Py性能分析示例

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#!/usr/bin/python
import time
def timefunc(f):    
    def f_timer(*args, **kwargs):
        start = time.time()
        result = f(*args, **kwargs)
        end = time.time()        
        print f.__name__, 'took', end - start, 'time'        
        return result    
    return f_timer


@timefunc
def test():
    for i in xrange(100):
        print i

test()

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import timeit
timeit.timeit(stmt='pass', setup='pass', timer=<default timer>, number=1000000)

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#!/usr/bin/python
import timeit
def test():
    for i in xrange(1000):
        print i
    
if __name__ == '__main__':
    timeit.timeit('test()', setup='from __main__ import test', number=1)

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/usr/bin/time -f "Memory: %M bytes" python script.py

Time using for-loop: 0.155635 seconds 
Memory: 66212 bytes

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import line_profiler
import sys

def fib(n):
    a, b = 0, 1
    for i in range(0, n):
        a, b = b, a + b
        return a


prof = line_profiler.LineProfiler(fib)
prof.enable()
fib(100)
prof.disable()
prof.print_stats(sys.stdout)

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class Foobar(object):
    def __init__(self, x):
    self.x = x
    
@profile 
def main():
    f = [ Foobar(i) for i in range(100000) ]
if __name__ == '__main__':
    main()

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>>> def x():
...     return 42 
...
>>> import dis
>>> dis.dis(x) 
2   0 LOAD_CONST     1 (42)
    3 RETURN_VALUE  

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import cProfile
import pstats
import os
def do_cprofile(func):
    def wrapper(*args, **kwargs):
        profile = cProfile.Profile()
        # 开始收集性能分析数据
        profile.enable()
        result = func(*args, **kwargs)
        # 停止收集性能分析数据
        profile.disable()
        # Sort stat by internal time.
        sortby = "tottime"
        # 对报告列表进行排序
        ps = pstats.Stats(profile).sort_stats(sortby)
        # 把信息打印到标准输出
        ps.print_stats()
        return result
    return wrapper
    
    
@do_cprofile 
def test():
    for i in range(100):
        print(i)

if __name__ == '__main__':
    test()