Hey all, I just happened upon a trove (~100gb) of MP3s from when I was a sweaty teenager with a DSL line and a 5-disc ripper. Anyone have recommendations on OSS toolsuites to begin indexing/sorting out the files? Everything apparently got flat dumped from a directory structure to a folder. There’s metadata in about 90% of the content - ~10k songs to sort through shouldn’t be too rough with hashing.
I’d be more than willing to seed once everything is in a happy place, there’s probably a few hundred studio cuts of songs that haven’t seen the light of day yet.
You must log in or register to comment.
Picard can help you sort through most of it. It can identify most things even without tags. Just be careful and check everything it wants to do before letting it do its thing.
This is why thumb drives and write bits were made
Music isn’t torrents in 2026. We’re all on Soulseek. You could certainly start there but make sure it’s tagged well.
The real question, will rawdogging it trigger a DCMA?
Is VPN enough protection for Soulseek? I think Nicotine+ flatpak is available on my distro
Sounds like a good task for MusicBrainz Picard
Now that’s a name I haven’t seen in a loooooooong time. Excellent tool last time I used it…about 15 years ago.
Good recommendation.
I used this very recently to clean up multiple iPod backups (80-120GB) from my high school days. You still need to delete duplicates manually, but the software makes the task immensely easier.
If you don’t have trouble using the terminal, I’d recommend Beets.
Oooooooooo, this is hot af. You’re a real one
Picard mentioned in the other comment is great. If you want a more manual approach, on a Linux machine you can use
exiftoolto extract the metadata and then use that information to do whatever, e.g. organise them by folders.A bit long code block
$ exiftool -j 救世主.ogg [{ "SourceFile": "救世主.ogg", "FileName": "救世主.ogg", "FileSize": "3.4 MB", "FileType": "OPUS", "FileTypeExtension": "opus", "MIMEType": "audio/ogg", "OpusVersion": 1, "AudioChannels": 2, "SampleRate": 48000, "OutputGain": 1, "Vendor": "Lavf60.9.100", "PictureType": "Front Cover", "PictureMIMEType": "image/jpeg", "PictureDescription": "", "PictureWidth": 0, "PictureHeight": 0, "PictureBitsPerPixel": 0, "PictureIndexedColors": 0, "PictureLength": 102126, "Picture": "(Binary data 102126 bytes, use -b option to extract)", "Totaldiscs": 1, "Genre": "J-POP", "Encoder": "Lavf60.9.100", "Releasetype": "single", "Album": "救世主", "Language": "jpn", "Date": "2023-05-07", "Title": "救世主", "Totaltracks": 1, "Artist": "月詠み", "Duration": "00:03:20.868000000", "TrackNumber": 1, "Tracktotal": 1, "Disctotal": 1 }]My sushi roll experience was going to be iterating the byte-string headers and grabbing out anything of value, so essentially this. My hope was that there was a solution present to reduce the hand-rolling… tbd but it appears that Picard is a viable option based on yours and others commentary/upvotes
You’re saying each mp3 is ~10MB? That’s probably 320Kbps quality, so should be at least better than topical 128Kbps.
My maths: 10,000,000B ÷ 240 seconds song = 41,666B(yte).
41,666B × 8(bit) = ~333,333b
333,333b ÷ 1,024 = 325bps (thinking kibibit vs kilobit depending on your IS)
(again, rough numbers)
I haven’t said anything 😘
I’ve for plenty of space to seed indefinitely. Waiting for that AA scrape to finally be available from Spotify lol
There were grand ambitions for a n-petabyte scale u. server in a milk crate, but then LLM happened 😭
I could make it happen eventually. I currently house a 4U 36 bay and 3U 24 bay in my 42U rack. Not fully populated, but currently 10x 8TB in raid 5 and 8x 16TB in raid 5. Only 1 spare 8TB 😅 a few older 3TB in raid 10 with plenty of spares.
Sitting on mostly spinny shucked wd reds from whenever they’ve gone on sale and a few 1u servers w u. shenannigans. Nothing insane, still under 100tb in raid 10.
The only upside to my spinning disks are they’re SAS enterprise grade. So long uptime and expected lifespan
Have you tried strawberry music player? Has some pretty decent tools to get music files organized.
They use a bunch of copilot LLM actions and code updates across their platform. Picards last release is before any major agent rewrites to the main branch, so it’s been pinned.
