Property-based testing is a great benefit to the robustness and maintainability of your software. Yet, the technique is still vastly underused in the Python community. The workshop gives a hands-on introduction to Hypothesis and practices different approaches for writing property-based tests.
Do you find yourself working through pages of copied and pasted tests to accommodate a simple code change? Does your software frequently break in unexpected ways despite your testing efforts? Don’t despair! Property-based testing could be your way out of that mess. Rather than working harder and writing more test code, property-based testing forces you to work smarter and test more code with fewer tests.
Traditional tests are example-based. They require the developer to come up with arbitrary inputs and check a system’s behavior against explicit outputs. More often than not, developers only think of inputs that are handled correctly by their code, thus leaving bugs hidden. Property-based tests generate the inputs for you and they’re in many cases more likely to find invalid inputs than humans. The difficulty lies in formulating these test cases.
After this workshop you’ll be comfortable with property-based testing using Hypothesis. You’ll have experience requesting appropriate test data from Hypothesis and in writing tests for common and more advanced properties. In your next project your co-workers will be impressed by your unbreakable code ;)
Participants are expected to have basic familiarity with unit testing and a testing framework. Provided code examples use pytest.