Professional Python

Chapter 11Unit Testing

When you think about testing the code that you write, the first thing that probably comes to mind is simply running your program directly. If your program executes, you at least know that you do not have any syntax errors (provided every module was imported).

Similarly, if you provide appropriate inputs, and do not get a traceback, you know that your program completes successfully with those inputs. And, if the result matches the result you expect, that is additional inductive evidence that your program works.

This has a couple of key limitations, though. The first is that for a non-trivial program, it is not possible to test every scenario. It is impossible to avoid this limitation, although it is important to be as complete as possible when thinking through potential scenarios to test.

The second limitation (and the one that the bulk of this chapter covers) is time. For most ­applications, it is not practical to manually test every scenario you imagine for every change that you ever make to your program, because iterating over these scenarios is time-consuming.

It is possible, however, to ameliorate this limitation somewhat by automating your tests. An automated test suite can run while you are absent or working on something else, providing a significant time savings and making it much easier to test your work early and often.

This chapter explores some of the world of testing. Specifically, it focuses on unit testing using the built-in tools provided ...