For the PaperWM fans, this is a dedicated WM based on the same idea

When science kills the mystery, semantics keeps the debate alive!

To answer your other question, yes there are still single-cell organisms evolving into new species all the time, in the ocean and elsewhere. That includes new multi-cellular species evolving from single cells all the time. But it takes a long time to develop from cell, to clump of slime, to something with legs. So you might not notice the changes if you aren’t super patient.

Or were those separate questions? Are you asking if chickens descended from single-cell organisms? Yes they did. With a lot of steps in between.

For some more detail see https://dev.to/martiliones/how-i-got-linus-torvalds-in-my-contributors-on-github-3k4g

Here is a source with lots of detail on how carbon emissions compare: https://www.theguardian.com/business/2023/dec/23/do-electric-cars-really-produce-fewer-carbon-emissions-than-petrol-or-diesel-vehicles

The tl;dr is that EVs have lower lifetime emissions. If the relevant grids use low-carbon sources then emissions are far lower. (But not as low as bicycles.)

I did not realize nano implemented syntax highlighting!

Oh right, there are some particular things that are helpful for a deeper language understanding.

Type classes and algebraic types are for sure standout features of Rust that make it better than most languages. Much of my experience before Rust was Typescript, but I have some background in Haskell so I was fortunate to have a head start on these concepts. I haven’t done any Rust interviews - my current role switched from Haskell to Rust after I joined. So I don’t know what interviewers are asking.

None of the prior languages you listed use manual memory management (which was the same for me). And even if you have that background, Rust does some things differently. (Although from what I understand explicitly codifies a number of ideas that experienced C++ devs have in their heads as “good practice”.) I think you’ll want to study up on how memory works. One of my favorite resources for this is Logan Smith’s Youtube channel. Those videos get me thinking about how this stuff I take for granted really works. The first two Rust videos on there, Use Arc Instead of Vec and Choose the Right Option are good ones to watch. Even if you opt not to use Arc<[T]> or Box it’s useful to understand how those differ from Vec and String.

Closures are weird in Rust, and are worth understanding. You have to choose between Fn, FnMut, and FnOnce. Plus there is the move keyword. I love the post Finding Closure in Rust for explaining what’s going on there. (It takes the implement-your-own-version approach which is a genre where I’ve incidentally seen some other gems, like Implementing a simple Promise in Javascript, and The Git Parable for understanding how git really works.)

Another area that is helpful to study is Rust’s implementation of async. It is similar to async as you’ve seen it before, but also different. For example in Javascript when you call an async function like, say, fetch it dispatches network requests right away. But in Rust a Future does not do anything until you call await on it. Learning about async leads into understanding of some more general language features. At the shallower end you learn about functions that return types based on trait, like impl Future or Box> because Future types often can’t be named directly so you have to describe what trait they implement instead. (This is very similar to how you work with functions that return closures.) At the deeper end you learn about working with Pin. You can get a deep dive on that in Pin and suffering by fasterthanlime. All of that guy’s posts are useful, but they are deep plunges so it can take some motivation to read them.

Since I seem to be recommending people to learn from I’ll add Mara Bos’ blog. She’s the Rust Library team lead. Her blog gets into some of the nitty-gritty stuff that gets you thinking about the language on a deeper level. She also wrote a book recently, Rust Atomics And Locks. I haven’t read it yet, but it looks useful.

Hey, you’re on a similar path to me. I’ve been on a Rust job for the past year.

Being a general-purpose programming language Rust can be used in a lot of contexts. The work I’m doing is all API server stuff, which I’m sure you already have a solid background in. There are some niches where Rust stands out that might be worth studying depending on your interest, but none of these are essential to Rust work generally.

• Crypto startups seem to be enthusiastic adopters of Rust. It’s not an area I want to get into personally, but this is likely the fastest path to a Rust job.
• Rust is probably the best language for compiling to WASM for running in browsers, in lightweight server-less functions, and as plugins. That could dovetail with your frontend experience. Although it’s a bit of an uphill battle to argue for WASM over Javascript in these cases.
• Rust makes an appealing choice for embedded programming as a safer alternative to C. This kind of work involves learning to program with nostd, and learning about controlling hardware.
• In non-embedded systems low-level pieces like device drivers are another good candidate for Rust.

It looks like there is at least one work-in-pprogress implementation. I found a Hacker News comment that points to github.com/n0-computer/iroh

Yeah, that makes a lot of sense. If the thinking is that AI learning from others’ works is analogous to humans learning from others’ works then the logical conclusion is that AI is an independent creative, non-human entity. And there is precedent that works created by non-humans cannot be copyrighted. (I’m guessing this is what you are thinking, I just wanted to think it out for myself.)

I’ve been thinking about this issue as two opposing viewpoints:

The logic-in-a-vacuum viewpoint says that AI learning from others’ works is analogous to humans learning from others works. If one is not restricted by copyright, neither should the other be.

The pragmatic viewpoint says that AI imperils human creators, and it’s beneficial to society to put restrictions on its use.

I think historically that kind of pragmatic viewpoint has been steamrolled by the utility of a new technology. But maybe if AI work is not copyrightable that could help somewhat to mitigate screwing people over.

That sounds like a good learning project to me. I think there are two approaches you might take: web scraping, or an API client.

My guess is that web scraping might be easier for getting started because scrapers are easy to set up, and you can find very good documentation. In that case I think Perl is a reasonable choice of language since you’re familiar with it, and I believe it has good scraping libraries. Personally I would go with Typescript since I’m familiar with it, it’s not hard (relatively speaking) to get started with, and I find static type checking helpful for guiding one to a correctly working program.

OTOH if you opt to make a Lemmy API client I think the best language choices are Typescript or Rust because that’s what Lemmy is written in. So you can import the existing API client code. Much as I love Rust, it has a steeper learning curve so I would suggest going with Typescript. The main difficulty with this option is that you might not find much documentation on how to write a custom Lemmy client.

Whatever you choose I find it very helpful to set up LSP integration in vim for whatever language you use, especially if you’re using a statically type-checked language. I’ll be a snob for just a second and say that now that programming support has generally moved to the portable LSP model the difference between vim+LSP and an IDE is that the IDE has a worse editor and a worse integrated terminal.

I pretty much always use list/iterator combinators (map, filter, flat_map, reduce), or recursion. I guess the choice is whether it is convenient to model the problem as an iterator. I think both options are safer than for loops because you avoid mutable variables.

In nearly every case the performance difference between the strategies doesn’t matter. If it does matter you can always change it once you’ve identified your bottlenecks through profiling. But if your language implements optimizations like tail call elimination to avoid stack build-up, or stream fusion / lazy iterators then you might not see performance benefits from a for loop anyway.

Specifically in Pasadena

Allow me to share, Federated Wiki. I don’t think it uses ActivityPub, but otherwise I think it’s close to what you described. Instead of letting anyone edit articles it uses more of a fork & pull request model.

PaperWM has columns - you can move multiple windows into a column (Super+I by default, or Super+O to move a window out of a column). When you move windows left or right or resize horizontally the column moves or resizes as a group. That’s the only feature that groups windows.

I mention Niri because I’m interested to see more implementations of the same idea. The only other scrolling window manager I know of is CardboardWM which is long dead. A native implementation like Niri might be able to explore ideas that are difficult to implement in an extension.

I’ve been using this for maybe a couple of years, and I love it! I like that windows stay at the sizes I set them to, and at the same time I can put as many windows in a workspace as I want.

PaperWM is not bug-free, but an active dev community has grown around it, and they do a lot of work to keep it running as smoothly as possible. That includes the essential task of working around breaking extension API changes when new Gnome releases are coming.

I’ve also been keeping an eye on Niri which applies the same idea to a standalone window manager. I haven’t switched because Niri doesn’t currently implement XWayland. But it looks like Wine is getting closer to native Wayland support so XWayland might not be a requirement for me for much longer.

And there is also Nushell and similar projects. Nushell has a concept with the same purpose as jc where you can install Nushell frontend functions for familiar commands such that the frontends parse output into a structured format, and you also get Nushell auto-completions as part of the package. Some of those frontends are included by default.

As an example if you run ps you get output as a Nushell table where you can select columns, filter rows, etc. Or you can run ^ps to bypass the Nushell frontend and get the old output format.

Of course the trade-off is that Nushell wants to be your whole shell while jc drops into an existing shell.

I’m a fan! I don’t necessarily learn more than I would watching and reading at home. The main value for me is socializing and networking. Also I usually learn about some things I wouldn’t have sought out myself, but which are often interesting.

Good to hear!

Well if you want to try another avenue, I’ve read about implementing self-referential structs using Pin.

There’s a discussion here, https://blog.cloudflare.com/pin-and-unpin-in-rust/

There’s a deep dive on pins here, but I don’t remember if it addresses self-referential types: https://fasterthanli.me/articles/pin-and-suffering