Python line_profiler code example

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陌清茗
陌清茗 2020-12-02 19:31

I am trying to figure out how I can run Python\'s line_profiler to get the line by line execution times in the format given in the answer to this question.

I install

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  • 2020-12-02 19:40

    As described in the documentation:

    in your script, you can decorate any function you want to profile with @profile

    You want to decorate your do_stuff function with @profile and then run

    kernprof.py -v -l script_to_profile.py
    

    to get the annotated output printed to your terminal. The profile will also be written to script_to_profile.py.lprof and you can re-create the output later with

    python -m line_profiler script_to_profile.py.lprof
    
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  • 2020-12-02 19:57

    The line_profiler test cases (found on GitHub) have an example of how to generate profile data from within a Python script. You have to wrap the function that you want to profile and then call the wrapper passing any desired function arguments.

    from line_profiler import LineProfiler
    import random
    
    def do_stuff(numbers):
        s = sum(numbers)
        l = [numbers[i]/43 for i in range(len(numbers))]
        m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    
    numbers = [random.randint(1,100) for i in range(1000)]
    lp = LineProfiler()
    lp_wrapper = lp(do_stuff)
    lp_wrapper(numbers)
    lp.print_stats()
    

    Output:

    Timer unit: 1e-06 s
    
    Total time: 0.000649 s
    File: <ipython-input-2-2e060b054fea>
    Function: do_stuff at line 4
    
    Line #      Hits         Time  Per Hit   % Time  Line Contents
    ==============================================================
         4                                           def do_stuff(numbers):
         5         1           10     10.0      1.5      s = sum(numbers)
         6         1          186    186.0     28.7      l = [numbers[i]/43 for i in range(len(numbers))]
         7         1          453    453.0     69.8      m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    

    Adding Additional Functions to Profile

    Also, you can add additional functions to be profiled as well. For example, if you had a second called function and you only wrap the calling function, you'll only see the profile results from the calling function.

    from line_profiler import LineProfiler
    import random
    
    def do_other_stuff(numbers):
        s = sum(numbers)
    
    def do_stuff(numbers):
        do_other_stuff(numbers)
        l = [numbers[i]/43 for i in range(len(numbers))]
        m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    
    numbers = [random.randint(1,100) for i in range(1000)]
    lp = LineProfiler()
    lp_wrapper = lp(do_stuff)
    lp_wrapper(numbers)
    lp.print_stats()
    

    The above would only produce the following profile output for the calling function:

    Timer unit: 1e-06 s
    
    Total time: 0.000773 s
    File: <ipython-input-3-ec0394d0a501>
    Function: do_stuff at line 7
    
    Line #      Hits         Time  Per Hit   % Time  Line Contents
    ==============================================================
         7                                           def do_stuff(numbers):
         8         1           11     11.0      1.4      do_other_stuff(numbers)
         9         1          236    236.0     30.5      l = [numbers[i]/43 for i in range(len(numbers))]
        10         1          526    526.0     68.0      m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    

    In this case, you can add the additional called function to profile like this:

    from line_profiler import LineProfiler
    import random
    
    def do_other_stuff(numbers):
        s = sum(numbers)
    
    def do_stuff(numbers):
        do_other_stuff(numbers)
        l = [numbers[i]/43 for i in range(len(numbers))]
        m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    
    numbers = [random.randint(1,100) for i in range(1000)]
    lp = LineProfiler()
    lp.add_function(do_other_stuff)   # add additional function to profile
    lp_wrapper = lp(do_stuff)
    lp_wrapper(numbers)
    lp.print_stats()
    

    Output:

    Timer unit: 1e-06 s
    
    Total time: 9e-06 s
    File: <ipython-input-4-dae73707787c>
    Function: do_other_stuff at line 4
    
    Line #      Hits         Time  Per Hit   % Time  Line Contents
    ==============================================================
         4                                           def do_other_stuff(numbers):
         5         1            9      9.0    100.0      s = sum(numbers)
    
    Total time: 0.000694 s
    File: <ipython-input-4-dae73707787c>
    Function: do_stuff at line 7
    
    Line #      Hits         Time  Per Hit   % Time  Line Contents
    ==============================================================
         7                                           def do_stuff(numbers):
         8         1           12     12.0      1.7      do_other_stuff(numbers)
         9         1          208    208.0     30.0      l = [numbers[i]/43 for i in range(len(numbers))]
        10         1          474    474.0     68.3      m = ['hello'+str(numbers[i]) for i in range(len(numbers))]
    

    NOTE: Adding functions to profile in this way does not require changes to the profiled code (i.e., no need to add @profile decorators).

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