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[Feature Request] parallel downloads feature using a batch file #3003
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opened 2026-02-21 01:02:25 -05:00 by deekerman
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pull/29816/head
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2024.07.11-nightly
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Originally created by @Rush2088 on GitHub (Sep 13, 2014).
Is there a way to enable parallel download session fed in by a --batch-file.
Some sites have very slow band width per video, therefore instead of waiting to finish previous file, it is much efficient to run parallel downloads.
@optikfluffel commented on GitHub (Dec 19, 2014):
This would be nice for playlists for example at Youtube, too :)
@ffigiel commented on GitHub (Feb 21, 2016):
👍 It's doable with external downloaders, but that's an annoying hurdle
@schmod commented on GitHub (Apr 21, 2017):
Is there any reason why
xargsis not be sufficient for this?@yan12125 commented on GitHub (Apr 22, 2017):
Some cases: custom output templates, postprocessing...
@Roman2K commented on GitHub (Nov 8, 2017):
I would rather have the complexity of parallel downloads kept out of youtube-dl so that its code base remains more maintainable.
Parallelism can be already be delegated to
xargs -P x -n ywherexis the number of parallel downloads andyis the number of URLs/IDs to pass to youtube-dl, most likely1. I find this a very elegant solution, composing various tools, each one doing a single job well. Used it successfully many times, saving me hours or days.@yan12125
Maybe I'm missing something but why can't this be done with
xargs youtube-dlpassing the same arguments (for templates, postprocessing, ...) as you wouldyoutube-dl?@yan12125 commented on GitHub (Nov 8, 2017):
From the viewpoint of youtube-dl internals, a series of urls is not different than a playlist with several videos. I was considering the latter case when I wrote the previous comment. If you want to achieve downloading videos of a playlist in parallel along with postprocessing them, you'll need to run the parallel download step - either via internal codes or external tools - from youtube-dl, instead of run youtube-dl in parallel, and then the postprocessing step can continue inside youtube-dl.
Or moving postprocessing codes to standalone commands. That would be interesting.
@siddht4 commented on GitHub (Nov 28, 2017):
After bit of research and all,I found out that https://github.com/MrS0m30n3/youtube-dl-gui already does supports it in series form,tinkering of it can support the parallel form
https://pypi.python.org/pypi/twodict may help.
https://github.com/MrS0m30n3/youtube-dl-gui/blob/master/youtube_dl_gui/downloadmanager.py#L106-L122 manages the current state.
https://github.com/MrS0m30n3/youtube-dl-gui/blob/master/youtube_dl_gui/downloadmanager.py#L239-L385 manages the queue which can be modified to work in parallel.
So it seems the process already exist so a little tinkering will add to the main project.
@epitron commented on GitHub (Dec 11, 2018):
If you use xargs, it's nontrivial to include the numerical playlist index in the filename (for playlists where order matters).
@ghost commented on GitHub (Dec 12, 2018):
@siddht4 get the download data using youtube-dl (
--skip-download --dump-json), write #1 an aria2 compatible-list, and rely on aria2 for both the queue-management and download #2, to get both multipart-download and multi-file download.For example, aria2 with
--split=3 --min-split-size=1M --max-concurrent-downloads=5 --max-connection-per-server=16will give you an active download-queue of five files, each has three parallel segment-download at a time. works well on youtube. With--continue=true --allow-overwrite=false --auto-file-renaming=falseyou can re-run the aria2 command in-case of an error, skipping completed files.@alex-hofmann commented on GitHub (Feb 20, 2019):
Just wanted to thank @Roman2K and provide the full one-liner, since many youtube-dl users may not be familiar with xargs or the shell.
cat files.txt | xargs -n 1 -P 4 youtube-dlHere,
files.txtis my batch file; -n 1 indicates one url for each youtube-dl call; -P 4 indicates 4 parallel youtube-dl calls@aryehbeitz commented on GitHub (Feb 22, 2019):
@alex-hofmann can this be used to download in parallel when downloading a channel or playlist on youtube?
@PiotrDabrowskey commented on GitHub (Feb 22, 2019):
@aryehbeitz No, I guess. It only allows you to download multiple links in parallel, but you need to specify those links in the file. Playlists and channels are just single link which are passed to youtube-dl as you normally do, so it does not solve the problem of this issue.
If there's a way to gather all the links from one playlist and place them into the file, this would do the trick.
@alex-hofmann commented on GitHub (Feb 22, 2019):
@aryehbeitz @PiotrDabrowskey Yeah I think you're right, this is only useful when you can feed the known links. For example, if someone wanted to download the Jeopardy! episodes that a reddit user graciously uploads daily they could use something like
My guess is that something similar is available for pulling the urls from a youtube playlist with a little curl+grep
@Roman2K commented on GitHub (Feb 22, 2019):
@aryehbeitz You can get the individual URLs from a playlist with:
That can be fed directly to
xargsfor parallel downloads as in @alex-hofmann's example.@Roman2K commented on GitHub (Mar 6, 2019):
If anyone's interested, I made a cronjob for backing up my YouTube playlists to Google Drive (using rclone). Idempotent/incremental. Kind of rough scripting but I've been running it with several 500+ long playlists over the last few days and it works well.
https://github.com/Roman2K/ytdump
ruby dl.rb PLAYLIST_URL./out./metadl_to_rclonefavorites/dl.shcrontabandcronjobDownloader::NTHREADSin dl.rbClone and customize to your needs.
@zer0def commented on GitHub (Apr 3, 2019):
Based on @alex-hofmann's and @Roman2K's hints, here's a trashman's oneliner that should work with any extractor (requires
jqalongside typicalcoreutilsbinaries):Adjust to your heart's content.
@epitron commented on GitHub (Apr 3, 2019):
@zer0def Nice!
Small issue: the number of parallel downloaders is set to the number of CPU cores (-P`nproc`). That parameter should be tuned to match the network capacity, not the CPU capacity.
Anyone who wants to try that should start it around -P5, and increase it until it saturates their connection.
@zer0def commented on GitHub (Apr 4, 2019):
@epitron As long as your extractions don't fall back to ffmpeg, it's safe to ramp up the process number, but when they do, you might end up unnecessarily extending your downloads due to threads fighting for CPU time, so I've picked
nprocsimply because it's fairly idiot-proof, while remaining faster than a sequential run on a large playlist.As per my previous comment: adjust to your heart's content, since everyone's case might be different.
@epitron commented on GitHub (Apr 4, 2019):
@zer0def Hyperthreading can also artificially increase your CPU count. What if you have 32 cores, and a regular network connection?
I thought YTDL only used ffmpeg to copy streams into different containers (unless you pass
--recode-videoor a specific format that needs to be transcoded). Are there any services that will by-default transcode video, and which support playlists?@zer0def commented on GitHub (Apr 5, 2019):
Then you have threads stalling for data, which is hardly a concern compared to saturating out low-end and/or low-core count CPUs with a pipe huge enough to overwhelm it.
@epitron commented on GitHub (Apr 8, 2019):
@zer0def What if YouTube bans or throttles you for spamming their servers with connections?
@zer0def commented on GitHub (Apr 9, 2019):
Do you have an actual case to provide as basis or are we just talking hypotheses? Because if you're looking for a golden mean, then yes, you could just cobble up a proper solution, write a wrapper script or use
parallel --limit. All of which go beyond a minimal dependencies "trashman's" case (ideally, I would've liked to omitjq, but haven't yet figured out a way to output necessary information in one line without running into issues with whitespace delimited paths).@dirkf commented on GitHub (May 16, 2025):
The original question was answered (tldr: yes, but) with no specific changes required. Linked issues discuss parallelisation within the program.