestCommands:
|
||||
def test_delayed_command_from_timestamp(self):
|
||||
"""
|
||||
Ensure a delayed command can be constructed from a timestamp.
|
||||
"""
|
||||
t = time.time()
|
||||
schedule.DelayedCommand.at_time(t, do_nothing)
|
||||
|
||||
def test_command_at_noon(self):
|
||||
"""
|
||||
Create a periodic command that's run at noon every day.
|
||||
"""
|
||||
when = datetime.time(12, 0, tzinfo=pytz.utc)
|
||||
cmd = schedule.PeriodicCommandFixedDelay.daily_at(when, target=None)
|
||||
assert cmd.due() is False
|
||||
next_cmd = cmd.next()
|
||||
daily = datetime.timedelta(days=1)
|
||||
day_from_now = schedule.now() + daily
|
||||
two_days_from_now = day_from_now + daily
|
||||
assert day_from_now < next_cmd < two_days_from_now
|
||||
|
||||
@pytest.mark.parametrize("hour", range(10, 14))
|
||||
@pytest.mark.parametrize("tz_offset", (14, -14))
|
||||
def test_command_at_noon_distant_local(self, hour, tz_offset):
|
||||
"""
|
||||
Run test_command_at_noon, but with the local timezone
|
||||
more than 12 hours away from UTC.
|
||||
"""
|
||||
with freezegun.freeze_time(f"2020-01-10 {hour:02}:01", tz_offset=tz_offset):
|
||||
self.test_command_at_noon()
|
||||
|
||||
|
||||
class TestTimezones:
|
||||
def test_alternate_timezone_west(self):
|
||||
target_tz = pytz.timezone('US/Pacific')
|
||||
target = schedule.now().astimezone(target_tz)
|
||||
cmd = schedule.DelayedCommand.at_time(target, target=None)
|
||||
assert cmd.due()
|
||||
|
||||
def test_alternate_timezone_east(self):
|
||||
target_tz = pytz.timezone('Europe/Amsterdam')
|
||||
target = schedule.now().astimezone(target_tz)
|
||||
cmd = schedule.DelayedCommand.at_time(target, target=None)
|
||||
assert cmd.due()
|
||||
|
||||
def test_daylight_savings(self):
|
||||
"""
|
||||
A command at 9am should always be 9am regardless of
|
||||
a DST boundary.
|
||||
"""
|
||||
with freezegun.freeze_time('2018-03-10 08:00:00'):
|
||||
target_tz = pytz.timezone('US/Eastern')
|
||||
target_time = datetime.time(9, tzinfo=target_tz)
|
||||
cmd = schedule.PeriodicCommandFixedDelay.daily_at(
|
||||
target_time, target=lambda: None
|
||||
)
|
||||
|
||||
def naive(dt):
|
||||
return dt.replace(tzinfo=None)
|
||||
|
||||
assert naive(cmd) == datetime.datetime(2018, 3, 10, 9, 0, 0)
|
||||
next_ = cmd.next()
|
||||
assert naive(next_) == datetime.datetime(2018, 3, 11, 9, 0, 0)
|
||||
assert next_ - cmd == datetime.timedelta(hours=23)
|
||||
|
||||
|
||||
class TestScheduler:
|
||||
def test_invoke_scheduler(self):
|
||||
sched = schedule.InvokeScheduler()
|
||||
target = mock.MagicMock()
|
||||
cmd = schedule.DelayedCommand.after(0, target)
|
||||
sched.add(cmd)
|
||||
sched.run_pending()
|
||||
target.assert_called_once()
|
||||
assert not sched.queue
|
||||
|
||||
def test_callback_scheduler(self):
|
||||
callback = mock.MagicMock()
|
||||
sched = schedule.CallbackScheduler(callback)
|
||||
target = mock.MagicMock()
|
||||
cmd = schedule.DelayedCommand.after(0, target)
|
||||
sched.add(cmd)
|
||||
sched.run_pending()
|
||||
callback.assert_called_once_with(target)
|
||||
|
||||
def test_periodic_command(self):
|
||||
sched = schedule.InvokeScheduler()
|
||||
target = mock.MagicMock()
|
||||
|
||||
before = datetime.datetime.utcnow()
|
||||
|
||||
cmd = schedule.PeriodicCommand.after(10, target)
|
||||
sched.add(cmd)
|
||||
sched.run_pending()
|
||||
target.assert_not_called()
|
||||
|
||||
with freezegun.freeze_time(before + datetime.timedelta(seconds=15)):
|
||||
sched.run_pending()
|
||||
assert sched.queue
|
||||
target.assert_called_once()
|
||||
|
||||
with freezegun.freeze_time(before + datetime.timedelta(seconds=25)):
|
||||
sched.run_pending()
|
||||
assert target.call_count == 2
|
||||
|
|
@ -1,50 +0,0 @@
|
|||
import datetime
|
||||
import time
|
||||
import contextlib
|
||||
import os
|
||||
from unittest import mock
|
||||
|
||||
import pytest
|
||||
from tempora import timing
|
||||
|
||||
|
||||
def test_IntervalGovernor():
|
||||
"""
|
||||
IntervalGovernor should prevent a function from being called more than
|
||||
once per interval.
|
||||
"""
|
||||
func_under_test = mock.MagicMock()
|
||||
# to look like a function, it needs a __name__ attribute
|
||||
func_under_test.__name__ = 'func_under_test'
|
||||
interval = datetime.timedelta(seconds=1)
|
||||
governed = timing.IntervalGovernor(interval)(func_under_test)
|
||||
governed('a')
|
||||
governed('b')
|
||||
governed(3, 'sir')
|
||||
func_under_test.assert_called_once_with('a')
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def alt_tz(monkeypatch):
|
||||
hasattr(time, 'tzset') or pytest.skip("tzset not available")
|
||||
|
||||
@contextlib.contextmanager
|
||||
def change():
|
||||
val = 'AEST-10AEDT-11,M10.5.0,M3.5.0'
|
||||
with monkeypatch.context() as ctx:
|
||||
ctx.setitem(os.environ, 'TZ', val)
|
||||
time.tzset()
|
||||
yield
|
||||
time.tzset()
|
||||
|
||||
return change()
|
||||
|
||||
|
||||
def test_Stopwatch_timezone_change(alt_tz):
|
||||
"""
|
||||
The stopwatch should provide a consistent duration even
|
||||
if the timezone changes.
|
||||
"""
|
||||
watch = timing.Stopwatch()
|
||||
with alt_tz:
|
||||
assert abs(watch.split().total_seconds()) < 0.1
|
||||
|
|
@ -42,7 +42,7 @@ rumps==0.4.0; platform_system == "Darwin"
|
|||
simplejson==3.18.0
|
||||
six==1.16.0
|
||||
soupsieve==2.3.2.post1
|
||||
tempora==5.1.0
|
||||
tempora==5.2.1
|
||||
tokenize-rt==5.0.0
|
||||
tzdata==2022.7
|
||||
tzlocal==4.2
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue