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Add support to use the "Nightly" yt-dlp train, and pull latest #1154

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eduncan911 opened this issue Jan 9, 2025 · 0 comments
Open

Add support to use the "Nightly" yt-dlp train, and pull latest #1154

eduncan911 opened this issue Jan 9, 2025 · 0 comments

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@eduncan911
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eduncan911 commented Jan 9, 2025

It should be noted that "nightly" is what is recommended by yt-dlp to use. Not stable, release, or main. Says so right in the README. ;)

If we want to keep using the older not-recommended version in ytdl-sub releases, then there should be an easier procedure for end users to update to the Recommended version of yt-dlp.

We could simply switch to nightly and be done. It wouldn't hurt existing users, and would satisfy this issue. Using the yt-dlp documented ways to try to update is broken:

$ yt-dlp --update-to nightly
Current version: [email protected] from yt-dlp/yt-dlp
Latest version: [email protected] from yt-dlp/yt-dlp-nightly-builds
ERROR: You installed yt-dlp with pip or using the wheel from PyPi; Use that to update

Currently, to update, one has to:

  • set a SUDO password in the compose file (and the lookup for how to do that)
  • use sudo/root to pip uninstall yt-dlp
  • and then sudo pip install --pre yt-dlp to get the nightly. And of course, this doesn't survive a container restart/rebuild/upgrade either.

...which yields an interesting ERROR below. however, it does seem to continue working.

abc@e35b3754346a:~/ytdl-sub-configs$ sudo pip install --pre yt-dlp
Collecting yt-dlp
  Using cached yt_dlp-2024.12.26.232815.dev0-py3-none-any.whl (3.2 MB)
Installing collected packages: yt-dlp
ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
ytdl-sub 2024.12.27.post1 requires yt-dlp[default]==2024.12.23, but you have yt-dlp 2024.12.26.232815.dev0 which is incompatible.
Successfully installed yt-dlp-2024.12.26.232815.dev0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
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