I've been using your app for the last 3-4 months very successfully. There are a few niggles here and there but overall it's been exactly what I needed, and I'm very grateful for it!
Just as a note, the GitHub CLI doesn't use bubbletea itself right now, though it does use other charm libraries such as lipgloss and glamour. That said, it's quite likely that at some point we will use huh for our prompting library, which does use bubbletea.
Ah, I think you might be pleasantly surprised that this is an area being focused on right now with attestations[1] for example, here are the attestations for the GitHub CLI[2].
Maybe this whole cryptographic stuff has some use, but all that which was needed was for GitHub to declare when a file was uploaded manually and when by a workflow (specifying which workflow).
This looks so complex that it might well be just smoke and mirrors
Recently I've been wondering if there is a "build your own X" for some of these concepts. For example, there is https://github.com/xyproto/vt100 which seems relatively straightforward (though maybe not "simple") to learn from but are there any resources that would actually teach this stuff?
I'm a maintainer for the GitHub CLI. When our prompting dependency became unmaintained, the folks from Charm reached out to us looking to collaborate on a replacement (collaborate is a strong word for the amount of work they actually did compared to us).
While we haven't yet been able to prioritise using this package, our discussions with them were great and I think that in typical Charm fashion, they've created something really awesome here. In particular, we mentioned to them our desire to have accessibility as a first class experience and I think they really took that on board.
Recently, I've been toying with including asciinema in automated tests. Spinning up a TUI or richer CLI experience, sending it keystrokes, asserting on the output, all wrapped up in asciinema so that if it fails I can see what went wrong via the playback.
Jury is still out but it's been an interesting experiment.
Years ago when I was starting to interview for Uber in Europe I went through some data structure exercise which I failed at horribly. When I asked the hiring manager whether this was representative of the job, because I would probably not be good at it they said "no", and to follow up, when I asked why we did it they said, "in the next round my colleagues in the USA are going to ask you something similar".
I guess this wasn't entirely without sense but sort of seemed to be missing the point.
https://relatedwords.org/ is also pretty neat for this. It's slightly less strict than a thesaurus so it can aid in exploring the semantic space a bit more.
