I could see migrating from C or C++ or Python to Rust, for various reasons, but for web back-end work Go is a good match. I write almost entirely in Rust, but the last time I had to do something web server side in Rust, I now wish I'd used Go.
The OP points out the wordyness of Go's error syntax. That's a good point. Rust started with the same problem, and added the "?" syntax, which just does a return with an error value on errors. Most Go error handling is exactly that, written out. Rust lacks a uniform error type. Rust has three main error systems (io::Error, thiserror, and anyhow), which is a pain when you have to pass them upward through a chain of calls.
(There are a number of things which tend to be left out of new languages and are a pain to retrofit, because there will be nearly identical but incompatible versions. Constant types. Boolean types. Error types. Multidimensional array types. Vector and matrix types of size 2, 3, and 4 with their usual operations. If those are not standardized early, programs will spend much time fussing with multiple representations of the same thing. Except for error handling, these issues do not affect web dev much, but they are a huge pain for numerical work, graphics, and modeling, where standard operations are applied to arrays of numbers.)
Go has two main advantages for web services. First, goroutines, as the OP points out.
Second, libraries, which the OP doesn't mention much. Go has libraries for most of the things a web service might need, and they are the ones Google uses internally. So they've survived in very heavily used environments. Even the obscure cases are heavily used. This is not true of Rust's crates, which are less mature and often don't have formal QA support.
> Rust has three main error systems (io::Error, thiserror, and anyhow), which is a pain when you have to pass them upward through a chain of calls
anyhow explicitly isn't designed for what you are trying to do here. It's designed to be the last link in the chain (and complementary to thiserror, not in competition). If you are using anyhow any deeper than your top-level binary crate, you are likely to be in for an unpleasant time.
also thiserror isn't incompatible with io::Error? all thiserror does is do code generation for "typical" enum errors. The errors it generates are normal rust code though, and the fact that they're generated by thiserror shouldn't really matter?
I don't get where the idea comes from that the popular error crates make error handling complicated in Rust. Because you're right, all thiserror is doing is giving you a shorter syntax for writing error enums. You could write the exact same things out by hand if you wanted to, and from the library user's side nothing would change.
As for anyhow, if a library ever exposes that, then that's just the author being lazy and not doing errors correctly. It's the equivalent of doing throw Exception("error!") in C#.
In my experience it's not quite as automatic as you'd hope. I always often to throw in stuff like `.map_err(Into::into)` or `Ok(foo?)` to convert the errors.
Not the end of the world but I do think defending the proliferation of error types in typical Rust projects is copium.
There are plenty of reasons you can complain about Rust's error handling, but "proliferation of error types" feels like a misunderstanding of how Rust error handling works in the first place.
I love Go and used to write it heavily for anything non LLM based.
Now that we have agentic coding I just write everything in Rust and couldn’t be happier. The struggle with rust was writing it, go was made so it was easy to write for mid level engineers. Now that we have agentic coding I’m not sure Go’s value prop holds up anymore
My rust services have been nothing short of amazing from a performance and reliability perspective
In my experience LLMs (I speak mainly of Claude Code & Cursor) write very poor quality Rust.
They treat it like it's JavaScript, falling back to using String/&str needlessly instead of making new types. They do ugly `static Mutex<Refcell<` a-la global JS variables for info sharing instead of working out the lifetimes to do it properly. It loves making functions infallible and then panic-ing within them and certainly I wouldn't use them for unsafe at all - they hallucinate safety comments which are in fact, totally unsound.
Of course these are all surmountable with an experienced developer to regularly step in and unfuck the code, but forcing them into 'harder' territory where every problem is not solved by a .clone() and an Arc<Mutex<>> means they will spend minutes 'thinking' about basic lifetime issues until I step in and add the missing `move` in a closure.
We’ve developed incredibly strict and comprehensive clippy rules and found that to drastically improve the quality of the code as the LLM now should pass all clippy checks. You can add a clippy skill as well to attempt to turn “should” into “must.”
That is interesting. I make LLMs write C with the general hope that a simpler language they can manage well. That is not entirely true, though. They reason about C fluently indeed. The problem is, Claude pumps lots of bad C into the codebase if left unattended for 5 min.
So, I need some clean-up passes afterwards to get to some acceptable quality level (both by LLMs and my own eyes). At which point, Claude sees the problem clearly, for some mysterious reason.
Also, I use a C dialect heavly influenced by Go (slices, generics, no smart tricks, virtually no malloc).
> general hope that a simpler language they can manage well
It's the opposite; a language with lots of guardrails allows the AI to write better code especially as it is able to use the compiler and linter to guide it through the process. It's why OpenAI for example was able to disprove some recent theorem recently, due to the LLM converting its thoughts into a formal language theorem prover to then check its work.
Is THAT how people use AI? I thought _I_ was vibe coding by telling it to write one function at a time and making sure I understand every line it outputs.
"Vibe coding" is a term that means "Prompt the LLM with a request for a project and wait for it to finish". If you're reading and understanding anything it made, that's not vibe coding, that's agentic development.
this was true a year ago but not so much anymore. You still have to supervise the agents, but they can write maintainable code if you keep an eye on it.
For me the bottleneck now is reading/reviewing code, not writing code. As you said, AI makes it way easier to write, but do you not review the code? And isn't a verbose, cryptic language with lots of nitty gritty memory management not harder to read/review?
I'm not sold on Rust being a great language to use with AI unless the reason to use it is a lot more than just Rust being fashionable.
The verbose error handling diluting the interesting parts is one thing, but the main issue is the weak type system. Having to read the callee's code to check if it deviates from `res xor err`, or if it mutates its arguments. Figuring out which interface that `func (o *Obj) ()` is implementing, if any. Dealing with documentation that is a wall of 100 disappointing oneliners all repeating the function name.
Rust is information-dense and takes longer to master, but it's not inherently cryptic, there's a finite amount of things to know. Memory management sometimes take a bit of thought to write, but it's straightforward to review, you can trust it's correct if it compiles, you just keep an eye out for optimizations.
I don't see the difference in exploring an dense custom type system versus a flatter one. Both force you to look things up when you don't know about them.
In my opinion these problems originate in architectural style. Much of the open source written today is designed to impress the audience instead of focusing on the problem.
In my experience, Rust is only mildly unpleasant to review, if only because the GitHub PR review interface is not an IDE. It can be hard to tell why .as_ref()s and whatnot had to be used without being able to hover over a variable to see its type. This is probably because of the language's preference for type inference, though personally I would rather that than having to skim over explicit types.
Compared to Rust, Go as a language requires a lot more effort to review. You have to be on the lookout for basic gotchas like not checking if a pointer is nil, placing `defer` in the wrong place, using a result when err isn't nil, and so on. Plus, diffs are messier because unused variables are a compilation error, and _, err := can change into _, err = solely due to new lines above.
It's the same logic for human and for AI code: In Rust the compiler catches many bugs so you don't have to.
If the LLM gives you safe code you know there are entire classes of things you don't have to review for.
That said, I agree with you. My experience is that LLMs are great if you are highly competent in the domain in which you let them work. And it's probably easier to be competent in Go than in Rust.
Safe? No compiler is going to catch badly designed code, or intentionally backdoored code. Memory leaks as well. Compilers are the ground floor of validation and the least of your problems with AI generated code.
If the program design follows the principle of making illegal states unrepresentable (credit to Yaron Minsky), the compiler can catch much, much more than most people realize.
The process of designing a program like that itself catches a lot of "badly designed code". And such a design also naturally exposes many kinds of intentional backdoors, because security properties can quite easily be statically checked. For example, IDORs can be made literally impossible in such a design.
In discussions like this, I'm reminded of the William Gibson quote, "the future is already here, it's just unevenly distributed."
I found it's the opposite. Thanks to LLM's whole classes of problems otherwise solved by using Rust are gone. It's now more important that the generated code is easy to read.
Relative to Go? I'm pretty sure your Go code won't be faster if you used LLMs. If you need that, Rust is still preferred.
Relative to C/C++? That'll be very interesting. Do you have some evidence that LLMs can create memory-safe code in C/C++? It'll be truly amazing if true, but given that they apparently struggle to create/maintain big codebases in already-memory-safe languages I seriously doubt it.
IMO neither Go nor Rust are great for reading/reviewing code.
Go is too verbose and the type system isn't expressive enough. Rust code is littered with little memory management details and it requires tons of third party libraries.
I think coding agents will eventually be able to get the low level details right on their own. Reviewers should be able to focus on architecture, design and logic mistakes.
I also think we need a high level formal specification language to tell agents what we expect them to do.
> I also think we need a high level formal specification language to tell agents what we expect them to do.
Let’s make that specification Turing complete while at it.
Jokes aside, IMO it will be a good natural progression. Specify the problem statement in LLM specification, generate the code in Go/Rust whatever is the language of your choice and review the generated code to make sure it adheres to the architecture/design principles that you have set.
It absolutely should be Turing complete. I want to formally specify some constraints/invariants that any generated code has to meet, like very high level test cases.
It doesn't have to be a new language. I'm sure some existing language can be used to create a DSL that serves this purpose.
It can obviously never be complete. Some parts of the spec will always have to be natural language if we want to make the best use of LLMs.
Maybe we can have Large Logic Models instead, and they could have formalized keywords with rigid meanings? Like IF, WHILE and FOREACH maybe. Or even ASYNC if you want to be modern about it.
I do think that AI models should get better at logic. But if code generators are supposed to be tools, we have to tell them what to do. I'm not sure what combination of languages is best for that purpose.
It would be so much easier if we could precisely specify what we wanted, without all the double meanings, slang and general ambiguity that comes from using a natural language.
If only there was an entire class of well-studied languages which don't have any such ambiguity. They'd be perfect for programming LLMs! We could call them "programming languages" perhaps.
Time isn't the constraint here, but ability. Someone complaining about how hard Rust is to write is probably not capable of reviewing Rust code very well.
The usual reaction or opinion from e.g. good C++ programmers switching to Rust is that the added guardrails and expressivity are great and make things easier.
The benefit is if you lean heavily on types then successful compilation is a massive indicator in the feedback loop. Using stop hooks to ensure successful compilation after every iteration is a game changer. Go also has compilation of course but because the type system is so much more robust in Rust the compilation guarantees so much more about the behaviour of your program. You end up just code reviewing the shape and flow of data.
Code compiling is really the lowest bar of code validation, and doesn't say much of anything of the code running correctly. AI will pump out the most convoluted, over engineered, and at the same time sloppy code if you let it - and it will all compile fine.
Well, a good type system like Rust's lets you make impossible states impossible to enter/represent by the system.
Writing code so that impossible states are impossible is one of the hardest parts of software, so a good type system means that the code compiling means that the software is validated to be unable to represent certain states which is a very high bar of validation.
I suppose in your mind you were thinking of more trivial errors like typos, accessing variables that aren't available in scope, and such.
This is the main reason I use Rust over Go these days. The simplicity of Go was great for when I had to hold everything in my head and write everything myself. Rust makes more sense to me in the LLM era where I can offload more modeling/assumptions/invariants to the type system without having to be a Rust veteran.
The pinned invariants in my plan/spec become first-class invariants in the type system. It's great.
Yes, but all else being equal it is a higher bar in Rust than in Go. There are fewer things left for the human to check after a clean build+lint in Rust than in Go. The issue of over-engineered AI output is orthogonal to that.
Go was never about being easy to write (thought it is), but it was always about being easy to read and it is, by far, the easiest language to read that I've ever used (and throughout the decades, I went through Basic, Pascal, C, Java, JavaScript, C#, TypeScript, Ruby and Python). That becomes even more important if you are not writing the code yourself...
you need to know the conventions to spot what's not there (did you miss the error handling? or the magic comment for the whatever codegen serializer? c'est la vie!)
> The struggle with rust was writing it, go was made so it was easy to write for mid level engineers.
In practice, anything that makes it easier for humans to program also makes it easier for LLMs to program.
You also wont typically learn that the LLM is close to the limits of understanding your code base until after it has blown past it's own capabilities, leaving you with a mountain of code that you are not skilled enough to fix.
Java, C# are good choices as they tend to enforce a certain structure. Go, good because it's very readable even if you dont know the language.
C++, Rust are poor choices unless you are already a senior in that language.
Go is really easy to read and write, even if Go's philosophy means that some of that feels clunky because it's less featureful than other languages. It makes up for it with a comprehensive stlib that makes it trivial to build services with few to no third party dependencies.
I don't think the value prop has changed at all there. One day the AI gravy train will stop and people who used AI to punch above their weight will no longer be able to debug the stuff they built unless they put in the hard work of learning the language.
Nothing to worry about with Go in that respect because of how much it's been designed to be simple. Even the annoying err/nil checks you need to do all the time are in service of that simplicity. It gets old fast but it leaves nothing to the imagination.
>Now that we have agentic coding I just write everything in Rust and couldn’t be happier. The struggle with rust was writing it, go was made so it was easy to write for mid level engineers. Now that we have agentic coding I’m not sure Go’s value prop holds up anymore
Agents seem to have a better time with Go. Humans need to review the agents outputs and in general they have an easier time to do it with Go.
The value prop of Go in not on writing, but in reading and comprehension by people different from the autor(s).
For systems expected to last some years, this translates in reduced total cost of maintenance over the life of the system (in my experience typically 80% or more of the total cost) and facilitating traspassing maintenance to diferent people than the authors.
In use cases where Go has "good enough" performance, for backend systems with business logic and small amount of "bare metal" programming, I recommend Go to teams instead of Rust. When extreme performance and reduced memory footprint is more important than the other properties, Rust is better than Go.
For me the main advantage of Go over Rust is compilation speed. Then compared with Go Rust still rely on many C and C++ libraries making it problematic to cross-compile or generate reproducible builds or static binaries.
The minus side of Go is too simplistic GC. When latency spikes hit, there are little options to address them besides painful rewrite.
I've run into GC pauses, I think in many (most?) cases there is some class of bulky data that you can either move into slices of pointer-free structs (so the GC doesn't scan them) or off-heap entirely. The workload where GC is slow is also likely prone to fragmentation so whatever the language you'll have to deal with it.
Java with its copying GC deals fine with fragmentation albeit at the cost of more upfront memory. And even in Rust one can change the allocator to try to deal with fragmentation. But with Go there is simply no good options besides the rewrite.
Possibly in your specific application, usually there are a handful of options far less painful than a rewrite.
For the original issue of GC pauses, a narrow change is to move problem data to non-pointer-carrying types, or the bigger hammer of manually managed slices of those types. The second helps with fragmentation too. Some workloads can be split into multiple processes as a direct way to have smaller heaps. If none of those options are enough then off-heap storage lets you do whatever you want.
I do have some complaints about Go, but one of the big ones has been fixed since I last wrote much Go code and it seems like a fine choice for a lot of applications.
> For me the main advantage of Go over Rust is compilation speed.
Interestingly, Rust has quite good failed compilation speed. That's almost good enough. The usual Rust experience is that it's hard to get things to compile, and then they work the first time.
I've never been bothered by long compilation times, it gives me time to think about what the code should actually do.
To other people's usage patterns though, I imagine the group of people who don't do much with the type system rely more on running a built binary to see if it worked, which means they'll pay the full compile/link time cost more often.
Isn’t it somewhat easy to remove allocations in Go? I haven’t had to “rewrite” as such, but rather lifting some allocation out of loop. Am I misunderstanding the scenario?
Pauses are a problem with heap size and structure, not allocation rate, because the pause is caused by GC code that is O(heap size). Making garbage slower reduces the frequency but not severity. This is an issue with most GCs to some degree, there are phases of collection where the GC stops execution and the duration is relative to how much work it has to do which is based on how many objects and how much memory needs to be checked. "Concurrent" garbage collection is the approach of trying to reduce the pauses by doing more of the work while program execution continues. It's complicated and hard to get right, so Go's original GC was IIRC fully stop-the-world.
There are some fine points to the O(heap size), for example it's clearly unnecessary for the GC to scan objects that do not themselves contain pointers, and work is somewhat proportional to the total number of objects. Combining numerous small objects into manually managed slices, coming up with ways to make the most numerous items pointer-free, etc.
I learned a bit about this when an analytics workload I had ended up with unacceptable pauses (I think over 1 second), Go's GC is more sophisticated now but I think in any GC runtime you have the same considerations to some degree. Some of the best writing at the time was by Gil Tene, one of the principal authors of the C4 concurrent collector at Azul Systems, starting point here:
With backend serving many clients with widely varying performance profile of individual requests when latency spikes happen there is no particular hot loop. Just many go routines each doing reasonable thing but with a particular request pattern hitting pathological case of GC.
Yes but Rust has a lot more availability of libraries to do stuff as a result. Want to do anything ML or scientific? You at least have a route in Rust where you don’t with Go.
With Go basic stuff like url parsing or HTTPS support is written in Go and comes with the standard library. With Rust too many necessary things are just wrappers around C and C++ making cross-compilation and reproducible builds much harder to archive.
As for availability if CGO is ok, then calling C or C++ code from Go is not that hard. Also, there is always an option to just start C++ process if extra data copies are OK.
Has there been a lot of progress with ML in Rust? I don't really keep up with it because it seems like every crate ends up getting abandoned and I just gave up caring.
Rust has practically one error, it's the Error trait. The things you've listed are some common ways to use it, but you're entirely fine with just Box<dyn Error> (which is basically what anyhow::Error is) and similar.
They all convert seamlessly, and the enums make the branches explicit. Don't even need to check the documentation to find which errors supposedly exists like in Go with its errors.Is, errors.As, wrapping and what not.
An easy rule before you make a knowledge based choice is Thiserror for libraries, helping you create the standard library error types and Anyhow for applications, easy strings you bubble up.
Or just go with anyhow until you find a need for something else.
I’ve repeatedly tried using Rust and the error handling has tripped me up every time and has been ~90% of the reason for moving a project back to another language. I’m sure I’m just holding it wrong, but what I run into usually goes something like this (mind you, I have read the Rust book):
* Someone tells me to use enums for errors, in a comment like yours
* I try writing the enums by hand, implementing the error trait
* I realize that in order to use the ? operator I need to implement From on my errors (I’ve read so many comments about how awfully verbose Go errors are, so I assume I’m supposed to use ? in Rust). There are also some other traits IIRC but I’ve forgotten them.
* I realize that this is pretty tedious, manual work, so someone points me to thiserr or similar
* Now I’m debugging macro expansion errors and spending approximately the same amount of time
* I ask around and someone tells me not to bother with thiserr and to just write the boilerplate myself or else to use anyhow or boxed errors everywhere
* I try using boxed errors everywhere, which works, but now I have all of these allocations which feels like I’m doing something that will bite me later. Oh well, but now I need to annotate my errors so I can figure out what is actually happening. I guess I should use anyhow for this?
* Anyhow mostly works but this is approximately as verbose as the Go error handling that I’m told is Very Bad, and when I ask for code review most Rust people are telling me not to use anyhow because errors should be enums, at least in the API surface
I’m sure I’m doing it wrong, but as with many things in Rust, the Right Way is so rarely clear and every other Rust person gives different advice about how to solve my problem and the only thing they seem to agree on is that Rust has an easy solution and that I’m following the wrong advice. (Similarly when I had lifetime problems and half the community told me to just use clone and Rc everywhere until I had performance problems, so instead I just had different static analysis problems).
I don’t love Go’s error handling. It feels like there has to be something better than its runtime-typing. But it largely gets out of the way—creating an error is just implementing the Error method, and if you need a concrete type you use Is/As/AsType. Wrapping is fmt.Errorf. All of this is built into the stdlib and used pretty ubiquitously across the ecosystem—I don’t run into “this dependency uses a different error framework”. Error handling is marginally more verbose than with Rust if you are actually attaching context in both, and neither solves the problem of which call frame attaches the context about specific function parameters (e.g., which level of error context specifies that the function was called with path “/foo/bar.baz”). It’s terrible, but it works—feels like the least bad thing until the Rust community can arrive at some consensus and document it in The Book. Or maybe I just need to try again in the LLM era?
there are many (right) ways for writing monad transformers, and it's usually situation dependent which one makes sense. (practical aspects such as which errors do you want to merge, ignore, provide some default/fallback result; and of course overall coding style consistency helps guide this, but it's not trivial.)
(there's a lot of this in Scala too, because of the various monads/containers, eg. the built-in Future, and then Scalaz.IO, FS2, Cats, ZIO, etc...)
regarding lifetime and performance problems, the best practice seems to design the rough scaffolding of the program first, with the structs, so the who owns whom can be figured out. but this is far from trivial. Rust is very good at forcing developers to stare at these problems, but solving them requires practice and patience.
for me the tech toolbox that makes sense is TS by default (because of the super convenient type system and tooling), and Rust when the circumstances really justify it (latency, throughput, scalability, cost effectiveness, or a need for a single native executable [though nowadays this is also pretty simple with Deno], or more safety/control [no GC])
I'm so perplexed by this, because Rust errors are what make the language so amazing.
> Now I’m debugging macro expansion errors and spending approximately the same amount of time
This never happens once you've learned the language a bit more. Anyhow and thiserror are a cinch.
> I realize that this is pretty tedious, manual work, so someone points me to thiserr or similar
Claude writes Rust so effectively. It can do all of this for you now. It's effortless. In fact, I don't see any reason to use any other language unless I'm targeting web or some specific platform, or dealing with legacy code. Rust is now the best tool for most problems.
> Similarly when I had lifetime problems and half the community told me to just use clone and Rc everywhere until I had performance problems, so instead I just had different static analysis problems
Do this for a month, then it'll click and be second nature. Also Claude will make quick work of it now.
> feels like the least bad thing until the Rust community can arrive at some consensus and document it in The Book
It's difficult because it's so different. But once you get used to it, you'll realize it's the best approach we have right now.
> Or maybe I just need to try again in the LLM era?
Seriously this. You'll be writing Rust code as quickly as you would Python code. It'll be high quality. And the type system will mean that Claude emits better code on average. You'll pick it up quickly.
I think Claude may be what makes me use Rust successfully. Firstly it’s ability to deal with the tedium and secondly not needing to solicit help from people who tell me my problem is trivial while giving contradictory solutions :)
> And the type system will mean that Claude emits better code on average.
I’m curious if this is true. I believe that it emits better code than with a dynamically typed language, but as with people I don’t know that the sweet spot is at the extreme. Or maybe it is at the extreme when the context is small but as the context grows perhaps code quality suffers as it has more constraints to balance?
There's a number of things about rust that help compared to other statically typed languages.
1. the compiler gives very high quality error messages. It helps humans, and also helps LLMs
2. Rust reduces memory management to local reasoning (via the borrow checker). This means that it performs well even as context grows, because checks in one function/module are well-encapsulated to that function/module.
3. Rust can more easily obtain this encapsulation for more general properties than many other statically typed languages. In particular, rust's type system is very strong, so it's easy to take a function `func(x: T)` that relies on some implicit assumption on `x` (say that it is non-zero), and turn it into an explicit requirement. By this, I mean you define `pub struct NonZero(T)`, and provide constructors `pub try_new(t: T) -> Result<NonZero<T>, _>` that error if the condition doesn't hold. If you additionally only provide public methods on `NonZero<T>` that uphold the invariant, you can lift runtime runtime assertions to the type level. This is both good practice, and helps out LLMs quite a bit.
This is to say that rust makes it quite easy to encapsulate implementation details (both regarding memory management, as well as other details) essentially completely. Sometimes you still have invariants that need care/can't be encapsulated in the type system, but such invariants should be marked `unsafe`, so it can be easier to audit the LLM's output.
Anyway, the "more constraints to balance" is only problematic if all the constraints are inter-dependent. It's definitely possible to get LLMs to generate spaghetti code like this, but the way you fix it is the way you fix similar issues in other languages.
> This is both good practice, and helps out LLMs quite a bit.
Don’t get me wrong, I like this aspect of Rust, but I can’t make heads or tails as to whether it helps or if they just have to iterate more to figure out how to make something work. LLMs already do pretty well with a comment “this value can’t be zero” in my experience, so I’m unsure how much value the static typing provides. Maybe it lets you get by with a lower quality model, but that model will likely just spend more tokens on iteration so I can’t discern an obvious win. (shrug) I hope I’m wrong though—if I can have super fast code with the ease of LLM generation then I’m happy.
> Rust reduces memory management to local reasoning (via the borrow checker). This means that it performs well even as context grows, because checks in one function/module are well-encapsulated to that function/module.
I don’t think this is true, right? Changing a single lifetime in a function signature can easily propagate across your entire program. Maybe I’m just a Rust noob, but any time I change a field from owned to borrowed or vice versa I have to propagate that change pretty broadly, which to my mind implies consuming a lot of the context window. Garbage collection (I know, ewww, shame on me, etc) allows for local reasoning in a much more meaningful way however morally impure it may be. :)
LLMs do significantly better when they get reliable feedback on their actions (try to create any non-trivial project in some language without letting the LLM use a compiler. Similarly, talking with a "chat LLM" will produce worse code than an "agentic LLM").
Anyway, making such a (breaking) change in rust immediately tells you all of the callsites that break. You have to chase it through, but that's mechanical/low context work. More formally, you can parallelize across files with sub-agents to not pollute your main agents context window. So it really should be a "zero context window" cost.
Whether or not strict typing is strictly better is really a correctness/velocity tradeoff, the same as it always has been. For most projects something in the middle is right.
As for owned vs borrowed and things propagating quite a bit, sometimes it happens. It's often avoidable with a couple of tricks
1. always default to borrowed unless you have a good reason to otherwise
2. make your function signatures more permissive so they can support either way. This can be done by modifying f<T>(x: T) (or f<T>(x: &T)) to f<U: AsRef<T>>(x: U). The later can be equivalently written as f(x: impl AsRef<T>).
When you say "change a field from owned to borrowed", I'd generally suggest not doing that. It's generally easier to start with some owned type MyType. You can then have function signatures take &MyType as input. This borrows all the fields, and is often good enough for most functions.
If you have a more esoteric function (that needs a combination of borrowed and owned inputs), it's typically easier to define a struct for that function. The steps are
1. Define a FunctionInputsRef<'a>
2. write `impl<'a> From<&'a MyStruct> for FunctionInputsRef<'a>`, then
3. update your function to take as input FunctionInputsRef<'a> rather than `&MyStruct`, and
4. update callers with `input -> input.into()`.
It has the benefit of less churn, as you're maintaining the old def (which might be useful elsewhere), and only updating the callers in a fairly trivial way. `FunctionInputsRef<'a>` can also be defined local to the function, so it is modularized better. If you later have other functions with other requirements, it's a relatively easy pattern to duplicate as well.
> Firstly it’s ability to deal with the tedium and secondly not needing to solicit help from people who tell me my problem is trivial while giving contradictory solutions :)
I'm so sorry for this btw.
The problems are trivial once you've used Rust for n hours, for some value n. It's just that these folks forgot the learning and headache they went through.
You're going to build that same recognition and familiarity using Claude over time. It'll seep in pretty quick, I'd imagine.
> I’m curious if this is true.
Being forced to emit an Option<T> or Result<T,E> and then having to actually use syntax to get at the goods forces the code to deal with errors the appropriate way, clearly, idiomatically, and typically in a good flow that is amenable to readability and easy refactoring. Other languages without Option, Result, and sum types baked into the language so fundamentally do not have this advantage.
I feel it every time I have to work in a TypeScript codebase, for instance. It's a strongly typed language, and can emulate sum types via discriminated unions. But that doesn't convey the same advantages because it doesn't enforce anything. It's far too lose to have the same advantages Rust has.
I think you'll feel the same way as you use the language more and more.
All good. It happens in every community, but it seems like Rust has more of these problems where there are N ways to do something and none of them are obvious. Reminds me of Python where everyone swears they have a package manager that will fix all previous problems and then you invest a bunch of time into their suggestion only to find that it introduces half a dozen new glaring problems (e.g., pipenv taking 30 minutes to resolve a lock file for a relatively small project).
> The problems are trivial once you've used Rust for n hours, for some value n.
Heh, I've been taking a real stab at Rust every year since 2014. `n` can be a pretty large value! I'm optimistic that Claude and friends will help me get there though.
> Being forced to emit an Option<T> or Result<T,E> and then having to actually use syntax to get at the goods forces the code to deal with errors the appropriate way, clearly, idiomatically, and typically in a good flow that is amenable to readability and easy refactoring. Other languages without Option, Result, and sum types baked into the language so fundamentally do not have this advantage.
Honestly I use Go as my daily driver these days and while I wish it had sum types for error handling, it's really not a problem. It's more aesthetics than anything, and LLMs do just fine with managing errors in Go. There may be other advantages for LLMs with respect to Rust's rigorous type system, but I could easily see it going the other way as well (additional constraints for the LLM to focus on, taking more of its context budget that could go to the fundamental product constraints). I really don't know what the right answer is here--I suppose time will tell.
1. thiserror just does codegen of the "standard" enum things people do. if you find debugging thiserror difficult, just write out the enums manually. sure it's uglier, but (roughly) equivalent. so its preferable as synctatic sugar for enums, but doesn't have any technical benefits (in the same way that syntatic sugar never really does).
2. for boxed errors, you only get allocations on your error path. Hopefully this is a cold path so it shouldn't matter.
There is a general theme behind rust error handling though which it can be good to internalize. In particular, the more details of your errors you encode in the type system, the more powerful things are. Any error type could just be
pub struct MyError(String)
the issue is that this gives very little information to a caller on what to do with your error. If you have no callers (e.g. are making a binary) it's fine, and (roughly) what `anyhow` does.
That all being said, when designing errors a natural question to ask is "can my caller do anything meaningful with this error"? For example, in Rust stdlib, `Vec::push` can allocate. This allocation can fail, which panics. "Proper" error handling would use the fallible allocation API, and propagating an OOM error or whatever through results. For most applications, this is not an error that is worth investing that much time into guarding against, so using the (potentially panicing) `Vector::push` makes things easier.
You can take this same perspective in other settings as well, in particular separating out errors into
1. structured data, that a caller should be able to extract/process to handle the error, and
2. unstructured data, that is more used for logging, and you expect the caller to pass up the call stack without inspecting themself.
Handling both types of these errors with `thiserror` can be tedious for little benefit. I've found it useful to instead solely use `thiserror` for category 1, and category 2 does other things. This could be using `.expect(...)`. There are some crates that make this nicer (e.g. `error_stack`). But the point is that it can significantly clean things up if you only encode in your error enums failures that you expect someone to handle, rather than just e.g. log.
This does somewhat validate your point that the "right way" I've been experimenting with (and mentioned above) is not just "use this-error".
Also: a big issue with `thiserror` is the tedium of handling the large error enums (or giving up on using it "properly" and shoving together multiple error variants in some unstructured error type). that is somewhat better in the LLM era, as you can have the LLM handle the tedium.
Anything other than panic/abort on allocation failure is outside the scope of the vast majority of programs, including anything using the standard library in Rust. I wouldn't worry about Box<dyn Error>.
You're already writing Rust in a very different style if you're writing the type of code that gracefully handles allocation failure. It's to Rust's immense credit that this type of coding is actually fairly well-supported (unlike in Go), but you're already a bit off the beaten path for stuff like error handling.
If you need to handle an allocation error in the error path, then the error reporting path must abort, which means that the allocation error must be bubbled up.
There is no real solution to an allocation error inside the error path. Even if you preallocate an arena for errors, the error might be large enough that it won't fit inside the arena.
Hence the best thing you can do from that point onwards is to have an error enum with an AllocError variant that doesn't allocate. Said error won't contain any information beyond line numbers of the allocation error since you just don't have the space for it.
In the end you will basically end up with panic free code, but the error still bubbles up like regular unwinding.
So yeah you can do it, and I will do it in the future, but I personally think that the people who think this is some huge deal breaker don't understand the problem in the first place.
Do you really want that data passed back down to the caller of the allocation? From the description of the failure state you'd want to log that data instead: what's the caller of the allocation going to do if you tell it it failed with a crazy size? It already knows the size, it's the one who asked for it.
So, suppose it's a rust library -- you're locking me into whatever logging system the library author chooses? Maybe I'd like to consume the relevant data at the entry point and send it to a logging system of my choice.
A Rust library likely wouldn't be returning an opaque Box<dyn Error> to begin with. Errors are part of a library's API—it's what allows consumers to handle them—so you'd define an enum of possible errors your library could produce and return that, which would be stored on the stack.
You can do better than the errors in other languages. You can provide all the relevant information in the emum variant.
enum MyApiBindingCrateError {
// You didn't provide an
// API key. Maybe we should
// design our interface to
// make this impossible
ApiKeyMissing,
// Client was unauthorized
// to make this request
AuthorizationError,
// The entity you requested
// did not exist (404'd)
NotFoundError,
// You're sending too many
// requests to the server
TooManyRequests,
// That specific error with
// the API
// Maybe users can't delete
// folders until they're empty
// Whatever
SpecificApiIssue1,
// Some other specific error
// with the API
SpecificApiError2,
// Server didn't respond the
// way we expected.
// Here's what it told us
UnexpectedHttpResponse {
// HTTP status code
status_code: StatusCode,
// If it had a
// string-encoded body
body: Option<String>,
},
// Unhandled Issue with IO
IoError(io::Error),
// Unhandled Issue with
// request library
ReqwestError(reqwest::Error),
}
The beauty with Rust is that you can create really detailed concrete errors at the crate level. Your callers will know exactly what the actual error states are.
Your application can be a little less structured if you want. Though with LLMs, I'm using anyhow and thiserror a lot less.
I think this is a clash of terminology: a Rust enum isn't an integer with pretensions of an identity.
You'd describe it as a tagged union in some languages. So when you say you'd return an error with extra information, what that information is is associated with the specific variant of the enum.
Using yuriks AllocError as an example, if the error is SizeTooLarge, it has the size field. Other errors may have no additional data, others may have different data.
When you return an error from your allocating function, it's a known size, the size of the largest enum variant + the discriminant (tag).
There's a few confusing things here. For one, just because the allocator gave you an AllocError, that doesn't mean your function has to return an AllocError: you can return whatever error type you choose. If you want to collect a stack trace at that point, put one in there.
What value would a stack trace that includes internal allocator functions be to you? What do you lose by having to collect the stack trace at the point where your function receives an AllocError?
usually “stdout” is good enough, wrapper/runner routes output to logserver for collation and search. who cares about formats as long as it’s reasonably structured and searchable?
it depends, if the functionality represented by the library is known to require a lot of memory (or simply allocation failures are an expected part of its operation), then it should be pretty much part of the API, probably with some tracing/diagnostics interface to get the required visibility into how much memory goes and where.
but for most libraries I on allocation failure I don't expect any fancy logging system. maybe even panic is fine.
If you let the allocation error panic you will get your stack trace.
You can't have a stack trace on an error in the error path that failed to allocate. If you have a "jumbo sized" error and the error fails to allocate, it won't get reported. The only reporting you will get is that the error failed to allocate and this new allocation error overrides the error that failed to allocate.
if you have an OOM and want to log why, if your logging allocates it will likely fail as well. You could in principle work around this with enough effort, but "properly" handling OOM is typically much more trouble than its worth.
That's because the types of errors where you want a stack trace are a relatively small subset of all possible errors.
Stack traces are only useful for errors that indicate a bug in the program, i.e. something a programmers has to respond to. It's not useful for the vast class of bugs that are a result of wrong input, wrong external state, or infrastructure issues.
Rust projects tend to favor panicking over error handling for programmer bugs (which does indeed give you a stack trace depending on environment variables), or even better encoding the invariants in the type system, but there are cases where an error coming from a library are truly, actually unexpected, so both `anyhow` and `thiserror` do provide support for attaching a stack trace in those situations.
This sounds disingenuous. They explained why the language doesn't force stack traces on all errors, and then explained how to get them if you want them.
I see a very opinionated explanation, not a "this is why the language does not" explanation.
>Stack traces are only useful for errors that indicate a bug in the program, i.e. something a programmers has to respond to. It's not useful for the vast class of bugs that are a result of wrong input, wrong external state, or infrastructure issues.
This is a personal opinion, not something you can declare as the objective truth. There is a lot of value in seeing what path the program took before it encountered a eg. validation error.
>but there are cases where an error coming from a library are truly, actually unexpected, so both `anyhow` and `thiserror` do provide support for attaching a stack trace in those situations.
This is wrong because it's up to the library to attach the stacktrace, not the userland code using the library, so saying "you can get them if you want them" is not true.
If the author of the library did not decide to attach the stacktrace, your only option is wrapping it yourself, which you can only do if you already know up front all the paths that can fail. Also, you are not supposed to expose errors from a library with anyhow, they are only for application/top level code.
I'm curious, what's the value of a stack trace of another person's library functions? As mentioned, you can get a stack trace that includes all of your code, that's what was offered to you.
The only thing a library gathering a stack trace instead of you gives you is that it includes traces through code you didn't write & ostensibly aren't responsible for. If you're going to go to the effort of tracing through a dependencies code, you might as well add the stack trace yourself; it's a single line of code from the standard library to collect it, std::backtrace::Backtrace::capture().
EDIT: capture will only actually grab a trace when env vars say it should, you can use force_capture to ignore those. To get to why this isn't the default for errors you're asking for, here's a line from their documentation:
> Capturing a backtrace can be both memory intensive and slow
Ideally (in my ideal world), it would be Result<T, E> that holds the backtrace. The value is that I don't know up front which method call is going to cause an error that is hard to track down, which is why I don't see how "instrument your calls with backtrace yourself" helps. It requires that I already have some idea about the execution path, otherwise I don't know where to put the backtrace instrumentation.
Since Backtrace::capture() is already tied to an env var, we could have the backtrace on Result without affecting performance, since you would only enable it for debugging. This would allow you to eg. easily track down a situation where you see in your prod logs that you are encountering a lot of "validation error: string is too long" but you can't tell where it is coming from. Flip the env var, redeploy the application, read the backtrace, turn off the env var, fix the problem.
> track down a situation where you see in your prod logs that you are encountering a lot of "validation error: string is too long" but you can't tell where it is coming from.
Capturing a stack trace is a hefty operation: making it happen on _every_ error creation, which would include creating an error in response to another error (like <failure to allocate> causing <failure to create object>) could easily grind a production server to a halt. Especially if there's correctly handled errors happening: every one of them will pay this cost, every time.
It sounds like a really specific problem here; the log line that's happening is generic enough that it doesn't identify which line of code is emitting the log, so you can't just add `capture` to that line (what logging system even does this? printf logging?).
I feel like we are talking past each other, because you ignored the whole part about "it is already tied to an env var, and it would be still tied to an env var" that you would only enable on demand, so who cares if it's a hefty operation? Also what about other languages that capture stacktraces all the time with exceptions, or scripting languages with type errors, where you can't even turn it off? Rust is somehow different?
It is a specific problem, so what? You see that you are sending 500 from an axum handler, and you are logging "serde deserialization error: line 4 invalid", wouldn't it be nice to see where that came from, without instrumenting all the places you are deserializing something?
Rust errors are not exceptions. Catching exceptions is unbelievably expensive in all languages that support them, compared to handling a Rust error value.
Some languages have exceptions as the only error handling mechanism (C#, Java, scripting languages), and it sounds like that's what you're used to. But this is also broadly agreed to be a severely limiting factor of those languages, resulting from being designed at a time when we didn't know better.
If you want to go fast (and Rust does), you cannot be catching exceptions in the hot path, and you certainly can't be throwing exceptions that carry stack traces, because walking the stack to build up the stack trace is many orders of magnitude slower than returning an error value.
Rust's error handling modes are designed with the benefit of hindsight from all those other languages from the last few decades, and reflects the fact that errors broadly fall in two categories: validation failures and programmer errors. The former should be a cheap error code that can be handled, the latter should terminate the program/thread/task and give you enough information to diagnose the problem.
I can't reconcile what you're asking for with the situation you're describing. If every single error everywhere in the program created a stack trace and logged it at creation time, your error would be lost under an avalanche of benign errors that are handled. And if you only want to selectively log _that_ error that's interesting, you need to selectively modify the place that logs it, which you don't want to do (because you don't want to have to find it).
It sounds like what you want is the errors you log to always log stack traces. Which is a fine position, I do something like that. It's just not something that can be the default, because it can't be done everywhere.
…the "dataset_id" path variable is parsed straight into the dataset_id arg, and a query string "verbose" is parsed into a boolean. Super convenient compared to Go, and you type validation along with it.
Many other things to like: The absence of context.Context, the fact that handlers can just return the response data, etc.
I'm not sure if that's a great example. What kind of errors could ShouldBindQuery return?
I would assume Axum returns a bad request error for you when query parsing fails, but if you do want more control over how the error is handled, you can change the parameter type to Result<Query<bool>, QueryRejection>, and the type system itself documents precisely what errors you can match against.[0]
To be fair, it's not -quite- as useful - `req.PathValue` only returns `string` and you have to do the conversion to other types yourself which could lead to a faffy mess of code.
I agree! The line early on about this being for backend services caught my attention. I love the Rust language and use it for embedded firmware and PC applications, but still use Python for web backends, because Rust doesn't have any tool sets on the tier of Django (Or Rails). It has Flask analogs, without the robust Flask ecosystem. I have less experience with Go, but would choose it over Rust for web backends, for the same reason you highlight: The library (including framework) ecosystem. I am also not the biggest Async Rust fan for the standard reasons (The rust web ecosystem is almost fully Async-required).
Conversely, the Go community tends to actively shun frameworks, especially anything Rails-like, and will tell you to just use the standard library. Which is good advice, the standard library really does have everything you need. But it's also roughly on a par with what's available in Rust (though as someone said above, the Go stdlib routines have been heavily, massively, tested in production by now, and are fully mature and load-bearing).
Interesting! Are Go backend building custom auth, admin, DB ORM/migrations/auto migrations, templates, email, dev server etc for each project? Or each person and org has their own toolkit they use?
There are various libraries people use for auth, etc. But rolling your own isn't hard - Go has (e.g.) bcrypt in the standard library, so most of the heavy lifting is already done, you can write a solid auth implementation in <50 lines of code using that.
Generally Go prefers libraries to frameworks. Wrap the hard bits up into a library that can then be used widely in any implementation, rather than rolling it into a one-size-fits-all implementation that doesn't really suit anyone properly.
I second that no-ORM statement. I even follow that in Java. Object mapping is fine, but I’ll write my own SQL, rather than debug obscure (to me) HQL queries.
“we” are all different and i can tell you from experience that there are also many people and teams who use go and prefer ORMs and frameworks and do not build everything from scratch …
This is typical Go culture. If it is not readily available in the language or the standard library, it's evil. It's an easy cop out to explain away the gaps in the ecosystem.
Not long ago, the Go team was saying that generics are evil for that very same reason.
Rust backend is like this too, albeit softer. The gaps are explained as "Why would I want that/I don't need that" instead of "evil".
My GitHub is dominated by rust projects, and I think it's the nicest overall language. But not nice enough to write bespoke solutions for problems that have had robust solutions since before I started programming! There is a basic set of functionality most web apps use, and that hasn't changed in a decade+; I don't want to re-write my own version of this, nor fight compatibility problems from (comparatively) poorly-integrated and documented libs.
I am trying to make good decisions, and am weighing "This long-standing solution does everything I need, and is easy to use and well-documented etc" vs "People on the internet are telling me I don't need it, or I can use X rust lib instead". It feels like the "We have McDonald's at home" meme.
I think it's contextual... IMO IoC/DI in JavaScript/TypeScript is evil, because there's a built in reference system and it's easy enough to override in testing frameworks already, so IoC/DI has much less real value and is more likely to cause harm than help.
I would say that ORMs are often similar, in that depending on the environment and Object Mapper is more than enough for most use cases, again in my opinion.
I think few people would want to use an ORM for the stuff you use Go for, but there are things like SQLC which can generate a lot of your "dynamic DB magic" without actually being a real dependency. You can set SQLC up to run in a container in a completely isolated environment, and then use the output, but you can frankly also just maintain the SQL which frankly isn't that different than using an ORM once you've set up the automation with ridicilously strict policies.
We use Go for some of our more vital backend parts. We mainly use Python for entirely different reasons, but since we're an energy company it's nice to have a standard library that can do everything without any sort of external dependencies. It's not because we have some sort of "not invented here" fetish, it's because we have to write and maintain a literal fuckton of complaince documents for every external dependency we use and it's already a full time job for just for Python in our information security department.
>Are Go backend building custom auth, admin, DB ORM/migrations/auto migrations, templates, email, dev server etc for each project?
lmao, basically, yes. except when you bring this up ppl think it's not a big deal / a means for self-expression. having to sort through which libraries you prefer to glue together is a kind of freedom, if you squint hard enough.
I get the "you're reinventing the wheel!" thing, but trying to fit a formula 1 car wheel to my horse-and-cart system really isn't working for me. I need a different wheel, so I'll just build my own. Luckily there's a ton of good libraries available that have all the tricky bits covered so it's relatively easy to build my own wheel.
For me going from JVM and CLR ecosystem of programming languages into Go for backend development is a downgrade.
The language design makes sense in the context of Oberon (1987), and Limbo (1995).
Now when there are so many options finally building on top of Standard ML, and Lisp heritage, having to settle with Go feels like a downgrade.
I code since 1986, if I wanted if boilerplate error handling, or having cost as the only mechanism to declare constant values, there have been plenty of options.
Rust does not have three error systems. It has one: the Error trait. io::Error is one of many that implement it (nothing special about it). Errors defined via thiserror also implement it.
“Anyhow” just allows you to conveniently say “some Error” if you don’t care to write out an API contract specifying types of errors your function might spit out.
Not sure what you mean by that. If you're consuming the API of a crate that has functions that return errors, you're not really dealing with a "framework", you're just dealing with whatever the `E` is in the `Result<T, E>`. If that `E` doesn't implement std::error::Error, I'd consider that a deficiency (even a bug) for that crate. (Yes, I know some crates want to support use in `no_std` environments; that's what features are for.)
If I care about the specific variants of error that a function can return, so I can do different things depending on what kind of error occurred, I'll read the docs and match. That's not really a "framework" thing; that's just a basic thing that anyone has to do in any language in order to consume an API. If I need to propagate the error, I'll do so (either directly, or by wrapping it in a variant of my own error type). I don't see how any of this is "framework"-y.
A crate's decision to use thiserror (or not) does not matter to me. If a crate exposes `anyhow::Error`, that's a lazy choice and bad API design, but still "works" and I generally don't need to care about it.
Or is there something else you meant when you said "error frameworks"?
I guess you might have to if you need to use a library someone's written that doesn't implement the standard.
Writing primarily applications, I couldn't tell you what error handling frameworks my dependencies are using: I literally don't know, and haven't needed to know in order to display, fail, or succeed.
EDIT to add: I use anyhow for this, so I should also add "add context to an error when I fall" to the list of things I do.
What's the standard? I'm not being snarky; I'm going down the thought process of how this would work in practice.
I am on team Io Error [on std rust]", somewhat arbitrarily. If I call a lib that is on Team Anyhow, or Team Custom Error Enum, I will have to do some (Straightfoward, but a little clumsy) conversions if I want ? to work. This is complicated by being able to impl From<ErrorType1> for ErrorType2 only in one direction if you don't control the other crate. (due to the orphan rule)
By standard I meant an error type that implements std::error::Error.
EDIT: Which I assume all my dependencies have done, given that anyhow is able to consume all of them.
I specifically called out writing applications as my use case: my only objection to tptacek's note is the somewhat universal "in practice". The burden for designing errors for a library that others will use is higher, but that's far from the default/universal experience.
Many more people are going to consume libraries & not produce any of their own, and I think my experience is representative there.
Not rust specific, and most certainly not a criticism of you - but I hate when people call a lib that errors, then just bubble that error up.
I mean the error is supposed to be tailored to the audience - I guess what you are saying is that you handle the error by saying "I called foo with X, Y, Z, and got this error back" in the logs - which your caller then also does - producing a log message of
ERROR: I called Foo with X Y and Z and got error: Die MF die
followed by
ERROR: I called Bar with X Y Z and a and got error: ERROR: I called Foo with X Y and Z and got error: Die MF die mf (still fool)
And so on and so forth.
If the counter is - don't log, that's fine, but you have to know where in the call graph that error state was reported to the logs
I have tried to figure out some kind of unification between "collecting error state in a function", "logging error state", and "return error state to a parent".
I haven't found any satisfying solution to it all; collecting information for logging vs information that a caller would want... I've been meaning to investigate tracing_error to see if it brings it all together.
Regardless of language - if you find a good, clear answer - blog the hang out of it - I for one have been searching for the right way to manage this, and it's not (yet) clearer - other than what I've said so far
Yeah - but that's the same as my final point - you have to know who is supposed to manage the error/log - all the way up (and down) the call graph
edit: I've just finished debugging a multi system chain - FE -> SNS -> SQS -> Lambda -> DynamoDB -> Lambda -> Webhook -> My poor code
My code has multiple layers - and I was trying to find where in the very long chain of calls the data was being mangled
It turned out that there was an unlogged error, which was mismanaged by a caller - there's no shade here - the caller was handling the error how it was designed to, but by not logging that there was an error - it took a minute to understand.
I’m sorry but this is simply incorrect and I think stems from insufficient understanding of best practices and/or how the Error trait composes, as the other replies alluded to. There’s a lot of reading material on the subject but unfortunately I can’t recommend anything off the top of my head
How it reads to me: "This is easy. No problem! There's reams of pages written about it, because it's easy, which is always why whole treatises get written about stuff. I can't think of the best to recommend right now, not because the topic is nuanced and there's no best one and you probably have to read many different things to determine whether to e.g. reinvent pointers as integer indexes into arrays, but don't take from any of this the idea that any part of this is complicated. Noooo!"
I mean, you said it way more concisely than I did. Good on you!
I was not asserting it was easy nor trying to attack you. Merely recommending you find reading material because your understanding is lacking. You’ll probably find it scratching an itch when you realize how nicely it all composes together.
Though I have little hope for that after your little drive-by at memory safety further showcasing you’re way out of your depth
I feel pretty comfortable with my level of conversance with these issues, but if you think "you're way out of your depth" is persuading readers of this thread, have at it; you have my permission to establish to those readers that that's the level you're arguing at.
I was a big fan of go for a while. Though now that I have programmed more swift and rust recently, having a compiler that doesn’t protect against null pointer deferences or provide concurrency safety guarantees feels a little prehistoric.
Though go certainly did a much better job than rust on the standard library front.
Standard library is something you have to maintain for all eternity, with identical API. It had been argued that some concurrency primitives like channels would have been better outside of std (for rust, to be clear). Once dependency management is solved, a small std is beneficial.
> you have to maintain for all eternity, with identical API
People always tout this as a huge reason for not wanting a too big std in Rust (or "too useful" either), but IMHO that's just talking about reaching theoretical optimals, while leaving the community for years without good guidance via providing a opinionated practical and pragmatic way of doing things. Which I find to be a very unhelpful stance for a tool such as a programming language.
If a design of some std package didn't pass the test of time, and a new iteration would be beneficial, the language can leave its original API version right there, and evolve with a v2, with an improved and better thought out API after learning from the mistakes of v1.
Prime example: "hey we found that math/rand had some flaws, so here is math/rand/v2". A practical solution, and zero dramas as a result of having rand be part of std.
Perhaps it would help if stdlibs were be versioned, with the chosen version declared in the project file. For existing languages, a lack of version would simply indicate the original stdlib, meaning nothing should break.
I definitely don't think stdlibs should be changed often, but it seems fairly damaging to a language when things may be added to a stdlib but never removed, no matter how broken or misconceived (see C++).
Rust is a great language, but the poor stdlib + overreliance on crates + explosion of unvetted transient dependencies makes it a hard sell for a lot of projects.
I use go because of the large and useful stdlib. I rarely have to reach for an external library, and even then I only consider libraries that are very popular. If a library isn’t available, I’ll just write my own, using the stdlib. I recently used the awesome crypto library to implement an envelope encryption system, I didn’t need anything outside of the stdlib or Google’s x library (x is effectively the experimental stdlib).
Having too much external code, like npm or rust crates, seems like a nightmare for me.
I believe the stdlib can't be versioned like that: there's only one stdlib linked into a final artifact, you can't have two versions with differing APIs in there.
There's work on edition aware name resolution so that a type with the "nice path" can change over an edition while still accessible through a longer path, but 1) it's not implemented yet, 2) it hasn't been used yet (see 1), 3) if it is ever used it should be done very sparingly (because of the bafflement that can occur if someone follows older docs in the new edition, implementation will come with efforts to mitigate these problems).
thiserror and anyhow are just std::error with extra steps. Note that io::error is just a specific std::error.
The entire point in Rust is that you wrap Error impls with other Error impls, or translate one impl into another using a match. I've found this is far more flexible and verifiable than most other languages, because if you craft your error types with enough rigor, you can basically have a complete semantic backtrace without the overhead of a real backtrace.
I use thiserror a lot to help with my impls. Notably, all it does is impl Display and Error. It's not a specific other paradigm because it basically compiles out, it's just a macro.
Anyhow is perhaps the closest one to another paradigm because it allows you to discard typed information in favor of just the string messages, but it still integrates well with Errors (and is one).
They're external crates that either generate Error implementations (thiserror) or act as dynamic wrappers implementing Error (anyhow), so they're more than a simple hand-written implementation. But the developer experience of pulling thiserror or anyhow off the shelf can certainly be more convenient than the hand-written implementation, sure.
Not quite true. The unifying error trait is std::error::Error.
> pain when you have to pass them upward through a chain of calls
Kind of? You just make an enum with the various variants that need to be passed through and use the #[from] macro to generate the conversion code automatically.
It’s more characters than eg. A union type in Python or TypeScript, but it’s not much more.
Plus, it makes you think about your error design, which is important!
In Go you can ignore the error value though, and use directly the returned value (`int` in your example). In Rust you cannot do that, you need to unwrap the Result or use the `?`
If the returned value is still valid despite an error, then the function would return (u32, Option<Error>), perfectly valid rust. If the value is meaningless in case of an error then using it is incorrect code; you wouldn't want to do that in either language and rust makes that assumption explicit with unwrap. If you want a default value in case of error just use unwrap_or_default.
Dunno... I really like FastEndpoints in C# a lot as well as Hono in JS/TS environments. That said, I do like Axum in Rust. All for varying reasons though.
It's not that bad, but when compared to C or Go, it's not something that I would like to type by hand. At least Java has IDEs which reduce the amount of verbosity you need to type. I know you get safety, but the verbosity and cargo is is a con in my opinion.
I find Elixir's memory and threading models much more compelling than Go's for web services. There are many great libraries for Elixir as well, but if you need something else, Elixir makes rolling your own libraries very easy. I'd recommend giving Elixir a try, if you haven't already.
> Rust has three main error systems (io::Error, thiserror, and anyhow), which is a pain when you have to pass them upward through a chain of calls.
nit: Rust has three main Error implementations not systems. std::error::Error is a trait because it's left up to the user to provide project-specific error types, even if those types are anyhow::Errors. The system follows any implementation you use: ? syntax, .unwrap(), .expect(), handling, formatting, etc.
I've never had a problem using anyhow to pass errors up the call stack in any project I've used it in. What exactly is a pain?
I just hate how many dependencies you have to pull in for a typical Rust project vs Go. As far as Go being an ugly language, there are some interesting wrappers that put lipstick on that pig such as https://lisette.run/
But personally, I don’t mind Go at all. I’ve even begun to prefer it for some things. That may be Stockholm syndrome, though.
>I could see migrating from C or C++ or Python to Rust, for various reasons, but for web back-end work Go is a good match. I write almost entirely in Rust, but the last time I had to do something web server side in Rust, I now wish I'd used Go.
Now there is a cult of rewriting everything in Rust. System level software? Yes. Web? I prefer not to.
Praising go for how it handles errors, when it's even worse than C where the compiler at least warns you if you're ignoring return values of calls. That's a new one.
Linters are available to catch you before you compile - with Go
Generally speaking there has to be a mechanism for optional handling of return values, in Go you can ignore everything (ew), you can use placeholders `_`, or you can explicitly handle things - my preference.
If you say "Well in C you have to handle the returns - I am not across C enough to comment, but I will ask you - Does C actually force you, or does it allow you to say "ok I will put some variables in to catch the returns, but I will never actually use those variables" - because that's very much the same as Go with the placeholder approach
edit: I am told the following is possible in C
trySomething(); // Assumes that the author of trySomething has not annotated the function as a `nodiscard`
(void)trySomething(); // Casts the return(s) to void, telling the compiler to ignore the non-handling
int dummy = trySomething(); // assign to a variable that's never used again
C, as a language, cannot bother less about you using or not using the return values, checking them, discarding them, or using them to index an array without any bounds checking. Various linters and compilers may have their opinions, expressed as warnings, but at the end of the day it's completely up to you as a developer.
The OP points out the wordyness of Go's error syntax. That's a good point. Rust started with the same problem, and added the "?" syntax, which just does a return with an error value on errors. Most Go error handling is exactly that, written out. Rust lacks a uniform error type. Rust has three main error systems (io::Error, thiserror, and anyhow), which is a pain when you have to pass them upward through a chain of calls.
(There are a number of things which tend to be left out of new languages and are a pain to retrofit, because there will be nearly identical but incompatible versions. Constant types. Boolean types. Error types. Multidimensional array types. Vector and matrix types of size 2, 3, and 4 with their usual operations. If those are not standardized early, programs will spend much time fussing with multiple representations of the same thing. Except for error handling, these issues do not affect web dev much, but they are a huge pain for numerical work, graphics, and modeling, where standard operations are applied to arrays of numbers.)
Go has two main advantages for web services. First, goroutines, as the OP points out. Second, libraries, which the OP doesn't mention much. Go has libraries for most of the things a web service might need, and they are the ones Google uses internally. So they've survived in very heavily used environments. Even the obscure cases are heavily used. This is not true of Rust's crates, which are less mature and often don't have formal QA support.