Python itertools 模块

itertools模块

一、概念

标准库中的itertools包提供了更加灵活的生成器工具，这些工具的输入大多是已有的循环器。

二、功能

#无限循环#从5开始的整数循环器，每次增加2，即5, 7, 9, 11, 13, 15 ..."""def count(start=0, step=1):    n = start    while True:        yield n        n += start"""from itertools import countprint (next(count(5,2)))

#重复序列的元素，既a, b, c, a, b, c ..."""def cycle(iterable):    saved = []    for element in iterable:        yield element        saved.append(element)    while saved:        for element in saved:            yield element"""from itertools import cycleprint (next(cycle('abc')))

#重复"""def repeat(obj, times=None):    if itmes is None:        while True:            yield obj    else:        for i range(times):            yield obj"""from itertools import repeatprint (next(repeat(1.2)))#重复10，共重复5次print (next(repeat(10, 5)))

#函数式工具"""将函数本身作为处理对象的编程范式，在Python中，函数也是对象，因此可以轻松的进行一些函数式的处理，比如map(), filter(), reduce() 函数itertools包含类似的工具。这些函数接收函数作为参数，并将结果返回为一个循环器。"""#累积"""def accumulate(iterable, func=operator.add):    it = iter(iterable)    try:        total = next(it)    except StopIteration:        return     yield total    for element in it:        total = func(total, element)        yield total"""from itertools import accumulatefrom operator import suba = accumulate([1,2,3,4,5])a = accumulate([1,2,3,4,5], sub)print(list(a)) #->[1, -1, -4, -8, -13]

#依次将 序列中的值传递给pow函数（多次调用一个函数）from itertools import starmap"""def starmap(function, iterable):    for args in iterable:        yield function(*args)"""a = starmap(pow, [(1, 1),(2, 2), (3, 3)])print (list(a))

#组合工具#连接"""def chain(*iterables):    for it in iterables:        for element in it:            yield element"""from itertools import chainc = chain([1,2,3], "abc", "def")print (list(c)) #[1, 2, 3, 'a', 'b', 'c', 'd', 'e', 'f']# 从一个列表中获取"""def from_iterable(iterables):    for it in iterables:        for element in it:            yield element"""d = chain.from_iterable(['abc', 'edf'])print (list(d))

#根据一组Ture/False选择值"""def compress:    return (d for d,s in zip(data, selectors) if s)"""from itertools import compressc = compress('abc', [1, 0, 1])print (list(c))

# 截取第一个不满足条件的序列到结尾"""def dropwhile(predicate, iterable):    iterbale = iter(iterable)    for x in iterable:        if not predicate(x):            yield x            break    #迭代下面的元素    for x in iterable:        yield x"""from itertools import dropwhiled = dropwhile(lambda x : x > 6, (7, 8, 3, 4, 5, 7, 8))print(list(d))

# 过滤值返回值为false的iterbale"""def filterfalse(predicate, iterable):    if predicate is None:        predicate = bool    for x in iterable:        if not predicate(x):            yield x"""from itertools import filterfalsef = filterfalse(None, ["aa", "", 0, "v", 0.0])print (list(f))

# 获取知道调用predicate(x)为False之前的数据(和dropwhile类似)#如果第一条就不满足的话，就返回空迭代器"""def takewhile(predicate, iterable):    for x in iterable:        if predicate(x):            yield x        else:            break"""from itertools import takewhilet = takewhile(lambda x : x > 5, [1, 2, 3, 4, 5])print (list(t))

#组合 group"""将key函数作用于原循环器的各个元素。根据key函数结果，将拥有相同函数结果的元素分到一个新的循环器。每个新的循环器以函数返回结果为标签。这就好像一群人的身高作为循环器。我们可以使 用这样一个key函数: 如果身高大于180，返回"tall"；如果身高底于160，返回"short";中间的返回"middle"。最终，所有身高将分为三个循环器， 即"tall", "short", "middle"。"""from itertools import groupbydef high_class(h):    if h> 180:        return "tall"    elif h < 160:        return "short"    else:        return "middle"friends = [191, 158, 159, 165, 170, 177, 181, 182, 190]friends = sorted(friends, key=high_class)for m,n in groupby(friends,key=high_class):    print (m, list(n))#注意，groupby的功能类似于UNIX中的uniq命令。#分组之前需要使用sorted()对原循环器的元素，根据key函数进行排序，让同组元素先在位置上靠拢。

# islice() 命名切片迭代器"""def islice(iterable, *args):    s = slice(*args) #生成切片对象    it = iter(range(s.start or 0, s.stop or sys.maxsize, s.step or 1))    try:        nexti = next(it)    except StopIteration:        return    for i, element in enumerate(iterable):        if i == nexti:            yield element            nexti = next(it)"""from itertools import isliceislice("ABCDEFG", 2) #  start = 0, stop = 2, step = 1islice("ABCDEFG", 2, 4) # start = 2, stop = 4, step = 1islice("ABCDEFG", 2, None) # start = 2, stop = sys.maxsize, step = 1islice("ABCDEFG", 0, None, 2) # start=2, stop=sys.maxsize, step = 2

"""def tee(iterable, n = 2):    it = iter(iterable)    deques = [collections.deque() for i in range(n)]    def gen(mydeque):        while True:            if not mydeque:  # when the local deque is empty                try:                    newval = next(it)                except StopIteration:                    return                 for d in deques:                    d.append(newval)            yield mydeque.popleft()    return tuple(gen(d) for d in deques)""""""从iterable创建n个独立的迭代器，创建的迭代器以n元组的形式返回，n的默认值为2，此函数适用于任何可迭代的对象，但是，为了克隆原始迭代器，生成的项会被缓存，并在所有新创建的迭代器中使用，一定要注意，不要在调用tee()之后使用原始迭代器iterable，否则缓存机制可能无法正确工作"""from itertools import teet = tee([1, 2, 3])print (list(t))

"""操作zip 函数时，多余的话，会被截取掉zip_longest() 则会补充fillvalue, 默认值为None"""from itertools import zip_longestz = zip_longest('abc', 'bacd', fillvalue='-')print(list(z)) #->[('a', 'b'), ('b', 'a'), ('c', 'c'), ('-', 'd')]z = zip("abcdd", "edf")print (list(z))

三、参考

https://docs.python.org/3.5/library/itertools.html