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- Hacker News
- That comparison figure of LaTeX vs Typst is ridiculous, choosing math-dense example for LaTeX vs classical markdown text for Typst. Yes, Typst syntax is much simpler https://typst.app/docs/reference/math/ but one doesn't need to make unfair comparisons to make Rust look better, Rust has a lot of good things going for it anyway, for example cargo.by bragh
- I would love it if jetbrains were to speed up IntelliJ. I started a new job writing Java professionally last year and, up that point, I had no idea that IDE's could actually be that slow.
My company gave me a brand new, beefy Macbook pro and that thing can barely handle IntelliJ sometimes...
by joshdavham - This topic has somewhat recently acquired a connotation where it yields a polarized response. People seem "tired" of the language and the episodes like Bun rewrite don't help, especially in current LLM-obsessed era.
Amidst this, just let me try to give my own experience with language while working in a field where it doesn't have much traction (scientific/numerical programming). A couple of years ago, after being tired trying to make Python faster, I was looking for a language to write simulation code in. Fortran (and C/C++) has been the go-to choice in my field for decades but I wanted to try a modern language. I tried Julia but the workflow didn't come naturally to me. Also by default, it also wasn't ahead-of-time compilable. Rust was my second choice but it's type system/design, expressiveness and tooling (rust-analyzer) won me over. I have written so much of it and I really enjoy writing it. Borrow checker isn't really an issue 99% of time when writing scientific code. And when it is (self-referential data structures), you can just use an arena (or something equivalent). The C/Fortran inter-op is great so it's still so easy for me to build my own abstractions on top for the more general stuff like solving ODEs and sparse matrices.
And of course, there is speed, memory safety and ability to parallelize things so effortlessly (rayon is magical), but I feel those were never the things that actually won me over. The language was just a joy to write.
by kmaitreys - Small related anecdote:
Was just testing latest gen LLM capabilities, and decided to give it goal of rewriting a small opensource project in Rust. (Should be noted: was not some tiny library, but an actually useful network service).
It completed the entire rewrite from typescript to rust in about 2 hours, ~600k tokens used. Worked perfectly on first try with no follow up changes required. Memory and CPU usage now a tiny fraction of TS version (obviously). Rust code was simple, easy to read, accurate test suite, etc.
I was pleasantly surprised.
Obviously bigger code bases with more complex business logic will likely struggle here, but there are some advantages to "RIIR" when performance matters, even security benefits aside. Rust can help squeeze more juice out of old hardware; reduced memory footprint especially helpful with current RAM prices.
For small services where operational cost matters, having LLMs "rewrite it in rust" might be worth the spend.
by BluSyn - This post advocates rewriting incrementally instead of all at once. Just like Joel said back in 2000, and like everyone continues to always say to this day. Yet in practice, people don't actually do this; complete rewrites in Rust remain far more common than incremental ones, particularly when rewriting from a language other than C. The high-profile exceptions, like Linux, Windows, and Firefox, are codebases so huge and ancient that they obviously cannot be rewritten from scratch. When rewriting from scratch is an option, it tends to be taken.
The reason for this is pretty straightforward: Incrementally porting a codebase from another language to Rust (especially if it's not C) is a deeply unpleasant experience, because the interop tooling isn't good enough and you spend most of your time fighting it. Consider the case of rewriting from C++; in the simplest case, you use bindgen and cbindgen, which only work with extern "C" functions in both languages. So you effectively have to rewrite each API first from idiomatic C++ to C-in-C++, then translate to C-in-Rust, then rewrite again in idiomatic Rust. And then repeat for the next API. And so on. It's not going to take long for most programmers to go "screw it, I don't care what Joel said, at least when I rewrite all my work I'll be doing it in one language where anything can call anything else". cxx and autocxx modestly improve things, but still leave you with an impoverished API vocabulary and similar problems, and you still have to do the three-step rewrite for each API, one at a time.
This is also why TypeScript, Kotlin, and Swift worked so hard to have seamless two-way interop with JavaScript, Java, and Objective-C. Without that, they couldn't have credibly promised to replace the earlier languages (because large existing codebases where a rewrite wasn't economical would still be stuck with them), and so couldn't have gotten off the ground.
Crubit is supposed to fix this for C++-to-Rust, and I'm rooting really hard for it, but it's not there yet. For most other languages, a Crubit-like thing probably isn't even possible in principle, because the differences are too great.
(I'm not talking here about the use case where you started with a garbage-collected language but have hit a performance ceiling with it, so you rewrite just the most performance-sensitive parts in Rust, while continuing to develop the rest of the codebase in the original language. This is often a great way to use Rust, but it's solving an easier problem and so poses fewer difficult tradeoffs.)
- For a brief second I thought JetBrains were rewriting their tools in Rust and we were going to get some performance improvements.
- Note, I am a co-maintainer of GNU coreutils. Whether that makes my opinion relevant, biased, or both, you can decide. :)
I really wished the documented their benchmarking methodology here, or at least cautioned the reader not to jump to conclusions based on the benchmarks shown.
GNU 'sort' performance can drastically be altered by the locale in use, the input, and the arguments given to the --buffer-size and --parallel options. GNU 'sort' is fairly conservative in how many threads it will use by default, and in my experience, much more so than uutils. This is because throwing more threads at 'sort' may make it faster (or may not), but also risks running out of memory. This is an issue with uutils, which is poor at deciding when to use external sorting:
Here is the same command using the latest uutils commit compiled with 'make PROFILE=release':$ export LC_ALL=C $ for i in {a..z}; do yes $i | head -n $(numfmt --from=iec 512M) | tr -d '\n' >> input; done $ time sort input > /dev/null real 0m24.245s user 0m0.896s sys 0m19.161s
The process gets killed by the OOM killer. This is likely because uutils 'sort' decides to use 18 threads, instead of the 1 used by GNU 'sort'. I find it a bit frustrating that benchmarks are thrown out without any methodology or citations, because they are often trusted without question. These could be benchmarks from before uutils had localization, which was the case before 2025, and treated LC_ALL=en_US.UTF-8 as LC_ALL=C. In that case, of course it would be much faster than GNU coreutils, but it also means uutils would give you the wrong results for non-ASCII characters. There is, as shown above, much more considerations beyond speed that seemingly never get the time of day next to flashy benchmarks...$ time uu-sort input > /dev/null Killed uu-sort input > /dev/null real 2m53.560s user 1m40.634s sys 0m59.847sby collinfunk - This feels like a really good blog post to write - something I'd really want to read - but the generated AI prose distracts, and makes me lose trust and not want to read this. I'm very AI-pilled, so this is not a criticism of AI as a whole, just this piece.by joshka