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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 how you can speed up your Python code in general, we will dig into source code optimization. I will show you some simple and fast ways of measuring the execution time of your code, and then we will discuss examples of how to improve some common code structures.
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
Sebastian Witowski
Sebastian is a Python consultant based in Poland. He started his journey with programming as a software developer at CERN, where he fell in love with Python (and teaching). Now he is helping companies untangle their complicated architecture and build all sorts of interesting Python projects.
In his spare time, he talks about Python, best practices in programming, and productivity.