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This article mainly explains "python how to use cProfile for performance analysis of back test", the content of the article is simple and clear, easy to learn and understand, now please follow the editor's train of thought slowly in depth, together to study and learn "python how to use cProfile for back test performance analysis"!

Installation

There is no need to install, python usually comes with it.

Use

There are several ways to use it, and I output it directly. Is to put the test back code in a method, such as runBackTesting (). Then the main method runs according to the following code, which is sorted by cumulative time. Hint, it is best to comment out the Matplot image output, because the interaction time is also statistical.

If _ _ name__ = ='_ main__': cProfile.run ("runBackTesting ()", sort= "cumulative") performance analysis results

As shown in the following figure

The first line is the total number of function calls and the total elapsed time

The description of the following column

Ncalls: indicates the number of times a function is called

Tottime: indicates the total running time of the specified function, excluding the running time of the calling subfunction in the function

Percall: (the first percall) equals tottime/ncalls

Cumtime: indicates the time that the call to the function and all its subfunctions runs, that is, the time from the start of the call to the return of the function

Percall: (the second percall) is the average time for a function to run once, which is equal to cumtime/ncalls

Filename:lineno (function): the specific information of each function call; it is preceded by the file name, the number of lines, followed by the method name, and some methods, such as max,min, do not have a file name.

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