从range和xrange的性能对比到yield关键字(上)

使用xrange

 

当我们获取某个数量的循环时,我们惯用的手法是for循环和range函数,例如:

for i in range(10):
    print i

这里range(10)生成了一个长度为10的列表,内容为从0到9,所以这里的for循环实际上是在遍历其中的元素。

如果循环次数过大的时候,range要生成一个巨大的列表,这将导致程序的性能降低。

解决方案是采用xrange,用法基本与range相同:

for i in xrange(10):
    print i

但是二者的性能差距到底有多大?

 

性能测评

 

我们使用下面的程序做一个测试:

from time import time
from time import sleep
import sys

def count_time():
    def tmp(func):
        def wrapped(*args, **kargs):
            begin_time = time()
            result = func(*args, **kargs)
            end_time = time()
            cost_time = end_time - begin_time
            print '%s called cost time : %s ms' %(func.__name__, float(cost_time)*1000)
            return result
        return wrapped
    return tmp

@count_time()
def test1(length):
    for i in range(length):
        pass

@count_time()
def test2(length):
    for i in xrange(length):
        pass

if __name__ == '__main__':
    length = int(sys.argv[1])
    test1(length)
    test2(length)

上面的代码中,count_time是一个装饰器,用于统计程序运行的时间。

我们下面开始正式的测试:

wing@ubuntu:~/Documents/py|⇒  python 10.py 100000
test1 called cost time : 13.8590335846 ms
test2 called cost time : 3.76796722412 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 100000
test1 called cost time : 16.725063324 ms
test2 called cost time : 3.08418273926 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 200000
test1 called cost time : 34.875869751 ms
test2 called cost time : 7.85899162292 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 500000
test1 called cost time : 41.6638851166 ms
test2 called cost time : 17.1940326691 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 500000
test1 called cost time : 59.8731040955 ms
test2 called cost time : 14.0538215637 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 500000
test1 called cost time : 94.1109657288 ms
test2 called cost time : 8.5780620575 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 500000
test1 called cost time : 61.615228653 ms
test2 called cost time : 7.21502304077 ms

结果令我们大吃一惊,二者的差距非常明显,最高的时候差距了十几倍。

我们再选取几个较小的数据:

wing@ubuntu:~/Documents/py|⇒  python 10.py 10    
test1 called cost time : 0.00596046447754 ms
test2 called cost time : 0.0109672546387 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 20
test1 called cost time : 0.00619888305664 ms
test2 called cost time : 0.159025192261 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 50
test1 called cost time : 0.00786781311035 ms
test2 called cost time : 0.00405311584473 ms
wing@ubuntu:~/Documents/py|⇒  python 10.py 100
test1 called cost time : 0.00786781311035 ms
test2 called cost time : 0.00309944152832 ms

这次range的性能并不差,甚至开始还略显高。

我们可以得出结论,当n较小时,我们使用range,但当i超过一定范围时,我们就必须考虑使用xrange了

但是,二者性能差距的原因在哪里?

我们下文分析。

posted on 2015-01-11 19:04  inevermore  阅读(243)  评论(0编辑  收藏  举报