How slow is Python's string concatenation vs. str.join?

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 secondsString of len:   4 took:     0.9480     0.5830 secondsString of len:   6 took:     1.2770     0.8130 secondsString of len:  12 took:     2.0610     1.5930 secondsString of len:  80 took:    10.5140    37.8590 secondsString of len: 222 took:    27.3400   134.7440 secondsString 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 secondsString of len:   4 took:     1.0660     0.6920 secondsString of len:   6 took:     1.3300     0.8560 secondsString of len:  12 took:     1.9980     1.5330 secondsString of len:  80 took:     9.0520    25.7190 secondsString of len: 222 took:    23.1620    71.3620 secondsString 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 secondsString of len:   4 took:     2.8394     1.9663 secondsString of len:   6 took:     3.5177     2.4162 secondsString of len:  12 took:     5.5456     4.1695 secondsString of len:  80 took:    27.8813    19.2180 secondsString of len: 222 took:    69.5679    55.7790 secondsString of len: 443 took:   135.6101   153.8212 seconds

And here is the code:

from __future__ import print_functionimport timedef strcat(string):    newstr = ''    for char in string:        newstr += char    return newstrdef 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.