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uvicorn | hypercorn | |
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57 | 3 | |
7,819 | - | |
3.0% | - | |
8.8 | - | |
3 days ago | - | |
Python | ||
BSD 3-clause "New" or "Revised" License | - |
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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, letโs 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
hypercorn
- Gunicorn
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HTTP/3: Practical Deployment Options (Part 3)
Whilst the article rightly mentions aioquic to use HTTP/3 with Python, it is only a minimal example server. Hypercorn is a compete ASGI server built on aioquic that is likely more useful practically.
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ASGI webservers producing strange unmotivated random spikes of delay (seconds!) and generally only half as fast as their gevent or eventlet counterparts. Very strange.
This is interesting, and not something I've seen before. I'm preoccupied with a Werkzeug/Flask release at the moment then I'll take at look into this. Any more details would be welcome on https://gitlab.com/pgjones/hypercorn/-/issues/181
What are some alternatives?
daphne - Django Channels HTTP/WebSocket server
gunicorn - gunicorn 'Green Unicorn' is a WSGI HTTP Server for UNIX, fast clients and sleepy applications.
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.
Flask - The Python micro framework for building web applications.
python-uvicorn - Multiarchitecture Docker Containers for Python and Uvicorn
dash - Data Apps & Dashboards for Python. No JavaScript Required.
aioquic - QUIC and HTTP/3 implementation in Python
starlette - The little ASGI framework that shines. ๐
python-gunicorn-uvicorn - Multiarchitecture Docker Containers for Python using Gunicorn and Uvicorn
uvloop - Ultra fast asyncio event loop.
build-a-saas-app-with-flask - Learn how to build a production ready web app with Flask and Docker.