python模塊:profile,pst
- 2020 年 1 月 8 日
- 筆記
profile和pstats是python代碼的分析器,可以很客觀查看代碼的運行質量和使用的資源.在調試程序時有很大的幫助.
1.使用profile分析python的代碼
[root@node1 tmp]# vim profile12.py
#!/bin/env python #!-*- coding:UTF-8 -*- import profile def one(): #定義一個one函數
sum=0 for i in range(10000): sum+=i return sum def two(): sum=0 for i in range(100000): sum+=i return sum def there(): sum=0 for i in range(100000): sum+=i return sum if __name__=="__main__": profile.run("one()","result") #將結果保存到result文件中
profile.run("two()") profile.run("there()") [root@node1 tmp]# python profile12.py 5 function calls in 0.010 CPU seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.003 0.003 0.003 0.003 :0(range) 1 0.000 0.000 0.000 0.000 :0(setprofile) 1 0.000 0.000 0.010 0.010 <string>:1(<module>) 1 0.007 0.007 0.010 0.010 profile12.py:12(two) 0 0.000 0.000 profile:0(profiler) 1 0.000 0.000 0.010 0.010 profile:0(two()) ncalls:函數調用的次數
tottime:函數的總的運行時間,除掉函數中調用子函數的運行時間
percall:(第一個 percall)等於tottime/ncalls
cumtime:函數及其所有子函數的調用運行的時間,即函數開始調用到返回的時間
percall:(第二個 percall)即函數運行一次的平均時間,等於 cumtime/ncalls
filename:lineno(function):每個函數調用的具體信息
5 function calls in 0.008 CPU seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.001 0.001 0.001 0.001 :0(range) 1 0.000 0.000 0.000 0.000 :0(setprofile) 1 0.000 0.000 0.008 0.008 <string>:1(<module>) 1 0.007 0.007 0.008 0.008 profile12.py:18(there) 0 0.000 0.000 profile:0(profiler) 1 0.000 0.000 0.008 0.008 profile:0(there()) Thu May 5 17:30:09 2016 result 5 function calls in 0.001 CPU seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.000 0.000 0.000 0.000 :0(range) 1 0.000 0.000 0.000 0.000 :0(setprofile) 1 0.000 0.000 0.001 0.001 <string>:1(<module>) 1 0.001 0.001 0.001 0.001 profile12.py:6(one) 1 0.000 0.000 0.001 0.001 profile:0(one()) 0 0.000 0.000 profile:0(profiler) [root@node1 tmp]#
2.使用pstats分析python代碼
[root@node1 tmp]# vim profile12.py
#!/bin/env python #!-*- coding:UTF-8 -*- import profile,pstats def one(): sum=0 for i in range(10000): sum+=i return sum if __name__=="__main__": profile.run("one()","result") #將結果保存到result文件中
p=pstats.Stats("result") #創建一上pstats變量 p.strip_dirs().sort_stats(-1).print_stats() #strip_dirs:從所有模塊名中去掉無關的路徑信息
p.strip_dirs().sort_stats("name").print_stats() #sort_stats():把打印信息按照標準的module/name/line字符串進行排序
p.strip_dirs().sort_stats("cumulative").print_stats(3) #print_stats():打印出所有分析信息
[root@node1 tmp]# python profile12.py Thu May 5 17:54:49 2016 result 5 function calls in 0.001 CPU seconds Ordered by: standard name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.000 0.000 0.000 0.000 :0(range) 1 0.000 0.000 0.000 0.000 :0(setprofile) 1 0.000 0.000 0.001 0.001 <string>:1(<module>) 1 0.001 0.001 0.001 0.001 profile12.py:6(one) 1 0.000 0.000 0.001 0.001 profile:0(one()) 0 0.000 0.000 profile:0(profiler) Thu May 5 17:54:49 2016 result 5 function calls in 0.001 CPU seconds Ordered by: function name ncalls tottime percall cumtime percall filename:lineno(function) 1 0.000 0.000 0.001 0.001 <string>:1(<module>) 1 0.001 0.001 0.001 0.001 profile12.py:6(one) 1 0.000 0.000 0.001 0.001 profile:0(one()) 0 0.000 0.000 profile:0(profiler) 1 0.000 0.000 0.000 0.000 :0(range) 1 0.000 0.000 0.000 0.000 :0(setprofile) Thu May 5 17:54:49 2016 result 5 function calls in 0.001 CPU seconds Ordered by: cumulative time List reduced from 6 to 3 due to restriction <3> ncalls tottime percall cumtime percall filename:lineno(function) 1 0.001 0.001 0.001 0.001 profile12.py:6(one) 1 0.000 0.000 0.001 0.001 profile:0(one()) 1 0.000 0.000 0.001 0.001 <string>:1(<module>) [root@node1 tmp]#
