The Last.fm Project

My server is down for maintenance for the next 16 hours.  It was a perfect opportunity to begin my next long term music project.

When Innerspace Labs first switched to the cloud, I used the web-based RacksandTags service through my OrangeCD DB to create an index of all track information from my library.  Collections on the service can be searched by artist, album, or track, but lacks support for 2nd level organization like genre clustering, playlists, and other more valuable data points.

RacksandTags Interface

I later switched to Discogs.com.  Discogs offers real time market value assessment of your collection, but only supports physical media.  I was also disappointed to find that user-generated category foldersare not presently shareable with other users.  
Discogs Interface As I prepared for the downtime last night, I realized that I hadn’t given Last.fm a shot since I wiped my account clean in 2014.  That year I scrobbled 30,000 tracks, but was frustrated that there was no way to submit all my library’s data without playing every track in real time.

My goal was to explore the service’s recommendation engine, and my library data would likely produce some valuable results.

So last night, I went to work.  I quickly realized that the best approach would be to queue all 100,000+ tracks and to scrobble them in order of ascending track duration.  I organized the songs into four pools of nearly equal size.  Below is a map of my library based upon these four classes – less than five minutes, less than ten minutes, less than thirty minutes, and up to 24 hours.

Tracks by Duration

As the largest batch was that of the shortest tracks, there would be the greatest (and fastest) return from scrobbling these first.

I charted the play duration of each of these groupings to see what sort of timetable I’d be looking at for project completion.

Project Duration

Graphing the duration of each grouping clearly demonstrates that this was in fact the best course of action.

Projected Sync Progress

I began scrobbling immediately for the first time in a year.  Once the project is complete I’ll share some of the resulting recommendation data Last.fm provides.  I’m looking forward to it!

Happy Labor Day weekend everyone!

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