Stalking Last.fm Streams On Spotify

Back in the early days of social media and Web 2.0, Last.fm was one of the premier music sites on the internet. With a huge library containing what felt like every song ever, along with an excellent algorithm for recommending new tracks, it quickly gained a large following. Unfortunately, its business model and following changed over the years, but there’s still a diehard userbase. [Hexalyse] was unhappy with Spotify’s algorithms, so built a tool to allow her to shadow what Last.fm users were listening to in real time.

Last.fm’s major feature is that it allows you to tell others what you’re listening to, by “scrobbling” your tracks as you play them. It’s possible to scrape this live data from any user via the Last.fm API, making the project possible. [Hexalyse] whipped up a Python script to query a selected user’s current playing track via Last.fm, before then handing the song data to the Spotify API to play the music locally.

It’s a fun way to find new music, relying on human taste rather than a pile of data center algebra. [Hexalyse] has uploaded the code to Github if you’re eager to try it for yourself. Of course, you get bonus points if you integrate it with Spotify on the Macintosh SE/30.

8 thoughts on “Stalking Last.fm Streams On Spotify

  1. “It’s a fun way to find new music, relying on human taste rather than a pile of data center algebra. ”

    Heaven help you if you stumble across that person with no taste in music.

  2. It was silly. For example, you’d listen to an album that has 40 1-minute songs of band X, then an album that has 1 40-minute piece by band Y. You’re now 40-fold more a fan of X than of Y and need to listen to that Y album 40 times over to balance it out.

    It was completely useless in the end.

    1. Or you could not care about how many times you’ve listened to an artist, and just use the service as a nice way to keep a log of everything you’ve listened to.

      And it’s a pretty peculiar situation that you’re describing here (and I say that as a post-rock lover, with 20 minutes songs, so yes it kinds of bias the algorithm towards genres with shorter songs)

      1. If I can’t remember some stuff that I listened, it’s best forgotten.

        I tried using it to find new interesting stuff to listen to by checking out what other people with similar tastes are listening. And it was only good if you’re into pop and want to find more pop. The situation with very long pieces vs many short ones is not hypothetical, that’s how it ended up for me.

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