Python的字符串连接与str.join的速度有多慢？
Way*_*ner 61 python string list string-concatenation
由于我在这个帖子的回答中的评论,我想知道+=运营商和运营商之间的速度差异''.join()
那两者之间的速度比较是什么？
Dom*_*mra 85
来自:高效字符串连接
方法1:
def method1():
out_str = ''
for num in xrange(loop_count):
out_str += 'num'
return out_str
方法4:
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,并且第四种方法在迭代并加入每个项目之前附加到列表中,但这是一个公平的指示.
字符串连接比串联快得多.
为什么？字符串是不可变的,不能在适当的位置进行更改.要改变一个,需要创建一个新的表示(两者的串联).
- 从PEP 8开始:"例如,不要依赖CPython为a + = b或a = a + b形式的语句有效实现就地字符串连接.这些语句在Jython中运行得更慢.在库的性能敏感部分,应该使用'.join()形式.这将确保连接在各种实现中以线性时间发生." (9认同)
- -1.string.join和+ concatenation之间的速度差没有固定的比率,因为它们具有完全不同的**增长率**/大的复杂度.随着要连接的字符串数量的增长,与字符串连接相比,string.join将具有更大和更大的余量. (5认同)
- 好吧,我本来就是回答这个问题(因此标签),但看起来你打败了我!+1,特别是对于有用的链接! (3认同)
- @Wayne:*有用的链接*是从您链接到的问题中复制的! (2认同)
Jul*_*les 11
现有的答案写得非常好，经过研究，但这是 Python 3.6 时代的另一个答案，因为现在我们有了文字字符串插值（AKA，f-strings）：
>>> 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 款 Retina MacBook Pro 和 Intel Core i7 频率为 2.3 GHz 上执行的测试。
这绝不是任何正式的基准测试，但看起来使用f-strings 的性能与使用+=串联的性能大致相同；当然，欢迎任何改进的指标或建议。
- 请参阅类似问题的答案：/sf/answers/94520261/ += 不应使用，其性能提升是一种幻觉。 (2认同)
我的原始代码是错误的,似乎+连接通常更快(特别是在较新的硬件上使用较新版本的Python)
时间如下:
Iterations: 1,000,000
Windows 7,Core i7上的Python 3.3
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
Windows 7,Core i7上的Python 2.7
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上,Python 2.7,一些较慢的处理器
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
以下是代码:
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()