元ネタ
1はできるlistが違うから比較として不適切では? そしてpypyを使うのがいろいろ解決してしまうこともある | あなたのPythonを爆速にする７つの方法 http://t.co/0lWErBIzU4
— Yuichiro Fukubayashi (@fukubaya) 2015, 5月 8あと時間計測ならば1回だけじゃなくて，何回か実行した平均を取った方がいい．
条件を揃えてやってみた
全要素が0のリストの生成
- 空の配列に1つずつ0をappend (list_0_append)
- リスト内包表記 (list_0_comp)
- 乗算 (list_0_multi)
- array (list_0_array)
- rangeで作ったリストに0を代入 (list_0_range)
要素が[0, 1, ..., n-1]のリストの生成
- 空の配列に1つずつ数値をappend (list_i_append)
- リスト内包表記 (list_i_comp)
- 全0のリストを作ったあとに代入 (list_i_multi)
- array (list_i_array)
- range (list_i_range)
実証スクリプト
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| #!/usr/bin/python | |
| # -*- coding: utf-8 -*- | |
| # | |
| # bench.py | |
| # | |
| # Created by FUKUBAYASHI Yuichiro on 2015/05/09 | |
| # Copyright (c) 2015, FUKUBAYASHI Yuichiro | |
| # | |
| # last update: <2015/05/09 02:42:22> | |
| # | |
| import sys | |
| from optparse import OptionParser | |
| import time | |
| from array import array | |
| # list all 0 | |
| def list_0_append(n): | |
| xs = [] | |
| for i in xrange(n): | |
| xs.append(0) | |
| return xs | |
| def list_0_comp(n): | |
| return [0 for i in xrange(n)] | |
| def list_0_multi(n): | |
| return [0] * n | |
| def list_0_array(n): | |
| return array('I', [0 for i in xrange(n)]) | |
| def list_0_range(n): | |
| xs = range(n) | |
| for i in xrange(n): | |
| xs[i] = 0 | |
| return xs | |
| # list i | |
| def list_i_append(n): | |
| xs = [] | |
| for i in xrange(n): | |
| xs.append(i) | |
| return xs | |
| def list_i_comp(n): | |
| return [i for i in xrange(n)] | |
| def list_i_multi(n): | |
| xs = [0] * n | |
| for i in xrange(n): | |
| xs[i] = i | |
| return xs | |
| def list_i_array(n): | |
| return array('I', [i for i in xrange(n)]) | |
| def list_i_range(n): | |
| return range(n) | |
| # measure exec time | |
| def exec_time(n, n_sample, func): | |
| t = 0.0 | |
| for i in range(n_sample): | |
| start = time.clock() | |
| func(n) | |
| end = time.clock() | |
| t += (end - start) | |
| return t / n_sample | |
| def main(options, args): | |
| n = options.n | |
| n_sample = 5 | |
| print "--Python version--" | |
| print sys.version | |
| print "--list_0--" | |
| for f in [list_0_append, | |
| list_0_comp, | |
| list_0_multi, | |
| list_0_array, | |
| list_0_range]: | |
| print "%s(%d) in %f(s)" % (f.__name__, | |
| n, | |
| exec_time(n, n_sample, f)) | |
| print "--list_i--" | |
| for f in [list_i_append, | |
| list_i_comp, | |
| list_i_multi, | |
| list_i_array, | |
| list_i_range]: | |
| print "%s(%d) in %f(s)" % (f.__name__, | |
| n, | |
| exec_time(n, n_sample, f)) | |
| if __name__ == '__main__': | |
| parser = OptionParser() | |
| parser.add_option('-n', action='store', type='int', default=10000) | |
| options, args = parser.parse_args() | |
| main(options, args) |
結果
% python bench.py -n 1000000 --Python version-- 2.7.9 (v2.7.9:648dcafa7e5f, Dec 10 2014, 10:10:46) [GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] --list_0-- list_0_append(1000000) in 0.229992(s) list_0_comp(1000000) in 0.087843(s) list_0_multi(1000000) in 0.016838(s) list_0_array(1000000) in 0.212526(s) list_0_range(1000000) in 0.175999(s) --list_i-- list_i_append(1000000) in 0.241931(s) list_i_comp(1000000) in 0.112636(s) list_i_multi(1000000) in 0.155012(s) list_i_array(1000000) in 0.237255(s) list_i_range(1000000) in 0.050963(s)
全要素0であっても乗算が一番速かった． [0, 1,...,n-1]の場合は，乗算よりリスト内包表記の方が速い．が，range(n)の方がもっと速かった．
pypyでもやってみた
pypy bench.py -n 1000000 --Python version-- 2.7.9 (9c4588d731b7, Mar 23 2015, 16:20:40) [PyPy 2.5.1 with GCC 4.2.1 Compatible Apple LLVM 6.0 (clang-600.0.57)] --list_0-- list_0_append(1000000) in 0.152410(s) list_0_comp(1000000) in 0.014103(s) list_0_multi(1000000) in 0.010896(s) list_0_array(1000000) in 0.022531(s) list_0_range(1000000) in 0.022315(s) --list_i-- list_i_append(1000000) in 0.143897(s) list_i_comp(1000000) in 0.014448(s) list_i_multi(1000000) in 0.016995(s) list_i_array(1000000) in 0.023090(s) list_i_range(1000000) in 0.000005(s)
CPythonよりだいぶ速い．list_i_rangeは異常 (笑)．
結論
全要素同じの場合は乗算，[0, 1,...,n-1]ならばrangeが速い． そしてpypy超速い (もちろんメモリやCPUの使い方まで比較してないので一概にpypyがいいとは言えない)．