di
pydantic
di | pydantic | |
---|---|---|
5 | 167 | |
277 | 18,942 | |
- | 3.8% | |
0.0 | 9.8 | |
7 months ago | about 21 hours ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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di
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Python Type Hints Are Turing Complete
Indeed.
The dep injection is fastapi and typer code though, and quite tied to it. So it's worth mentioning that somebody is attempting (quite successfully from the look of it) to create a generic lib of dep injection using annotation named DI, inspired by those libs: https://github.com/adriangb/di
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I built a standalone version of FastAPI's dependency injection system
Also, to clarify because I realized my comment above was confusing: I did not mean that 1 file == 1 function in the def a_function sense, I meant it in the "functionality" sense. So for example di/_scope_validation.py is a piece of functionality (validating scopes) and so it is in it's own file instead of being at the top of di/container.py. I guess the entire project could be a 1000 LOC container.py file, I think I would personally find that a bit hard to digest, but it's for others to read not me so...
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di: pythonic dependency injection
We provide some basic benchmarks comparing to FastAPI.
pydantic
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Advanced RAG with guided generation
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.
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utype VS pydantic - a user suggested alternative
2 projects | 15 Feb 2024
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
- Pydantic v2 ruined the elegance of Pydantic v1
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Ask HN: Pydantic has too much deprecation. Why is it popular?
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
- OpenAI uses Pydantic for their ChatCompletions API
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🍹GinAI - Cocktails mixed with generative AI
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.
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FastStream: Python's framework for Efficient Message Queue Handling
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.
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Introducing FastStream: the easiest way to write microservices for Apache Kafka and RabbitMQ in Python
Pydantic Validation: Leverage Pydantic's validation capabilities to serialize and validate incoming messages
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Cannot get Langchain to work
Not sure if it is exactly related, but there is an open issue on Github for that exact message.
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FastAPI 0.100.0:Release Notes
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.
What are some alternatives?
xlcalculator - xlcalculator converts MS Excel formulas to Python and evaluates them.
Cerberus - Lightweight, extensible data validation library for Python
LaTeXML - LaTeXML: a TeX and LaTeX to XML/HTML/ePub/MathML translator.
nexe - 🎉 create a single executable out of your node.js apps
json-parser-in-typescript-very-bad-idea-please-dont-use - JSON Parser written entirely in TypeScript's type system
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
ideas
SQLAlchemy - The Database Toolkit for Python
python-typing-machines - Python type hints are Turing complete.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
mypy - Optional static typing for Python
pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]