[dendrite9]

Wow I like this idea at least for many conversation based podcasts. I try to download mine at home but data isn't as expensive for the times I don't. Still there are reasons to use this.

I need to look into how the mirroring works, for some time I have wanted a way to subscribe to a podcast with a timeshifted start. Say from the beginning up to the date I start, or a range between 2 dates. For podcasts that have existed for a long time I find it hard to work through the back catalog in any consistent way.

[xk3]

yt-dlp works with many but not all podcast websites. You could download everything with metadata and mtime and then sort by earliest to most recent in a file browser.

I wrote a tool that might help with this if you don't want to download the files immediately but it definitely isn't required if you just download everything and use yt-dlp's download-archive.

    pip install xklb
    lb tubeadd podcasts.db 'http://www.hellointernet.fm/podcast?format=rss'
    lb listen podcast.db  # it will keep track of what you played and prioritize playing things that haven't been played before

And later do tubeupdate to check for new episodes:

    lb tubeupdate podcasts.db

If the website extractor provides metadata about file creation (eg. YouTube extractor) then you could use this to play the oldest videos first:

    lb listen podcast.db -u time_modified

If you want to download later you could do this:

    lb dl podcast.db --audio  # with the above example it saves to the folder "Generic" in the current working directory since it uses the yt-dlp generic extractor

https://github.com/chapmanjacobd/library

[a_bored_husky]

The mirroring part is for the rss feed specifically. When a podcast is added to the website a feed is generated with the same data as the original feed but only including the processed episodes and the media links pointing to our files. Then you subscribe to that feed instead of the original using your favorite podcasts app.

We have some "hidden" features like subscribing to a tag or merging many podcasts in one feed, but nothing time related.