cyanide VS go

No, it stands for "Binary JSON".

BSON specification

I recommend looking at https://ubjson.org and https://bsonspec.org , this will answer most of your questions.

or https://bsonspec.org/

BJSON Binary JSON, with a Swift Library here and should be one for your other end

Starting this tutorial we specified that data in MongoDB is stored in collections. We also specified that in MongoDB we use syntax similar to JSON. That syntax is called "Binary JSON" or BSON. BSON is similar to JSON; but it's more like an encoded serialization of JSON. We can find useful information in the BSON website.

> I'm saying that when you decode an Avro document, the result that comes out (presuming you don't tell the Avro decoder anything special about custom types your runtime supports and how it should map them) is a JSON document.

Semantic point: it's not a "document".

There are tools which will decode Avro and output the data in JSON (typically using the JSON encoding of Avro: https://avro.apache.org/docs/current/spec.html#json_encoding), but the ADT that is created is by no means a JSON document. The ADT that is created has more complex semantics than JSON; JSON is not the canonical representation.

> By which I don't mean JSON-encoded text, but rather an in-memory ADT that has the exact set of types that exist in JSON, no more and no less.

Except Avro has data types that are not the exact set of types that exist in JSON. The first clue on this might be that the Avro spec includes mappings that list how primitive Avro types are mapped to JSON types.

> Or, to put that another way, Avro is a way to encode JSON-typed data, just as "JSON text", or https://bsonspec.org/, is a way to encode JSON-typed data

BSON, by design, was meant to be a more efficient way to encode JSON data, so yes, it is a way to encode JSON-typed data. Avro, however, was not defined as a way to encode JSON data. It was defined as a way to encode data (with a degree of specialization for the case of Hadoop sequence files, where you are generally storing a large number of small records in one file).

A simple counter example: Avro has a "float" type, which is a 32-bit IEEE 754 floating point number. Neither JSON nor BSON have that type.

Technically, JSON doesn't really have types, it has values, but even if you pretend that JavaScript's types are JSON's types, there's nothing "canonical" about JavaScript's types for Avro.

Yes, you can represent JSON data in Avro, and Avro in JSON, much as you can represent data in two different serialization formats. Avro's data model is very much defined independently of JSON's data model (as you'd expect).

For me, this exploration started when I was attempting to improve handling of Unicode surrogate pair values in the MongoDB Go driver's Extended JSON unmarshaler. The Extended JSON format is an extension to the standard JSON format that adds type information and allows deterministic conversion to and from BSON.

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/.