aleph VS zeal

If you're talking about tools for data, it really depends on what kind of data you're looking at and why you have it. For exploring datasets that you don't know what is contained inside (like data leaks) there's OCCRP's Aleph tool: https://github.com/alephdata/aleph

https://github.com/paperless-ngx/paperless-ngx https://github.com/alephdata/aleph

If you are doing investigative journalism, there is the OCCRP's Aleph for working with big amounts of data and connecting entities https://aleph.occrp.org/ . It's open source and self-hostable. Also for big messy dataset, the ICIJ's Datashare might be interesting.

There's also Zeal (https://zealdocs.org/) which is basically the same as Dash but open source and runs on non-Mac devices.

For offline tech documentation you can use Zeal. Must have tool for poor internet connection places. Present in ubuntu repos. https://zealdocs.org/

ads don't have to proprietary

here's one example of ads in FOSS https://github.com/zealdocs/zeal/issues/779

There’s stuff like https://zealdocs.org/ that allow you to take all relevant documentation with you so offline coding will work.

If you just want to be productive, you could also bring a lot of books or downloaded tutorials on a drive.

Btw, make sure your drive is encrypted and you think of a way to backup your data so you don’t lose the offline progress.

I’d suggest you look into Kiwix¹ and also Zeal².

1. https://www.kiwix.org/

2. https://zealdocs.org/

For offline documentation, I use Zeal (called Dash on macos) which looks/works almost identically to rubydoc.info but much faster since it's offline, has a standard interface for all installed language documentations, and only 1 global hotkey away while programming.

I highly recommend using local solutions to this local issue: Zeal[1] (aka Dash[2] on MacOS)

Load up the "docsets" of your languages (lightly edited HTML docs for indexing purposes) and use a global keyboard shortcut (F8 for me) to pull up Python/Postgres/Terraform docs, searching for the right function without internet query.

This isn't straight up applicable to all questions of course, but "How do I search regular expressions in Python again?" is now as easy as "re"

Note that the docsets can be converted from normal HTML ones via doc2dash[3], especially useful to load up custom docs like private providers.

[1]: https://zealdocs.org/