How slow is Python's string concatenation vs. str.join?
由于我在回答这个问题时的评论，我想知道
那么，两者之间的速度比较是什么呢？
发件人：有效的字符串连接
方法1：
1 2 3 4 5 | def method1(): out_str = '' for num in xrange(loop_count): out_str += 'num' return out_str |
方法4：
1 2 3 4 5 | def method4(): str_list = [] for num in xrange(loop_count): str_list.append('num') return ''.join(str_list) |
现在我意识到它们并不具有严格的代表性，第四种方法在遍历和联接每个项之前附加到一个列表中，但这是一个公平的指示。
字符串联接比连接快得多。
为什么？字符串是不可变的，不能就地更改。要更改一个，需要创建一个新的表示(二者的串联)。
我的原始代码是错误的，看起来
时间如下：
1 | Iterations: 1,000,000 |
Windows7上的python 3.3，核心i7
1 2 3 4 5 6 7 | String of len: 1 took: 0.5710 0.2880 seconds String of len: 4 took: 0.9480 0.5830 seconds String of len: 6 took: 1.2770 0.8130 seconds String of len: 12 took: 2.0610 1.5930 seconds String of len: 80 took: 10.5140 37.8590 seconds String of len: 222 took: 27.3400 134.7440 seconds String of len: 443 took: 52.9640 170.6440 seconds |
Windows7上的python 2.7，核心i7
1 2 3 4 5 6 7 | String of len: 1 took: 0.7190 0.4960 seconds String of len: 4 took: 1.0660 0.6920 seconds String of len: 6 took: 1.3300 0.8560 seconds String of len: 12 took: 1.9980 1.5330 seconds String of len: 80 took: 9.0520 25.7190 seconds String of len: 222 took: 23.1620 71.3620 seconds String of len: 443 took: 44.3620 117.1510 seconds |
在linux mint、python 2.7上，一些较慢的处理器
1 2 3 4 5 6 7 | String of len: 1 took: 1.8840 1.2990 seconds String of len: 4 took: 2.8394 1.9663 seconds String of len: 6 took: 3.5177 2.4162 seconds String of len: 12 took: 5.5456 4.1695 seconds String of len: 80 took: 27.8813 19.2180 seconds String of len: 222 took: 69.5679 55.7790 seconds String of len: 443 took: 135.6101 153.8212 seconds |
代码如下：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | from __future__ import print_function import time def strcat(string): newstr = '' for char in string: newstr += char return newstr def listcat(string): chars = [] for char in string: chars.append(char) return ''.join(chars) def test(fn, times, *args): start = time.time() for x in range(times): fn(*args) return"{:>10.4f}".format(time.time() - start) def testall(): strings = ['a', 'long', 'longer', 'a bit longer', '''adjkrsn widn fskejwoskemwkoskdfisdfasdfjiz oijewf sdkjjka dsf sdk siasjk dfwijs''', '''this is a really long string that's so long it had to be triple quoted and contains lots of superflous characters for kicks and gigles @!#(*_#)(*$(*!#@&)(*E\xc4\x32\xff\x92\x23\xDF\xDFk^%#$!)%#^(*#''', '''I needed another long string but this one won't have any new lines or crazy characters in it, I'm just going to type normal characters that I would usually write blah blah blah blah this is some more text hey cool what's crazy is that it looks that the str += is really close to the O(n^2) worst case performance, but it looks more like the other method increases in a perhaps linear scale? I don't know but I think this is enough text I hope.'''] for string in strings: print("String of len:", len(string),"took:", test(listcat, 1000000, string), test(strcat, 1000000, string),"seconds") testall() |
现有的答案写得很好，研究得也很好，但这里是另一个关于python 3.6时代的答案，因为现在我们有了文字字符串插值(aka，
1 2 3 4 5 6 7 | >>> import timeit >>> timeit.timeit('f\'{"a"}{"b"}{"c"}\'', number=1000000) 0.14618930302094668 >>> timeit.timeit('"".join(["a","b","c"])', number=1000000) 0.23334730707574636 >>> timeit.timeit('a ="a"; a +="b"; a +="c"', number=1000000) 0.14985873899422586 |
使用CPython 3.6.5在2012视网膜MacBook Pro上进行测试，Intel Core i7的频率为2.3 GHz。
这绝不是任何正式的基准，但看起来使用
我重写了最后一个答案，周可以分享一下你对我测试方法的看法吗？
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | import time start1 = time.clock() for x in range (10000000): dog1 = ' and '.join(['spam', 'eggs', 'spam', 'spam', 'eggs', 'spam','spam', 'eggs', 'spam', 'spam', 'eggs', 'spam']) end1 = time.clock() print("Time to run Joiner =", end1 - start1,"seconds") start2 = time.clock() for x in range (10000000): dog2 = 'spam'+' and '+'eggs'+' and '+'spam'+' and '+'spam'+' and '+'eggs'+' and '+'spam'+' and '+'spam'+' and '+'eggs'+' and '+'spam'+' and '+'spam'+' and '+'eggs'+' and '+'spam' end2 = time.clock() print("Time to run + =", end2 - start2,"seconds") |
注意：这个例子是用python 3.5编写的，其中range()的作用类似于前一个xrange()。
我得到的输出：
1 2 | Time to run Joiner = 27.086106206103153 seconds Time to run + = 69.79100515996426 seconds |
就我个人而言，我更喜欢''加入([])而不是'plusser方式'，因为它更干净，更易读。
这就是愚蠢的程序设计用来测试的原因：)
使用加
1 2 3 4 5 6 7 8 9 | import time if __name__ == '__main__': start = time.clock() for x in range (1, 10000000): dog ="a" +"b" end = time.clock() print"Time to run Plusser =", end - start,"seconds" |
产量：
1 | Time to run Plusser = 1.16350010965 seconds |
现在加入……
1 2 3 4 5 6 7 8 | import time if __name__ == '__main__': start = time.clock() for x in range (1, 10000000): dog ="a".join("b") end = time.clock() print"Time to run Joiner =", end - start,"seconds" |
产量：
1 | Time to run Joiner = 21.3877386651 seconds |
所以在Windows上的python2.6上，我会说+比join快18倍。)