pydantic
uvicorn
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pydantic | uvicorn | |
---|---|---|
167 | 57 | |
18,617 | 7,819 | |
4.3% | 3.0% | |
9.8 | 8.8 | |
2 days ago | 6 days ago | |
Python | Python | |
MIT License | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
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.
uvicorn
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How to Deploy a Fast API Application to a Kubernetes Cluster using Podman and Minikube
FastAPI & Uvicorn
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LangChain, Python, and Heroku
This tells Heroku to run uvicorn, which is a web server implementation in Python.
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Fun with Avatars: Crafting the core engine | Part. 1
FastAPI uses Uvicorn, an ASGI (Asynchronous Server Gateway Interface) web server implementation for Python.
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Effortless API Documentation: Accelerating Development with FastAPI, Swagger, and ReDoc
Now, let’s run our FastAPI application using Uvicorn: uvicorn main:app --reload
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FastHttp for Python (64k requests/s)
Uvicorn + Starlette 8k requests/s
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Ask HN: Where to Host a FastAPI App
I switched to Hypercorn because Uvicorn currently supports HTTP/1.1 and WebSockets as mentioned at https://www.uvicorn.org
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How to use Chroma to store and query vector embeddings
This will set up Chroma and run it as a server with uvicorn, making port 8000 accessible outside the net docker network. The command also mounts a persistent docker volume for Chroma's database, found at chroma/chroma from your project's root.
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Unresolved Memory Management Issues in FastAPI/Starlette/Uvicorn/Python During High-Load Scenarios
There's an open discussion under the Uvicorn repository and we prepared a repository for Reproduction GitHub Repo
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How to Dockerize and Deploy a Fast API Application to Kubernetes Cluster
FastAPI is a popular Python Web framework that developers use to create RESTful APIs. It is based on Pydantic and Python-type hints that assist in the serialization, deserialization, and validation of data. In this tutorial, we will use FastAPI to create a simple "Hello World" application. We test and run the application locally. FastAPI requires a ASGI server to run the application production such as Uvicorn.
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FastAPI 0.100.0:Release Notes
- [3] https://github.com/encode/uvicorn/issues/527
What are some alternatives?
Cerberus - Lightweight, extensible data validation library for Python
daphne - Django Channels HTTP/WebSocket server
nexe - 🎉 create a single executable out of your node.js apps
hypercorn
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.
SQLAlchemy - The Database Toolkit for Python
Flask - The Python micro framework for building web applications.
sqlmodel - SQL databases in Python, designed for simplicity, compatibility, and robustness.
dash - Data Apps & Dashboards for Python. No JavaScript Required.
mypy - Optional static typing for Python
starlette - The little ASGI framework that shines. 🌟