A Comprehensive Guide to Profiling Python Programs #Python @eyaltra @BttrProgramming
Eyal Trabelsi reviews the art of profiling Python programs. Profiling is understanding what parts of your code are problematic.
You must be asking yourself why should I even care about optimizing my code, my feature is already done. You should care about optimization because it affects our users and our company. These are the main reasons:
Fast programs are better than slow ones — whether latency or throughput.
Memory efficiency is good — Most of us are terrified of out-of-memory errors.
Saving money is awesome — If out-of-memory errors do not terrify you, your AWS bills might.
Hardware has limits— Even if we are willing to pay to improve performance, hardware will only take you so far.
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