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Update vendored windows libs

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Labrys of Knossos 2022-11-28 05:59:32 -05:00
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484
libs/win/more_itertools/recipes.py
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@ -7,20 +7,33 @@ Some backward-compatible usability improvements have been made.
.. [1] http://docs.python.org/library/itertools.html#recipes
"""
from collections import deque
from itertools import (
chain, combinations, count, cycle, groupby, islice, repeat, starmap, tee
)
import math
import operator
from collections import deque
from collections.abc import Sized
from functools import reduce
from itertools import (
chain,
combinations,
compress,
count,
cycle,
groupby,
islice,
repeat,
starmap,
tee,
zip_longest,
)
from random import randrange, sample, choice
from six import PY2
from six.moves import filter, filterfalse, map, range, zip, zip_longest
__all__ = [
'accumulate',
'all_equal',
'batched',
'before_and_after',
'consume',
'convolve',
'dotproduct',
'first_true',
'flatten',
@ -30,8 +43,10 @@ __all__ = [
'nth',
'nth_combination',
'padnone',
'pad_none',
'pairwise',
'partition',
'polynomial_from_roots',
'powerset',
'prepend',
'quantify',
@ -41,42 +56,18 @@ __all__ = [
'random_product',
'repeatfunc',
'roundrobin',
'sieve',
'sliding_window',
'subslices',
'tabulate',
'tail',
'take',
'triplewise',
'unique_everseen',
'unique_justseen',
]
def accumulate(iterable, func=operator.add):
"""
Return an iterator whose items are the accumulated results of a function
(specified by the optional *func* argument) that takes two arguments.
By default, returns accumulated sums with :func:`operator.add`.
>>> list(accumulate([1, 2, 3, 4, 5])) # Running sum
[1, 3, 6, 10, 15]
>>> list(accumulate([1, 2, 3], func=operator.mul)) # Running product
[1, 2, 6]
>>> list(accumulate([0, 1, -1, 2, 3, 2], func=max)) # Running maximum
[0, 1, 1, 2, 3, 3]
This function is available in the ``itertools`` module for Python 3.2 and
greater.
"""
it = iter(iterable)
try:
total = next(it)
except StopIteration:
return
else:
yield total
for element in it:
total = func(total, element)
yield total
_marker = object()
def take(n, iterable):
@ -84,11 +75,12 @@ def take(n, iterable):
>>> take(3, range(10))
[0, 1, 2]
>>> take(5, range(3))
[0, 1, 2]
Effectively a short replacement for ``next`` based iterator consumption
when you want more than one item, but less than the whole iterator.
If there are fewer than *n* items in the iterable, all of them are
returned.
>>> take(10, range(3))
[0, 1, 2]
"""
return list(islice(iterable, n))
@ -115,12 +107,19 @@ def tabulate(function, start=0):
def tail(n, iterable):
"""Return an iterator over the last *n* items of *iterable*.
>>> t = tail(3, 'ABCDEFG')
>>> list(t)
['E', 'F', 'G']
>>> t = tail(3, 'ABCDEFG')
>>> list(t)
['E', 'F', 'G']
"""
return iter(deque(iterable, maxlen=n))
# If the given iterable has a length, then we can use islice to get its
# final elements. Note that if the iterable is not actually Iterable,
# either islice or deque will throw a TypeError. This is why we don't
# check if it is Iterable.
if isinstance(iterable, Sized):
yield from islice(iterable, max(0, len(iterable) - n), None)
else:
yield from iter(deque(iterable, maxlen=n))
def consume(iterator, n=None):
@ -166,11 +165,11 @@ def consume(iterator, n=None):
def nth(iterable, n, default=None):
"""Returns the nth item or a default value.
>>> l = range(10)
>>> nth(l, 3)
3
>>> nth(l, 20, "zebra")
'zebra'
>>> l = range(10)
>>> nth(l, 3)
3
>>> nth(l, 20, "zebra")
'zebra'
"""
return next(islice(iterable, n, None), default)
@ -193,17 +192,17 @@ def all_equal(iterable):
def quantify(iterable, pred=bool):
"""Return the how many times the predicate is true.
>>> quantify([True, False, True])
2
>>> quantify([True, False, True])
2
"""
return sum(map(pred, iterable))
def padnone(iterable):
def pad_none(iterable):
"""Returns the sequence of elements and then returns ``None`` indefinitely.
>>> take(5, padnone(range(3)))
>>> take(5, pad_none(range(3)))
[0, 1, 2, None, None]
Useful for emulating the behavior of the built-in :func:`map` function.
@ -214,11 +213,14 @@ def padnone(iterable):
return chain(iterable, repeat(None))
padnone = pad_none
def ncycles(iterable, n):
"""Returns the sequence elements *n* times
>>> list(ncycles(["a", "b"], 3))
['a', 'b', 'a', 'b', 'a', 'b']
>>> list(ncycles(["a", "b"], 3))
['a', 'b', 'a', 'b', 'a', 'b']
"""
return chain.from_iterable(repeat(tuple(iterable), n))
@ -227,8 +229,8 @@ def ncycles(iterable, n):
def dotproduct(vec1, vec2):
"""Returns the dot product of the two iterables.
>>> dotproduct([10, 10], [20, 20])
400
>>> dotproduct([10, 10], [20, 20])
400
"""
return sum(map(operator.mul, vec1, vec2))
@ -273,27 +275,109 @@ def repeatfunc(func, times=None, *args):
return starmap(func, repeat(args, times))
def pairwise(iterable):
def _pairwise(iterable):
"""Returns an iterator of paired items, overlapping, from the original
>>> take(4, pairwise(count()))
[(0, 1), (1, 2), (2, 3), (3, 4)]
>>> take(4, pairwise(count()))
[(0, 1), (1, 2), (2, 3), (3, 4)]
On Python 3.10 and above, this is an alias for :func:`itertools.pairwise`.
"""
a, b = tee(iterable)
next(b, None)
return zip(a, b)
yield from zip(a, b)
def grouper(n, iterable, fillvalue=None):
"""Collect data into fixed-length chunks or blocks.
try:
from itertools import pairwise as itertools_pairwise
except ImportError:
pairwise = _pairwise
else:
>>> list(grouper(3, 'ABCDEFG', 'x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
def pairwise(iterable):
yield from itertools_pairwise(iterable)
pairwise.__doc__ = _pairwise.__doc__
class UnequalIterablesError(ValueError):
def __init__(self, details=None):
msg = 'Iterables have different lengths'
if details is not None:
msg += (': index 0 has length {}; index {} has length {}').format(
*details
)
super().__init__(msg)
def _zip_equal_generator(iterables):
for combo in zip_longest(*iterables, fillvalue=_marker):
for val in combo:
if val is _marker:
raise UnequalIterablesError()
yield combo
def _zip_equal(*iterables):
# Check whether the iterables are all the same size.
try:
first_size = len(iterables[0])
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))
# If any one of the iterables didn't have a length, start reading
# them until one runs out.
except TypeError:
return _zip_equal_generator(iterables)
def grouper(iterable, n, incomplete='fill', fillvalue=None):
"""Group elements from *iterable* into fixed-length groups of length *n*.
>>> list(grouper('ABCDEF', 3))
[('A', 'B', 'C'), ('D', 'E', 'F')]
The keyword arguments *incomplete* and *fillvalue* control what happens for
iterables whose length is not a multiple of *n*.
When *incomplete* is `'fill'`, the last group will contain instances of
*fillvalue*.
>>> list(grouper('ABCDEFG', 3, incomplete='fill', fillvalue='x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
When *incomplete* is `'ignore'`, the last group will not be emitted.
>>> list(grouper('ABCDEFG', 3, incomplete='ignore', fillvalue='x'))
[('A', 'B', 'C'), ('D', 'E', 'F')]
When *incomplete* is `'strict'`, a subclass of `ValueError` will be raised.
>>> it = grouper('ABCDEFG', 3, incomplete='strict')
>>> list(it) # doctest: +IGNORE_EXCEPTION_DETAIL
Traceback (most recent call last):
...
UnequalIterablesError
"""
args = [iter(iterable)] * n
return zip_longest(fillvalue=fillvalue, *args)
if incomplete == 'fill':
return zip_longest(*args, fillvalue=fillvalue)
if incomplete == 'strict':
return _zip_equal(*args)
if incomplete == 'ignore':
return zip(*args)
else:
raise ValueError('Expected fill, strict, or ignore')
def roundrobin(*iterables):
@ -309,10 +393,7 @@ def roundrobin(*iterables):
"""
# Recipe credited to George Sakkis
pending = len(iterables)
if PY2:
nexts = cycle(iter(it).next for it in iterables)
else:
nexts = cycle(iter(it).__next__ for it in iterables)
nexts = cycle(iter(it).__next__ for it in iterables)
while pending:
try:
for next in nexts:
@ -334,18 +415,43 @@ def partition(pred, iterable):
>>> list(even_items), list(odd_items)
([0, 2, 4, 6, 8], [1, 3, 5, 7, 9])
If *pred* is None, :func:`bool` is used.
>>> iterable = [0, 1, False, True, '', ' ']
>>> false_items, true_items = partition(None, iterable)
>>> list(false_items), list(true_items)
([0, False, ''], [1, True, ' '])
"""
# partition(is_odd, range(10)) --> 0 2 4 6 8 and 1 3 5 7 9
t1, t2 = tee(iterable)
return filterfalse(pred, t1), filter(pred, t2)
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),
)
def powerset(iterable):
"""Yields all possible subsets of the iterable.
>>> list(powerset([1,2,3]))
>>> list(powerset([1, 2, 3]))
[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
:func:`powerset` will operate on iterables that aren't :class:`set`
instances, so repeated elements in the input will produce repeated elements
in the output. Use :func:`unique_everseen` on the input to avoid generating
duplicates:
>>> seq = [1, 1, 0]
>>> list(powerset(seq))
[(), (1,), (1,), (0,), (1, 1), (1, 0), (1, 0), (1, 1, 0)]
>>> from more_itertools import unique_everseen
>>> list(powerset(unique_everseen(seq)))
[(), (1,), (0,), (1, 0)]
"""
s = list(iterable)
return chain.from_iterable(combinations(s, r) for r in range(len(s) + 1))
@ -363,41 +469,46 @@ def unique_everseen(iterable, key=None):
Sequences with a mix of hashable and unhashable items can be used.
The function will be slower (i.e., `O(n^2)`) for unhashable items.
Remember that ``list`` objects are unhashable - you can use the *key*
parameter to transform the list to a tuple (which is hashable) to
avoid a slowdown.
>>> iterable = ([1, 2], [2, 3], [1, 2])
>>> list(unique_everseen(iterable)) # Slow
[[1, 2], [2, 3]]
>>> list(unique_everseen(iterable, key=tuple)) # Faster
[[1, 2], [2, 3]]
Similary, you may want to convert unhashable ``set`` objects with
``key=frozenset``. For ``dict`` objects,
``key=lambda x: frozenset(x.items())`` can be used.
"""
seenset = set()
seenset_add = seenset.add
seenlist = []
seenlist_add = seenlist.append
if key is None:
for element in iterable:
try:
if element not in seenset:
seenset_add(element)
yield element
except TypeError:
if element not in seenlist:
seenlist_add(element)
yield element
else:
for element in iterable:
k = key(element)
try:
if k not in seenset:
seenset_add(k)
yield element
except TypeError:
if k not in seenlist:
seenlist_add(k)
yield element
use_key = key is not None
for element in iterable:
k = key(element) if use_key else element
try:
if k not in seenset:
seenset_add(k)
yield element
except TypeError:
if k not in seenlist:
seenlist_add(k)
yield element
def unique_justseen(iterable, key=None):
"""Yields elements in order, ignoring serial duplicates
>>> list(unique_justseen('AAAABBBCCDAABBB'))
['A', 'B', 'C', 'D', 'A', 'B']
>>> list(unique_justseen('ABBCcAD', str.lower))
['A', 'B', 'C', 'A', 'D']
>>> list(unique_justseen('AAAABBBCCDAABBB'))
['A', 'B', 'C', 'D', 'A', 'B']
>>> list(unique_justseen('ABBCcAD', str.lower))
['A', 'B', 'C', 'A', 'D']
"""
return map(next, map(operator.itemgetter(1), groupby(iterable, key)))
@ -414,6 +525,16 @@ def iter_except(func, exception, first=None):
>>> list(iter_except(l.pop, IndexError))
[2, 1, 0]
Multiple exceptions can be specified as a stopping condition:
>>> l = [1, 2, 3, '...', 4, 5, 6]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[7, 6, 5]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[4, 3, 2]
>>> list(iter_except(lambda: 1 + l.pop(), (IndexError, TypeError)))
[]
"""
try:
if first is not None:
@ -424,7 +545,7 @@ def iter_except(func, exception, first=None):
pass
def first_true(iterable, default=False, pred=None):
def first_true(iterable, default=None, pred=None):
"""
Returns the first true value in the iterable.
@ -444,7 +565,7 @@ def first_true(iterable, default=False, pred=None):
return next(filter(pred, iterable), default)
def random_product(*args, **kwds):
def random_product(*args, repeat=1):
"""Draw an item at random from each of the input iterables.
>>> random_product('abc', range(4), 'XYZ') # doctest:+SKIP
@ -460,7 +581,7 @@ def random_product(*args, **kwds):
``itertools.product(*args, **kwarg)``.
"""
pools = [tuple(pool) for pool in args] * kwds.get('repeat', 1)
pools = [tuple(pool) for pool in args] * repeat
return tuple(choice(pool) for pool in pools)
@ -523,6 +644,12 @@ def nth_combination(iterable, r, index):
sort position *index* directly, without computing the previous
subsequences.
>>> nth_combination(range(5), 3, 5)
(0, 3, 4)
``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)
@ -559,7 +686,156 @@ def prepend(value, iterator):
>>> list(prepend(value, iterator))
['0', '1', '2', '3']
To prepend multiple values, see :func:`itertools.chain`.
To prepend multiple values, see :func:`itertools.chain`
or :func:`value_chain`.
"""
return chain([value], iterator)
def convolve(signal, kernel):
"""Convolve the iterable *signal* with the iterable *kernel*.
>>> signal = (1, 2, 3, 4, 5)
>>> kernel = [3, 2, 1]
>>> list(convolve(signal, kernel))
[3, 8, 14, 20, 26, 14, 5]
Note: the input arguments are not interchangeable, as the *kernel*
is immediately consumed and stored.
"""
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))
def before_and_after(predicate, it):
"""A variant of :func:`takewhile` that allows complete access to the
remainder of the iterator.
>>> it = iter('ABCdEfGhI')
>>> all_upper, remainder = before_and_after(str.isupper, it)
>>> ''.join(all_upper)
'ABC'
>>> ''.join(remainder) # takewhile() would lose the 'd'
'dEfGhI'
Note that the first iterator must be fully consumed before the second
iterator can generate valid results.
"""
it = iter(it)
transition = []
def true_iterator():
for elem in it:
if predicate(elem):
yield elem
else:
transition.append(elem)
return
# Note: this is different from itertools recipes to allow nesting
# before_and_after remainders into before_and_after again. See tests
# for an example.
remainder_iterator = chain(transition, it)
return true_iterator(), remainder_iterator
def triplewise(iterable):
"""Return overlapping triplets from *iterable*.
>>> list(triplewise('ABCDE'))
[('A', 'B', 'C'), ('B', 'C', 'D'), ('C', 'D', 'E')]
"""
for (a, _), (b, c) in pairwise(pairwise(iterable)):
yield a, b, c
def sliding_window(iterable, n):
"""Return a sliding window of width *n* over *iterable*.
>>> list(sliding_window(range(6), 4))
[(0, 1, 2, 3), (1, 2, 3, 4), (2, 3, 4, 5)]
If *iterable* has fewer than *n* items, then nothing is yielded:
>>> list(sliding_window(range(3), 4))
[]
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)
for x in it:
window.append(x)
yield tuple(window)
def subslices(iterable):
"""Return all contiguous non-empty subslices of *iterable*.
>>> list(subslices('ABC'))
[['A'], ['A', 'B'], ['A', 'B', 'C'], ['B'], ['B', 'C'], ['C']]
This is similar to :func:`substrings`, but emits items in a different
order.
"""
seq = list(iterable)
slices = starmap(slice, combinations(range(len(seq) + 1), 2))
return map(operator.getitem, repeat(seq), slices)
def polynomial_from_roots(roots):
"""Compute a polynomial's coefficients from its roots.
>>> roots = [5, -4, 3] # (x - 5) * (x + 4) * (x - 3)
>>> 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)
]
def sieve(n):
"""Yield the primes less than n.
>>> list(sieve(30))
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29]
"""
isqrt = getattr(math, 'isqrt', lambda x: int(math.sqrt(x)))
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)
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']]
This recipe is from the ``itertools`` docs. This library also provides
:func:`chunked`, which has a different implementation.
"""
it = iter(iterable)
while True:
batch = list(islice(it, n))
if not batch:
break
yield batch