Somehow always, someone somewhere rediscovers that cutting down the time between coding and code execution makes our lives easier and to a degree be able to write better programs.
Perhaps the earliest and best attempt was Lisp's computational model. Since then, the idea manifested itself again[1], again[2], and again[3] in different forms.
Spot on, hence why having a mix of JIT/AOT tooling is such a great experience.
Besides your examples, Eiffel, Oberon, Java, .NET, C++ (yep even for it), Cedar, Standard ML, OCaml, Haskell, Prolog, BASIC, Forth
Capricorn2481 4 hours ago [-]
This implies that Rust build times haven't been a topic of discussion for the last 10 years. They don't have long build times just for funsies, Rust is completely different from Lisp.
pjmlp 2 hours ago [-]
Haskell, Standard ML and OCaml have the tools for faster development workflows, or going for lunch while producing an optimised build.
It is a matter of priorities.
christophilus 3 hours ago [-]
But there's not really a great reason for the long build times. There are plenty of languages that compile very fast. The Rust borrowchecker isn't the source of the bulk of the slowness. It seems to be a combination of language design (e.g. they didn't design it for fast compile times from the start), and implementation decisions. It does seem like there's room for a Rust-like language with Go-like tooling, standard lib, and a focus on development speed.
pcwalton 2 hours ago [-]
It remains to be seen whether you can have a useful borrow checker on top of a simpler type system (at least, a type system that's significantly simpler so as to meaningfully reduce compile times). I have my doubts, personally.
rikarendsmp 21 minutes ago [-]
Relax runs the borrow checker 'lazily' so it already starts your app whilst the borrow checker runs asynchronous. It's jokingly called 'gandalf' because I think It halts the JIT if it finds a problem.
treyd 55 minutes ago [-]
The borrowchecker is not the source of the bulk of the language's slowness. It takes a fairly small fraction of the total time, I think I remember the number was 5%-15% depending on the project.
The majority of time is spent between the trait solver and LLVM optimization passes. There is work being done to improve the trait solver and to produce more efficient LLIR code from the get-go (so LLVM has less to optimize).
nu11ptr 2 hours ago [-]
The Rust compiler, while not extremely fast, is not extremely slow either. As an example, my toy compiler is 130K LoC of Rust and compiles in under 7 seconds on a cold build on my M5 Max. An incremental build is nearly instant. So then why is it that so many projects have a minute compile time with far fewer LoC?
The answer: dependencies (My compiler has virtually none, intentionally)
Rust has a very small stdlib, so you are forced to bring in dependency crates, and not just a few. Many programs have 50-100 or more, and they all have dependencies, and so on. Contrast with Go where it has a culture of few dependencies, and those project have few dependencies. Your Rust compiler is doing a lot more work for what appears to be the same program as in other langs, but ultimately is a lot more code (typically).
To make matters worse, cargo does a decent job of parallelizing the builds, but it can only do so a) at the crate level b) only as much as the dependency graph allows.
faresahmed 4 hours ago [-]
I beg to differ. It's not that Rust is completely different from Lisp. PL writers get so caught up with their 'killer feature' which in the case of Rust is the borrow checker, that they completely abandon the other 50% which is the environment.
If we stopped treating the compiler as a one-shot program, we could theoretically shorten this edit-build-test loop by 99%.
LoganDark 3 hours ago [-]
The borrow checker is an example of a certain kind of reasoning that Rust benefits from. There's a reason a Lisp can be inspected and rewritten as the process runs, and it's the same thing that makes Rust difficult to rewrite in the same way. Not sure the exact term for it, but it's very easy to have profound nonlocal effects, for example with TAIT (type alias impl trait).
wahern 3 hours ago [-]
The borrow checker doesn't rely on interprocedural analysis. The function prototype provides all the information needed to maintain lifetime invariants across functions, so given static typing already then interprocedural borrow checking is effectively zero cost at compile time. (Cf. Intraprocedural, non-lexical borrow checking.) So borrow checking is no impediment to dynamically replacing function definitions. And it would be less of a headache for intraprocedural REPL but-for non-lexical semantics. But in a REPL you could always use an interpreter for running a function currently being edited, then compile it down once complete. REPLs are a headache for languages like Rust because of static typing generally, generics, trait semantics, etc.
Ar-Curunir 51 minutes ago [-]
rustc is not really a one-shot program! Incremental computation is a big part of rustc !
jkelleyrtp 3 hours ago [-]
I built something similar - tbd on maintaining it - but I got Rust Analyzer emitting code and as well as running in the web. This new concept of rust compile daemon is pretty sick.
It's great to have zero deps, but that's a lot of code to maintain.
rikarendsmp 23 minutes ago [-]
AI maintains it, and its developer tooling really. The main use case is hotloading for LLM's to reduce wait-for-result time and to allow applications other be hot-debugged. Pause on panic is one of its main features I use all the time.
kennykartman 1 days ago [-]
I knew that makepad devs were focused on build times, but didn't imagine this much!
rikarendsmp 23 minutes ago [-]
Indeed but I could only do this in the age of AI. Before a project like this was just out of reach.
ridiculous_fish 3 hours ago [-]
This is preposterously ambitious - a complete Rust re-implementation. Looks like it's mostly claude?
pcwalton 3 hours ago [-]
Yeah, this is pretty much a textbook example of what AI agents make possible these days: things that are ridiculously ambitious, but aren't conceptually very difficult (or, at least, are conceptually well-trodden ground). Things like emulators, language runtimes, platform reimplementations like Darling, etc.
JITting Rust isn't conceptually very hard: you just take rustc and make everything dynamic instead of static. The only thing that was stopping it before was the sheer amount of effort. Well, now we have a way to reduce that effort.
rikarendsmp 24 minutes ago [-]
Yea it's claude+codex over the course of a month. It definitely isn't a one shot.
baq 2 hours ago [-]
Common Lisp lurks in the shadows, watching its own reinvention comfortably, yet another time
tontinton 4 hours ago [-]
The world really needs something like this, but why such a slop UI website.
Just tell Opus 5.5 to "redesign the UI to not look like AI slop, design it like a human expert designer would" at bare minimum.
rikarendsmp 24 minutes ago [-]
Its only prompt is 'make a flashy website for this project'. I think it's fine who reads websites anymore anyway. Readme.md for GitHub is the main thing.
hn_submit 1 hours ago [-]
The code is slop and the website too.
poly2it 2 hours ago [-]
Perhaps a cynical take, but I feel sloppy content advertised seriously is enabling a transparent form of cross-domain self-selection which can be interesting to observe from the outside.
Surac 4 hours ago [-]
moving errors from compile time to runtime is good?
andix 3 hours ago [-]
For quick iterations it's perfectly fine. Change something, see if it works. If it doesn't keep changing until it works.
In runtimes that provide quick dev loops some developers have continiously running unit testing sessions. They just fire off every few seconds and give intimidate feedback.
jtwaleson 4 hours ago [-]
For some use cases, like speeding up local development, it's an excellent trade off.
rikarendsmp 25 minutes ago [-]
It's a technology to improve iteration time with agents, or humans for live coding but nobody really writes code anymore so.
Perhaps the earliest and best attempt was Lisp's computational model. Since then, the idea manifested itself again[1], again[2], and again[3] in different forms.
[1]: Inventing on Principle, Bret Victor: https://www.youtube.com/watch?v=PUv66718DII
[2]: REPL-Driven Development, Stuart Halloway: https://vimeo.com/223309989
[3]: LIVE, Live Programming workshop: https://liveprog.org/
Besides your examples, Eiffel, Oberon, Java, .NET, C++ (yep even for it), Cedar, Standard ML, OCaml, Haskell, Prolog, BASIC, Forth
It is a matter of priorities.
The majority of time is spent between the trait solver and LLVM optimization passes. There is work being done to improve the trait solver and to produce more efficient LLIR code from the get-go (so LLVM has less to optimize).
The answer: dependencies (My compiler has virtually none, intentionally)
Rust has a very small stdlib, so you are forced to bring in dependency crates, and not just a few. Many programs have 50-100 or more, and they all have dependencies, and so on. Contrast with Go where it has a culture of few dependencies, and those project have few dependencies. Your Rust compiler is doing a lot more work for what appears to be the same program as in other langs, but ultimately is a lot more code (typically).
To make matters worse, cargo does a decent job of parallelizing the builds, but it can only do so a) at the crate level b) only as much as the dependency graph allows.
If we stopped treating the compiler as a one-shot program, we could theoretically shorten this edit-build-test loop by 99%.
Can build and iterate on Rust in the browser!
https://dioxuslabs.github.io/rustd/
It's great to have zero deps, but that's a lot of code to maintain.
JITting Rust isn't conceptually very hard: you just take rustc and make everything dynamic instead of static. The only thing that was stopping it before was the sheer amount of effort. Well, now we have a way to reduce that effort.
Just tell Opus 5.5 to "redesign the UI to not look like AI slop, design it like a human expert designer would" at bare minimum.
In runtimes that provide quick dev loops some developers have continiously running unit testing sessions. They just fire off every few seconds and give intimidate feedback.