Writing faster Python

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 of 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 very brief overview of how to optimize Python code (rule 1: don’t do this, rule 2: don’t do this yet, rule 3: ok, but what if I really want to do this ?), I will show simple and fast ways of measuring the execution time and finally, discuss examples of how some code structures could be improved. You will see:

• What is 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 good ol’ for loop
• If the lookup is faster in a list or a set (and when it makes sense to use each)
• How the “It’s better to beg for forgiveness than to ask for permission” rule works in practice

I will NOT go into details of "serious" optimization, like using different Python implementation or rewriting critical code in C, etc.