Scientific Computing (for the rest of us)

One specific challenge, when writing code as a scientist, is that we care alot about getting the right answer; but of course, the right answer is notalways obvious. So we should be very careful with the code we write. A piece ofcode that crashes is annoying; but a piece of code that runs, and give you thewrong answer can compromise your science and your career. This guide will helpyou adopt practices that make it less likely to introduce mistakes in your code,and more likely to catch them. Hopefully, this will let all of us write code wecan trust more.

Good principles in scientific computing can help you write code that is easierto maintain, easier to reproduce, and easier to debug. But it can be difficultto find an introduction to get you started. The goal of this project is to getyou started on the most important points. You can use these lessons on your own,or as a group.

This material is aimed at people who have already interacted with a computerusing a programming language (we use Julia, but the code is meant to be fairlygeneral), but want to adopt best practices that make their code more robust. Itcan also be used to facilitate the onboarding of new people in your lab or yourproject.