Refresh

I’ve been playing around with a new web service called Stalkify for the past week or so. The notion is simple: Stalkify makes the social graph from Last.fm available in Spotify. So all the tracks you’re scrobbling to Last.fm (and have been for the past decade or so…) suddenly makes sense in the brave new world of Spotify.

Stalkify was inspired by @Claus’s Spotify DJ, which allows you to have peers listen into DJ sets. Classy clever used spotify: URIs and some Adobe Air magic to patch this piece of software together, but I figured that you could build the same live experience by using tracks recently scrobbled to Last.fm — and making a live-updated playlist in Spotify.

So that’s the first feature: You’ll key in a username (or your username) and you’ll get a live playlist of what’s being played by that user.

An awesome upside of using Last.fm as the data exchange is that you’ll also be able to stalk non-Spotify users. For example, my good friend PolleTheWonder is a heavy Last.fm user with a list of almost 20.000 listened tracks; but he isn’t a Spotify user. With Stalkify, I’ll still be able to listen live to what Paul is playing.

I have four years of Last.fm usage and 22.559 plays to my name, and Last.fm is pretty good at collating this information into a sense of my musical taste. For example, they compile lists of my favorite tracks (from both my Winamp, my iTunes and my Spotify days), which is something I’d love to have ready at hand in Spotify. Stalkify does that: It give me a list of daily updated list of what I’m listening to the most.

(I’ll be updating Stalkify to use more features from Last.fm in the future: Top albums, Recommended artists, Neighbouring users…)

For the geeks…

Stalkify is pieced together from The Last.fm API using pylast, from libspotify (0.0.3 because 0.0.4 is buggy in playlist handling) using greenstripes and Spotify’s Metadata API using spotimeta.

All the code is a) ugly and b) available at github.com/steffentchr/Stalkify.