To align with what we use at Glints, we'd prefer you use React on the frontend, Node.js on the backend and Postgres as the database, with Typescript if you are confident. If you’re a frontend developer with no backend background, Firebase is always an option, but a more suitable stack will definitely earn you bonus points.
This is the raw data for restaurant opening hours - (https://gist.githubusercontent.com/seahyc/7ee4da8a3fb75a13739bdf5549172b1f/raw/f1c3084250b1cb263198e433ae36ba8d7a0d9ea9/hours.csv). Treat it as a raw data source that you can extract, transform and load into your database.
Build a simple user-facing webapp that allows the user to filter for restaurants open by date time as well as restaurant name. On top of that, users can save restaurants into their own named collections (eg. Vegetarian favourites, Meat-lovers etc.).
This is optional, it just serves as an additional proof point. Even if you submit without these features, we will consider the submission complete.
Users can also invite their friends to collaborate (add, remove, edit name) on the collections via email, and they can see updates to their collections in real-time, without page refreshes.
It'd be great if you can deploy this on the free tier of any cloud hosting platform (eg. free dyno on Heroku), so that we can easily access the application via an url.