intellij-community VS go

Also, no BuSL stupidity, they're all Apache 2 AFAIK: https://github.com/JetBrains/intellij-community/blob/idea/23...

And the "all you can eat" toolbox license is just a staggeringly good deal, IMHO, which also comes with a "you can keep your license forever, just no updates" which is way different from setting subscription-based licensing money on fire when your license expires. Whoever came up with that should be applauded because it really drives down my "what about" anxiety of paying subscription money for IDEs

I readily admit I am not familiar enough with fossil to know about the impedance mismatch, but I'll point out that https://github.com/JetBrains/intellij-plugins/tree/idea/241.... https://github.com/JetBrains/intellij-community/tree/idea/24... https://github.com/JetBrains/intellij-community/tree/idea/24... https://github.com/JetBrains/intellij-community/tree/idea/24... may a long way toward finding how they think about those operations

There is quite a bit going on in our view’s class, so we'll take it slow and go through its functions one by one, according to their importance. The first thing we need to do is to create the structure our items will fit into. com.intellij.ui.treeStructure.Tree seems to best match our needs, and that’s what we’ll use. In order to prepare it for what is coming, we need to configure it.

I think it's time to wrap it up. We've made a pull request to the IDEA developers, and I've accomplished the tasks I set out to do. I'm really happy to help the developers of my favorite IDE.

I offer, again, my JetBrains GrammarKit counterpoint from the last time that assertion came up <https://news.ycombinator.com/item?id=38192427>

>>>

I consider the JetBrains parsing system to be world class and they seem to hand-write very few (instead building on this system: https://github.com/JetBrains/Grammar-Kit#readme )

- https://github.com/JetBrains/intellij-community/blob/idea/23... (the parser I'll concede, as they do seem to be hand-rolling that part)

- https://github.com/JetBrains/intellij-community/blob/idea/23... (same for its parser)

- https://github.com/JetBrains/intellij-community/blob/idea/23... and https://github.com/JetBrains/intellij-community/blob/idea/23...

- https://github.com/JetBrains/intellij-plugins/blob/idea/233.... and https://github.com/JetBrains/intellij-plugins/blob/idea/233....

I had the same experience with OmniGraffle, https://www.omnigroup.com/omnigraffle

It just worked. There was support. I wouldn't dig a hole in the ground with my bare hands, why wouldn't I use good tools. Of course I would like to use F/OSS for various reasons.

The model I absolutely love is Jetbrains, their core product is OSS, Apache licensed. The whole thing, totally usable. https://github.com/JetBrains/intellij-community

The money I send their way does both, it pays for developers and it puts an amazing artifact in the world that others can use and learn from. If they weren't open source, I wouldnt pay for it. I don't know how many others are the same as me, but Jetbrains really deserves credit here.

# https://github.com/JetBrains/intellij-community/blob/idea/233.9802.14/json/src/jsonSchema/schema.json#L52

and also FOSS (Apache 2): https://github.com/JetBrains/intellij-community (as well as PyCharm found in the "python" subdirectory)

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/.