導讀

相信日常使用Python作為生產力的讀者，一定會存在想要分析程式碼中每一行的執行時間與變數佔用記憶體大小的需求，本文主要分析兩個模組，用於分析每行程式碼的記憶體使用情況和執行時間情況。

記憶體使用

• memory-profiler

安裝

pip install memory-profiler

使用方法一

1. 在需要分析的函式上，新增裝飾器@profile

@profile
def test1():
	c=0
	for item in xrange(100000):
 		c+=1
 	print (c)
        

2. 使用下面的命令執行

python -m memory_profiler memory_profiler_test.py     
 

使用方法二

 from memory_profiler import profile
 
 @profile(precision=4,stream=open('memory_profiler.log','w+'))
# @profile
def test1():
     c=0
     for item in xrange(100000):
         c+=1
     print c

# 直接執行即可    

結果

Filename: memory_profiler_test.py

Line #    Mem usage    Increment   Line Contents
================================================
     5   21.492 MiB   21.492 MiB   @profile
     6                             def test1():
     7   21.492 MiB    0.000 MiB       c=0
     8   21.492 MiB    0.000 MiB       for item in xrange(100000):
     9   21.492 MiB    0.000 MiB           c+=1
    10   21.492 MiB    0.000 MiB       print c
 

• Mem usage: 記憶體佔用情況
• Increment: 執行該行程式碼後新增的記憶體

執行時間

• line-profiler

安裝

pip install line-profiler

使用

1. 在需要分析的函式上，新增裝飾器@profile

@profile
def slow_function(a, b, c):
    ...

2. 執行

python -m line_profiler script_to_profile.py.lprof

結果

Pystone(1.1) time for 50000 passes = 2.48
This machine benchmarks at 20161.3 pystones/second
Wrote profile results to pystone.py.lprof
Timer unit: 1e-06 s

File: pystone.py
Function: Proc2 at line 149
Total time: 0.606656 s

Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
   149                                           @profile
   150                                           def Proc2(IntParIO):
   151     50000        82003      1.6     13.5      IntLoc = IntParIO + 10
   152     50000        63162      1.3     10.4      while 1:
   153     50000        69065      1.4     11.4          if Char1Glob == 'A':
   154     50000        66354      1.3     10.9              IntLoc = IntLoc - 1
   155     50000        67263      1.3     11.1              IntParIO = IntLoc - IntGlob
   156     50000        65494      1.3     10.8              EnumLoc = Ident1
   157     50000        68001      1.4     11.2          if EnumLoc == Ident1:
   158     50000        63739      1.3     10.5              break
   159     50000        61575      1.2     10.1      return IntParIO
 

• 每列含義

> - Line #: The line number in the file.
> - Hits: The number of times that line was executed.
> - Time: The total amount of time spent executing the line in the timer's units. In the header information before the tables, you will see a line "Timer unit:" giving the conversion factor to seconds. It may be different on different systems.
> - Per Hit: The average amount of time spent executing the line once in the timer's units.
> - % Time: The percentage of time spent on that line relative to the total amount of recorded time spent in the function.
> - Line Contents: The actual source code. Note that this is always read from disk when the formatted results are viewed, *not* when the code was executed. If you have edited the file in the meantime, the lines will not match up, and the formatter may not even be able to locate the function for display.

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本文由mdnice多平臺釋出