A FastAPI/Starlette demo implementing a real-time chatroom with WebSocket broadcast and private messaging.
fastapi-websocket-broadcast is a demonstration project that implements a real-time chat application using FastAPI and Starlette's WebSocket capabilities. It solves the problem of building scalable, real-time communication features by providing a working example of WebSocket broadcast, user presence tracking, and private messaging.
Python developers learning to build real-time applications with FastAPI, or those seeking a reference implementation for WebSocket-based features like chatrooms or notifications.
Developers choose this project because it offers a concise, production-ready example of WebSocket handling in FastAPI, with clear code structure and features like broadcast messaging and user presence that are immediately applicable to real-world projects.
Websocket 'broadcast' demo using FastAPI/Starlette
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Uses a consistent JSON format for all WebSocket messages, including types like ROOM_JOIN and WHISPER, which simplifies client-side parsing and error handling as shown in the README.
Implements broadcast messaging, private whispers, and user presence events in a single example, providing a ready reference for common chat functionalities without extra dependencies.
Leverages FastAPI's auto-generated REST API documentation via the /docs endpoint, making it easy to explore and test the application setup.
Emphasizes idiomatic FastAPI and Starlette patterns, serving as a practical, production-style example for developers learning WebSocket implementation.
Lacks database integration or storage mechanisms, so chat messages and user data are lost on server restart, limiting real-world usability.
Only supports a common chatroom without dynamic room creation or management, reducing flexibility for applications requiring multiple isolated spaces.
Does not include user authentication or authorization features, making it unsuitable for secure environments without significant additional development.
As a demonstration project, it may not handle high concurrency or include optimizations like connection pooling, requiring extra work for production scaling.