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Update more-itertools-8.10.0

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JonnyWong16 2021-10-14 21:13:45 -07:00
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247
lib/more_itertools/recipes.py
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@ -7,20 +7,27 @@ Some backward-compatible usability improvements have been made.
.. [1] http://docs.python.org/library/itertools.html#recipes
"""
import warnings
from collections import deque
from itertools import (
chain, combinations, count, cycle, groupby, islice, repeat, starmap, tee
chain,
combinations,
count,
cycle,
groupby,
islice,
repeat,
starmap,
tee,
zip_longest,
)
import operator
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',
'consume',
'convolve',
'dotproduct',
'first_true',
'flatten',
@ -30,6 +37,7 @@ __all__ = [
'nth',
'nth_combination',
'padnone',
'pad_none',
'pairwise',
'partition',
'powerset',
@ -49,46 +57,17 @@ __all__ = [
]
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
def take(n, iterable):
"""Return first *n* items of the iterable as a list.
>>> 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))
@ -115,9 +94,9 @@ 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))
@ -166,11 +145,11 @@ 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 +172,17 @@ 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 +193,14 @@ 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 +209,8 @@ 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))
@ -273,25 +255,44 @@ 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):
try:
from itertools import pairwise as itertools_pairwise
except ImportError:
pairwise = _pairwise
else:
def pairwise(iterable):
yield from itertools_pairwise(iterable)
pairwise.__doc__ = _pairwise.__doc__
def grouper(iterable, n, fillvalue=None):
"""Collect data into fixed-length chunks or blocks.
>>> list(grouper(3, 'ABCDEFG', 'x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
>>> list(grouper('ABCDEFG', 3, 'x'))
[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
"""
if isinstance(iterable, int):
warnings.warn(
"grouper expects iterable as first parameter", DeprecationWarning
)
n, iterable = iterable, n
args = [iter(iterable)] * n
return zip_longest(fillvalue=fillvalue, *args)
@ -309,10 +310,7 @@ 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:
@ -334,10 +332,23 @@ 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):
@ -375,41 +386,46 @@ 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)))
@ -426,6 +442,16 @@ 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:
@ -456,7 +482,7 @@ def first_true(iterable, default=None, 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
@ -472,7 +498,7 @@ 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)
@ -535,6 +561,12 @@ 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)
@ -571,7 +603,28 @@ 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))