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Bump tempora from 5.2.1 to 5.5.0 (#2111)

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* 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>

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62
lib/jaraco/functools.py
View file

@ -1,9 +1,10 @@
import functools
import time
import inspect
import collections
import types
import functools
import inspect
import itertools
import operator
import time
import types
import warnings
import more_itertools
@ -183,8 +184,9 @@ def method_cache(
# Support cache clear even before cache has been created.
wrapper.cache_clear = lambda: None # type: ignore[attr-defined]
return ( # type: ignore[return-value]
_special_method_cache(method, cache_wrapper) or wrapper
return (
_special_method_cache(method, cache_wrapper) # type: ignore[return-value]
or wrapper
)
@ -554,3 +556,51 @@ def except_(*exceptions, replace=None, use=None):
return wrapper
return decorate
def identity(x):
return x
def bypass_when(check, *, _op=identity):
"""
Decorate a function to return its parameter when ``check``.
>>> bypassed = [] # False
>>> @bypass_when(bypassed)
... def double(x):
... return x * 2
>>> double(2)
4
>>> bypassed[:] = [object()] # True
>>> double(2)
2
"""
def decorate(func):
@functools.wraps(func)
def wrapper(param):
return param if _op(check) else func(param)
return wrapper
return decorate
def bypass_unless(check):
"""
Decorate a function to return its parameter unless ``check``.
>>> enabled = [object()] # True
>>> @bypass_unless(enabled)
... def double(x):
... return x * 2
>>> double(2)
4
>>> del enabled[:] # False
>>> double(2)
2
"""
return bypass_when(check, _op=operator.not_)

2
lib/more_itertools/__init__.py
View file

@ -3,4 +3,4 @@
from .more import * # noqa
from .recipes import * # noqa
__version__ = '9.1.0'
__version__ = '10.1.0'

279
lib/more_itertools/more.py
View file

@ -2,7 +2,7 @@ import warnings
from collections import Counter, defaultdict, deque, abc
from collections.abc import Sequence
from functools import partial, reduce, wraps
from functools import cached_property, partial, reduce, wraps
from heapq import heapify, heapreplace, heappop
from itertools import (
chain,
@ -17,6 +17,7 @@ from itertools import (
takewhile,
tee,
zip_longest,
product,
)
from math import exp, factorial, floor, log
from queue import Empty, Queue
@ -36,6 +37,7 @@ from .recipes import (
take,
unique_everseen,
all_equal,
batched,
)
__all__ = [
@ -53,6 +55,7 @@ __all__ = [
'circular_shifts',
'collapse',
'combination_index',
'combination_with_replacement_index',
'consecutive_groups',
'constrained_batches',
'consumer',
@ -93,10 +96,13 @@ __all__ = [
'nth_or_last',
'nth_permutation',
'nth_product',
'nth_combination_with_replacement',
'numeric_range',
'one',
'only',
'outer_product',
'padded',
'partial_product',
'partitions',
'peekable',
'permutation_index',
@ -125,6 +131,7 @@ __all__ = [
'strictly_n',
'substrings',
'substrings_indexes',
'takewhile_inclusive',
'time_limited',
'unique_in_window',
'unique_to_each',
@ -472,7 +479,10 @@ def iterate(func, start):
"""
while True:
yield start
start = func(start)
try:
start = func(start)
except StopIteration:
break
def with_iter(context_manager):
@ -2069,7 +2079,6 @@ class numeric_range(abc.Sequence, abc.Hashable):
if self._step == self._zero:
raise ValueError('numeric_range() arg 3 must not be zero')
self._growing = self._step > self._zero
self._init_len()
def __bool__(self):
if self._growing:
@ -2145,7 +2154,8 @@ class numeric_range(abc.Sequence, abc.Hashable):
def __len__(self):
return self._len
def _init_len(self):
@cached_property
def _len(self):
if self._growing:
start = self._start
stop = self._stop
@ -2156,10 +2166,10 @@ class numeric_range(abc.Sequence, abc.Hashable):
step = -self._step
distance = stop - start
if distance <= self._zero:
self._len = 0
return 0
else: # distance > 0 and step > 0: regular euclidean division
q, r = divmod(distance, step)
self._len = int(q) + int(r != self._zero)
return int(q) + int(r != self._zero)
def __reduce__(self):
return numeric_range, (self._start, self._stop, self._step)
@ -2699,6 +2709,9 @@ class seekable:
>>> it.seek(10)
>>> next(it)
'10'
>>> it.relative_seek(-2) # Seeking relative to the current position
>>> next(it)
'9'
>>> it.seek(20) # Seeking past the end of the source isn't a problem
>>> list(it)
[]
@ -2812,6 +2825,10 @@ class seekable:
if remainder > 0:
consume(self, remainder)
def relative_seek(self, count):
index = len(self._cache)
self.seek(max(index + count, 0))
class run_length:
"""
@ -3859,6 +3876,54 @@ def nth_permutation(iterable, r, index):
return tuple(map(pool.pop, result))
def nth_combination_with_replacement(iterable, r, index):
"""Equivalent to
``list(combinations_with_replacement(iterable, r))[index]``.
The subsequences with repetition of *iterable* that are of length *r* can
be ordered lexicographically. :func:`nth_combination_with_replacement`
computes the subsequence at sort position *index* directly, without
computing the previous subsequences with replacement.
>>> nth_combination_with_replacement(range(5), 3, 5)
(0, 1, 1)
``ValueError`` will be raised If *r* is negative or greater than the length
of *iterable*.
``IndexError`` will be raised if the given *index* is invalid.
"""
pool = tuple(iterable)
n = len(pool)
if (r < 0) or (r > n):
raise ValueError
c = factorial(n + r - 1) // (factorial(r) * factorial(n - 1))
if index < 0:
index += c
if (index < 0) or (index >= c):
raise IndexError
result = []
i = 0
while r:
r -= 1
while n >= 0:
num_combs = factorial(n + r - 1) // (
factorial(r) * factorial(n - 1)
)
if index < num_combs:
break
n -= 1
i += 1
index -= num_combs
result.append(pool[i])
return tuple(result)
def value_chain(*args):
"""Yield all arguments passed to the function in the same order in which
they were passed. If an argument itself is iterable then iterate over its
@ -3955,6 +4020,61 @@ def combination_index(element, iterable):
return factorial(n + 1) // (factorial(k + 1) * factorial(n - k)) - index
def combination_with_replacement_index(element, iterable):
"""Equivalent to
``list(combinations_with_replacement(iterable, r)).index(element)``
The subsequences with repetition of *iterable* that are of length *r* can
be ordered lexicographically. :func:`combination_with_replacement_index`
computes the index of the first *element*, without computing the previous
combinations with replacement.
>>> combination_with_replacement_index('adf', 'abcdefg')
20
``ValueError`` will be raised if the given *element* isn't one of the
combinations with replacement of *iterable*.
"""
element = tuple(element)
l = len(element)
element = enumerate(element)
k, y = next(element, (None, None))
if k is None:
return 0
indexes = []
pool = tuple(iterable)
for n, x in enumerate(pool):
while x == y:
indexes.append(n)
tmp, y = next(element, (None, None))
if tmp is None:
break
else:
k = tmp
if y is None:
break
else:
raise ValueError(
'element is not a combination with replacment of iterable'
)
n = len(pool)
occupations = [0] * n
for p in indexes:
occupations[p] += 1
index = 0
for k in range(1, n):
j = l + n - 1 - k - sum(occupations[:k])
i = n - k
if i <= j:
index += factorial(j) // (factorial(i) * factorial(j - i))
return index
def permutation_index(element, iterable):
"""Equivalent to ``list(permutations(iterable, r)).index(element)```
@ -4057,26 +4177,20 @@ def _chunked_even_finite(iterable, N, n):
num_full = N - partial_size * num_lists
num_partial = num_lists - num_full
buffer = []
iterator = iter(iterable)
# Yield num_full lists of full_size
for x in iterator:
buffer.append(x)
if len(buffer) == full_size:
yield buffer
buffer = []
num_full -= 1
if num_full <= 0:
break
partial_start_idx = num_full * full_size
if full_size > 0:
for i in range(0, partial_start_idx, full_size):
yield list(islice(iterable, i, i + full_size))
# Yield num_partial lists of partial_size
for x in iterator:
buffer.append(x)
if len(buffer) == partial_size:
yield buffer
buffer = []
num_partial -= 1
if partial_size > 0:
for i in range(
partial_start_idx,
partial_start_idx + (num_partial * partial_size),
partial_size,
):
yield list(islice(iterable, i, i + partial_size))
def zip_broadcast(*objects, scalar_types=(str, bytes), strict=False):
@ -4115,30 +4229,23 @@ def zip_broadcast(*objects, scalar_types=(str, bytes), strict=False):
if not size:
return
new_item = [None] * size
iterables, iterable_positions = [], []
scalars, scalar_positions = [], []
for i, obj in enumerate(objects):
if is_scalar(obj):
scalars.append(obj)
scalar_positions.append(i)
new_item[i] = obj
else:
iterables.append(iter(obj))
iterable_positions.append(i)
if len(scalars) == size:
if not iterables:
yield tuple(objects)
return
zipper = _zip_equal if strict else zip
for item in zipper(*iterables):
new_item = [None] * size
for i, elem in zip(iterable_positions, item):
new_item[i] = elem
for i, elem in zip(scalar_positions, scalars):
new_item[i] = elem
for i, new_item[i] in zip(iterable_positions, item):
pass
yield tuple(new_item)
@ -4163,22 +4270,23 @@ def unique_in_window(iterable, n, key=None):
raise ValueError('n must be greater than 0')
window = deque(maxlen=n)
uniques = set()
counts = defaultdict(int)
use_key = key is not None
for item in iterable:
if len(window) == n:
to_discard = window[0]
if counts[to_discard] == 1:
del counts[to_discard]
else:
counts[to_discard] -= 1
k = key(item) if use_key else item
if k in uniques:
continue
if len(uniques) == n:
uniques.discard(window[0])
uniques.add(k)
if k not in counts:
yield item
counts[k] += 1
window.append(k)
yield item
def duplicates_everseen(iterable, key=None):
"""Yield duplicate elements after their first appearance.
@ -4221,12 +4329,7 @@ def duplicates_justseen(iterable, key=None):
This function is analagous to :func:`unique_justseen`.
"""
return flatten(
map(
lambda group_tuple: islice_extended(group_tuple[1])[1:],
groupby(iterable, key),
)
)
return flatten(g for _, g in groupby(iterable, key) for _ in g)
def minmax(iterable_or_value, *others, key=None, default=_marker):
@ -4390,3 +4493,77 @@ def gray_product(*iterables):
o[j] = -o[j]
f[j] = f[j + 1]
f[j + 1] = j + 1
def partial_product(*iterables):
"""Yields tuples containing one item from each iterator, with subsequent
tuples changing a single item at a time by advancing each iterator until it
is exhausted. This sequence guarantees every value in each iterable is
output at least once without generating all possible combinations.
This may be useful, for example, when testing an expensive function.
>>> list(partial_product('AB', 'C', 'DEF'))
[('A', 'C', 'D'), ('B', 'C', 'D'), ('B', 'C', 'E'), ('B', 'C', 'F')]
"""
iterators = list(map(iter, iterables))
try:
prod = [next(it) for it in iterators]
except StopIteration:
return
yield tuple(prod)
for i, it in enumerate(iterators):
for prod[i] in it:
yield tuple(prod)
def takewhile_inclusive(predicate, iterable):
"""A variant of :func:`takewhile` that yields one additional element.
>>> list(takewhile_inclusive(lambda x: x < 5, [1, 4, 6, 4, 1]))
[1, 4, 6]
:func:`takewhile` would return ``[1, 4]``.
"""
for x in iterable:
if predicate(x):
yield x
else:
yield x
break
def outer_product(func, xs, ys, *args, **kwargs):
"""A generalized outer product that applies a binary function to all
pairs of items. Returns a 2D matrix with ``len(xs)`` rows and ``len(ys)``
columns.
Also accepts ``*args`` and ``**kwargs`` that are passed to ``func``.
Multiplication table:
>>> list(outer_product(mul, range(1, 4), range(1, 6)))
[(1, 2, 3, 4, 5), (2, 4, 6, 8, 10), (3, 6, 9, 12, 15)]
Cross tabulation:
>>> xs = ['A', 'B', 'A', 'A', 'B', 'B', 'A', 'A', 'B', 'B']
>>> ys = ['X', 'X', 'X', 'Y', 'Z', 'Z', 'Y', 'Y', 'Z', 'Z']
>>> rows = list(zip(xs, ys))
>>> count_rows = lambda x, y: rows.count((x, y))
>>> list(outer_product(count_rows, sorted(set(xs)), sorted(set(ys))))
[(2, 3, 0), (1, 0, 4)]
Usage with ``*args`` and ``**kwargs``:
>>> animals = ['cat', 'wolf', 'mouse']
>>> list(outer_product(min, animals, animals, key=len))
[('cat', 'cat', 'cat'), ('cat', 'wolf', 'wolf'), ('cat', 'wolf', 'mouse')]
"""
ys = tuple(ys)
return batched(
starmap(lambda x, y: func(x, y, *args, **kwargs), product(xs, ys)),
n=len(ys),
)

18
lib/more_itertools/more.pyi
View file

@ -440,6 +440,7 @@ class seekable(Generic[_T], Iterator[_T]):
def peek(self, default: _U) -> _T | _U: ...
def elements(self) -> SequenceView[_T]: ...
def seek(self, index: int) -> None: ...
def relative_seek(self, count: int) -> None: ...
class run_length:
@staticmethod
@ -578,6 +579,9 @@ def all_unique(
iterable: Iterable[_T], key: Callable[[_T], _U] | None = ...
) -> bool: ...
def nth_product(index: int, *args: Iterable[_T]) -> tuple[_T, ...]: ...
def nth_combination_with_replacement(
iterable: Iterable[_T], r: int, index: int
) -> tuple[_T, ...]: ...
def nth_permutation(
iterable: Iterable[_T], r: int, index: int
) -> tuple[_T, ...]: ...
@ -586,6 +590,9 @@ def product_index(element: Iterable[_T], *args: Iterable[_T]) -> int: ...
def combination_index(
element: Iterable[_T], iterable: Iterable[_T]
) -> int: ...
def combination_with_replacement_index(
element: Iterable[_T], iterable: Iterable[_T]
) -> int: ...
def permutation_index(
element: Iterable[_T], iterable: Iterable[_T]
) -> int: ...
@ -664,3 +671,14 @@ def constrained_batches(
strict: bool = ...,
) -> Iterator[tuple[_T]]: ...
def gray_product(*iterables: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
def partial_product(*iterables: Iterable[_T]) -> Iterator[tuple[_T, ...]]: ...
def takewhile_inclusive(
predicate: Callable[[_T], bool], iterable: Iterable[_T]
) -> Iterator[_T]: ...
def outer_product(
func: Callable[[_T, _U], _V],
xs: Iterable[_T],
ys: Iterable[_U],
*args: Any,
**kwargs: Any,
) -> Iterator[tuple[_V, ...]]: ...

161
lib/more_itertools/recipes.py
View file

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

13
lib/more_itertools/recipes.pyi
View file

@ -21,7 +21,7 @@ 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: int | None = ...) -> None: ...
def consume(iterator: Iterable[_T], n: int | None = ...) -> None: ...
@overload
def nth(iterable: Iterable[_T], n: int) -> _T | None: ...
@overload
@ -101,7 +101,7 @@ 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]: ...
def polynomial_from_roots(roots: Sequence[_T]) -> list[_T]: ...
def iter_index(
iterable: Iterable[object],
value: Any,
@ -111,9 +111,12 @@ def sieve(n: int) -> Iterator[int]: ...
def batched(
iterable: Iterable[_T],
n: int,
) -> Iterator[list[_T]]: ...
) -> Iterator[tuple[_T]]: ...
def transpose(
it: Iterable[Iterable[_T]],
) -> tuple[Iterator[_T], ...]: ...
def matmul(m1: Sequence[_T], m2: Sequence[_T]) -> Iterator[list[_T]]: ...
) -> Iterator[tuple[_T, ...]]: ...
def matmul(m1: Sequence[_T], m2: Sequence[_T]) -> Iterator[tuple[_T]]: ...
def factor(n: int) -> Iterator[int]: ...
def polynomial_eval(coefficients: Sequence[_T], x: _U) -> _U: ...
def sum_of_squares(it: Iterable[_T]) -> _T: ...
def polynomial_derivative(coefficients: Sequence[_T]) -> list[_T]: ...

6
lib/tempora/__init__.py
View file

@ -383,9 +383,9 @@ def parse_timedelta(str):
Note that months and years strict intervals, not aligned
to a calendar:
>>> now = datetime.datetime.now()
>>> later = now + parse_timedelta('1 year')
>>> diff = later.replace(year=now.year) - now
>>> date = datetime.datetime.fromisoformat('2000-01-01')
>>> later = date + parse_timedelta('1 year')
>>> diff = later.replace(year=date.year) - date
>>> diff.seconds
20940

4
lib/tempora/schedule.py
View file

@ -28,7 +28,7 @@ def now():
A client may override this function to change the default behavior,
such as to use local time or timezone-naïve times.
"""
return datetime.datetime.utcnow().replace(tzinfo=pytz.utc)
return datetime.datetime.now(pytz.utc)
def from_timestamp(ts):
@ -38,7 +38,7 @@ def from_timestamp(ts):
A client may override this function to change the default behavior,
such as to use local time or timezone-naïve times.
"""
return datetime.datetime.utcfromtimestamp(ts).replace(tzinfo=pytz.utc)
return datetime.datetime.fromtimestamp(ts, pytz.utc)
class DelayedCommand(datetime.datetime):

15
lib/tempora/timing.py
View file

@ -48,20 +48,21 @@ class Stopwatch:
def reset(self):
self.elapsed = datetime.timedelta(0)
with contextlib.suppress(AttributeError):
del self.start_time
del self._start
def _diff(self):
return datetime.timedelta(seconds=time.monotonic() - self._start)
def start(self):
self.start_time = datetime.datetime.utcnow()
self._start = time.monotonic()
def stop(self):
stop_time = datetime.datetime.utcnow()
self.elapsed += stop_time - self.start_time
del self.start_time
self.elapsed += self._diff()
del self._start
return self.elapsed
def split(self):
local_duration = datetime.datetime.utcnow() - self.start_time
return self.elapsed + local_duration
return self.elapsed + self._diff()
# context manager support
def __enter__(self):

2
requirements.txt
View file

@ -41,7 +41,7 @@ requests-oauthlib==1.3.1
rumps==0.4.0; platform_system == "Darwin"
simplejson==3.19.1
six==1.16.0
tempora==5.2.1
tempora==5.5.0
tokenize-rt==5.0.0
tzdata==2023.3
tzlocal==4.2