This week’s focus was on project selection and progress. The project choices were really diverse and interesting, I think the spread from useful daily libraries like Pandas and p5.js to learning platforms like Oppia to deep cryptography stuff like Keycloak is super fascinating.

I think our project compares really interestingly to the selection from the class - I’m in particular super excited to see what the P5 team does in terms of navigating the large organisational codebase. In comparison, our project is super small, and it’s managed by the Hong Kong University Data Science program, so it’s mostly collaborative with other students from schools around the world.

This week, we’ve made some great progress. Everyone has nanobots running locally now, and I’m even thinking of getting my own Raspberry Pi setup to run it constantly. We’ve also built a live issue feed, and I think we’re going to also just set up an automatic system to tag issues so we don’t have to do it manually. Most of the issues seem to be small and fixed relatively quickly, and even though we’ve scraped all the issues and tagged them, we regularly see issues we’re thinking of working on solved relatively quickly. It’s worth keeping this in mind as we go forward, because we’ll need to either do more challenging issues (not really a problem) or react fast to new issues (which is quite doable).

The emphasis on code quality is huge, we’ve noticed, so this should train us to write clean code by the standards of other skilled engineers, as well.