rich VS pydantic

There is an open issue [1] on GitHub to make it more modular and get rid of markdown and syntax highlighting but I have no hope for rich to get more minimal.

[1]: https://github.com/Textualize/rich/issues/2277

I hope he doesn't mind, but the creator of Rich and Textualize is a good guy, and Scottish: https://www.willmcgugan.com/about/

https://www.textualize.io/

https://github.com/Textualize/rich

They keep getting improved error messaging and this is one of my favorite features. But I'd love if we could get some real rich text. Idk if anyone else uses rich, but it has infected all my programs now. Not just to print with colors, but because it makes debugging so much easier. Not just print(f"{var=}") but the handler[0,1]. Color is so important to these types of things and so is formatting. Plus, the progress bars are nice and have almost completely replaced tqdm for me[2]. They're just easier and prettier.

[0] https://rich.readthedocs.io/en/stable/logging.html

[1] Try this example: https://github.com/Textualize/rich/blob/master/examples/exce...

[2] Side note: does anyone know how to get these properly working when using DDP with pytorch? I get flickering when using this and I think it is actually down to a pytorch issue and how they're handling their loggers and flushing the screen. I know pytorch doesn't want to depend on rich, but hey, pip uses rich so why shouldn't everyone?

colors.crumb extends Crumb with basic terminal styling functions and RGB, HEX, ANSI conversion functions. It is in the realm of JavaScript's chalk and Python's rich but slightly more functional 😉.

I am working on a new python project and one of the first things I added was https://github.com/Textualize/rich because of how easy it is to make things look good in the terminal.

I am not rewriting anything but I'd love to have a library like `rich` in Rust: https://github.com/textualize/rich

Add some cool-looking stuff to your output with rich.

You might consider taking inspiration from the rich module. In particular, I like how rich supports inline color theming which seems much more cumbersome in your framework, requiring the use of context managers as well as familiarity with how your framework structures color objects. Other than that though, I'm impressed!

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.