Great discussion! Here are some ways that you can learn a lot about the library, whilst also contributing to the community:
- Pick a class, function, or method and write tests for it. For instance, here are the tests for
fastai.core. Adding tests for anything without good test coverage is a great way to really understand that part of the library deeply, and have in depth conversations with the dev team about the reasoning behind decisions in the code - Document something that is currently undocumented. You can find them by looking for the “new methods” section in any doc notebook. Here’s a search that lists them
- Add an example of use to the docs for something that doesn’t currently have an example of use. We’d like everything soon in the docs to include an actual piece of working code demonstrating it. Currently we’ve largely only provided working examples for stuff higher up the abstraction ladder.