https://github.com/Syzygies/Compare
So you're in a restaurant where you don't speak the language, you can't read the menu, but you see three price points for set meals featuring the house specialty. (Say, "Crossing the Bridge" noodles in Yunnan.) Which do you choose? My tour guide, the author Fuchsia Dunlop, later agreed with me this is obvious: The middle choice.
So you're choosing between Go and C23 as candidate successors to K&R C. They both have "royal blood". One got the name. Knowing nothing more, which do you choose?
The answer is equally obvious. The one that got the name also got the warts.
I've been messing around with a language that I summarize as:
ALOE = Scheme + Smalltalk + Types
https://github.com/dharmatech/2026-09-02-aloe-racket
One of the examples is a very basic computer algebra simplifier:
https://github.com/dharmatech/2026-09-02-aloe-racket/blob/ma...
That simplifier is based on a computer algebra library in Scheme:
Minimal rewrite due to the breaking changes introduced in C23 versus K&R C, while the others are a complete rewrite.
Even if the syntax is a bit of a kludge there are now ways to indicate bounds on function arguments.
You might want to take a look at Odin as well.
For example, write in whatever language you know best, then translate to a more appropriate language using LLMs once the desired behavior can be checked automatically. It is a tactic that works in some cases.
If you’re not stupid it fails because you can find out and then make an informed decision. An informed decision will dominate the suggested strategy in terms of chances of not screwing up.
This really should be obvious.
(In the analogy, your phone has an automatic translator and you use it).
Note that I have made no argument for one language over another.
Zig has a language server and "The majority of LSP features are supported" (https://github.com/zigtools/zls#features).
That said, I've been re-evaluating my choices lately.
The code in that section is clear in its purpose and broad outline: "Give me a function and data; if the data is bare apply the function to it; if the data is a container apply the function to each item inside it."
You can absolutely do that with immutable data structures in Zig. You just have to pass an allocator to the function (i.e. instead of calling data.flat_map(f), you call data.flat_map(a, f) where a is your allocator).
That the Zig version of the code does mutation is a matter of programmer choice, not something imposed by the language.
(Also, what do monads have to do with it?)
> But the language quickly forces you to diverge from the functional style, mostly because you’re now dealing with allocators directly, and a genuinely pure functional approach means constantly constructing new structures. That’s either expensive in memory or expensive in the manual bookkeeping needed to avoid it.
So I don’t think he’s trying to say that it’s literally impossible. It felt more like the result of a good faith attempt to understand how Zig itself actually wants to be used, and to compare that to how he’s used to using Rust.
I actually liked that he did it. So many other comparisons want to evaluate one language against the other language’s values. But I don’t want to know how well Zig can do Rust; I want to know how well Zig accomplishes its own goals, and what those goals are.
unsafe impl<I, U, F> InPlaceIterable for FlatMap<I, U, F> where
I: InPlaceIterable,
U: BoundedSize + IntoIterator,
In Zig you end up spending a lot of time writing How to do a thing, where in Rust you only wrote What the thing is and the machine did it. There are edge cases where Zig's explicitness wins for the best programmers, but there just aren't enough of those cases or those programmers for this to net out IMNSHO.
1. Tooling (as an extension to the mentioned IDE support point). Zig and Rust are both praised for their tooling and I think rightfully so. The C/C++ interop story and the cross-compiling story in Zig are great. From the standpoint of a working practitioner though I think Rust is way ahead. Not surprising given that Zig is much younger, but something to keep in mind.
2. Compile Time Stuff: Here Zig is praised and Rust not so much. I think this is undeserved. Rust has much higher aspirations for their compile time features, namely that outcome must be identical regardless when the code runs. This is a very useful property but makes the task much harder and fundamentally incomparable with Zig comptime.
As far as I know this is not a concern for Zig comptime.
to expand, if two different host platforms cross compiling to the same target platform have different results, I am almost certain that would be considered a compiler bug.
if you're pointing out that a runtime operation and a compile time operation might not agree, I'd be more interested in understanding when that would ever have any meaningful impact on anything. given the compilation is supposed to be deterministic, the difference can easily be addressed by comptime branching on target architecture in the rare case that it matters for your program.
It's something Rust guarantees (without me having to take care of it e.g. by manually branching) and Zig does not.
I am genuinely interested in a place that this matters for a program, or any practical consequence this has for an end user of the language.
no idea why your response was flagged originally.
As far as I’m aware, they do produce semantically identical results, but something like the specific bit pattern of a NaN value can theoretically vary, and people might do fun things like encoding extra information in those bits.
Nonetheless, if you use a comparison function for which all NaNs are equivalent, different CPU architectures that are standard-compliant must produce bitwise identical results for the same sequence of operations.
Differences appear mainly when the compilers generate different operations or in a different order. Moreover, transcendental functions are computed using various approximations by the standard library, so if you use different libraries on different computers, you will get different results.
However, these are differences caused by software, not by hardware, and they happen even on the same computer when you use different versions of a compiler or of a standard library. Therefore such differences can be eliminated, if desired.
Absolutely, that’s why I wanted to know what types of things aren’t covered yet, and that’s also why I don’t share your certainty that they won’t be resolved later.
From what I understand, there is hope for sqrt but there is no consensus on transcendentals.
Rust is concerned about memory-safety, yes, but the only strict requirement for memory-safety when it comes to const-evaluation is as follows: "The only guarantee the type system needs is that evaluating `some_crate::SOME_CONST` will produce consistent results if evaluation is repeated in different compilation units" ( https://rust-lang.github.io/rfcs/3514-float-semantics.html ).
Beyond that, from a philosophical standpoint, Rust takes great pains to ensure that const functions produce identical results regardless of whether or not those functions are called at compile-time or at runtime. Rust has adopted this stance because it wants to reserve the right to opportunistically evaluate const-capable functions at compile time, as a performance optimization, even if the user has not explicitly asked for it (for that matter, Rust also does its best to const-evaluate non-const functions when it can). Because of this, Rust's assumption is that users would be annoyed if their program's visible behavior depends on whether or not the optimizer has exercised its discretion to evaluate a specific function at compile-time.
However, this is only a guideline, not a strict guarantee. There is one exception to the above rule: "when a floating-point operation produces a NaN result, the resulting NaN bit pattern is some deterministic function of the operation’s inputs that satisfies the constraints placed on run-time floating point semantics. However, the exact function is not specified, and it is allowed to change across targets and Rust versions, and even with compiler flags. In particular, there is no guarantee that the choice made in const evaluation is consistent with the choice made at runtime."
In other words, calling the `.to_bits()` function on a floating-point value that happens to be NaN is allowed to produce a different result at runtime than it does at compile-time (note that all compile-time evaluations are guaranteed to always produce the same result for a given toolchain version for a given target, as required above).
This exception is made because otherwise otherwise it would be basically impossible to support floating-point math at all, thanks to the way various platforms have implemented their floating-point functions in practice.
In contrast, Zig doesn't have such a philosophical compunction against a function's result being determined by whether or not it's being evaluated at compile-time, as shown by the existence of the `@inComptime` builtin. But Zig does still broadly attempt to make comptime deterministic, including going so far as to forbid I/O, though I don't see where any specific guarantees are documented in the Zig reference.
And the zig core team is absolutely concerned with bitwise determinism in the compiled artifacts, iirc this is why they rejected the sloppy bun PR to the compiler.
Other parts, like floats are harder. This is where a difference shows. Rust is like: "Sorry, since we cannot uphold our guarantees, no transcendentals for you at comptime ", whereas Zig is chill about that and let you have your transcendentals even if results may differ between comptime and runtime. Different mindsets.
This could be done, for instance, if the standard math library would be dynamically linked into the compiler, so the same library would be available for the compiled program.
* floating point differences between the build machine and the target. By far the most common
* endiannes - code assumes little median runs on big endian
There’s other more subtle issues that can crop up but those are the big two.
Not saying I agree though - those can happen anyway when you run on two different machines anyway.
In Rust we can expand what is possible at compile time without breaking existing code because we took a very careful approach only stabilizing what we are sure about. Some things will probably never be possible at compile time in Rust.
Zig is much more powerful but that also means they cannot take stuff away without breaking existing code and making comptime more restricted. So it is unlikely Zig will ever become like Rust in that regard, but that is ok - just different approaches.
For one of my crates I needed to have a build script make a bunch of lookup tables as separate files for me to `include_bytes!` because at the time I couldn't generate a bunch of floating point conversions in const.
The biggest constraint today on Rust's constant evaluation compared to where you'd expect is that trait implementations can't ever be constant, this obviously means you can't call SomeTrait::function in your constant, even if you can see the implementation of SomeTrait::function and if it were not a trait it'd obviously be constant -- but it also means sugar like Rust's for loop, which de-sugars into trait invocations, can never be constant today.
I think we can expect that to get fixed in the relatively near future, but I'd have said that last year too so what do I know.
If you have C++ experience you'd probably want a lot more. C++ is allowed to allocate inside constant evaluation, and I believe in C++ 26 it's now even allowed to persist the allocation to runtime rather than being required to always clean up during compilation, so that's a much bigger set of crazy things you can do at compile time.
Yep, that was my annoyance.
Const allocation is possible in Rust as an unstable feature. Not sure if you can persist it to runtime, though you can persist a reference which will become a static reference. I think it being unstable is why I needed `include_bytes!`.
That's why having no auto-destructors is a dead-end. This is the greatest mistake of such languages like Zig or Odin.
I programmed in rust a bit and can't say I'm an expert, but in my view rust mostly-solved the memory management problem at compile time and without a GC, and it works very well. The biggest con and cost I've always seen repeated so far is that "it's slow to compile", and I get that, if you're past 250 crates the final --release link tends to become noticeable, but there were improvements to incremental compilation.
On the other hand - looking at the syntax from this post - Zig feels a blend of javascript, python and golang syntax that still requires memory management. So a nicer-written C that inherits all the issues from C? From the post: no functional programming, data mutation, memory leak, double-free, memory corruption.
Personally I'd rather trade a couple minutes of final link every time when this is the other option.
As a long-time low-level programmer, and as someone working on a popular mainstream language, I find Zig fascinating, and I also think it addresses a long-standing problem in low-level programming. I'll get to the problem later, but the fascinating part is its use of partial evaluation (comptime) as a single coherent mechanism that replaces a myriad of other partial-evaluation mechanisms (macros, templates/generics, constexprs). That one mechanism is the core of the language, like macros are in lisps, and that design - whether you like it or not - is revolutionary. It's never been done before (other languages have partial evaluation mechanisms that are almost as general, but they're offered in addition to, not as a replacement of, other features).
> rust mostly-solved the memory management problem at compile time and without a GC
"Mostly" does a lot of work here because 1., if you look at the implementation of very efficient, possibly specialised data structures - the very thing you reach for a low-level language for - they typically require unsafe, and 2., it still suffers from the problem C++ has had for decades, which is that over time, as program changes and evolves over years, things tend to drift toward the more general mechanisms that rely on malloc/free on an individual objects, and the program gets slower and slower (huge runtimes like TCMalloc help, but not enough, because they can't move pointers). This problem, of programs that start out fast, but after five or ten years of evolution need to spend a lot of effort to remain fast, is one of the things moving collectors were designed to solve, but they require moving pointers, which doesn't work in low-level languages that are not meant to have an FFI layer between them and the hardware.
To compete with the performance of moving GCs, which allocate through bumping a pointer, like on the stack, and free memory in bulk, low-level languages need to rely on arenas (which work based on a similar principle), and Zig is the first language that makes arenas almost user-friendly and hopefully sufficiently composable to withstand program evolution. Of course, time will tell how well this works in practice.
So sad dlang never gets the credit it deserves. None of these ideas in zig are novel.
There's a formal proof asserting that if you keep up the safety invariants within an unsafe region then that will not infect other code, even in the presence of arbitrary other correctly-written unsafe blocks.
This means you can build abstractions on top of these low-level primitives to keep it contained, so consumer code never has to even think about or know there's unsafe blocks in it. The type system lets you build very powerful abstractions so these go a long way.
There's a lot of woo-woo scare quoting around how much you actually have to use unsafe code in Rust. It's fairly uncommon to actually have to reach for them in practice. Most of my usage ends up being things like converting a &[u8] to a &str when I know it's already valid UTF-8 so I want to skip the linear-time validity check. Very rarely do I have to build data structures with complicated pointer juggling, because there's often a library that already does what I need!
> which is that over time, as program changes and evolves over years, things tend to drift toward the more general mechanisms that rely on malloc/free on an individual objects, and the program gets slower and slower
What are you talking about? I've never encountered this and I've been using Rust for 10 years.
We could use rust. But it wouldn’t give us anything.
I think the idea is that a small program can organize its allocations and data structures to minimize number of calls to malloc, e.g. with preallocated workspace structs, or slab allocation, and similar approaches. But as a program gets bigger, there's a pressure to have looser coupling, to have subsystems with simple convenient APIs which leads to them doing on-demand malloc calls internally, rather than having consumers pre-allocate their needed workspace. Because that kind of workspace management results in more complex APIs and more burden on the consumer.
That said, I don't really believe it either, at least for the kind of codebase where it would matter (scientific computing, in-memory DB server, etc). A codebase that places an emphasis on minimizing heap operations in hot codepaths can do so by consistently using workspaces and allocation-avoiding APIs. I don't think it's so difficult really, but it does take a conscious design decision to do so. But writing something like a web browser in this way could be annoying due to most data having wildly variable sizes, and zig's arena concept would be very handy -- but rust has crates like bumpalo for that purpose.
My personal mantra: "Think in FORTRAN, code in Rust/Julia/C++". But I'm mostly working on HPC-style code where I don't have to do with wildly varying input or output sizes.
Except that's not composable - not only do you need specialised data structures, but all (transitively) allocating calls need to be specialised. That's the exact same issue we have in C++, and that's the issue Zig seeks to address. BTW, just the other day there was a post here about a language with another interesting approach, but I have yet to give it a close look: https://github.com/aardappel/goose/
> But I'm mostly working on HPC-style code where I don't have to do with wildly varying input or output sizes.
There you have it. The problems arise more quickly in concurrent rather than parallel code, and when there are lots of features added over the years that touch the hot paths.
> in-memory DB server
Actually, here there can be big problems (as it's also about concurrency rather than parallelism). Last week a colleague of mine looked at Moka and saw that it could only offer half the throughput as Java's Caffeine at the same latency and RAM footprint (almost; the Java program used 5% more RAM). When he looked into it, he saw that over 40% of the program's CPU was spent on the epoch-based reclamation.
Most crates for containers will be written such that the container types take an optional allocator type parameter that defaults to the global allocator. You can set it and it transparently uses the other allocator.
To improve the ergonomics, you'd define local aliases that use that allocator.
type MyVec<T> = Vec<T, A = MyAlloc>; with_allocator(&arena, || {
third_party_library::do_work()
});
but custom allocators are rarely used in rust because they're simply not needed the vast majority of the time. if your language is not memory safe and you need to manage memory yourself, they're more important. but this isn't the case with rust.
c and zig folks are obsessed with arena allocators particularly because they can group lifetimes of individual objects, reducing the amount of malloc/free calls and thus the amount of use after free, double free, nullptr derefs, or leaks that can occur.
in rust this isn't a concern so custom allocators are only used for performance reasons.
but it turns out that in performance sensitive areas, you generally use custom data structures or those that already have their own allocation strategy baked in, like the generational_arena crate.
most of the time you are not calling thirdparty crates that allocate in performance-sensitive regions. either the crate is designed for this usecase and already uses a performant allocation strategy, or you're writing your own code here.
and in the rare case, you can trivially vendor the crate and pass your own allocator into it, or toggle the global allocator for callers.
but you also need to benchmark first before choosing an allocation strategy because it's not clear that a custom allocator will always guarantee better performance anyways.
and btw zig doesn't guarantee this anyways. you could pull in a dependency that instantiates their own allocator. at least in rust almost all crates use the global allocator as a default which lets you swap it out. if a zig dependency uses their own allocator the only recourse is to fork it.
rust doesn't have a performance problem, so any claims about it's custom allocator support leading to poor performance is unfounded. and thus so are claims about the superiority of zig's approach to allocators.
> What are you talking about? I've never encountered this and I've been using Rust for 10 years.
Okay, but I've been doing low-level programming professionally for 25 years, and have encountered this over and over in large programs (over 500KLOC) as they evolve.
It's just that sometimes some of the abstractions you need to build go outside what the ownership and borrowing system can model. And when you don't need to do that (which is 99% of the time) you also get all the benefits of the ownership/borrow system for free.
I mean, someone can think it's solved for them, but if they're asking why others don't see it the same way and why many expert low-level programmers are at least intrigued by Zig, this is why. I prefer a simpler high-performance high-level language for high-level things, and a simpler low-level language for low-level things, and I dislike the C++/Rust approach of combining them into one complicated language. Some may think you get the best of both worlds; others, like me, think you get the worst of both worlds.
Suppose you're writing a program that's mostly high-level, say some kind of concurrent server, and it's large-ish, say around 1MLOC (most C++ programs I've worked on were significantly larger). Because the language is also a low-level language, it has low-level constraints, so:
1. It needs to use an AOT compiler, and consequently to get good performance you need to use less general mechanisms, such as direct (as opposed to dynamic) dispatch and even manual monorphisation (with generics/templates). These are viral, so they have to be carefully chosen (you can't monomorphise everything or you'll get machine code explosion). Five years later you need to make a big change that requires more generality, and then you either have to reconsider all of your manual optimisations, which is expensive, or go for more general constructs (dynamic dispatch) and the program gets slower.
2. It needs to use machine pointers (i.e. you can't enjoy a moving GC), and so you try to use the stack as much as possible (which you can't really do for anything dynamic), or suffer the high cost of malloc/free on individual objects. As the program evolves, you need to make things more general, and objects that could live on the stack now need to go on the heap, and objects that lived on the heap now may need to be shared among threads, in which case you often add the additional cost of refcounting GC. Of course, you want to use arenas in many cases, but they're very, very hard to use in C++ and Rust.
You'd be better off - performance-wise and maintenance-wise - with a good optimising JIT and a moving GC. This was exactly a problem with many C++ programs that didn't really need a lot of direct hardware interaction - everything worked great for a few years, and then the evolution and maintenance costs became really high (or the programs became slow).
Now suppose you're writing something low-level, i.e. you really need to interact with the hardware and/or OS directly a lot, and want to control everything - where everything is in memory, exactly when it's initialised, exactly when it's freed, exactly which operations are executed and when. But now you have a language that's also high-level, so it has a lot of implicitness that hides from you the things you want to see (and in Rust's case, you lose the safety). Best case scenario, you rely on disciplne and avoid implicit features, but then you also need to avoid much of the standard library.
Anyway, combining high and low level in the same language was C++'s dream: one language for everything. Of course, for a while we didn't know about the maintenance problems, as those appear only years down the line, but more importantly, there weren't really high-performance high-level languages back then. These days, with lessons learnt and with more options, I prefer a language that focuses on being high-level for high-level stuff, and a language that focuses on low-level for low-level stuff. If you really need both kinds, use two languages.
You haven't been doing any Rust though. You seem to think you can extrapolate your C++ experience to Rust. That's preposterous. The actual Rust programmers can't recognize this theoretical problem in their Rust programs.
And if you look at other comments in this thread, many engineers have this mentality of "just use a crate, it's probably optimised already". They might not have performance problems immediately or obviously but it's more like ten thousand papercuts - a few allocations here and there, a few extra copies here and there and you've got a way slower program than it should have been.
In general "unsafe" does not compose.
"if you keep up the safety invariants within an unsafe region"
This condition is doing a lot of heavy lifting.
I'm curious why you think that statement is doing heavy lifting. It's much easier to write and verify that a few lines of code are correct than it is to write and verify that an entire program is correct. But that's the norm in C and Zig, and historically people haven't been very good at it. That's why we try to do it as little as possible.
The reason it's not "the norm" is that (especially with spatial safety taken care of), not every line is equally dangerous at all. Still, there's no doubt that more guarantees help, but that is only when all other things are equal. If you pick a low-level language for mostly low-level things, so Rust doesn't offer safety for the trickiest code, and furthermore it makes certain things harder to see because the language is more complicated, then things become much less clear. Obviously, when the vast majority of the trickiest, most important code doesn't need to be low-level, Rust would probably be safer on the whole, but in such situations I see no reason to choose either Rust or Zig. You need to choose a low-level language if the core of what you're doing needs to be low-level.
Is there a word missing before "memory"? Seems odd to specifically call out spatial memory safety when memory safety subsumes it.
You must reason about the invariants in unsafe code on a global level. In particular, you could have unsafe code in crate A, whose data are then used by crate B. It could be fine. But then crate B changes its implementation which now violates the invariant expectations of crate A.
Is this backwards? If B consumes data from A then to me that does not imply that A depends on anything from B; for a more concrete example that sentence reads to me like A is basically "throwing data over the wall" to B and whatever B does with said data is of no relevance to A. As a result, if B changes that shouldn't affect A.
Also for what it's worth I get the impression you and treyd might be talking about slightly different things when talking about whether unsafe code composes. I believe treyd is referring to the RustBelt series of papers [0, 1], for which the statement "unsafe code composes" means (at a high level) that adding a module with a memory-safe API to a memory-safe system will result in a memory-safe system as long as the implementation upholds the safe semantics. Yes, the last bit can be a rather significant caveat, as you said.
What you're talking about seems more along the lines of needing to look beyond the boundaries of unsafe blocks to prove that the unsafe block upholds its invariants, which is also true. I think you only need to check within whatever safe encapsulation boundary is relevant, though, rather than globally.
[0]: https://people.mpi-sws.org/~dreyer/papers/rustbelt/paper.pdf
To address the problem that once integrity can be violated anywhere, only global analysis can prove that nothing bad happens, we've done two things:
1. We require the application to explicitly permit any integrity violation by a module; i.e. a library can't allow itself to violate integrity. This is a principle we call "Integrity by Default" (https://openjdk.org/jeps/8305968).
2. We try to minimise the need for potential integrity violations (this is very different from Rust, which requires unsafe even for things like benign write/write races, which are fairly common, and various basic data structures). Over the years we've offered safe replacements for things that used to require Unsafe. In other words, clearly demarcating unsafe code isn't enough if it's needed at all in many situations.
It isn't perfect, of course, as some libraries do require unsafe operations for direct interaction with native code or with memory, but their number has been greatly reduced, and they cannot do this without the application's explicit approval. Interestingly, this has annoyed library authors who want to do unsafe things but don't want to application authors to be alarmed because "we know what we're doing," and it's also annoyed some application authors who want to use such libraries and are forced to explicitly add permissions. But I think that the community, as a whole, has eventually accepted this because the harm done to those who don't care is small (they just need to add the permissions), to those who do care it helps a lot, and because fewer and fewer libraries require "integrity-busting" permissions, many applications need to do absolutely nothing and get important guarantees for free.
I know this paper [0] is quite old at this point, but the mention of benign data races reminded me of it. Would you happen to know how applicable it is to modern memory models?
[0]: https://www.usenix.org/legacy/event/hotpar11/tech/final_file...
Note that AT&T, where UNIX and C were born, the language they were researching as C replacement was Cyclone, not something that is not much different.
I don’t think it’s an accident that it has succeeded as multicore took over. We are now well past a point that a task that can be split with 70% efficiency into multiple parallel tasks is 5-10x faster than the optimal sequential solution. Expensive multicore machines existed when Rust was a baby but it didn’t really catch on until 4 core was common in consumer hardware. And now I have an ancient laptop with 16 cores.
But Rust is also good for producing correct code to run on those systems. So it benefits twice.
The C interop is a huge win as someone who wants to do more posix/wayland projects.
Kelley first created Zig when hr was working on a digital audio workstation and found most existing languages to be awkward for working with particularly hard real time requirements, but still wanted something more modern than C. Im speculating here, but I believe its advantage over Rust for that specific application is that you have tighter control over exactly when memory is allocated and deallocated, and how data is laid out in it. Rust wants to tie allocation lifetimes to scope in a very fine grained way that I would guess is beneficial the vast majority of the time, but does still make it harder to reason about when you’re about to stall out the CPU while the allocator does its thing.
Rust had like 3 allocating types total. If you aren't working with extremely deeply nested 3rd party types it's trivial to identify when allocations happen. Hell you could throw a lint rule together in like 5 minutes to warn on it if you're really worried. Besides Drop (excluding async) is there even any hidden control flow?
> Im speculating here, but I believe its advantage over Rust for that specific application is that you have tighter control over exactly when memory is allocated and deallocated, and how data is laid out in it.
Rust has almost exactly the same semantics for controlling allocations and deallocations, it just prevents you from screwing it up and not freeing something or using the allocation after freeing it. You still have to pass around your reference in your call stack until you no longer need it.
> Rust wants to tie allocation lifetimes to scope in a very fine grained way that I would guess is beneficial the vast majority of the time, but does still make it harder to reason about when you’re about to stall out the CPU while the allocator does its thing.
It's really not substantially different. You allocate ahead of time or don't allocate at all. The only real difference is you might want to use an Option instead of an uninitialized pointer because it's semantically more correct and harder to screw up.
So, in the case of Zig, every function that wants to be able to allocate or deallocate heap memory needs an explicit reference to an allocator. That means that you can tell whether a function might allocate memory from its signature. It also means that changing a function so that it can allocate is explicitly a breaking change.
That’s a really interesting design decision. And the reasons why someone would or would not want something like that baked directly into the language are so much more interesting than bickering about how technically with proper discipline you can have that kind of control in any non-GC language.
In practice that's not the case, as many objects own a reference to their allocator. It's still explicit, but it might be hidden in the signature, especially if you have some sort of interface that can take an allocating and a nonallocating data structure alike.
However, there's no global allocator in zig. You simply cannot call the language's equivalent of malloc() because it doesn't exist - at least not as a global symbol. That leaves you with three choices: 1) Define a global allocator; is a valid choice and would make a zig program more like C, C++ or Rust in terms of not having to think about scope-level allocation patterns 2) Pass an allocator into that scope (this is the community convention) 3) Create/instantiate an allocator itself inside that scope
(1) would be valid, though may not be idiomatic; global allocator like malloc becomes an opt-in
(2) Expensive and inefficient for most scopes, though not all.
(3) cheap, idiomatic but potential for noise/boilerplate
I mean std.heap.page_allocator is global, and there's only the one, and you can call it from wherever (just as you can malloc). Same with std.heap. c_allocator, which is... malloc! you can also create your own global allocator.
Don't do this in libraries ofc or the ghost of Andrew Kelly will haunt you in hour sleep.
Seriously? Categories of types maybe, but literal types it's more than that.
Even closures allocate if they need to capture their environment.
When you want to have a closure allocate an environment, the closure itself does not: the Box you wrap it in, which is a stdlib type, does.
Zig and Rust are equivalently "low level". Zig isn't any closer to the hardware than Rust is.
> but I believe its advantage over Rust for that specific application is that you have tighter control over exactly when memory is allocated and deallocated, and how data is laid out in it.
Rust gives you all this, too.
Zig's primary (possibly only) advantage over Rust is that it has much faster compilation times.
The industry where it seems strongest positioned is embedded. Will it actually break into that domain? No idea.
Microbenchmarks are cool, but better algorithms are where you get faster code.
And inherits all of the benefits of C. C is the foundation of the computing world. "C, but not built 50 years ago" is, by itself, a tremendous value add to a programming ecosystem that has largely abandoned attempts to write a truly performant language in favor of handicapping programmers with fully automated safety.
Rust is a low-level language for people who don't write low-level code. Zig is for those who do.
let mut arena = Bump::new(); // create arena
let foo = arena.alloc(Foo { x: 42 }); // allocate item in arena
bump.reset(); // clear arena
foo.x += 1; // compiler error preventing use-after-freeYes, on paper zig has more features than C, but what zig has is explicitness. C has a big murky space of implicitness. For example, there might be 5 different zig features which can be used at various times you might use a void* in C, buy the conceptual space of void* fully contains(and then some) the spaces of those zig features.
I would have completely expected that.
All of the Handmade "C successor" languages seem to have this obsession, including not only Zig but Odin, C3 and Jai.
For some toy problems you can do clever allocator tricks and get a huge perf win. For example Jai and Odin both seem to really want you to write code which can throw away a "per-frame" arena periodically so they're not paying to track allocations in the arena because they're all thrown away at the same time.
But a lot of real world software just isn't that simple. This doesn't make such features worthless, it just means they're one of a thousand tools the experienced developer could want in their toolkit, not really deserving headline status.
Allocators have been in wide use long before the 2020s but I agree there does seem to be a resurgent interest lately. Although I would argue it's part of a more broad trend of focusing data driven design. Which makes sense because accessing main memory is one of the slowest things your program can do.
They do, but not necessarily together with generic, standard containers.
When you find yourself wanting a nonstandard allocator, you usually want it because you want it to have some interesting property. It's not necessarily trivial to fit that into the interface of something like `std::vector`, or `std::unordered_map`, etc.
Here's my take as a game developer: 99% of use cases for custom allocators are scratch allocators for doing stuff within a frame. 95% of those are much easier to serve by just amortizing allocations by storing things in an `std::vector` (or equivalent) that gets cleared every frame. You can use linear storage to back many interesting data structures, including queues, ring buffers, priority queues, binary heaps, etc., and that's more than enough for a large number of systems in a game.
The overwhelming majority of the time, more complex data structures (like hash maps etc.) have a longer lifetime than the current frame, because the whole point of using them in the first place is to amortize lookup time across frames.
The important part is a language where the standard library isn't special, and Rust has this property, too. So in domains where things like per-frame allocators are useful, you can still have them. That capability just isn't cluttering up the more common path where that isn't useful.
I haven't used the relatively new C++17 polymorphic_allocator, though, maybe it fixes this.
What does that mean?
Zig doesn't force or even tends to prefer one way or another. If I want unassuming heap allocations that can be reclaimed in any order, there's an allocator for that. If I want an arena to discard at the end of something like a request or a video frame, there's an allocator for that. If I want to use a fixed backing buffer for the allocations, there's an allocator for that.
The point is that the standard library doesn't assume one or the other, which seems good if the problem is that "real world software just isn't that simple" in the more general sense that there's no one-size-fits-all allocation strategy.
The automatic solutions are usually pretty good and usually the right place to start. But if performance is a priority, you want options.
BTW, “per-frame arena” is part of a general pattern of a repeated interval of work doing significant allocation. This is really common in software of all kinds… servers that process requests (like web servers and database servers) and typical command line tools.
I haven’t tried to replicate this for myself. And, even assuming for the sake of argument that it was definitely true back then, a lot can happen in 20 years. But still, it does speak to wanting options when performance really is critical.
You can generalize this far beyond per-frame semantics. Think per-http-request, per-pubsub-message.
Per each, you can create a new virtual.Arena, set it as your context.temp_allocator and use it for the entirety of the request or message. Afterwards, throw it away.
Sometimes using a global one isn't the best thing (it's often a good idea to specialise base on allocation size, reuse and lifetimes), but I've used them quite a bit in C++ over the past 16 years doing HPC for graphics, rendering and simulation, so calling them only useful for "toy problems" likely shows you just haven't found a need for them in what you've been doing.
this goes back decades, its not just a feature of the 2020s. as a systems programmer I always want this, and the idea that allocator state should be completely hidden and implicit is shortsighted.
but yes, it is a bit onerous to pass around allocator(s). the real complaint that I have is that if 'malloc' is global and a compiler primitive, then we can do things like coalesce allocations and have compiler managed lifetimes when appropriate.
explicit allocators are an important lever, its not clear to me that we could never find a way to make them possible without the minor downsides.
fn run_query(alloc) {
arena = init_arena(alloc);
defer arena.deinit();
}For example, bump style allocators allocate very quickly, but at the cost of higher memory usage and therefore sometimes worse cache locality.
The only way to know is to actually measure.
> I think it should be preferred wherever it's an option for that reason most of all.
And that’s far too broad in my opinion.
Sure, if you’re writing in a language that makes memory management difficult, like C or Zig, that might be worth it, but arena allocators apply to many other languages too.
It makes it much easier to avoid lifetime mistakes in my experience.
Using arena allocation also makes me think more about how much memory I am using and how much memory I should be using etc.
It is hard to benchmark it against just using a global allocator because it is a structural change to the whole codebase.
eg https://www.dgtlgrove.com/p/untangling-lifetimes-the-arena-a...
that being said, it's even easier to not manage any lifetimes at all :)
although i suppose some will say that you still manage lifetimes in rust, you just have full support from the compiler to make sure you do it right. that seems better to me than relying on simplification to ensure you don't make mistakes.
As for me, I’d like to keep contributing to the ecosystem, and I will, whenever I come across a project worth building.”
Idk I don’t write either well enough to have a hand in this but losing out all of this for more Imperative stuff seems like a step back.
“ No functional paradigm
Rust is technically an imperative language, but it draws heavily on functional concepts: zero-cost iterators, lazy evaluation, ADTs, pattern matching, monadic types, traits, closures, and so on. Having also spent time with Haskell and Erlang, I’ve become fairly inclined toward the functional style, and it shows in this library. It leans heavily on FP idioms:
Monadic error control via combinators like Queryable and related types Monadic-style data types like Data<T> with map, flat_map, reduce, and friends Pure, immutable transformations Combinators over iterators instead of loops Closures for local abstraction Declarative macros as a small embedded DSL Sum types and product types”
Even hardware (GPUs) that functional language could trivially exploit, it’s still higher performance to write low level code and manages all the memory imperatively
I'm glad NVIDIA found a way to make GPUs programmable and got us out of the shaders tarpit, but did it have to be C++...
FWIW I've actually worked for 6 months on a large old Delphi project. It was some performance work that, as almost always, mainly required getting the language crap out of the way. In the end I got the job done (100x-1000x speedup) but I wouldn't want to switch back to this ecosystem: Licensing costs, weird language warts there too. A slow moving ecosystem. Ultimately, I just need something that does what I tell it to do, reliably and fast, and that doesn't get in the way.
Thus we can keep filling HN with pointless comments or move on.
Here is an hint, I won't stop having my opinion, so you can keep replying every time I do them, and we will repeat similar discussion threads, or move on and touch grass or something.
I get why, and it makes it a better fit for its obvious “C++ reimagined, cleaner, and better” niche.
Happy for you.
CLI tooling counter intuitively makes for very less friction especially when you are moving very fast.
items.iter().enumerate().filter(|(_, i)| cond(i)).map(|(idx, i)| Pointer::idx(i, path, idx)).collect()
while (i < cursors.len) {
if (actual_index < arr.items.len) { cursors[i] = .{...}; i += 1; }
else iteration.remove(i);
}
But then, saying while "let Some(item) = iter.next()" everytime is tedious, so they give you .iter() - for any type that is efficiently iterable.
Nothing stopping you using a manual loop that you need to update if you change the container type.
items.filter(|(i)| cond(i)).map(Pointer::idx).collect()
items is already an iteratible so you can do direct .filter on it as well
tl;dr if the code looks ugly you're probably not taking advantage of a language feature that allows it to look pretty.
I still don’t know that I find it more intuitive or readable than the simple loop, but it’s much less awful than before.
items.filter(cond).map(Pointer::idx)
https://gist.github.com/corporatepiyush/5382d79192be9737cf3b...
Now it all feels so pointless though. Like memorizing rules to do mental arithmetic. Sure, there is still use for language expertise, but not enough to get excited over new concepts and ideas.
For years I used Rust as my hobby-programming language and loved it greatly. I never managed to land a job working with it full-time, because either the work was too niche or it didn't pay enough, or I was simply too comfortable where I was to change. And now that I finally have enough discretion over my technology choices to run a "proper" project using whatever tools and languages I want, it is not me but the AI that writes all of the code.
There's a part of me that feels a quite sad about all this. It's almost as if there actually all along existed a real final deadline on finding that "dream job". And I missed it. And while I expect this one miss to be just a small piece in the grand picture of things that we're going to lose or have already lost to the zeitgeist of agentic SWE, it feels big to me. It was my professional dream, while I still had professional dreams.
Let’s say I’m writing some concurrent code with an LLM. I’d probably feel much safer having it write Rust, rather than C. So even in a post-LLM world, languages will continue to evolve as long as abstractions can be improved.
I just upgraded a less important service to Java 27, a few days after its release (several nice features). It's cool how easy it is to upgrade nowadays.
That an agent writes most of the code doesn't mean anything to me here.
My examples are Java because that is the main language where I work.
I would argue that "concepts" actually are more important than ever. Let's take my structured concurrency example. It doesn't matter here exactly what is, but if it ends up being as important as I think it will be, I likely want to write most concurrent code that way going forward.
However, it will likely be years until agents go to it unless deliberately steered in that direction. And if I want to make agents write it, I need to review it, and if I'm going to review, I need to understand it.
I think this is why I'm not pessimistic about the profession, it still feels like what I'm doing and learning matters.
eg. you dont need to memorise sorting algorithms or be able to write them, but you do need to understand the concept of sorting, and the concept of time complexity, etc etc. knowing what data structures to use and when to use them. knowing how to structure concurrency for your problem space. many many concepts.
system design is becoming the most important thing, and to me it's also the most interesting part of creating software. and there will always be more to know.
Programming and learning new things can still be fun in the era of agentic coding.
With LLMs, I get to quicky ask: what would this look like? Why do it that way? If you suspect that the LLM isn't doing it the right way, you can still investigate that yourself.
e.g. the other day, https://rhombus-lang.org/ was mentioned on HN. With LLMs, the cost for trying this out is practically much lower.
I’d push this more towards personal preference of how code is expressed matters much less now than how maintainable it is.
There is the aspect of long type names, they often don’t have much impact when tokenized. The character count of words is nearly negligible - they often become one or two tokens anyways. But, the choice of words may have a greater impact on how the word choice weights an LLMs contextual processing of that word (a human may be able to ignore an inaccuracy in naming a bit more flexibly than some LLMs).
The main thing to change this feeling for me is the large number of articles on programming languages written by an LLM.
In 5-10 years, the people who have paid attention to these will be needed to bail us out of the mess that the rest of the slop-addled monke brains have created.
Jokes aside, have you watched 2001 - a space Odyssey?
I prefer to prototype in Golang since it compiles fast and makes for quick iteration, but at the end I ask the LLM to port the Golang to Rust.
Nice Rust enums for APIs are the chef's kiss.
I absolutely will not write anything in Python or scripting languages anymore. They're too brittle and don't have great devex or deployment stories. Especially when you can just as easily build in a typesafe language with good error handling that compiles down to a single static binary.
First I thought you were going to comment about the grating LLM-isms in the article, which made me end up not enjoying reading it.
What's the pitch?
items.iter().enumerate().filter(|(_, i)| cond(i)).map(|(idx, i)| Pointer::idx(i, path, idx)).collect()
while (i < cursors.len) {
if (actual_index < arr.items.len) { cursors[i] = .{...}; i += 1; }
else iteration.remove(i);
}
The thing about Rust is that if you can appreciate zero-cost abstractions on iterators then the language feels like the only right way to program. But many programmers either don't use this sort of programming at all, or don't care if it has a cost in languages like JS, Python, Java, etc.
Personally I like Zig a lot because it feels like you're doing low-level programming but without having to program C which is... well, https://xkcd.com/918/
> Here’s the actual difference, side by side
I realize the author put a disclaimer at the bottom that they used AI for styling, but having to wade through this stuff at work all day my brain now actively rejects Claude-isms in prose.
Why can't people just write shorter bullet pointed lists of things and post that? Just post what you put into the AI!
"Holds up"
"not a toy, but not a sprawling project either, and ideally.."
"And that’s the trap"
ctrl F "real" -> 6 usages
ctrl F "genuine" -> 4 usages
"Rust: this exact shape can’t compile."
And even if LLMs didn’t exist (or had different idiosyncrasies), the article would still be exhibiting a repeatedly weird and stilted writing style.
> Disclaimer: styling and error handling throughout this article were cleaned up with the help of AI.
The implication seems to be "light editing", but the LLM styling really comes through, so I guess that tracks.
In this case it feels AI generated with human polish, or vice versa. A couple tells are "One caveat worth stating up front..." and of course, "...the shape of the language itself...".
I actually think this might be a good thing? I'm way more aware of cliches and filler in my writing these days, and it almost always reads better when I just remove them and plainly say the thing.
Is that what they said? If that's not what they said, why are you putting words in their mouth in an attempt to weaken their statement into some completely ridiculous stupid strawman that is obviously not actually what they said?
this isn't true and hasn't been true for a while
> I didn’t put words into anyones mouth
literally read your first sentence again, and notice the word "others"
It would be nice if people would note that their posts are AI generated, and put that in the title here to make it easier to ignore
It's entirely possible I'm just getting worse and worse at picking out LLM writing these days too, who knows.
The real problem is that people are using C for the wrong reasons. C is for the development of operating systems and low-level code, not applications.
Zig is more modern but anything that does even one iota more of hand-holding or has anything that looks like a guardrail fails the test.
If you want to write applications use Pascal, Java, C#, Swift or Go.
A lot of the “high level assembly” parts of C are actually compiler extensions and not from the C spec.
libc is even worse.
i do agree that applications are probably best built in fast garbage collected language. but it also seems like go, java, C#, etc have other downsides that push people towards things like zig or rust even for apps. it also depends on what you mean by "apps". is a server an app? what about an actual native cross-platform desktop application? does go, c#, or java have a good paradigm for that? what if you want to use an oss language not tied to a big tech company? you start running out of suitable languages pretty dang fast.
you could name any application type and i could probably give you reasons why you might want to build it in a "systems" language instead of a high level one.
We're trying to solve a problem that shouldn't be solved. We're continuing and even confirming the usage of systems programming languages for application development.
Postgres and Nginx make sense in system programming languages; they’re extremely performance sensitive and that granular level of control offers them features. Interpreters are sort of the same, they interact with the OS a ton, it makes sense to work in the same language as the OS.
I do generally agree for the app tier of a web app. I wouldn’t build a CMS in Rust, but I also wouldn’t build a reverse proxy in Python.
EVERYTHING ELSE is invalid usage no matter how performance critical people claim their application is. These are just excuses for people to use a grossly unsafe language to get that last 2% of performance whilst costing the world trillions in lost productivity and security breaches.