Python Data Analysis Cookbook

Unit testing your code

If code doesn't do what you want, it's hard to do reproducible data analysis. One way to gain control of your code is to test it. If you have tested code manually, you know it is repetitive and boring. When a task is boring and repetitive, you should automate it.

Unit testing automates testing and I hope you are familiar with it. When you learn unit testing for the first time, you start with simple tests such as comparing strings or numbers. However, you hit a wall when file I/O or other resources come into the picture. It turns out that in Python we can mock resources or external APIs easily. The packages needed are even part of the standard Python library. In the Learning to log for robust error checking recipe, we logged ...