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Bump tempora from 5.2.1 to 5.5.0 (#2111)
* Bump tempora from 5.2.1 to 5.5.0 Bumps [tempora](https://github.com/jaraco/tempora) from 5.2.1 to 5.5.0. - [Release notes](https://github.com/jaraco/tempora/releases) - [Changelog](https://github.com/jaraco/tempora/blob/main/NEWS.rst) - [Commits](https://github.com/jaraco/tempora/compare/v5.2.1...v5.5.0) --- 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==5.5.0 --------- 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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10 changed files with 429 additions and 133 deletions
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@ -9,11 +9,10 @@ Some backward-compatible usability improvements have been made.
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"""
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import math
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import operator
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import warnings
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from collections import deque
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from collections.abc import Sized
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from functools import reduce
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from functools import partial, reduce
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from itertools import (
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chain,
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combinations,
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@ -29,7 +28,6 @@ from itertools import (
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zip_longest,
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)
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from random import randrange, sample, choice
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from sys import hexversion
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__all__ = [
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'all_equal',
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@ -52,7 +50,9 @@ __all__ = [
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'pad_none',
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'pairwise',
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'partition',
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'polynomial_eval',
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'polynomial_from_roots',
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'polynomial_derivative',
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'powerset',
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'prepend',
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'quantify',
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@ -65,6 +65,7 @@ __all__ = [
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'sieve',
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'sliding_window',
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'subslices',
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'sum_of_squares',
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'tabulate',
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'tail',
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'take',
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@ -77,6 +78,18 @@ __all__ = [
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_marker = object()
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# zip with strict is available for Python 3.10+
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try:
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zip(strict=True)
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except TypeError:
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_zip_strict = zip
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else:
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_zip_strict = partial(zip, strict=True)
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# math.sumprod is available for Python 3.12+
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_sumprod = getattr(math, 'sumprod', lambda x, y: dotproduct(x, y))
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def take(n, iterable):
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"""Return first *n* items of the iterable as a list.
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@ -293,7 +306,7 @@ def _pairwise(iterable):
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"""
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a, b = tee(iterable)
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next(b, None)
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yield from zip(a, b)
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return zip(a, b)
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try:
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@ -303,7 +316,7 @@ except ImportError:
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else:
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def pairwise(iterable):
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yield from itertools_pairwise(iterable)
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return itertools_pairwise(iterable)
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pairwise.__doc__ = _pairwise.__doc__
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@ -334,13 +347,9 @@ def _zip_equal(*iterables):
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for i, it in enumerate(iterables[1:], 1):
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size = len(it)
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if size != first_size:
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break
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else:
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# If we didn't break out, we can use the built-in zip.
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return zip(*iterables)
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# If we did break out, there was a mismatch.
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raise UnequalIterablesError(details=(first_size, i, size))
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raise UnequalIterablesError(details=(first_size, i, size))
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# All sizes are equal, we can use the built-in zip.
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return zip(*iterables)
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# If any one of the iterables didn't have a length, start reading
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# them until one runs out.
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except TypeError:
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@ -433,12 +442,9 @@ def partition(pred, iterable):
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if pred is None:
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pred = bool
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evaluations = ((pred(x), x) for x in iterable)
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t1, t2 = tee(evaluations)
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return (
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(x for (cond, x) in t1 if not cond),
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(x for (cond, x) in t2 if cond),
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)
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t1, t2, p = tee(iterable, 3)
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p1, p2 = tee(map(pred, p))
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return (compress(t1, map(operator.not_, p1)), compress(t2, p2))
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def powerset(iterable):
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@ -712,12 +718,14 @@ def convolve(signal, kernel):
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is immediately consumed and stored.
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"""
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# This implementation intentionally doesn't match the one in the itertools
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# documentation.
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kernel = tuple(kernel)[::-1]
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n = len(kernel)
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window = deque([0], maxlen=n) * n
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for x in chain(signal, repeat(0, n - 1)):
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window.append(x)
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yield sum(map(operator.mul, kernel, window))
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yield _sumprod(kernel, window)
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def before_and_after(predicate, it):
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@ -778,9 +786,7 @@ def sliding_window(iterable, n):
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For a variant with more features, see :func:`windowed`.
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"""
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it = iter(iterable)
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window = deque(islice(it, n), maxlen=n)
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if len(window) == n:
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yield tuple(window)
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window = deque(islice(it, n - 1), maxlen=n)
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for x in it:
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window.append(x)
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yield tuple(window)
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@ -807,12 +813,8 @@ def polynomial_from_roots(roots):
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>>> polynomial_from_roots(roots) # x^3 - 4 * x^2 - 17 * x + 60
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[1, -4, -17, 60]
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"""
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# Use math.prod for Python 3.8+,
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prod = getattr(math, 'prod', lambda x: reduce(operator.mul, x, 1))
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roots = list(map(operator.neg, roots))
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return [
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sum(map(prod, combinations(roots, k))) for k in range(len(roots) + 1)
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]
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factors = zip(repeat(1), map(operator.neg, roots))
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return list(reduce(convolve, factors, [1]))
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def iter_index(iterable, value, start=0):
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@ -830,9 +832,13 @@ def iter_index(iterable, value, start=0):
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except AttributeError:
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# Slow path for general iterables
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it = islice(iterable, start, None)
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for i, element in enumerate(it, start):
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if element is value or element == value:
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i = start - 1
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try:
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while True:
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i = i + operator.indexOf(it, value) + 1
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yield i
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except ValueError:
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pass
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else:
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# Fast path for sequences
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i = start - 1
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@ -850,43 +856,45 @@ def sieve(n):
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>>> list(sieve(30))
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[2, 3, 5, 7, 11, 13, 17, 19, 23, 29]
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"""
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isqrt = getattr(math, 'isqrt', lambda x: int(math.sqrt(x)))
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data = bytearray((0, 1)) * (n // 2)
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data[:3] = 0, 0, 0
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limit = isqrt(n) + 1
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limit = math.isqrt(n) + 1
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for p in compress(range(limit), data):
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data[p * p : n : p + p] = bytes(len(range(p * p, n, p + p)))
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data[2] = 1
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return iter_index(data, 1) if n > 2 else iter([])
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def batched(iterable, n):
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def _batched(iterable, n):
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"""Batch data into lists of length *n*. The last batch may be shorter.
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>>> list(batched('ABCDEFG', 3))
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[['A', 'B', 'C'], ['D', 'E', 'F'], ['G']]
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[('A', 'B', 'C'), ('D', 'E', 'F'), ('G',)]
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This recipe is from the ``itertools`` docs. This library also provides
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:func:`chunked`, which has a different implementation.
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On Python 3.12 and above, this is an alias for :func:`itertools.batched`.
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"""
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if hexversion >= 0x30C00A0: # Python 3.12.0a0
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warnings.warn(
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(
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'batched will be removed in a future version of '
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'more-itertools. Use the standard library '
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'itertools.batched function instead'
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),
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DeprecationWarning,
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)
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if n < 1:
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raise ValueError('n must be at least one')
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it = iter(iterable)
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while True:
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batch = list(islice(it, n))
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batch = tuple(islice(it, n))
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if not batch:
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break
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yield batch
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try:
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from itertools import batched as itertools_batched
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except ImportError:
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batched = _batched
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else:
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def batched(iterable, n):
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return itertools_batched(iterable, n)
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batched.__doc__ = _batched.__doc__
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def transpose(it):
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"""Swap the rows and columns of the input.
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@ -894,21 +902,21 @@ def transpose(it):
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[(1, 11), (2, 22), (3, 33)]
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The caller should ensure that the dimensions of the input are compatible.
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If the input is empty, no output will be produced.
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"""
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# TODO: when 3.9 goes end-of-life, add stric=True to this.
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return zip(*it)
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return _zip_strict(*it)
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def matmul(m1, m2):
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"""Multiply two matrices.
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>>> list(matmul([(7, 5), (3, 5)], [(2, 5), (7, 9)]))
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[[49, 80], [41, 60]]
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[(49, 80), (41, 60)]
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The caller should ensure that the dimensions of the input matrices are
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compatible with each other.
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"""
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n = len(m2[0])
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return batched(starmap(dotproduct, product(m1, transpose(m2))), n)
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return batched(starmap(_sumprod, product(m1, transpose(m2))), n)
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def factor(n):
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@ -916,15 +924,54 @@ def factor(n):
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>>> list(factor(360))
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[2, 2, 2, 3, 3, 5]
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"""
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isqrt = getattr(math, 'isqrt', lambda x: int(math.sqrt(x)))
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for prime in sieve(isqrt(n) + 1):
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for prime in sieve(math.isqrt(n) + 1):
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while True:
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quotient, remainder = divmod(n, prime)
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if remainder:
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if n % prime:
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break
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yield prime
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n = quotient
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n //= prime
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if n == 1:
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return
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if n >= 2:
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if n > 1:
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yield n
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def polynomial_eval(coefficients, x):
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"""Evaluate a polynomial at a specific value.
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Example: evaluating x^3 - 4 * x^2 - 17 * x + 60 at x = 2.5:
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>>> coefficients = [1, -4, -17, 60]
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>>> x = 2.5
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>>> polynomial_eval(coefficients, x)
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8.125
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"""
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n = len(coefficients)
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if n == 0:
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return x * 0 # coerce zero to the type of x
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powers = map(pow, repeat(x), reversed(range(n)))
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return _sumprod(coefficients, powers)
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def sum_of_squares(it):
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"""Return the sum of the squares of the input values.
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>>> sum_of_squares([10, 20, 30])
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1400
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"""
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return _sumprod(*tee(it))
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def polynomial_derivative(coefficients):
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"""Compute the first derivative of a polynomial.
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Example: evaluating the derivative of x^3 - 4 * x^2 - 17 * x + 60
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>>> coefficients = [1, -4, -17, 60]
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>>> derivative_coefficients = polynomial_derivative(coefficients)
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>>> derivative_coefficients
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[3, -8, -17]
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"""
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n = len(coefficients)
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powers = reversed(range(1, n))
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return list(map(operator.mul, coefficients, powers))
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