bookshop VS go

It seems like CloudCannon has this with their open-source Bookshop component editor which can integrate with their hosted CMS.

https://github.com/CloudCannon/bookshop

The small user base, however, means there probably aren't other CMSs that use the same component representations or CMS live data bindings. This means while Bookshop components are portable between CMSs on paper, it's not in practice (e.g. you can't easily hook it up to another CMS with a visual editor like Wordpress's Gutenberg, Storyblok, etc.).

You can use a script to import your Hugo theme but this will only give you text editing functionality (markdown). For the visual editing experience you will need to convert your current theme to a cloudcannon theme using bookshop https://github.com/CloudCannon/bookshop

What's everybody using to make their javascript smaller nowadays? I used Grunt to minify my JS, CSS, and images many moons ago but I want to update my template to actually use bundle to deliver my assets since I'm creating a visual editor with CloudCannon.

Bookshop is a component development workflow for static websites. Bookshop defines a convention for building self-contained components in the templating languages supported by common SSGs. Using these conventions, Bookshop provides developer tooling that empowers you to integrate these components with your stack, build and browse UI components locally, and provide rich live editing experiences for your editors.

Sendit is a multipurpose Eleventy theme made with the Bootstrap CSS framework. The components have been converted to Bookshop. It’s the perfect starting point to see how CloudCannon works.

Sendit is a multipurpose Eleventy theme with a built-in blog, made with the Bootstrap CSS framework. The components have been converted to Bookshop. It’s the perfect starting point to see how CloudCannon’s Visual Editing and component-based page-building works, and how they can really speed up your blogging flow.

For users of our open-source component development workflow Bookshop, we’ve created a full reference guide for Bookshop on Eleventy and a Bookshop starter template. (The Sendit theme comes with Bookshop and a wide range of components already configured, too!)

The last place our improvements touch on is visual page building. You can now create new pages in the Visual Editor and edit the page’s default data right away — with no build needed. We also added an option to preview your new page without a build. To get a preview, you’ll need pages configured to render from your front matter using Data Bindings and Previews (we also recommend Bookshop here). Then you can use the new option new_preview_url to set your preview to another page’s output URL. The Visual Editor will load that set preview URL and use the Data Bindings and Previews to render your new page without saving. You can try this with our Megakit template.

Our SSGs through the ages series delves into the history of this space, and one of the trends that we’re seeing is larger and larger projects migrating to static websites, helped in part by the efficiency of static site generators like Hugo. We build many such sites for ourselves — the CloudCannon documentation is nothing to sneeze at — as well as for our Enterprise partners, and our customers build yet more on our platform every day. As this scale continues to increase, we find ourselves encountering new and interesting challenges. In the past we have released open-source tools for component-driven development, internationalization, pagination and portability. Now, we have our sights set on search.

Bookshop, one of our own open-source tools, allows the kind of component-based editing in SSGs such as Hugo, Jekyll, and Eleventy that — to put it bluntly — no one thought was possible. It’s an inflection point that will affect how these SSGs will be used in the coming years; think Elementor’s block-based builder for WordPress, with increasing support for additional platforms that don’t have rigid security and maintenance constraints. With Bookshop, developers can work with custom components on the SSG they choose, without being locked into a single platform.

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/.