Source code level optimization is often neglected - people don’t bother, because getting a faster server often gives better results. But if you - like me - always wonder what is the most efficient way to write some code, then this talk is for you!
Abstract
Did you know that Python preallocates integers from -5 to 257? Reusing them 1000 times, instead of allocating memory for a bigger integer, can save you a couple milliseconds of code’s execution time. If you want to learn more about this kind of optimizations then, … well, probably this presentation is not for you :) Instead of going into such small details, I will talk about more “sane” ideas for writing faster code.
After a brief overview of different levels of optimization and how they work in Python, I will show you simple and fast ways of measuring the execution time of your code and finally, discuss examples of how some code structures could be improved.
You will see:
- The fastest way of removing duplicates from a list
- How much faster your code is when you reuse the built-in functions instead of trying to reinvent the wheel
- What is faster than the “for loop”
- If the lookup is faster in a list or a set
- When it’s better to beg for forgiveness than to ask for permission
