I spend an enormous amount of time listening to music and I think hearing is my strongest sense. After working on PlaylistMint and learning about all the data Apple Music tracks, I was curious to see what the models could produce to share what I listen to. I keep a list of things I want to throw extra tokens at and we’ve been having a lot of Codex resets so I was able to build /Music on this site.
The page pulls two kinds of favorites out of that history: the songs I play most, and the ones I skip the least. You can browse across the whole library or pick a year. You can play individual songs in a mini player or entire sets of songs as published playlists with full support for both Spotify and Apple Music.
The underlying data comes from the XML export of my Apple Music Library. I clean up the data by combining copies and versions of a song (remixes, live recordings, extended cuts, etc.) adding their play and skip counts together under the most popular instance. Unfortunately the play data is only a snapshot so I can’t say what songs I played the most in each year, only which songs I added in a given year were played most. This gives my lifetime top picks a strong skew towards my previous taste.
Each song gets one spot across the two lists. If a most-played song also clears the almost-never-skipped threshold, it gets a badge there. I limit each artist to two songs per list so there’s room for more of the library.
Song playback uses Spotify and Apple Music embeds, with saved catalog IDs connecting my library entries to the versions on each service. Pressing a song’s play button opens the player at the bottom of the page. There’s a small switch to alternate between services and the player remains as you navigate to other pages on the site.
I used Codex computer use to build the rankings into 19 playlists on both Spotify and Apple Music.
I’m working on a version of the code that anyone can use to publish something similar. For now you can see my music at /music.