Data scientists, statisticians, analysts, researchers, and many other professionals write a lot of code.
Not only do they write a lot of code, but they must also read and review a lot of code as well. They either work in teams and need to review each other’s code, or need to be able to reproduce results from past projects, be it for peer review or auditing purposes. And yet, they never, or very rarely, get taught the tools and techniques that would make the process of writing, collaborating, reviewing and reproducing projects possible.
Which is truly unfortunate because software engineers face the same challenges and solved them decades ago.
The aim of this book is to teach you how to use some of the best practices from software engineering and DevOps to make your projects robust, reliable and reproducible. It doesn’t matter if you work alone, in a small or in a big team. It doesn’t matter if your work gets (peer-)reviewed or audited: the techniques presented in this book will make your projects more reliable and save you a lot of frustration!
As someone whose primary job is analysing data, you might think that you are not a developer. It seems as if developers are these genius types that write extremely high-quality code and create these super useful packages. The truth is that you are a developer as well. It’s just that your focus is on writing code for your purposes to get your analyses going instead of writing code for others. Or at least, that’s what you think. Because in others, your team-mates are included. Reviewers and auditors are included. Any people that will read your code are included, and there will be people that will read your code. At the very least future you will read your code. By learning how to set up projects and write code in a way that future you will understand and not want to murder you, you will actually work towards improving the quality of your work, naturally.
The book can be read for free on https://raps-with-r.dev and you can buy a DRM-free Epub or PDF on Leanpub1.
You can also buy a physical copy of the book on Amazon.
You can submit issues, PRs and ask questions on the book’s Github repository2.
Date: 19.07.2023