I’ve got this text file with my entire music collection that I made using foobar2000’s text tools. The format is like Artist - Track Title with each song on a new line. The thing is, I have around 85,000 tracks in there which is pretty massive.
I want to turn this into Spotify playlists but the online converter I tried is super slow. It processes about one track per second so we’re talking about a full day just to get through everything.
Does anyone know if there’s a faster way to do this? Maybe some local script from GitHub or a different website that can handle file uploads and process them quicker? I’m open to splitting it into multiple playlists if that helps with the speed.
I hit the same challenge when migrating from Google Play Music. The issue is Spotify’s rate limiting combined with subpar API calls from those online tools. I created a Python script using the Spotipy library, and the key is processing tracks in chunks overnight. I recommend running 5000 tracks at a time with delays between requests to avoid hitting the limits. This approach is much faster than those slow web converters. Additionally, my script included fuzzy matching, which was helpful in catching variations in artist names and track titles. Given that your foobar2000 export may have slightly different formatting than what Spotify recognizes, expect that migrating all 85k tracks could take several hours with this setup, but it will be a lot more efficient than the full day you mentioned. You should definitely check GitHub for a ‘spotify playlist generator python’ search—look for one that includes good error handling.
Been there with massive music libraries. You’re hitting API rate limits - Spotify throttles most tools hard.
I dealt with this last year importing 60k tracks from iTunes. Skip the slow converters and command line nonsense - I built a Latenode workflow that crushes this.
Latenode batch processes your tracks, handles Spotify’s API properly, and auto-splits into multiple playlists when you hit 10k. Feed it your text file and it parses each line, searches Spotify, and builds playlists while you grab coffee.
Best part? Error handling for tracks that don’t match perfectly. Instead of crashing, it logs the misses and keeps rolling.
Your 85k tracks become 8-9 playlists, all running in background. Beats babysitting slow web converters.
Consider using Playlist Converter or TuneMyMusic. I successfully transferred 70k tracks from my local library last summer, and both tools outperformed the standard converters for larger files. Make sure to clean up your text file beforehand, as I did with a simple text editor to remove duplicates and adjust formatting issues from foobar2000 exports, which significantly reduced processing time. Running conversions during off-peak hours, like late at night or early morning, also enhances speed. The matching was quite effective, even with slight variations in artist names. You might need to manually adjust some obscure tracks later, but the bulk processing saved me a significant amount of time compared to manually creating playlists.
totally get ur struggle! try spotdl or spotipy, they r super quick for batch stuff. just keep in mind the 10k track limit per playlist—u might wanna split it up a bit to make it manageable.