Quickly profile your Python code

Quickly profile your Python code

Profiling using a decorator:

Given some Python function for which profiling is required, add this decorator definition to the script:

def profile(profiled_func):
    
    def wrap(*args, **kwargs):
        import cProfile
        pr = cProfile.Profile()
        pr.enable()

        result = profiled_func(*args, **kwargs)

        pr.disable()
        pr.print_stats(sort='time')
        return result
    
    return wrap

Then, upon the definition of the function one wants to profile, just decorate it:

@profile
def some_fun():
	pass

Upon running the script, the output will include the following:

• ncalls is the number of calls made.
• tottime is a total of the time spent in the function/method excluding the time spent in the functions/methods that it calls.
• percall refers to the quotient of tottime divided by ncalls
• cumtime is the cumulative time spent in this and all subfunctions. It’s even accurate for recursive functions!
• The second percall column is the quotient of cumtime divided by primitive calls
• filename:lineno(function) provides the respective data of each function

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