Testing code using automated tools is common throughout the software development industry. This technique can improve the quality of the code you write as a data scientist. Testing helps refine your code, supports redesign, prevents errors, and makes it harder to write single-use code.
Here, we introduce the pytest framework and show how it can be used to test Python functions. If you don’t use a testing framework as part of your daily workflow, try experimenting with the techniques presented here the next time you write or extend a function.
I am a big fan of pytest because it strikes what I consider to be a great balance between convention and customization. There’s very little administrative overhead to creating test classes and test cases, so tests are easy to build and can it’s trivial to run a test suite or a specific part of one.