Learn Python by Building Data Science Applications

Testing the code so far

How would we know whether the code is good, anyway? The only good way is to rigorously test your code. While it may sound like a lot of somewhat unnecessary work, it is a practice that will repay you many times over in the future—once you're sure your code behaves as intended, it is much easier to add new features and be sure that they didn't break any of the existing ones. Furthermore, you can upgrade dependencies or compare different implementations, all being sure that your code behaves as intended.

As for many other things, Python has a standard library for testing—unittest. In contrast to most of the standard libraries, however, unittest is fairly unpopular. Instead, another library, pytest, is considered the ...