otto VS go

robertkrimen/otto

Ummm, excuse me, but where the f&$k has this been hiding? I’ve been looking for ways to extend my go applications with scripting support. I started with Lua (worked ) then Python (worked but hacky) then javascript using otto [1]. However it lacks ES6 support so having pretty OOP js code is a non-starter. I would love to have Java as a runtime that can be executed from goroutines.

[1] https://github.com/robertkrimen/otto

Either call a JavaScript interpreter like node with exec.Command and read its stdout, or use a pure Go JavaScript interpreter like goja or otto.

Otto https://github.com/robertkrimen/otto Seems interesting. It lets me call Go functions from inside JS as well as return results. The fncs pattern reminds me a bit of how the template engine works.

> why host other languages

Here's an example:

I recently finished building https://subzo.com.au which allows customizing and ordering 3D models. The way the model's cost, volume and other attributes are calculated needs to be done both on the frontend (for speed) and on the backend (to validate). Backend is in Go and we can't practically run Go in the browser. So instead, I wrote the calculation snippets in JavaScript (which runs natively in the browser) and ran them on the backend on a JavaScript VM library written in Go [1].

[1]: https://github.com/robertkrimen/otto

Googling suggests https://github.com/robertkrimen/otto which allows scripting in javascript for golang projects. This would be definitely enough, but in some way it may be a bit overkill - and scripts supporter shall need some knowledge of javascript which is not always straightforward :)

It doesn't make sense to ask the user (aka me) to change the code every time I want to modify any web apps right? So I decided to split the webapps into two parts. WebApps are those only require basic permissions and do not interact with the host OS. They will be run inside a sandbox created using ECMA5 VM called Otto. The other type is called Subservice, in which it will need extra permission to interact with the OS and require higher level of access to the backend file system.

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/.