The Right Way to Compare Floats in Python

Learn why floating-point errors are common, why they make sense, and how to deal with them in Python

Floating-point numbers are a fast and efficient way to store and work with numbers, but they come with a range of pitfalls that have surely stumped many fledgling programmers — perhaps some experienced programmers, too! The classic example demonstrating the pitfalls of floats goes like this:

Seeing this for the first time can be disorienting. But don’t throw your computer in the trash bin. This behavior is correct!

This article will show you why floating-point errors like the one above are common, why they make sense, and what you can do to deal with them in Python.

Your Computer is a Liar (Sort Of)

You’ve seen that 0.1 + 0.2 is not equal to 0.3 but the madness doesn't stop there. Here are some more confounding examples: