betterletter VS youtube-cue

meaning it not only replaces Umlauts and Eszett, it also knows when not to (Poeten), and handles arbitrary compound words. Write your text, slap it all into the tool, it spits out results instantly. The original text can use alternative spellings (ou, ae, ue, ss), which is ergonomic. Combined with tools like AutohotKey, GUI integration through a single keyboard shortcut is possible. See [0] for a similar example.

A niche need I haven't yet come across someone else having as well! (just the amount of text explaining what it's all about is saying a lot in terms of specificity...)

The tool now grew into a tree-sitter based (== language grammar-aware) text manipulation thing, mostly for fun. The bizarre German core is still there however.

[0]: https://github.com/alexpovel/betterletter/blob/c19245bf90589...

> 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.