Shulou(Shulou.com)06/02 Report--

In this issue, the editor will bring you about how to use the Dis module to analyze code performance in python. The article is rich in content and analyzed and described from a professional point of view. I hope you can get something after reading this article.

It's hard to figure out if you're not that good, but we can easily find the answer using the Dis module:

Results:

The results of Dis are actually easy to read:

First column: the corresponding number of lines of source code.

The second column: the index location of the corresponding memory bytecode.

The third column: the operation of internal machine code.

The fourth column: instruction parameters.

The fifth column: actual parameters.

The dis analysis of the two functions is separated by a * sign, and you can clearly see the difference between the statements between the two functions. The bytecode index of the second function is up to 30, while the bytecode index of the first function is only 22, so the first function consumes less memory than the second function.

Also, the > > sign between the first column and the second column indicates the target of the jump. You can look at 18 in the fourth column of the second function, indicating that it jumps to the instruction with index 18, that is, ROT_TWO. The second function also jumps more than the first function, which may also cause it to be less efficient than the first function in some special cases.

This is how to use the Dis module to analyze code performance in python shared by Xiaobian. If you happen to have similar doubts, you might as well refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.

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