How to access Spotify data using R (using the httr2 package)

[@rickymacharm4426]

Another smooth one...moving on to the next one

[@Uvinisihara]

Thank you so much for this video

[@djangoworldwide7925]

Question: when you added unlist() to lapply, could you also just use sapplly, or that wouldn't work? I'm a bit new school and would probably go straight to map_chr, but I try to get familiar with base R map-like functions

[@ggnot2]

I think sapply would work fine in this case!

[@nickamato3021]

Is this approach more lightweight for a server than building out a full blown RShiny app? Larger RShiny apps seem to be pretty demanding on the shiny-server running the app

[@ggnot2]

For this *particular* approach (i.e., Quarto dashboard using GitHub Actions), it would need to be pretty lightweight since you're limited by GitHub's max repo size (50MB I believe) and by the maximum GitHub runner size (16GB RAM if using `ubuntu-latest` docs.github.com/en/actions/using-github-hosted-runners/about-github-hosted-runners/about-github-hosted-runners#standard-github-hosted-runners-for-public-repositories), whereas you can purchase more compute as needed for Shiny :) I haven't compared compute resource usage between the two, but from my understanding Quarto dashboards aren't really "running" anything after they've been initially rendered to the output format