RSS-Link-Database-2023 VS youtube-cue

[4] https://github.com/rumca-js/Django-link-archive

These are exported then to github repositories:

[5] https://github.com/rumca-js/RSS-Link-Database - bookmarks

[6] https://github.com/rumca-js/RSS-Link-Database-2023 - 2023 year news headlines

[7] https://github.com/rumca-js/Internet-Places-Database - all known to me domains, and RSS feeds

My own repositories:

- bookmarked entries https://github.com/rumca-js/RSS-Link-Database

- mostly domains https://github.com/rumca-js/Internet-Places-Database

- all 'news' from 2023 https://github.com/rumca-js/RSS-Link-Database-2023

I am using my own Django program to capture and manage links https://github.com/rumca-js/Django-link-archive.

Hi, I am collecting links from various places. Even from Hacker news. I have links since start of the year [1]. Maybe someone will find them useful. You should look at files named like [2].

[1] https://github.com/rumca-js/RSS-Link-Database-2023

[2] https.hnrss.orgfrontpage_entries.json

That is why I wrote [1] for myself. It stores links in database, which I can query. Everything is later on exported, like in [2] and [3]. I can browse history, I can find useful data. I do not say it has replaced google for me. It is a nice addition that helped me gather data I encounter on the Internet.

It is a link database, at first glance resembles Reddit clone, but my focus is on creating link database, not on providing social media experience cancer.

Links:

[1] https://github.com/rumca-js/Django-link-archive

[2] https://github.com/rumca-js/RSS-Link-Database

[3] https://github.com/rumca-js/RSS-Link-Database-2023

- https://github.com/rumca-js/RSS-Link-Database-2023 - all captured links in 2023

> 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.