query-json
go
Our great sponsors
| query-json | go | |
|---|---|---|
| 4 | 2,070 | |
| 589 | 119,564 | |
| - | 1.2% | |
| 3.8 | 10.0 | |
| about 2 months ago | 5 days ago | |
| Reason | Go | |
| BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
query-json
-
Gojq: Pure Go Implementation of Jq
It's very possible it could be faster; jq seems to actually be fairly unoptimized. This implementation in OCaml was featured on HN a while back and it trashes the original jq in performance: https://github.com/davesnx/query-json
After seeing that one I did my own (less-complete) version in Rust and managed to squeeze out even more performance: https://github.com/brundonsmith/jqr
-
query-json: A story of cross-compilation with Reason
You can see more examples in the parsing tests
go
-
AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
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.
-
How to use Retrieval Augmented Generation (RAG) for Go applications
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!
-
From Homemade HTTP Router to New ServeMux
net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements
-
Building a Playful File Locker with GoFr
Make sure you have Go installed https://go.dev/.
- Fastest way to get IPv4 address from string
- We now have crypto/rand back ends that ~never fail
-
Why Go is great choice for Software engineering.
The Go Programming Language
-
OpenBSD 7.5 Released
When Go first shipped, it was already well-documented that the only stable ABI on some platforms was via dynamic libraries (such as libc) provided by said platforms. Go knowingly and deliberately ignored this on the assumption that they can get away with it. And then this happened:
https://github.com/golang/go/issues/16606
If that's not "getting burned", I don't know what is. "Trying to provide a nice feature" is an excuse, and it can be argued that it is a valid one, but nevertheless they knew that they were using an unstable ABI that could be pulled out from under them at any moment, and decided that it's worth the risk. I don't see what that has to do with "not being as broadly compatible as they had hoped", since it was all known well in advance.
-
Go's Error Handling Is Perfect
Sadly, I think that is indeed radically different from Go’s design. Go lacks anything like sum types, and proposals to add them to the language have revealed deep issues that have stalled any development. See https://github.com/golang/go/issues/57644
-
Golang: out-of-box backpressure handling with gRPC, proven by a Grafana dashboard
I've been writing a lot about Go and gRPC lately:
What are some alternatives?
pq - Like jq, but with Python
v - Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies. Supports automatic C => V translation. https://vlang.io
yojson - Low-level JSON parsing and pretty-printing library for OCaml
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
js_of_ocaml - Compiler from OCaml to Javascript.
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
tylr - a tiny tile-based editor
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
hashmap - A Golang lock-free thread-safe HashMap optimized for fastest read access.
Angular - Deliver web apps with confidence 🚀
jsoo-react - js_of_ocaml bindings for ReactJS. Based on ReasonReact.
golang-developer-roadmap - Roadmap to becoming a Go developer in 2020