lsd
youtube-cue
lsd | youtube-cue | |
---|---|---|
3 | 3 | |
158 | 14 | |
- | - | |
4.8 | 6.4 | |
about 1 year ago | 5 months ago | |
JavaScript | JavaScript | |
- | - |
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lsd
- LSD – line-square-dot: an addicting game
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Ask HN: What apps have you created for your own use?
yeah, but that glitching is also something that makes the game more fun, cause if the ball gets enclosed into an area, you can try to glitch yourself out of it.
the very ugly MIT-like licensed code can be found here, and it is from a time when I thought it was fun to code my own little physics engine
https://github.com/franzenzenhofer/lsd/blob/gh-pages/main-20...
- Ask HN: Favourite Open Source Game?
youtube-cue
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Ask HN: What apps have you created for your own use?
> 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
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Beets is the media library management system for obsessive music geeks
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.
What are some alternatives?
flowcus.bar - Maximize productivity and manage time effectively with flowcus macOS app featuring a customizable progress bar, screen video capture, and personalized alert sounds for focused and efficient work sessions
picard - A cross-platform music tagger powered by the MusicBrainz database. Picard organizes your music collection by updating your tags, renaming your files, and sorting them into a folder structure, exactly the way you want it.
soundfingerprinting - Open source audio fingerprinting in .NET. An efficient algorithm for acoustic fingerprinting written purely in C#.
stag - public domain utf8 curses based audio file tagger
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srgn - A code surgeon for precise text and code transplantation. A marriage of `tr`/`sed`, `rg` and `tree-sitter`.
BeetsPluginStructuredCommen
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stag - STag: A Stable Fiducial Marker System
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