具有Itertools的等效嵌套循环结构

Abh*_*jit 12 python foreach python-itertools python-2.7

Python的succint语法通过其电池允许详细的代码行以可读的一行表示.请考虑以下示例

====================================================|
for a in range(3):                                  |
    for b in range(3):                              |
        for c in range(3):                          |
            print (a,b,c),                          |
-  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -|
for e in product(range(3), repeat=3):               |
    print e,                                        |
====================================================|
for a in range(3):                                  |
    for b in range(a , 3):                          |
        for c in range(b , 3):                      |
            print (a,b,c),                          |
-  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -|
for e in combinations_with_replacement(range(3), 3):|
    print e,                                        |
====================================================|
for a in range(3):                                  |
    for b in range(a + 1, 3):                       |
        for c in range(b + 1, 3):                   |
            print (a,b,c),                          |
-  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -|
for e in combinations(range(3), 3):                 |
    print e,                                        |
====================================================|
for a in range(3):                                  |
    for b in range(3):                              |
        for c in range(3):                          |
            if len(set([a,b,c])) == 3:              |
                print (a,b,c),                      |
-  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -  -|
for e in permutations(range(3)):                    |
    print e,                                        |
====================================================|
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我最后得到一个深嵌套的依赖循环我试图简洁地表达但失败了

循环的结构如下

for a in A():
    for b in B(a):
        for c in C(b):
            foo(a,b,c)
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这种结构能用等效的itertools符号表示吗?

sen*_*rle 5

没有确切的itertools解决方案,但简单的itertools功能组合就足够了:

def chain_imap_accumulate(seq, f):
    def acc_f(x):
        for n in f(x[-1]):
            yield x + (n,)
    return chain.from_iterable(imap(acc_f, seq))

def accumulative_product(*generators):
    head, tail = generators[0], generators[1:]
    head = imap(tuple, head())
    return reduce(chain_imap_accumulate, tail, head)
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快速测试.定义:

from itertools import chain, imap, izip
chain_ = chain.from_iterable

def A():
    yield 'A'
    yield 'B'

def B(x):
    yield int(x, 16)
    yield int(x, 16) + 1

def C(x):
    yield str(x) + 'Z'
    yield str(x) + 'Y'
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结果如下:

>>> list(accumulative_product(A, B, C))
[('A', 10, '10Z'), ('A', 10, '10Y'), 
 ('A', 11, '11Z'), ('A', 11, '11Y'), 
 ('B', 11, '11Z'), ('B', 11, '11Y'), 
 ('B', 12, '12Z'), ('B', 12, '12Y')]
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几乎所有的复杂性都来自于输入的积累,正如上面代码的快速"推导"所示.在最终(c)值可以使用只是几个嵌套来生成itertools构建体:

>>> list(chain_(imap(C, chain_(imap(B, (A()))))))
['10Z', '10Y', '11Z', '11Y', '11Z', '11Y', '12Z', '12Y']
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这可以概括为reduce.要使用reduce,chain_imap不能使用标准imap参数顺序.它必须被交换:

def chain_imap(seq, f):
    return chain.from_iterable(imap(f, seq))
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这给出了相同的结果:

>>> list(reduce(chain_imap, [B, C], A()))
['10Z', '10Y', '11Z', '11Y', '11Z', '11Y', '12Z', '12Y']
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最后的任务是积累的初始值,让你有机会获得a,bc.这需要一点思想得到正确,但执行是相当简单-我们只需要转换f成忽略所有的输入值,但是最后的一个功能,并追加新值全情投入:

def chain_imap_accumulate(seq, f):
    def acc_f(x):
        for n in f(x[-1]):
            yield x + (n,)
    return chain.from_iterable(imap(acc_f, seq))
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这就需要首先输入被包裹在元组,所以我们映射Atuple:

>>> list(reduce(chain_imap_accumulate, [B, C], imap(tuple, A())))
[('A', 10, '10Z'), ('A', 10, '10Y'), 
 ('A', 11, '11Z'), ('A', 11, '11Y'), 
 ('B', 11, '11Z'), ('B', 11, '11Y'), 
 ('B', 12, '12Z'), ('B', 12, '12Y')]
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为清晰起见,重写上述内容,并在此答案的顶部显示代码.

顺便说一下,chain_imap_accumulate使用genex可以更简洁地重写一下.这可以与较短版本结合使用,accumulative_product以获得非常紧凑的定义(如果您对此类内容感兴趣).这也恰好完全消除了itertools依赖:

def chain_map_accumulate(seq, f):
    return (x + (n,) for x in seq for n in f(x[-1]))

def accumulative_product2(*gens):
    return reduce(chain_map_accumulate, gens[1:], (tuple(x) for x in gens[0]()))
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Bre*_*arn 4

没有,但你可以制作一个:

def chainGang(steps, currentVars=None):
    thisOne = steps[0]
    if currentVars is None:
        for item in thisOne():
            for gang in chainGang(steps[1:], [item]):
                yield gang
    elif len(steps) == 1:       
        for item in thisOne(currentVars[-1]):
            yield currentVars + [item]
    else:
        for item in thisOne(currentVars[-1]):
            for gang in chainGang(steps[1:], currentVars + [item]):
                yield gang
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进而:

>>> outer = lambda: ["A", "B", "C", "D"]
>>> middle = lambda letter: [letter, letter*2, letter*3]
>>> inner = lambda s: range(len(s)+1)
>>> for a in chainGang([outer, middle, inner]):
...     print a
[u'A', u'A', 0]
[u'A', u'A', 1]
[u'A', u'AA', 0]
[u'A', u'AA', 1]
[u'A', u'AA', 2]
[u'A', u'AAA', 0]
[u'A', u'AAA', 1]
[u'A', u'AAA', 2]
[u'A', u'AAA', 3]
[u'B', u'B', 0]
[u'B', u'B', 1]
[u'B', u'BB', 0]
[u'B', u'BB', 1]
[u'B', u'BB', 2]
[u'B', u'BBB', 0]
[u'B', u'BBB', 1]
[u'B', u'BBB', 2]
[u'B', u'BBB', 3]
[u'C', u'C', 0]
[u'C', u'C', 1]
[u'C', u'CC', 0]
[u'C', u'CC', 1]
[u'C', u'CC', 2]
[u'C', u'CCC', 0]
[u'C', u'CCC', 1]
[u'C', u'CCC', 2]
[u'C', u'CCC', 3]
[u'D', u'D', 0]
[u'D', u'D', 1]
[u'D', u'DD', 0]
[u'D', u'DD', 1]
[u'D', u'DD', 2]
[u'D', u'DDD', 0]
[u'D', u'DDD', 1]
[u'D', u'DDD', 2]
[u'D', u'DDD', 3]
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