I am working on a project contemplating the best use of notebooks in our search relevance workflow. We're a cross-disciplinary team of software engineers and data scientists. Recently, to decide best practices, I watched the two famous talks I don't like Notebooks by Joel Grus and I like notebooks by nbdev creator Jeremy Howard. As a senior dev, I want to have opinions for how my team should develop both the notebooks and any underlying libraries.
- Writing docs leads to better code - I have written better code when I know its being consumed as documentation by others, and needs to be read. I fully agree with the amazing feedback loop between writing and coding that creates much better libraries
- Jupyter as a dev env - For some people, Jupyter is their preferred dev environment, and should be supported as such.
- Philosophy - I generally agree with the philo