Yeah but wine helps lol
Hawk
ThinkPad or framework
We mostly use it privately, there are also a handful of software communities too that takes advantage of bridging.
Personally, I don't care about Nazis, they come for the same reason I do, privacy and place to speak. I don't have to let there negative disposition color the software.
I always bring my backpack personally.
What's your desktop environment? I'm pretty sure hyperland and sway will give a json output of open Windows.
You could parse that with jq and pipe it into fzf or dmenu?
Not quite the same as the clicking but probably just as quick.
Quartz or mkdocs
Or a makefile / justfile would be good too.
I put those on each directory and do just run
to pick up the thing I was working on quickly.
Usually canned is better for sauce because they're more ripe.
Perplexica is interesting too, but it uses a moderate amount of ram because of elastic search.
And of course you need to have ollama running
I've always had an easier time jumping into an oop code base, then eg a lisp one.
I hear people when they say they don't want their data mixed in with their logic but The pressure to structure code Is very nice.
I just wish people weren't so aggressive with politics.
I've noticed a severe lack of perspective and empathy in these communities which has greatly deterred me from engaging.
Reddit was bad as well, but it seemed to attract a more rounded and informed community at least in the early days. Probably a function of fragmentation more than anything.
It's a lot more like Seaborn. It produces gorgeous plots with a lovely syntax that is quick and easy to use, but it's not a full drawing toolkit like matplotlib.
If I need the plot to have a very precise aesthetic, mpl is great. But if I want a high quality statistical plot that looks great. ggplot2 will do it in about 2 seconds. See also plotnine.
I have no idea how op thinks they could make a decent histogram any quicker than
ggplot(data) + geom_histogram(x= x)
. I mean you don't even have to leave your shell/editor or extract the SQL into CSV.