本文介绍了带有生成器理解的“any"和不带括号的理解之间的区别?的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
回顾我的一些代码，我意识到我写的东西本质上是:'
if (any(predicate for predicate in list_of_predicates)):# 做一点事我预料到会出现这个语法错误，因为它缺少()"或[]".所以我在 ipython 中试了一下:
无括号:
在 [33]: timeit.repeat('any(True for x in xrange(10))', repeat=10)出[33]:[0.502741813659668,0.49950194358825684，0.6626348495483398，0.5485308170318604，0.5268769264221191，0.6033108234405518，0.4647831916809082，0.45836901664733887，0.46139097213745117，0.4977281093597412]生成器理解:
In [34]: timeit.repeat('any((True for x in xrange(10)))', repeat=10)出[34]:[0.7183680534362793,0.6293261051177979，0.5045809745788574，0.4723200798034668，0.4649538993835449，0.5164840221405029，0.5919051170349121，0.5790350437164307，0.594775915145874，0.5718569755554199]加速:
在 [52]: reg = timeit.repeat('any(True for x in xrange(10))', repeat=100)在 [53] 中:comp = timeit.repeat('any((True for x in xrange(10)))', repeat=100)在 [55] 中:avg(reg)出[55]:0.5245428466796875在 [56] 中:avg(comp)出[56]:0.5283565306663514在 [57] 中:stddev(reg)出[57]:0.05609485659272963在 [58] 中:stddev(comp)出[58]:0.058506353663056954在 [59] 中:reg[50]出[59]:0.46748805046081543在 [60] 中:comp[50]出[60]:0.5147180557250977没有括号似乎有一个边际(可能是噪音)的性能优势 - 增加测试它看起来更像是噪音.这些处理方式之间是否存在根本区别?
解决方案
这些表达式是等价的.性能差异是噪音.
来自原始genexp PEP:
如果一个函数调用只有一个位置参数，它可以是一个没有额外括号的生成器表达式，但在所有其他情况下，你必须把它加上括号.
查看反汇编，您可以看到它们编译为相同的字节码:
>>>定义 f():... 任何(对于 x 范围内的 x 为真(10))...>>>定义 g():... 任何((对于 x 范围内的 x 为真(10)))...>>>dis.dis(f)2 0 LOAD_GLOBAL 0(任意)3 LOAD_CONST 1 (<代码对象<genexpr>在0000000002B46A30，文件<stdin>"，第 2 行>)6 MAKE_FUNCTION 09 LOAD_GLOBAL 1 (xrange)12 LOAD_CONST 2 (10)15 CALL_FUNCTION 118 GET_ITER19 CALL_FUNCTION 122 CALL_FUNCTION 125 POP_TOP26 LOAD_CONST 0 (无)29 RETURN_VALUE>>>dis.dis(g)2 0 LOAD_GLOBAL 0(任意)3 LOAD_CONST 1 (<代码对象<genexpr>在0000000002BE0DB0，文件<stdin>"，第 2 行>)6 MAKE_FUNCTION 09 LOAD_GLOBAL 1 (xrange)12 LOAD_CONST 2 (10)15 CALL_FUNCTION 118 GET_ITER19 CALL_FUNCTION 122 CALL_FUNCTION 125 POP_TOP26 LOAD_CONST 0 (无)29 RETURN_VALUE>>>f.__code__.co_consts(无，<代码对象<genexpr>在0000000002B46A30，文件<stdin>"，第2行>，10)>>>dis.dis(f.__code__.co_consts[1]) # f 中 genexp 的代码对象2 0 LOAD_FAST 0 (.0)>>3 FOR_ITER 11(到 17)6 STORE_FAST 1 (x)9 LOAD_GLOBAL 0(真)12 YIELD_VALUE13 POP_TOP14 JUMP_ABSOLUTE 3>>17 LOAD_CONST 0 (无)20 RETURN_VALUE>>>dis.dis(g.__code__.co_consts[1]) # g中genexp的代码对象2 0 LOAD_FAST 0 (.0)>>3 FOR_ITER 11(到 17)6 STORE_FAST 1 (x)9 LOAD_GLOBAL 0(真)12 YIELD_VALUE13 POP_TOP14 JUMP_ABSOLUTE 3>>17 LOAD_CONST 0 (无)20 RETURN_VALUEReviewing some of my code and I realized I had written what is essentially:'
if (any(predicate for predicate in list_of_predicates)):
# do something
I had expected this syntax error since it was missing '()' or '[]'. So I tried it in ipython:
Without bracketing:
In [33]: timeit.repeat('any(True for x in xrange(10))', repeat=10)
Out[33]:
[0.502741813659668,
0.49950194358825684,
0.6626348495483398,
0.5485308170318604,
0.5268769264221191,
0.6033108234405518,
0.4647831916809082,
0.45836901664733887,
0.46139097213745117,
0.4977281093597412]
Generator comprehension:
In [34]: timeit.repeat('any((True for x in xrange(10)))', repeat=10)
Out[34]:
[0.7183680534362793,
0.6293261051177979,
0.5045809745788574,
0.4723200798034668,
0.4649538993835449,
0.5164840221405029,
0.5919051170349121,
0.5790350437164307,
0.594775915145874,
0.5718569755554199]
Ramping up:
In [52]: reg = timeit.repeat('any(True for x in xrange(10))', repeat=100)
In [53]: comp = timeit.repeat('any((True for x in xrange(10)))', repeat=100)
In [55]: avg(reg)
Out[55]: 0.5245428466796875
In [56]: avg(comp)
Out[56]: 0.5283565306663514
In [57]: stddev(reg)
Out[57]: 0.05609485659272963
In [58]: stddev(comp)
Out[58]: 0.058506353663056954
In [59]: reg[50]
Out[59]: 0.46748805046081543
In [60]: comp[50]
Out[60]: 0.5147180557250977
There seems to be a marginal (possibly noise) performance advantage to not having the parentheses - ramping up the test it appears more like noise. Is there a fundamental difference between how these are processed?
解决方案
These expressions are equivalent. The performance difference is noise.
From the original genexp PEP:
And viewing the disassembly, you can see that they compile to the same bytecode:
>>> def f():
... any(True for x in xrange(10))
...
>>> def g():
... any((True for x in xrange(10)))
...
>>> dis.dis(f)
2 0 LOAD_GLOBAL 0 (any)
3 LOAD_CONST 1 (<code object <genexpr> at 0000000002
B46A30, file "<stdin>", line 2>)
6 MAKE_FUNCTION 0
9 LOAD_GLOBAL 1 (xrange)
12 LOAD_CONST 2 (10)
15 CALL_FUNCTION 1
18 GET_ITER
19 CALL_FUNCTION 1
22 CALL_FUNCTION 1
25 POP_TOP
26 LOAD_CONST 0 (None)
29 RETURN_VALUE
>>> dis.dis(g)
2 0 LOAD_GLOBAL 0 (any)
3 LOAD_CONST 1 (<code object <genexpr> at 0000000002
BE0DB0, file "<stdin>", line 2>)
6 MAKE_FUNCTION 0
9 LOAD_GLOBAL 1 (xrange)
12 LOAD_CONST 2 (10)
15 CALL_FUNCTION 1
18 GET_ITER
19 CALL_FUNCTION 1
22 CALL_FUNCTION 1
25 POP_TOP
26 LOAD_CONST 0 (None)
29 RETURN_VALUE
>>> f.__code__.co_consts
(None, <code object <genexpr> at 0000000002B46A30, file "<stdin>", line 2>, 10)
>>> dis.dis(f.__code__.co_consts[1]) # the genexp's code object in f
2 0 LOAD_FAST 0 (.0)
>> 3 FOR_ITER 11 (to 17)
6 STORE_FAST 1 (x)
9 LOAD_GLOBAL 0 (True)
12 YIELD_VALUE
13 POP_TOP
14 JUMP_ABSOLUTE 3
>> 17 LOAD_CONST 0 (None)
20 RETURN_VALUE
>>> dis.dis(g.__code__.co_consts[1]) # the genexp's code object in g
2 0 LOAD_FAST 0 (.0)
>> 3 FOR_ITER 11 (to 17)
6 STORE_FAST 1 (x)
9 LOAD_GLOBAL 0 (True)
12 YIELD_VALUE
13 POP_TOP
14 JUMP_ABSOLUTE 3
>> 17 LOAD_CONST 0 (None)
20 RETURN_VALUE
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