ActivePython 2.7.18 Documentation

15.5. Summary

Unit testing is a powerful concept which, if properly implemented, can both reduce maintenance costs and increase flexibility in any long-term project. It is also important to understand that unit testing is not a panacea, a Magic Problem Solver, or a silver bullet. Writing good test cases is hard, and keeping them up to date takes discipline (especially when customers are screaming for critical bug fixes). Unit testing is not a replacement for other forms of testing, including functional testing, integration testing, and user acceptance testing. But it is feasible, and it does work, and once you've seen it work, you'll wonder how you ever got along without it.

This chapter covered a lot of ground, and much of it wasn't even Python-specific. There are unit testing frameworks for many languages, all of which require you to understand the same basic concepts:

Designing test cases that are specific, automated, and independent
Writing test cases before the code they are testing
Writing tests that test good input and check for proper results
Writing tests that test bad input and check for proper failures
Writing and updating test cases to illustrate bugs or reflect new requirements
Refactoring mercilessly to improve performance, scalability, readability, maintainability, or whatever other -ility you're lacking

Additionally, you should be comfortable doing all of the following Python-specific things:

Subclassing unittest.TestCase and writing methods for individual test cases
Using assertEqual to check that a function returns a known value
Using assertRaises to check that a function raises a known exception
Calling unittest.main() in your if __name__ clause to run all your test cases at once
Running unit tests in verbose or regular mode

Dive Into Python

15.5. Summary

Further reading