As a result of the comments in my answer on this thread, I wanted to know what the speed difference is between the += operator and ''.join()
So what is the speed comparison between the two?
From: Efficient String Concatenation
Method 1:
def method1(): out_str = '' for num in xrange(loop_count): out_str += 'num' return out_str Method 4:
def method4(): str_list = [] for num in xrange(loop_count): str_list.append('num') return ''.join(str_list) Now I realise they are not strictly representative, and the 4th method appends to a list before iterating through and joining each item, but it's a fair indication.
String join is significantly faster then concatenation.
Why? Strings are immutable and can't be changed in place. To alter one, a new representation needs to be created (a concatenation of the two).
My original code was wrong, it appears that + concatenation is usually faster (especially with newer versions of Python on newer hardware)
The times are as follows:
Iterations: 1,000,000 Python 3.3 on Windows 7, Core i7
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 Python 2.7 on Windows 7, Core i7
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 On Linux Mint, Python 2.7, some slower processor
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 And here is the code:
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() The existing answers are very well-written and researched, but here's another answer for the Python 3.6 era, since now we have literal string interpolation (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 Test performed using CPython 3.6.5 on a 2012 Retina MacBook Pro with an Intel Core i7 at 2.3 GHz.
This is by no means any formal benchmark, but it looks like using f-strings is roughly as performant as using += concatenation; any improved metrics or suggestions are, of course, welcome.
This is what silly programs are designed to test :)
Use plus
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" Output of:
Time to run Plusser = 1.16350010965 seconds Now with join....
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" Output Of:
Time to run Joiner = 21.3877386651 seconds So on python 2.6 on windows, I would say + is about 18 times faster than join :)
I rewrote the last answer, could jou please share your opinion on the way i tested?
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") NOTE: This example is written in Python 3.5, where range() acts like the former xrange()
The output i got:
Time to run Joiner = 27.086106206103153 seconds Time to run + = 69.79100515996426 seconds Personally i prefer ''.join([]) over the 'Plusser way' because it's cleaner and more readable.
来源：https://stackoverflow.com/questions/3055477/how-slow-is-pythons-string-concatenation-vs-str-join