uvicorn
starlette
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uvicorn | starlette | |
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57 | 55 | |
7,819 | 9,491 | |
3.0% | 2.8% | |
8.8 | 9.2 | |
5 days ago | 8 days ago | |
Python | Python | |
BSD 3-clause "New" or "Revised" 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.
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
starlette
- Ask HN: What is your go-to stack for the web?
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Building Fast APIs with FastAPI: A Comprehensive Guide
Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.
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Embracing Modern Python for Web Development
The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.
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FastHttp for Python (64k requests/s)
Uvicorn + Starlette 8k requests/s
- Microdot "The impossibly small web framework for Python and MicroPython"
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An Introduction to âš¡FastAPI
Starlette documentation
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Writing a chat application in Django 4.2 using async StreamingHttpResponse
Same here, but without these weird utils it doesn't get any better.
I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.
Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.
https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...
In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.
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Deploying an ML model to Paperspace and creating an API
Set up Starlette, a tool we'll use to make async requests
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FastAPI middleware doesn't run while making request to websocket endpoint
I never used websockets in FastAPI so I wouldn't know how to guide you more, but Middleware in Websockets are 100% supported by Starlette : https://github.com/encode/starlette/issues/641
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Chat implementation
Websockets are the way but I would not recommend django as it's still not fully async. I would go for other tools.
What are some alternatives?
daphne - Django Channels HTTP/WebSocket server
Flask - The Python micro framework for building web applications.
hypercorn
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
hypercorn - Hypercorn is an ASGI and WSGI Server based on Hyper libraries and inspired by Gunicorn.
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
starlite - Light, Flexible and Extensible ASGI API framework | Effortlessly Build Performant APIs [Moved to: https://github.com/litestar-org/litestar]
dash - Data Apps & Dashboards for Python. No JavaScript Required.
quart - An async Python micro framework for building web applications.
uvloop - Ultra fast asyncio event loop.
pydantic - Data validation using Python type hints