Spotify-qt VS Every Noice at Once

If you want to run Spotify on a Raspberry (or PinePhone or some other device), there’s Spot, which is great, but kinda heavy and slow. There’s Spotify-qt which is faster, requires messing with Spotify developer dashboard, and UI doesn’t fit on small screens. Spotify-qt is itself based on Spotify-tui which runs in the terminal (pretty cool IMO). And a bare client/daemon is spotifyd. So you have quite a few choices... Source: over 1 year ago

Would like to add that you can also use clients such as spotify-qt and Spotify TUI to control said "device". There's also Spot and psst that are standalone (librespot not required but no Connect functionality). Source: over 1 year ago

I have been using spotify-qt[1] lately. It's quite close to the original client from more than 10 years ago. 1. https://github.com/kraxarn/spotify-qt. - Source: Hacker News / almost 2 years ago

You could use an an unofficial client, for example: - Spot (GTK, can stream directly) - spotify-qt (QT, just a Spotify connect frontend, so you need something like spotifyd running) - spotify-tui (terminal, again just a Spotify connect frontend) - spotifyd (daemon that is controlled via Spotify connect). Source: over 2 years ago

I see this in https://everynoise.com/#updates > 2024-01-05 status update: With my layoff from Spotify on 2023-12-04, I lost the internal data-access required for ongoing updates to many parts of this site. Most of this, as a result, is now a static snapshot of what, for now, will be the final state from the site's 10-year history and evolution, hosted on my own server. Some pieces may get disabled and reenabled... - Source: Hacker News / 16 days ago

Anyone aware of a similar feature for foobar2000? I have an extensive library mostly tagged from Discogs, including release IDs. In theory, this should be sufficient to cluster music by genres, pull similar releases from Discogs "similar" feature and correlate data from https://everynoise.com. Obviously, in case of album mixed genres things will mix up, but I'm not sure there's a model that can correlate existing... - Source: Hacker News / about 1 month ago

The article mentions Glenn McDonald's musical genre page (https://everynoise.com/, no longer refreshing with new Spotify data) as an example of a flexible graph-like exploration format, without being burdened by explicit connections. The author also has a thorough description of pros and cons of the general concept. - Source: Hacker News / 4 months ago

This is from Glenn McDonald's blog, founder of "Every Noise at Once". He was laid off from Spotify (discussed here briefly [0]) --- https://everynoise.com/ is now in "archival copy" mode [1][2]. Super sad to read / see this. [0] https://news.ycombinator.com/item?id=38650917 [2] https://twitter.com/EveryNoise/status/1736086849339244935. - Source: Hacker News / 5 months ago

Data exported using: https://benjaminbenben.com/lastfm-to-csv/ Album art compiled using: https://www.neverendingchartrendering.org/ Genre data compiled using: http://organizeyourmusic.playlistmachinery.com/# https://everynoise.com/ https://www.tunemymusic.com/transfer Gender, year and country of origin information manually compiled using Last.fm and wikipedia. Data analysis done in excel and image created in GIMP. Source: 5 months ago