letlang VS go

That works for any types (except the functional types), and even the generic ones. During code generation, I create structs that implement the Type trait.

As stated on the website ( https://letlang.dev ), Letlang is a general-purpose language.

Author here, the article is more about how Rust and its ecosystem are nice tools for language designers rather than the beauty of Lisp.

The crates listed in that article are the ones I use for my compiler: https://letlang.dev

Lisp was only chosen as a way to demonstrate the power of those crates and Rust features. A kind of way of justifying my choices for Letlang.

It's not "you should do it like this" but "you can do it like this".

"Faster than C", I saw people write C code slower than a Python equivalent. So I have to admit, I don't know what it means for a language to be fast, because it depends on the algorithm being implemented.

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"simpler than Python", what does "simple" mean?

Simple design? Python's design is very complex (take a look at "Crimes with Python's pattern matching" < https://www.hillelwayne.com/post/python-abc/ > for example), on the other hand, assembly languages, or Lisp, or Forth, have a very simple design.

Simple as in "easy to use"? Rust is easy, write code, fix what the compiler tells you you did wrong. Joke aside, Go is quite easy to use and while I personally don't like this language, I get why it replaced Python in a lot of use cases.

Also, once you get used to the OTP framework, Erlang/Elixir/Gleam/any beam language are quite easy to use and have less footguns than Python.

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"safer than Rust" is too vague. Is it memory safety? type safety? thread safety? cosmic ray safety? A mix of all of that?

Let's guess you meant "memory safety". All languages with a Garbage Collector are "memory safe".

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On a semi-unrelated note, I've been working on https://letlang.dev

It's a language inspired by Erlang/Elixir (same concurrency model) that compiles to Rust code (the runtime use tokio). It is immutable, have no Garbage Collector thanks to Rust semantics, and dynamically typed.

I haven't run any benchmark (it's not even finished, I've been working on the specification before continuing the implementation), but I guess it could be slower than a rock.

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For some recommendations, have you looked at Zig? Nim? Hare?

  https://ziglang.org/

In my language (Letlang), I use the keyword class with structural pattern matching and optionally a predicate. Types (or rather, classes) can be combined with logical operators &, |, !:

Not sure this is what GP is talking about but to implement the actor model in https://letlang.dev I use tokio.

In the early drafts of Letlang, I had the goal to add an equation solver. I got rid of that because:

I'm working on a programming language inspired by erlang and which compiles to Rust: https://letlang.dev

For a contract based language and a "really dynamically typed language", I'm working on https://letlang.dev

And it's because I haven't thought yet about how to do static type checking with such a feature.

I haven't got any time to work on it in the past few weeks, and I'm the only dev (would really love some help). So, it will be ready when it will be ready :P

I use Rust generators to implement them, a rudimentary example: https://github.com/linkdd/letlang/blob/main/letlang_runtime/src/utils/entrypoint.rs

The description indicates it is not production ready, and is archived at the same time.

If you pull all stops in each respective language, C# will always end up winning at parsing text as it offers C structs, pointers, zero-cost interop, Rust-style struct generics, cross-platform SIMD API and simply has better compiler. You can win back some performance in Go by writing hot parts in Go's ASM dialect at much greater effort for a specific platform.

For example, Go has to resort to this https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f... in order to efficiently scan memory, while in C# you write the following once and it compiles to all supported ISAs with their respective SIMD instructions for a given vector width: https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (there is a lot of code because C# covers much wider range of scenarios and does not accept sacrificing performance in odd lengths and edge cases, which Go does).

Another example is computing CRC32: you have to write ASM for Go https://github.com/golang/go/blob/4ed358b57efdad9ed710be7f4f..., in C# you simply write standard vectorized routine once https://github.com/dotnet/runtime/blob/56e67a7aacb8a644cc6b8... (its codegen is competitive with hand-intrinsified C++ code).

There is a lot more of this. Performance and low-level primitives to achieve it have been an area of focus of .NET for a long time, so it is disheartening to see one tenth of effort in Go to receive so much spotlight.

A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.

I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles

The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397

There used to be the GO FIPS branch :

https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...

But it looks dead.

And it looks like https://github.com/golang-fips/go as well.

I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:

- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644

- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412

Here are some excerpts from the latest Go survey [1]:

- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."

- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."

I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.

[1]: https://go.dev/blog/survey2024-h1-results

Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.

Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!

net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements

Make sure you have Go installed https://go.dev/.