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Showcase a `unittest` variant of one of our `bot` test files.
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README.md

A unittest variant of our test suite

A couple of weeks ago, we started extending our test suite for our main Discord bot, @Python. I want to propose for us to switch to the unittest framework instead of the pytest framework we're currently using. I think that making this decision is especially important given the ambition we have with regards to requiring test coverage on bot as well as site.

Consistency

The main reason why I think we should switch is consistency. Both our bot and site repositories are central to our community and they are highly related as well. Therefore, I think it makes sense for us to use the same testing framework for both of them. Since the built-in testing utilities of Django are based on unittest, the most logical test for that framework would be unittest, not pytest.

I think that there are three major arguments in favor of that consistency:

  • Consistency in appearance and structure means our tests suites will be easer to read once someone gets used to that appearance and structure.

  • Contributors will not have to learn two frameworks in order to contribute to these two central repositories.

  • The output of both test suites (site and bot) will be identical, making it easier to interpret the results you get back once you get used to that output.

There are other arguments as well, such reducing the number of dependencies, increasing the number of reviewers who feel confident enough with the framework to make reviews, and being able to have a similar/identical set-up for the linting & testing phase in the pipeline of both repositories.

Examples of output

The base output of both frameworks with no failing cases is very similar: base_output_correct

When a test fails, there's a difference in output, though. However, both output the test values you put in (given that you use the self.subTest context manager with unittest like in the exposition file). For unittest, it's in the FAIL line, for pytest, you need to look at the code context to see the test values used. pytest gives slightly more context, but I think they both provide sufficient output to interpret the failing test: test_failure

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