uvicorn
starlette
uvicorn | starlette | |
---|---|---|
68 | 71 | |
9,211 | 10,990 | |
1.9% | 1.9% | |
8.5 | 9.1 | |
8 days ago | 15 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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A2A Python Tutorial - Comprehensive Guide
We're almost ready to start our server! We'll be using the A2AServer class from Google-A2A which under the hood starts a uvicorn server.
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Understanding the Relation Between FastAPI and Uvicorn
FastAPI and Uvicorn are two essential building blocks when developing high-performance Python APIs.
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How to use FastAPI for microservices in Python
To run the server, you will also need to install Uvicorn:
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Understanding Uvicorn: The basics
So I've decided to create another series of articles, and this time talking about another piece of FastAPI development: ASGI servers, and mainly focusing on π¦ uvicorn due to the evident synergy between both projects π.
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What I wish I knew about Python when I started
Finally, whatever file launches your application (in this case, mine is main.py), it is conventional to include that if __name__ == "main": block at the bottom (shown above), to specify the entrypoint to your application. This isn't strictly necessary in many use casesβfor instance, if you're writing a REST API using FastAPI and launching it via uvicorn, you don't need this block. But it also doesn't hurt to have it regardless. It's a helpful reminder of where things begin.
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FastAPI Tutorial: Build, Deploy, and Secure an API for Free
This article is written by Marcelo Trylesinski, a > FastAPI expert and > maintainer of Starlette and > Uvicorn. You can check out more of his work > here. All opinions expressed are his own.
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Show HN: I reverse engineered X to Read Threads without Any Account as Articles
Since, app has selenium minimum running requirement would be 1GB RAM on any OS, and free version of any hosting do not provide that, some that provide are limited by build times or shared cpus.
So it was only logical to go through the pain/pleasure of setting up deployment on VM.
Python Backend is deployed on Azure VM(with 4 GB), since it's built on Fastapi their AWSGI support helps keep the server running on long intervals.
This one is using CF Tunnels to Prod to reduce the latency due to server location.
You can see uvicorn docs to learn more https://www.uvicorn.org/
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Top 20 Python API Frameworks with OpenAPI Support
Uvicorn is a lightning-fast ASGI server implementation, using uvloop and httptools. It is designed to run asynchronous Python web applications, particularly those built with frameworks like FastAPI, Starlette, and others.
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How to Build a Python API from Scratch with FastAPI
Uvicorn - An ASGI web server implementation for Python
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uvicorn VS tremolo - a user suggested alternative
2 projects | 11 Jul 2024
starlette
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Python: Why Quart Might Be the Better Choice over FastAPI
FastAPI: A modern, high-performance framework designed for building APIs with Python 3.7+ that prioritizes speed and efficiency. It leverages Python type hints to improve code readability and maintainability, and it integrates seamlessly with Starlette for asynchronous capabilities and Pydantic for data validation.
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FastAPI is Overkill: Starlette and Pydantic Are All You Really Need
In the field of Python web development, FastAPI has received much attention due to its concise and user-friendly features. However, in reality, it is just a high-level encapsulation of Starlette and Pydantic. The official Starlette website showcases its rich features, and Pydantic is renowned for its powerful data validation capabilities. By directly using these two libraries, developers can flexibly build high-performance APIs without relying on the encapsulation of FastAPI. Next, we will elaborate in detail by combining the core functions and features of both.
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How to use FastAPI for microservices in Python
The framework's official website mentions a number of pros of FastAPI. In my opinion, the most useful features from a microservice perspective are: the simplicity of code (easy to use and avoid boilerplate), high operational capacity thanks to Starlette and Pydantic and compatibility with industry standards - OpenAPI and JSON Schema.
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π₯ The Fastest Python API Frameworks Ranked β Which One Should You Choose?
π Learn More: Starlette GitHub
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FastAPI Tutorial: Build, Deploy, and Secure an API for Free
This article is written by Marcelo Trylesinski, a > FastAPI expert and > maintainer of Starlette and > Uvicorn. You can check out more of his work > here. All opinions expressed are his own.
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Best Backend Frameworks for 2025: A Developer's Guide to Making the Right Choice
Starlette: The ASGI Foundation
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The Core of FastAPI: A Deep Dive into Starlette πππ
FastAPI is essentially an API wrapper for Starlette. To fully grasp FastAPI, one must first understand Starlette.
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Server-Sent Events (SSE) Are Underrated
I built several tool to tail logs with SSE using Flask/FastAPI. Easy to implement and maintain.
For FastAPI if you want some hooks when client disconnects aka nginx 499 errors, follow this simple tip
https://github.com/encode/starlette/discussions/1776#discuss...
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Is Flask Dead? Is FastAPI the Future?
ASGI Web Framework: Web frameworks that implement the ASGI specification (such as FastAPI), while Flask and Django are web frameworks that implement WSGI. These frameworks are designed for developers to write applications, with easy-to-use interfaces. Developers only need to fill in the business logic according to their needs. Early frameworks mostly implemented ASGI toolkits internally, while later frameworks usually combine suitable toolkits. For example, Flask uses Werkzeug (its own), and FastAPI uses Starlette (from others).
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Top 20 Python API Frameworks with OpenAPI Support
Starlette is a lightweight ASGI framework/toolkit, ideal for building high-performance async services in Python. It provides the essential components needed to build web applications, including routing, middleware, sessions, and more.
What are some alternatives?
granian - A Rust HTTP server for Python applications
AIOHTTP - Asynchronous HTTP client/server framework for asyncio and Python
daphne - Django Channels HTTP/WebSocket server
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.
Flask - The Python micro framework for building web applications.