timeit模块:
1) timeit.timeit(stmt=‘pass‘, setup=‘pass‘, timer=<defaulttimer>, number=1000000)
返回：返回执行stmt这段代码number遍所用的时间，单位为秒，float型
参数：stmt：要执行的那段代码
setup：执行代码的准备工作,初始化代码或构建环境导入语句,不计入时间，一般是import之类的
timer：这个在win32下是time.clock()，linux下是time.time()，默认的，不用管
number：要执行stmt多少遍
import timeit
print timeit.timeit("sum(x)","x=(i for i in range(100))")
0.114394682716
def test():
L = [i for i in range(100)]
#在setup中导入自定义函数
if __name__ == ‘__main__‘:
import timeit
print(timeit.timeit("test()", setup="from __main__ import test",number=10000))
0.0800761957937
2) repeat(stmt=‘pass‘, setup=‘pass‘, timer=<defaulttimer>, repeat=3, number=1000000)
这个函数比timeit函数多了一个repeat参数而已，表示重复执行timeit这个过程多少遍，返回一个列表，表示执行每遍的时间
当然，为了方便，python还用了一个Timer类，Timer类里面的函数跟上面介绍的两个函数是一样一样的
import timeit t = timeit.Timer(‘char in text‘, setup=‘text = "I love FishC.com!"; char = "o"‘) t.timeit() 0.054789127320191255 t.repeat() [0.05562128719998327, 0.046032358580077926, 0.044957160393096274]
3) timeit.default_timer()
默认的计时器
import timeit
s1=timeit.default_timer()
n=0
for i in range(101):
n+=i
d1=timeit.default_timer()
d1-s1
0.00017283636378806477
4)
Timer类，Timer类里面的函数跟上面介绍的两个函数是一样一样的
class timeit.Timer(stmt=‘pass‘, setup=‘pass‘,timer=<timer function>)
Timer.timeit(number=1000000)
Timer.repeat(repeat=3,number=1000000)
def test():
L = [i for i in range(100)]
timeObj=timeit.Timer(stmt="test()",setup="from __main__ import test")
print timeObj.timeit(number=2)
3.16114014822e-05
print timeObj.repeat(repeat=5)
[5.158685950990275, 4.8465939741281545, 4.779073662776227, 4.764550071228314, 4.747949980088833]
import timeit
import math
import pprint
def myfun():
for i in range(100):
for j in range(2, 10):
math.pow(i, 1/j)
n = 100
t1 = timeit.timeit(stmt=myfun, number=n)
pprint.pprint(t1)
t2 = timeit.repeat(stmt=myfun, number=n, repeat=5)
pprint.pprint(t2)
print()
timeitObj = timeit.Timer(stmt=myfun)
t3 = timeitObj.timeit(number=n)
pprint.pprint(t3)
t4 = timeitObj.repeat(number=n, repeat=5)
pprint.pprint(t4)
0.029213861394509877
[0.03452991382800974,
0.03289597385673915,
0.031878661483006,
0.03200839139026357,
0.03210733097148477]
()
0.021823362057602935
[0.024504583653197187,
0.02141200330106585,
0.02137833921096899,
0.021332358990548528,
0.022017956918261916]
5)命令行调用
python -m timeit [-n N] [-r N] [-s S] [-t] [-c] [-h] [statement...]
-n N 执行指定语句的次数
-r N 重复测量的次数(默认3次)
-s S 指定初始化代码活构建环境的导入语句(默认pass)
python 3.3新增
-t 使用time.time() (不推荐)
-c 使用time.clock() (不推荐)
-v 打印原始计时结果
-h 帮助
$ python -m timeit ‘"-".join(str(n) for n in range(100))‘ 10000 loops, best of 3: 40.3 usec per loop $ python -m timeit ‘"-".join([str(n) for n in range(100)])‘ 10000 loops, best of 3: 33.4 usec per loop $ python -m timeit ‘"-".join(map(str, range(100)))‘ 10000 loops, best of 3: 25.2 usec per loop