Robust Python

Part IV. Building a Safety Net

Welcome to Part IV of the book, which is about the importance of building a safety net around your codebase. Think about a tightrope walker perilously balanced, high in the air. No matter how many times the performer has practiced their routine, there is always a set of safety precautions should the worst happen. The tightrope walker can perform their act with confidence, trusting in the fact that something will break their fall if they slip. You want to provide your fellow collaborators with the same sort of confidence and trust as they work in your codebase.

Even if your code is completely error free, how long will it stay that way? Every change introduces risk. Every new developer coming into a codebase will take time before fully understanding all of its intricacies. Customers will change their minds and ask for the complete opposite of what they asked for six months ago. This is all a natural part of any software development life cycle.

Your development safety net is a combination of static analysis and tests. Much has been written on the topic of testing and how to write good tests. In the chapters that follow, I will focus on why you write tests, how to decide which tests you write, and how you can make those tests more valuable. I’ll go beyond simple unit and integration testing to talk about advanced testing techniques like acceptance testing, property-based testing, and mutation testing.