mirror of
https://github.com/clinton-hall/nzbToMedia.git
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6bb4ae56bd
Dependencies: * backports.functools-lru-cache 1.2.1 * jaraco.classes 1.3 * jaraco.collections 1.3.2 * jaraco.functools 1.11 * jaraco.structures 1.0 * jaraco.text 1.7 * jaraco.ui 1.4 * jaraco.windows 3.6 * more-itertools 2.2 * path.py 8.2.1 * six 1.10.0
331 lines
8.7 KiB
Python
331 lines
8.7 KiB
Python
"""Imported from the recipes section of the itertools documentation.
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All functions taken from the recipes section of the itertools library docs
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[1]_.
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Some backward-compatible usability improvements have been made.
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.. [1] http://docs.python.org/library/itertools.html#recipes
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"""
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from collections import deque
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from itertools import chain, combinations, count, cycle, groupby, ifilterfalse, imap, islice, izip, izip_longest, repeat, starmap, tee # Wrapping breaks 2to3.
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import operator
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from random import randrange, sample, choice
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__all__ = ['take', 'tabulate', 'consume', 'nth', 'quantify', 'padnone',
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'ncycles', 'dotproduct', 'flatten', 'repeatfunc', 'pairwise',
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'grouper', 'roundrobin', 'powerset', 'unique_everseen',
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'unique_justseen', 'iter_except', 'random_product',
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'random_permutation', 'random_combination',
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'random_combination_with_replacement']
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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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>>> take(3, range(10))
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[0, 1, 2]
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>>> take(5, range(3))
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[0, 1, 2]
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Effectively a short replacement for ``next`` based iterator consumption
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when you want more than one item, but less than the whole iterator.
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"""
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return list(islice(iterable, n))
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def tabulate(function, start=0):
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"""Return an iterator mapping the function over linear input.
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The start argument will be increased by 1 each time the iterator is called
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and fed into the function.
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>>> t = tabulate(lambda x: x**2, -3)
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>>> take(3, t)
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[9, 4, 1]
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"""
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return imap(function, count(start))
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def consume(iterator, n=None):
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"""Advance the iterator n-steps ahead. If n is none, consume entirely.
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Efficiently exhausts an iterator without returning values. Defaults to
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consuming the whole iterator, but an optional second argument may be
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provided to limit consumption.
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>>> i = (x for x in range(10))
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>>> next(i)
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0
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>>> consume(i, 3)
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>>> next(i)
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4
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>>> consume(i)
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>>> next(i)
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Traceback (most recent call last):
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File "<stdin>", line 1, in <module>
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StopIteration
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If the iterator has fewer items remaining than the provided limit, the
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whole iterator will be consumed.
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>>> i = (x for x in range(3))
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>>> consume(i, 5)
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>>> next(i)
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Traceback (most recent call last):
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File "<stdin>", line 1, in <module>
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StopIteration
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"""
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# Use functions that consume iterators at C speed.
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if n is None:
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# feed the entire iterator into a zero-length deque
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deque(iterator, maxlen=0)
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else:
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# advance to the empty slice starting at position n
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next(islice(iterator, n, n), None)
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def nth(iterable, n, default=None):
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"""Returns the nth item or a default value
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>>> l = range(10)
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>>> nth(l, 3)
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3
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>>> nth(l, 20, "zebra")
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'zebra'
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"""
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return next(islice(iterable, n, None), default)
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def quantify(iterable, pred=bool):
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"""Return the how many times the predicate is true
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>>> quantify([True, False, True])
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2
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"""
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return sum(imap(pred, iterable))
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def padnone(iterable):
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"""Returns the sequence of elements and then returns None indefinitely.
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>>> take(5, padnone(range(3)))
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[0, 1, 2, None, None]
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Useful for emulating the behavior of the built-in map() function.
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"""
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return chain(iterable, repeat(None))
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def ncycles(iterable, n):
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"""Returns the sequence elements n times
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>>> list(ncycles(["a", "b"], 3))
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['a', 'b', 'a', 'b', 'a', 'b']
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"""
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return chain.from_iterable(repeat(tuple(iterable), n))
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def dotproduct(vec1, vec2):
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"""Returns the dot product of the two iterables
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>>> dotproduct([10, 10], [20, 20])
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400
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"""
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return sum(imap(operator.mul, vec1, vec2))
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def flatten(listOfLists):
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"""Return an iterator flattening one level of nesting in a list of lists
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>>> list(flatten([[0, 1], [2, 3]]))
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[0, 1, 2, 3]
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"""
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return chain.from_iterable(listOfLists)
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def repeatfunc(func, times=None, *args):
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"""Repeat calls to func with specified arguments.
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>>> list(repeatfunc(lambda: 5, 3))
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[5, 5, 5]
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>>> list(repeatfunc(lambda x: x ** 2, 3, 3))
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[9, 9, 9]
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"""
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if times is None:
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return starmap(func, repeat(args))
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return starmap(func, repeat(args, times))
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def pairwise(iterable):
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"""Returns an iterator of paired items, overlapping, from the original
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>>> take(4, pairwise(count()))
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[(0, 1), (1, 2), (2, 3), (3, 4)]
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"""
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a, b = tee(iterable)
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next(b, None)
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return izip(a, b)
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def grouper(n, iterable, fillvalue=None):
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"""Collect data into fixed-length chunks or blocks
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>>> list(grouper(3, 'ABCDEFG', 'x'))
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[('A', 'B', 'C'), ('D', 'E', 'F'), ('G', 'x', 'x')]
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"""
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args = [iter(iterable)] * n
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return izip_longest(fillvalue=fillvalue, *args)
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def roundrobin(*iterables):
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"""Yields an item from each iterable, alternating between them
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>>> list(roundrobin('ABC', 'D', 'EF'))
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['A', 'D', 'E', 'B', 'F', 'C']
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"""
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# Recipe credited to George Sakkis
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pending = len(iterables)
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nexts = cycle(iter(it).next for it in iterables)
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while pending:
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try:
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for next in nexts:
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yield next()
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except StopIteration:
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pending -= 1
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nexts = cycle(islice(nexts, pending))
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def powerset(iterable):
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"""Yields all possible subsets of the iterable
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>>> list(powerset([1,2,3]))
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[(), (1,), (2,), (3,), (1, 2), (1, 3), (2, 3), (1, 2, 3)]
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"""
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s = list(iterable)
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return chain.from_iterable(combinations(s, r) for r in range(len(s)+1))
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def unique_everseen(iterable, key=None):
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"""Yield unique elements, preserving order.
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>>> list(unique_everseen('AAAABBBCCDAABBB'))
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['A', 'B', 'C', 'D']
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>>> list(unique_everseen('ABBCcAD', str.lower))
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['A', 'B', 'C', 'D']
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"""
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seen = set()
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seen_add = seen.add
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if key is None:
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for element in ifilterfalse(seen.__contains__, iterable):
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seen_add(element)
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yield element
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else:
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for element in iterable:
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k = key(element)
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if k not in seen:
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seen_add(k)
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yield element
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def unique_justseen(iterable, key=None):
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"""Yields elements in order, ignoring serial duplicates
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>>> list(unique_justseen('AAAABBBCCDAABBB'))
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['A', 'B', 'C', 'D', 'A', 'B']
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>>> list(unique_justseen('ABBCcAD', str.lower))
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['A', 'B', 'C', 'A', 'D']
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"""
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return imap(next, imap(operator.itemgetter(1), groupby(iterable, key)))
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def iter_except(func, exception, first=None):
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"""Yields results from a function repeatedly until an exception is raised.
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Converts a call-until-exception interface to an iterator interface.
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Like __builtin__.iter(func, sentinel) but uses an exception instead
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of a sentinel to end the loop.
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>>> l = range(3)
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>>> list(iter_except(l.pop, IndexError))
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[2, 1, 0]
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"""
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try:
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if first is not None:
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yield first()
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while 1:
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yield func()
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except exception:
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pass
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def random_product(*args, **kwds):
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"""Returns a random pairing of items from each iterable argument
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If `repeat` is provided as a kwarg, it's value will be used to indicate
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how many pairings should be chosen.
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>>> random_product(['a', 'b', 'c'], [1, 2], repeat=2) # doctest:+SKIP
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('b', '2', 'c', '2')
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"""
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pools = map(tuple, args) * kwds.get('repeat', 1)
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return tuple(choice(pool) for pool in pools)
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def random_permutation(iterable, r=None):
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"""Returns a random permutation.
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If r is provided, the permutation is truncated to length r.
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>>> random_permutation(range(5)) # doctest:+SKIP
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(3, 4, 0, 1, 2)
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"""
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pool = tuple(iterable)
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r = len(pool) if r is None else r
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return tuple(sample(pool, r))
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def random_combination(iterable, r):
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"""Returns a random combination of length r, chosen without replacement.
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>>> random_combination(range(5), 3) # doctest:+SKIP
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(2, 3, 4)
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"""
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pool = tuple(iterable)
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n = len(pool)
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indices = sorted(sample(xrange(n), r))
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return tuple(pool[i] for i in indices)
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def random_combination_with_replacement(iterable, r):
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"""Returns a random combination of length r, chosen with replacement.
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>>> random_combination_with_replacement(range(3), 5) # # doctest:+SKIP
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(0, 0, 1, 2, 2)
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"""
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pool = tuple(iterable)
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n = len(pool)
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indices = sorted(randrange(n) for i in xrange(r))
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return tuple(pool[i] for i in indices)
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