picard VS youtube-cue

Have you tried https://www.funkwhale.audio/?

It can be used effectively as a "private spotify". Labeling is a solved problem thanks to https://picard.musicbrainz.org/, and the fact that a lot of the music you buy these days comes pre-labeled already.

You then have a web-app (and/or a mobile app, if that's your thing) where you can stream music as you would with Spotify.

You can even build yourself a little music-sharing commune with friends, where you all upload the albums you buy and accumulate a nice collection of diverse tunes.

I use picard for my collection. My work flow is Picard > Lyrics Finder > Foobar for BPM, RealGain and DR > Custom python script to pull genre and mood from Last.FM and spotify> then Advanced Renamer to perform naming clean up of folder names. I lowercase and underscore spaces. Also does files if I happen to need Mp3Tag when Picard doesn't find anything. Once this is done I move files on to may NAS.

Musicbrainz Picard - A great application that I've used in the past to identify and organize my saved music collection. It's not focused on adding semantic tags though: it's used for adding metadata to .mp3 files.

I do the same but run it though Picard[0] before adding to Plex.

[0]https://picard.musicbrainz.org/

feed all of your music to something like 'musicbrainz picard' - it will sort out all the tags and provide the artwork too

Aside from properly ripping and tagging your own physical collection I'd generally refer you to r/piracy but I think they've gone a bit strange since the blackout. I'm fairly sure anything more specific in that direction would not be appropriate for this subreddit.

Downloading MusicBrainz will be a lifesaver for you.

> CLI: I wanted to download songs from youtube, but they were often stitched as complete albums - so I wrote a youtube-cue generator that generates cuesheets that can then be used to split and tag the yt-dlp downloaded audio file. (https://github.com/captn3m0/youtube-cue)

Thanks for this! I need to do some testing, this might automate the last manual step of my own script for converting YT mixes into distinct tracks. The problem I faced is that often the timestamps are not in the description, but instead in a comment, sometimes not even the pinned/top voted comment. That is why I paste it in via stdin for now.

As this fits the thread topic, a short description of this script. I enjoy YT mixes and wanted to listen to them in my car. I can use an USB stick with media files and playlists which are displayed decently by the infotainment system. I wrote a script that takes in a YT URL (or anything supported by yt-dlp), downloads & converts it to mp3, splits the mp3 file based on a list of timestamps, recognizes (tries to anyway) the songs via SongRec [0], tags & names the files correctly and finally generates an M3U playlist in the format recognized by my car. I use song recognition instead of parsing out the names from the timestamped list as the format of Artist - Title is nearly always slightly different. It was easier to use SongRec instead and get everything I need for tagging with >90% hit rate.

The heavy lifting is done by calling out to yt-dlp, ffmpeg and SongRec. I just glued them together with Python. I like your approach of a do one thing well and might add youtube-cue to the toolset.

[0] https://github.com/marin-m/SongRec

Beets is amazing and comes with great defaults. I wrote code recently to generate CUE sheets from YouTube mixes[0] and beet imports it nicely and easily.

[0]: https://github.com/captn3m0/youtube-cue There is a bash snippet in readme to show the Beets integration.