zeptoforth VS go

microcontroller options are interesting, also Forths (https://github.com/tabemann/zeptoforth)

Patch-level release 1.0.1 is out. This release improves the disassembler, particularly adding the ability to properly disassemble string literals.

This is a definite shameless plug, but I would recommend my zeptoforth - it has strong support for the RP2040 (e.g. the RPi Pico), including peripheral support and support for executing on both cores, and also has support for a number of STM32 platforms, and comes with a range of example code, documentation, and a wiki.

The release itself is at https://github.com/tabemann/zeptoforth/releases/tag/v0.45.0

Zeptoforth has this, but it’s for embedded systems. https://github.com/tabemann/zeptoforth

I initially implemented a rather Forth 2012-like wordlist system based on GET-ORDER, SET-ORDER, GET-CURRENT, SET-CURRENT, and WORDLIST for my Cortex-M Forth, zeptoforth. However, I ended up finding these quite cumbersome and error-prone to use in code that makes heavy use of wordlists to control the namespace, as is the case with zeptoforth. As a result I decided to completely remodel wordlists into a module system which, while internally based on those five words, is outwardly much more like the module systems found in other languages.

Multicore support for the RP2040 with zeptoforth has been in the works for a while but up until the last few days has not been mature enough for me to even consider including it in the devel branch of zeptoforth. However, now it has reached the point where I can run multiple tasks simultaneously on separate cores. I have a working test that blinks the LED on the Raspberry Pi Pico at two different rates in two different tasks, one on each core, while simultaneously writing an asterisk to the console once every second from the second core and having a usable REPL in the main task on the first core. It should be noted that even the Micropython does not do this, as it only allows two tasks, one per core, rather than allowing multiple tasks to run on each core separately.

I am the developer of zeptoforth, which is the main Forth I am using at the present. It supports the RP2040 (particularly the Raspberry Pi Pico, but it should work on other RP2040 boards), which I have been working with lately, and the STM32F407, STM32L476, and STM32F746 DISCOVERY boards. Note that it is not a desktop Forth; for that I would probably just recommend gforth.

zeptoforth 0.21.0 (https://github.com/tabemann/zeptoforth/releases/tag/v0.21.0) is now out, and introduces support for the RP2040 microcontroller (e.g. Raspberry Pi Pico, any RP2040 board with Winbond Quad SPI flash should work). Note that it comes in UF2 format, so one codes not need to solder pins for SWD onto one's Raspberry Pi Pico format to load it, and also the Makefile automatically generates UF2 files. Furthermore, when said UF2 file is first loaded, it erases flash above it up to the 1 MB mark, so one does not need to use OpenOCD (with SWD) or a special eraser UF2 file to clear old code out of flash.

The result of this is zeptoforth, which I have been developing for about a year and four months. One could say that it fits the same niche as Mecrisp-Stellaris, and it admittedly supports far fewer MCU's at the present. I could have just used that rather than bothered to implement my own Cortex-M Forth, but I wanted to create my own Forth environment which I could play with as I saw fit (e.g. adding preemptive multitasking and other multitasking supports such as locks and channels).

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/.