babili VS go

The key is that the scoping happens for each iteration, not around the entire loop. That detail is nonobvious, given how many other languages have gotten it wrong, but I wouldn’t say it’s wild.

(If you’re curious how Babel deals with the more complicated cases of continue, break, labelled break, and return, try it out at https://babeljs.io/repl.)

I used https://babeljs.io/repl to know the size after the code has been transpiled.

You must have a basic understanding of JavaScript and be familiar with some of the features of ES6, the most recent version of JavaScript, to follow this tutorial. More information is available here if you’re unfamiliar with ES6. If you are more familiar with the older version of JavaScript, you might find the babel REPL more helpful to see how ES6 code is translated.

The JSX code is far easy to understand, but React, ReactDOM, or browser does not understand it. Babel comes into picture to translate JSX code to equivalent React code.

If we copy and paste the code in a Babel repl editor, we will get the equivalent React elements that we used earlier:

In your node project, add Babel and Webpack. They can “transpile “ your JSX code to browser compatible code. You can try it out here

If your project uses a bundler like webpack or rollup, then you can use the nullish coalescing operator in your code. But if you are using a browser, then you should use a transpiler like babel to transpile your code to ES5. You can use babel repl to transpile your code.

The Babel REPL is an easy way to see what the transpiled output looks like.

babel has an online playground

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/.