Contents
Py vs Perl 运行
俊杰蔡 <[email protected]> reply-to [email protected], to [email protected], date Thu, Apr 3, 2008 at 5:50 PM subject [CPyUG:45860]
- 从以下对比得出
- （a）random.random()函数比random.randrange()函数快。
- （b）xrange不一定比range快。
- （c）使用StringIO缓存全部内容，一下子写也不一定快。
- （d）write() 块写效率会提高。
- （e）print 到文件句柄 写效率也不错高
- （f）脚本越短，引用的模块越少效率好
ZoomQuiet 测试环境:
- HP 520 笔记本电脑 (GQ349AA)
- 英特尔® 酷睿™ 双核处理器 T2300E 1.66GHz , 2MB 二级高速缓存, 667MHz FSB
- 内存 2Gb
time vs 0.1
5" random.pl
#!/usr/bin/perl -w
use strict;
open (WW,"> 500000") or die "$!";
foreach(1..5000000){
my $i = int(rand 10000000) % 3;
print WW $i."\n";
}
close WW;
31" random.py
1 import random
2 import time
3
4 __revision__ = '0.1'
5
6 def test():
7 fh = open("test_cjj","w")
8
9 for i in range(5000000):
10 data = random.randrange(1000000,9999999,1)
11 yu = data % 3
12 fh.write(str(yu)+"\n")
13
14 fh.close()
15
16 if __name__ == "__main__" :
17 test()
time vs 0.2
48" random0.2.py
1 import cStringIO as StringIO
2
3 import random
4 import time
5
6 __revision__ = '0.2'
7
8 def test():
9 fh = open("test_cjj0.2","w")
10 output = StringIO.StringIO()
11
12 for i in xrange(5000000):
13
14 data = random.randrange(1000000,9999999,1)
15 yu = data % 3
16 print >>output, yu
17
18 fh.write(output.getvalue())
19
20 fh.close()
21
22 if __name__ == "__main__" :
23 test()
time vs 0.3
33" random0.3.py
1 import random
2 import time
3
4 __revision__ = '0.3'
5
6 def test():
7 exp = ""
8 for i in xrange(5000000):
9 data = random.randrange(1000000,9999999,1)
10 exp += "%s\n"%(str(data % 3))
11
12 open("test_cjj0.3","w").write(exp)
13 if __name__ == "__main__" :
14 test()
time vs 0.4
27" random0.4.py
1 import random
2 __revision__ = '0.4'
3
4 fn = open("test_cjj0.4","w")
5 for i in xrange(5000000):
6 data = random.randrange(1000000,9999999,1)
7 print >> fn, (data % 3)
time vs 0.5
51" random0.5.py
1 import cStringIO as StringIO
2 import random
3 __revision__ = '0.5'
4
5 #fn = open("test_cjj0.4","w")
6 out = StringIO.StringIO()
7 for i in xrange(5000000):
8 data = random.randrange(1000000,9999999,1)
9 print >> out, (data % 3)
10
11 open("test_cjj0.5","w").write(out.getvalue())
time vs 0.6
26" random0.6.py
1 import random
2 __revision__ = '0.6'
3
4 fn = open("test_cjj0.6","w")
5 for i in xrange(5000000):
6 print >> fn, (random.randrange(1000000,9999999,1))% 3
time vs 0.7
10" random0.7.py
1 from random import random
2 __revision__ = '0.7'
3
4 fh = open("test_cjj0.7","w")
5 for i in range(5000000):
6 print >> fh,(int(random()*(9999999-1000000)+1000000))% 3
time vs 0.8
5" random0.8.py
1 from random import random
2
3 __revision__ = '0.8'
4
5 def test():
6 fh = open("test_cjj0.8","w")
7 for i in range(5000000):
8 print >> fh,(int(random()*(9999999-1000000)+1000000))% 3
9
10 if __name__ == "__main__" :
11 try:
12 import psyco
13 psyco.full()
14 except ImportError:
15 pass
16 test()
time vs 0.9
- 使用 pysco 前后的差异
15~11" random0.9.py
1 from random import random
2 __revision__ = '0.9'
3
4 def test():
5 five_million = 5000000
6 fh = open("test_cjj0.9","w")
7 for i in xrange(five_million):
8 data = int(random()*(9999999))
9 yu = data % 3
10 fh.write('%d\n' % yu)
11 fh.close()
12
13 if __name__ == "__main__" :
14 try:
15 import psyco
16 psyco.full()
17 except ImportError:
18 pass
19 test()
time vs 1.0
- 是否打开 pysco 的对比
- 使用迭代后,进行 pysco 加速反而无益
9~10" random1.0.py
#!pythonfrom random import random (-)
__revision__ = '1.0'
def gen_yu():
for i in xrange(5000000):
data = int(random()*(9999999))
yu = data % 3
yield yu
def test():
fh = open("test_cjj1.0","w")
content = '\n'.join([str(m) for m in gen_yu()])
fh.write(content)
fh.close()
if __name__ == "__main__" :
#'''
try:
import psyco
psyco.full()
except ImportError:
pass
#'''
test()
time vs end
俊杰蔡 <[email protected]> reply-to [email protected], to [email protected], date Sat, Apr 5, 2008 at 2:03 AM subject [CPyUG:45963] Re: 一段python程序的效率问题
Python 脚本胶水威力!
1" a.py
cjj.c：
#!cpp (-)
#include <stdio.h>
void amaze()
{
FILE *fp;
int i,num;
fp = fopen("test_cjj","w");
for(i=0;i<5000000;i++)
{
num = (rand()%9000000+1000000) % 3;
fprintf(fp,"%d\n",num);
}
fclose(fp);
}
cjj.i：
%module cjj
%{
extern void amaze();
%}
extern void amaze();
编译
swig -python cjj.i \ gcc -c cjj.c cjj_wrap.c -I/usr/include/python2.5 \ ld -shared cjj.o cjj_wrap.o -o _cjj.so
a.py：
1 import cjj
2 __revision__ = '0.1'
3
4 if __name__ == "__main__" :
5 try:
6 import psyco
7 psyco.full()
8 except ImportError:
9 pass
10 cjj.amaze()
运行
$time ./a.py real 0m1.271s user 0m1.228s sys 0m0.036s
反馈
创建 by -- ZoomQuiet [2008-04-03 13:26:48]