youtube-cue VS Internet-Places-Database

> 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.

You can find many RSS feeds, links in my repository

https://github.com/rumca-js/Internet-Places-Database/tree/ma...

It contains also domain lists, that include tag indicating, if it is personal, or not.

I am running my personal web crawler since September of 2022. I gather internet domains and assign them meta information. There are various sources of my data. I assign "personal" tag to any personal website. I assign "self-host" tag to any self-host program I find.

I have less than 30k of personal websites.

Data are in the repository.

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

I still rely on google for many things, or kagi. It is interesting to me, what my crawler finds next. It is always a surprise to see new blog, or forgotten forum of sorts.

This is how I discover real new content on the Internet. Certainly not by google which can find only BBC, or techcrunch.

Google will not be interested in fixing search. It also may not be possibile because of ai spam. They would like to invest in deep mind/bard/gemini than to fix technology that will be obsolete in a few years.

I have started scanning domains to see how many different places there are in the internet. Spoiler: Not many.

We could try to create curated open databases for links, forums, places, and links, but in ai era it will always be a niche.

Having said that I think that it is a good thing. If it is a niche it will not be spoiled by normal users expecting simple behavior, or corporations trying to control the output.

Start your blog

Start your curated lists of links.

Control your data. Share your data.

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

There are already many project about search:

- https://www.marginalia.nu/

- https://searchmysite.net/

- https://lucene.apache.org/

- elastic search

- https://presearch.com/

- https://stract.com/

- https://wiby.me/

I think that all project are fun. I would like to see one succeeding at reaching mainstream level of attention.

I have also been gathering links meta data for some time. Maybe I will use them to feed any eventual self hosted search engine, or language model, if I decide to experiment with that.

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

- bookmarks seed https://github.com/rumca-js/RSS-Link-Database

- links for year https://github.com/rumca-js/RSS-Link-Database-2024

I have myself dabbled a little bit in that subject. Some of my notes:

- some RSS feeds are protected by cloudflare. It is true however that it is not necessary for majority of blogs. If you would like to do more then selenium would be a way to solve "cloudflare" protected links

- sometimes even selenium headless is not enough and full blown browser in selenium is necessary to fool it's protection

- sometimes even that is not enough

- then I started to wonder, why some RSS feeds are so well protected by cloudflare, but who am I to judge?

- sometimes it is beneficial to cover user agent. I feel bad for setting my user agent to chrome, but again, why RSS feeds are so well protected?

- you cannot parse, read entire Internet, therefore you always need to think about compromises. For example I have narrowed area of my searches in one of my projects to domains only. Now I can find most of the common domains, and I sort them by their "importance"

- RSS links do change. There need to be automated means to disable some feeds automatically to prevent checking inactive domains

- I do not see any configurable timeout for reading a page, but I am not familiar with aiohttp. Some pages might waste your time

- I hate that some RSS feeds are not configured properly. Some sites do not provide a valid meta "link" with "application/rss+xml". Some RSS feeds have naive titles like "Home", or no title at all. Such a waste of opportunity

My RSS feed parser, link archiver, web crawler: https://github.com/rumca-js/Django-link-archive. Especially interesting could be file rsshistory/webtools.py. It is not advanced programming craft, but it got the job done.

Additionally, in other project I have collected around 2378 of personal sites. I collect domains in https://github.com/rumca-js/Internet-Places-Database/tree/ma... . These files are JSONs. All personal sites have tag "personal".

Most of the things are collected from:

https://nownownow.com/

https://searchmysite.net/

I wanted also to process domains from https://downloads.marginalia.nu/, but haven't got time to read structure of the files

On the other hand it is not 1995. Time has moved on. I wrote a Simple RSS feed, that also serves as search engine for bookmarks.

I am able to run it in attick on raspberry pi. We do not have to rely so heavily on google.

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

It is true that it does not serve me as google, or kagi replacement. It is a very nice addition though.

With a little bit off determination I do not have to be so dependent on google.

Here is also a dump of known domains. Some are personal.

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

...and my bookmarks

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

Some more years, and google can go to hell.

[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.