Unit tests are an important tool to ensure the proper functioning of your application, but writing them can be a chore. Stephan Lukasczyk wants to reduce the monotony of the process for Python developers. As part of his PhD research he created the Pynguin project to automate the creation of unit tests. In this episode he explains the complexity involved in generating useful tests for a dynamic language, how he has designed Pynguin to address the challenges, and how you can start using it today for your own work.
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- Your host as usual is Tobias Macey and today I’m interviewing Stephan Lukasczyk about Pynguin, the PYthoN General UnIt test geNerator
- How did you get introduced to Python?
- Can you describe what Pynguin is and the story behind it?
- What are the problems that Pynguin is designed to solve?
- What other projects are you drawing inspiration from?
- What are some of the use cases for automatic test generation?
- How is Pynguin implemented?
- What are the challenges that the dynamic nature of Python introduces?
- What are some of the packages and libraries that have been most helpful while building Pynguin?
- Can you talk through the workflow of using Pynguin to generate tests for a project?
- What are some of the limitations on what kinds of projects Pynguin can be used for?
- What are some design or implementation strategies in the code that you are generating tests for that will help make Pynguin’s job easier?
- Once a test suite has been created, what are the next steps?
- What are some of the initial assumptions or goals of the project that have been revised or challenged once you began implementing it?
- What are the most interesting, innovative, or unexpected ways that you have seen Pynguin used?
- What are the most interesting, unexpected, or challenging lessons that you have learned while working on Pynguin?
- When is Pynguin the wrong choice?
- What do you have planned for the future of Pynguin?
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