Unit testing is absolutely essential.
If there's no automated test to show a particular element functionality, then the feature doesn't really exist. Put another way, it's not done until there's a test that shows that it's done.
We'll touch, tangentially, on testing. If we delved into testing each object-oriented design feature, the book would be twice as long as it is. Omitting the details of testing has the disadvantage of making good unit tests seem optional. They're emphatically not optional.
When in doubt, design the tests first. Fit the code to the test cases.
Python offers two built-in testing frameworks. Most applications and libraries will make use of both. One general wrapper for testing is the unittest module. In addition, many public API docstrings will have examples that can be found and used by the doctest module. Also, unittest can incorporate doctest.
The pytest tool can locate test cases and execute them. This is a very useful tool, but must be installed separately from the rest of Python.
One lofty ideal is that every class and function has at least a unit test. The important, visible classes and functions will often also have doctest. There are other lofty ideals: 100% code coverage; 100% logic path coverage, and so on.
Pragmatically, some classes don't need testing. A class that extends typing.NamedTuple, for example, doesn't really need a sophisticated unit test. It's important to test the unique features of a class you've written and not the features inherited from the standard library.
Generally, we want to develop the test cases first, and then write code that fits the test cases. The test cases formalize the API for the code. This book will reveal numerous ways to write code that has the same interface. Once we've defined an interface, there are still numerous candidate implementations that fit the interface. One set of tests will apply to several different object-oriented designs.
One general approach to using the unittest and pytest tools is to create at least three parallel directories for your project:
- myproject: This directory is the final package that will be installed in lib/site-packages for your package or application. It has an __init__.py file. We'll put our files in here for each module.
- tests: This directory has the test scripts. In some cases, the scripts will parallel the modules. In some cases, the scripts may be larger and more complex than the modules themselves.
- docs: This has other documentation. We'll touch on this in the next section, as well as a chapter in part three.
In some cases, we'll want to run the same test suite on multiple candidate classes so that we can be sure each candidate works. There's no point in doing timeit comparisons on code that doesn't actually work.
