Delete extracted files when loading dataset
Sure @stas00, it is still a draft pull request. :) Yes, I noticed it after reviewing - my apologies. The problem with this approach is that it also deletes the downloaded files (if they need not be extracted). 😟  > The problem with this approach is that it also deletes the downloaded files (if they need not be extracted). worried

Right! These probably should not be deleted by default, but having an option for those users who are tight on disc space? > Right! These probably should not be deleted by default, but having an option for those users who are tight on disc space?

I propose leaving that for another PR, and leave this one handling only with "extracted" files. Is it OK for you? :)  Awesome thanks !
I just have one question: what about image/audio datasets for which we store the path to the extracted file on the arrow data ?
In this case the default should be to keep the extracted files.

So for now I would just make `keep_extracted=True` by default until we have a way to separate extracted files that can be deleted and extracted files that are actual resources of the dataset. @lhoestq, current implementation only deletes extracted "files", not extracted "directories", as it uses: `os.remove(path)`. I'm going to add a filter on files, so that this line does not throw an exception when passed a directory.

For audio datasets, the audio files are inside the extracted "directory", so they are not deleted. I'm still more in favor of having `keep_extracted=True` by default:
- When working with a dataset, you call `load_dataset` many times. By default we want to keep objects extracted to not extract them over and over again (it can take a long time). Then once you know what you're doing and you want to optimize disk space, you can do `keep_extracted=False`. Deleting the extracted files by default is a regression that can lead to slow downs for people calling `load_dataset` many times, which is common when experimenting
- This behavior doesn't sound natural as a default behavior. In the rest of the library, things are cached and not removed unless you explicitly say do (`map` caching for example). Moreover the function in the download manager is called `download_and_extract`, not `download_and_extract_and_remove_extracted_files`

Let me know what you think ! I think the main issue is that after doing some work users typically move on to other datasets and the amount of disc space used keeps on growing. So your logic is very sound and perhaps what's really needed is a cleansweep function that can go through **all** datasets and clean them up to the desired degree:

- delete all extracted files
- delete all sources
- delete all caches
- delete all caches that haven't been accessed  in 6 months
- delete completely old datasets that haven't been accessed  in 6 months
- more?

So a user can launch a little application, choose what they want to clean up and voila they have just freed up a huge amount of disc space. Makes me think of Ubuntu Tweak's Janitor app - very useful.

At the moment, this process of linting is very daunting and error-prone, especially due to all those dirs/files with hash names. @stas00 I've had the same idea. Instead of the full-fledged app, a simpler approach would be to add a new command to the CLI. oh, CLI would be perfect. I didn't mean to request a GUI-one specifically, was just using it as an example.

One could even do a crontab to delete old datasets that haven't been accesses in X months. @lhoestq I totally agree with you. I'm addressing that change.

@stas00, @mariosasko, that could eventually be addressed in another pull request. The objective of this PR is:
- add an option to pass to `load_dataset`, so that extracted files are deleted
- do this deletion file per file, once the file has been already used to generate the cache Arrow file I also like the idea of having a CLI tool to help users clean their cache and save disk space, good idea !
Close #2481, close #2604, close #2591.

cc: @stas00, @thomwolf, @BirgerMoell 