dactyl-keyboard VS pydantic

that's not entirely accurate. It is a derivation of the dactyl-manuform. I used the generator from this project to produce the case. https://github.com/ibnuda/dactyl-keyboard The earliest biuld of the dactyl-manuform that I can find is: https://github.com/abstracthat/dactyl-manuform

https://github.com/ibnuda/dactyl-keyboard/tree/hotswap/things This is where I pulled the stl from however it doesn't come with a base plate stl so I had to make that myself

What generator did you use? I’ve never been able to get this one to load: http://dactyl.siskam.link/

there used to be a generator at https://dactyl.siskam.link/ but is not loading now. (easily generated files from your input in a form) you could also have them built to order from https://ohkeycaps.com/products/built-to-order-dactyl-manuform-keyboard

There are external holders for pro micros and elite C under https://github.com/ibnuda/dactyl-keyboard/tree/refaktor/resources/public

Try this: https://dactyl.siskam.link

I'm happy to print the case for one for you for the cost of the filament, if you want (20EUR or so). Shipping to outside of europe might make local printers cheaper. There's a generator for custom shapes at https://dactyl.siskam.link

You can generate a custom one with https://dactyl.siskam.link/ (demo of how to use here: https://youtu.be/9nwXUfi49oU)

First, note the method prefix_allowed_tokens_fn. This method applies a Pydantic model to constrain/guide how the LLM generates tokens. Next, see how that constrain can be applied to txtai's LLM pipeline.

utype is a concise alternative of pydantic with simplified parameters and usages, supporting both sync/async functions and generators parsing, and capable of using native logic operators to define logical types like AND/OR/NOT, also provides custom type parsing by register mechanism that supports libraries like pydantic, attrs and dataclasses

I like some of the changes from v1 to v2. But then you have something like this [0] removed from the library without proper documentation or replacement, resulting in ugly workarounds in the link that wont' work properly.

[0]: https://github.com/pydantic/pydantic/discussions/6337

The easiest implementation I found was to use a PyDantic class for my target schema — and use that as a parameter for the method call to “ChatCompletion.create()”. Here’s a fragment of the GinAI Python classes used.

Also, FastStream uses Pydantic to parse input JSON-encoded data into Python objects, making it easy to work with structured data in your applications, so you can serialize your input messages just using type annotations.

Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages

Not sure if it is exactly related, but there is an open issue on Github for that exact message.

Well the performance increase is so huge because pydantic1 is really really slow. And for using rust, I'd have expected more tbh…

I've been benchmarking pydantic v2 against typedload (which I write) and despite the rust, it still manages to be slower than pure python in some benchmarks.

The ones on the website are still about comparing to v1 because v2 was not out yet at the time of the last release.

pydantic's author will refuse to benchmark any library that is faster (https://github.com/pydantic/pydantic/pull/3264 https://github.com/pydantic/pydantic/pull/1525 https://github.com/pydantic/pydantic/pull/1810) and keep boasting about amazing performances.

On pypy, v2 beta was really really really slow.