https://news.ycombinator.com/item?id=44893833
Still searching the true solution:
https://github.com/golang/go/issues/27179#issuecomment-53634...
A proposal of the missing datatype for this operation mode has been just accepted:
Or more concretely, if we had a parser generator + json parser specification that can generate efficient simdjson style parsers, then we should be able to parse json restricted to a subset of json based on a schema at least as efficiently as simdjson can parse general purpose json.
That way we could have the best of both worlds, a (potentially lazy) statically type-safe model and simdjson performance!
I still think that this is definitely doable, it's just that a lot of infrastructure needs to be built for it.
I remember reading that Meta is doing something similar with binary formats. I find it weird that there's nothing like that for json yet.
I think most people who use JSON don't want strong typing or to use schemas. If you do, you just use a different serialization format: JSON is designed to be a generic, human-readable way to basically represent any kind of data structure (since it deserializes to JS objects). So everything about JSON is working against you if you do try to enforce type/schemas on it.
A grpc-like protocol with more prescriptive type registries/discovery (over the network) and better interop with http (like grpc-gateway) would be the best approach IMO. Definitely not JSON schema
I have been using serde without issues, and never resorted to `serde::Value`[0], the untyped option, so far.
I have yet to experience anything working against me.
[0]: https://docs.rs/serde_json/latest/serde_json/enum.Value.html
We use JSON because it's standard, human-readable, mostly self-described and works natively with Javascript.
You can read JSON object without having to know the schema even if one exists.
Protobuf is unusablr garbage without a lot of supporting tooling.
Not necessarily. It's biggest advantage is probably that it has very good interoperability. Basically every language has a readily accessible library for json, and even if you don't, it isn't that hard to write a parser and/or generator for it. And being human readable isn't something to sneeze at either.
I wish they'd left `MarshalIndent` in there though. The equivalent code is super complicated and non-obvious, so it's a pain to migrate, and it's a pain when you're banging out some quick code and want to dump some readable JSON. I suppose these days the LLMs can write the complicated version for us, of course.
v := jsontext.Value(b)
v.Indent()
fmt.Println(string(v)) func WithIndent(indent string) Options
json.Marshal(v, jsontext.WithIndent(" "))
?Clearly it isn't, otherwise every language would have sorted it out by... a long time ago.
You can still use it though, and I built my tiny decimal library around it: https://github.com/ncruces/decimal
A JSON parser MAY accept non-JSON forms or extensions.
An implementation may set limits on the size of texts that it accepts. An implementation may set limits on the maximum depth of nesting. An implementation may set limits on the range and precision of numbers. An implementation may set limits on the length and character contents of strings.
Add to that things like duplicate keys being allowed by the spec. There’s a lot of implementation choices to decide on.
And then things can get really complex with JSON Schema.
A lot of specs contain these optional limitations. The C standard allowed implementations to truncate variable names to 31 characters if they have external linkage and 63 if internal linkage. Would you be happy if your implementation actually does that? Of course not. Neither LLVM nor GCC does that. That’s because people writing compilers also hold themselves to a higher standard. Now imagine this kind of attitude being pervasive.
Who knew the same object could have completely different definitions based on some flags?
There is no introspection and speed is superb. I would definitely recommend jsontext as a parser for anything non-straightforward.
I'm just getting the neuron-band back together where Golang is concerned. I have done some in the past for little system tasks, but I am switching away from interpreted languages entirely for web stuff, and initially to Go, as I switch away from hand-coding to at least LLM-supported coding.
So I am a bit out of date on the pain points (I never really felt pain points when I last used it, because the jobs I was doing had very small, quite Go-friendly shapes).
I'm not entirely surprised, and I'm glad the Go team is carefully considering their interfaces before launching. But 6 years seems like a lot of work to land a JSON API.
JSON processing, quite markedly, is renown in Go for being slow, so I don't really understand why it took so long
Within our company I saw people in other teams writing their own optimised JSON libraries for whatever hellish reason. I always reiterated the point that as soon as that app made a single IO request all those nanosecond savings are invisible. Yes, it affects your total CPU time for processing a request but compute was never ever a limitation for us and it's likely not a limitation for most people. And if the trade off is your app needs scale slightly larger versus writing custom JSON code or pulling in a third party dependency, then I'm accepting the larger scaling.
The biggest benefit of encoding/json/v2 isn't the speed, it's the improved API.
I kind of like that the standard library doesn’t move fast. It makes it easier to fit the ecosystem into my head (unlike, for example, the JavaScript ecosystem where I find code doesn’t survive 2 years before failing to compile).
But I do agree that slow and steady produces its own problems. Your example of generics is a good one. But think the example of Go modules is another, perhaps even better, example of how sometimes the Go team really should have accelerated their efforts on.
Dependency management is a freaking nightmare, nobody has managed to create something that is bulletproof, not cargo, npm, apt, yum, nix, homebrew, nothing.
The key issue is that you're managing 3rd party software that may or may not adhere to the prescribed lifecycle/versioning
The Linux variants do it by each having dedicated teams watching upstream sources, taking what they believe to be whatever they feel is right, building for their nominated target(s), then testing, before deploying (on top of that, all of these steps vary in importance and rigor depending on numerous variables)
For programming libraries (which is what depmod, goose, vgo, and modules are managing) it's just as bad, if not harder, because their very nature is to provide a base upon which other developers can turn into whatever their imagination.
Add to that, modules was (initially) written by people who were dealing with a slightly different ecosystem; Google rather famously has a monorepo, making their lives a little easier when it comes to managing dependencies.
So, with those things in mind, dependency management is always going to be a hard problem that is opinionated (eg. I have a firm opinion that there should be an easier way to "pin" a dependency, other than vendoring - note that this isn't an invitation to every junior Go developer to come and claim go.sum does that. It doesn't. go.sum is a log of what dependencies were used for the last build by whomever wrote to it)
But difficulty aside, my point was Go waited until there were multiple established 3rd party package management tools for Go already in widespread use before even releasing their own experimental implementation.
Their inaction caused far more disruption to the ecosystem because people got fed up of waiting, implemented their own, integrated it into their workflow and then had to reintegrate a whole new system all over again a year or two later.
Your point about Googles needs is the one often cited for Gos inaction. But I think that actually makes the situation worse. Because if the Go team cannot empathise with use cases outside of one bespoke enterprise, then it really shouldn’t be released as a general purpose language available for all to use.
And I say this as someone who generally likes the language.
Especially since "Go team cannot empathise with use cases outside of one bespoke enterprise" — it shows self-awareness of their shorcomings. I think it's wise to let the target audience explore the design space themselves a bit first. Considerably lowers the risk of cementing the wrong design.
I do somewhat remember the drama around this at the time, but I my impression was that of a petulent community of various dependency management projects with too much ego attached to them to see the bigger, long-term picture.
You left out the part that explains why.
Only about a year from when the Haskell guys lent their expertise in designing it and it landing in a release. That's actually fairly quick given that it was a pretty significant change under the hood and constrained by only two releases annually.
The Go team was always clear that they didn't have the necessary capabilities internally, despite a lot of failed efforts trying anyway, and were relying on the open source community to lend a hand. Unfortunately, open source doesn't mean open willingness to contribute. It turns out that for all the experts on HN, posting "go doesn't have generics lol" was preferable to helping out.
https://homepages.inf.ed.ac.uk/wadler/topics/gj.html
Before Featherweight Go, there was Featherweight Java.
So maybe a language designed in 2012 (v 1.0 release year), should learn from history instead of hand-waving it away as needless fluff.
> In retrospect, we were biased too much by experience with C++ without concepts and Java generics. We would have been well-served to spend more time with CLU and C++ concepts earlier.
https://github.com/golang/proposal/blob/master/design/go2dra...
And not all on the team were convinced even after Featherweight Go, here Rob Pike,
> I think the transition to getting polymorphism into the language through generics is has still got some years to work through there's still things that don't quite work right
If you go back and watch the original Go announcement it was made abundantly clear that they believed Go did need generics but that they didn't have the expertise to do it. Yes it is true that the book was already written on it, but that doesn't mean anyone on the Go team was familiar with it or had the time to become familiar with it. Programming languages do not require gods to design them. Imperfect humans can too.
The experts on HN who know all the ins and outs of generics could have contributed but, you know, shitposting "go doesn't have generics lol" was a better use of their time. There are so many hours in the day.
Go culture is not welcoming to experts contributions, Rust, D, C#, Swift and others, heck even Java, are more open arms to language designers.
You'd think one of the HN experts would have shown up to offer that expertise, but I guess there was a lot of "go doesn't have generics lol" needing to get out.
The Haskell muscle had proven their skills already with Featherweight Java, in 2006.
Wordpress powered by PHP is also the most widely deployed CMS.
That argument is not as great as you think it is.
This pragmatic attitude towards software engineering is exactly why I still reach for Go for pretty much everything these days. I still read and review code.
So working with a language that doesn't throw a splash of sigil soup on my face is quite nice while reviewing clanker output. Also, being able to do all this without needing 5 crates is nice. Oh the fast build time helps too.
I love it too, it’s a great way to keep the stdlib moving without actually breaking anything. Simple and efficient design.
So yea hopefully a nice new addition but only my prompts now matter. So need to make sure they pickup on the new API.
I am using local LLMs and Go has a bunch of strengths where smaller contexts are concerned; less complicated flow of control being one of them.
And the things that we do to manage this, that are symbolic or based on visceral real-world analogy, are good for us and bad for them.
Go is kind of in the middle, in the way that many vaguely Wirth-like and CSP-like languages possibly are, I guess.
I hope you're not still doing this, it's nothing to brag about.
Unfortunately, the world makes it hard to keep that cycle, and so instead I mostly do 17 hours awake / 7 asleep, which makes me feel constantly tired (though less tired than 16/8 at least).
If you code in Go, the code is more high level, prettier, simpler.
If you code in Rust, the code is more robust, efficient, faster.
Both are important for LLM, why can't we have a high level, simple language that is also robust, efficient and fast? =)
Expressive and type safety of a functional language, without the odd semantics of Haskell, where laziness can make performance difficult to predict and purity can make simple things like IO difficult to understand.
Does it still lack easy to use concurrency primitives?
I' just starting OCaml, so can't really compare, but it seems a good progress there.
Go is about as far as you can "go" to the efficiency end without becoming Rust. It's a low-overhead language (like C) but with a GC that ensures memory safety. If you want to manage memory yourself and still prove safety it gets very complicated, as we see in Rust.
I think many variants from Rust can be stripped to make it simple, especially in type system, which is way more complicated than go.
LLM can generate very cryptic rust code.
It's really great fun to build stuff in Crystal, I don't have anything prod-grade yet to say how it scores there but the community seems to be happy about that too.
The few times I've needed a language without a GC and used Rust and C as target languages, I've reviewed the code less and enjoyed it less.
JIT and AOT compilers, REPL development, bleeding edge GC implementations, Java, Scala, Kotlin, Clojure, C#, F# to chose from, and modern IDEs inspired by Smalltalk/Lisp Machines experience, batteries included backed and frontend development frameworks.
First, I like programming and don't want to stop doing it just because a machine can do it too. Second, I'm pretty sure atrophied coding skills will make me worse at directing the machines, thus worse at what seems to be "the job" these days.
In theory wouldn’t atrophied coding skills not matter if models are sufficiently good at coding? I mean isn’t whats left just design and architecture and testing?
Sure, if LLMs are producing shit code you need to have an understanding of what it should do instead. But I think that day is already gone.
Its hard to think of a skill that you’d need to build with an LLM that requires writing meaningful amounts of code by oneself. From my end all the complexity is business logic and system design.
No, because good understanding of design comes from programming experience. Atrophied skills mean you lose touch with the actual nuts and bolts of what you are building.
This is also the worst kind of lock-in you can imagine, by outsourcing all of your understanding of a codebase and your skills you are now completely at the mercy of LLM providers. Even if you switch to open weight models you're at the mercy of graphics cards producers and scalpers.
> Sure, if LLMs are producing shit code you need to have an understanding of what it should do instead. But I think that day is already gone.
Maybe your standards are too low. By my standard, they still produce shit code and require lots of iterations to get reasonable designs (I often end up just rewriting the bits that are obviously wrong rather than trying to figure out how to "prompt engineer" the right output).
They do often produce passable code but my experience is the longer you spend reading the code the more things you find wrong with it, almost like an uncanny valley.
At least that's my experience with Opus and Fable. Maybe it's too old-fashioned at this point to complain about code quality, but I find it very strange how many people have started proclaiming that their code quality is good.
“Programming” is a bit loaded. Do you mean thinking through and typing everything out yourself?
What design skills specifically can you only develop from continually programming in this way? I fully grant that you need to know how to code yourself to build things with models but what specific ability to use models atrophies alongside your no AI coding abilities?
Personally I’ve found the opposite to be true. As writing out code myself has shrank to nearly 0, I now do way more designing. There is a much shorter feedback loop on design now. You get a lot better at design when thats basically all you are doing, and seeing feedback on your design in minutes rather than weeks or even months.
Weeks and month for to wait for a feedback in developing software? Are you the sloth in zootopia?
The longest cycle for feedback for me has only been hours. And that was about redesigning the core architecture of an app. Otherwise, it’s like 10 minutes cycle if it’s edit-compile-run, 5 minutes if it’s REPL (lisp, bash, python,…).
As I write code myself I continously take into consideration stuff like following the consistency of the entire design, whether what I'm doing is efficient, etc. LLMs are terrible at this and I don't see how you could develop such skills by prompting only.
For example, I would never produce designs that require degenerate db access patterns (linear scans, etc.). Everything I write myself always takes into account using db & network efficiently from the ground-up. Every query is an index lookup, every api request is rate limited, everything is batched and cached, so on and so forth.
LLMs meanwhile don't care about any of this. I just had Claude happily try to fetch youtube page html because the api didn't expose something. Great idea, I'd love to be banned by google for scraping.
Designing with performance in mind is black magic too, I need to notice myself that stuff that I think has no reason to be slow (pretty much nothing does) is slow and hammering the llm to finally come up with a non-stupid design that's not ridiculously slow and wasteful. Yeah, why don't we pull 2.3mb of html to update a list, sounds good.
The best part is, LLMs are very obedient. If you tell them to make you a design that's inherently wasteful of resources and slow they will happily oblige, and since you have no programming experience to know better, you won't even know how bad what you're asking for is.
You don't expect everyone to stop wanting to do those just because they can be automated more or less effectively, right?
Please reread my comment and the one im replying to. That’s not what I’m addressing.
I am begging HN users to understand that some people enjoy writing software themselves
Agents make it too easy to gloss over too much. They're great at work where i care about productivity but I've zero interest at home where the point is learning and having fun
Why? Because I don’t give time to wait for code to compile on my time and I don’t have time for people to learn a new language for review at work.
Life is good! Would recommend that split.
However it kind of makes me feel like my professional life was wasted and I don't really know what kind of future I have. One of Go's main points was you can pick it up in a weekend. What career moat do people like us have?
Letting it generate machine code directly would be the opposite of that.
As for proven wrong,
"Frame was created over the past month largely via Claude Code. The Assembly code in all its glory can be found on GitHub."
Considering it just pulls and remixes blocks, this is a very tall order for today's LLMs, and maybe a couple of generations as well.
Calling GCC/clang at the back and emitting ASM is both cheating and has no advantages whatsoever as well.
This isn't futurology, besides a few projects that already came up on Phoronix and around here, with Assembly generation, there are enough SIGPLAN papers on ML driven compilers already.
However, starting with LLMs directly generating machine code and moving to ML directed optimization passes, you're moving the whole stadium with a crawler-transporter, not only the goalposts.
Helping compiler in a well defined way, and working on IR or driving it repeatedly to optimize the output is one thing, generating machine code from a training set is other. Let's not mix them.
"Compiler 2.0: Building the Next Generation of Compilers with Machine Learning"
https://eecs.berkeley.edu/research/colloquium/compiler-2-0-b...
There are other researchers if you interest yourself on the matter.
Then the whole iPaaS agentic coding environments like Workato and Boomi, that even if they might generate 3GL as intermediate step, you don't get to see it.
https://github.com/zwang4/awesome-machine-learning-in-compil...
Using small, purpose built ML "things" to make things better makes sense. We use them everywhere. I never argued against it, as well.
Enterprise applications are already being vibe coded in iPaaS platforms, and as mentioned in other comments with LLMs in the picture, that is what compiler research is switching to.
In case you answer there don't fit the same purpose, there are tiny baggers that replace shovels altogether.
I think those arguing for structured language generation, never had that much experience with 4GLs or declarative programming on the previous AI Summer.
So like the Assembly developers required those -S compiler switches, or nowadays Compiler Explorer snippets, there is a tendency to argue for 3GL code generation, when low code/no code tools with AI runtimes are already being adopted at enterprise level.
What in the past took a bunch of developers using structured programming languages to write their frontend, and the myriad of microservices, is slowly being taken over by MCP tools, SaaS AI orchestration prompts and UI generation tooling, most of which doesn't even expose whatever code gets generated.
If 3 GL code has to be generated, my option list won't certainly have Go on it.