Python framework to serve millions

Handling millions of concurrent connections is a significant challenge for any system. In the case of Python, there are several frameworks and libraries that can help build highly scalable and performant production systems capable of managing such workloads. Some of these frameworks and libraries include:

  1. Tornado: Tornado is a Python web framework and asynchronous networking library that uses non-blocking I/O and an event-driven approach. This makes it suitable for handling thousands to millions of concurrent connections. It is commonly used in real-time web applications and other services requiring high concurrency.
  2. Twisted: Twisted is an event-driven networking engine that supports various communication protocols, including TCP, UDP, SSL/TLS, and more. It can be used to create highly scalable servers that can handle millions of concurrent connections by using an asynchronous, non-blocking I/O model.
  3. FastAPI: FastAPI is a modern, high-performance web framework for building APIs with Python 3.7+ based on standard Python type hints. It is built on top of Starlette for the web parts and Pydantic for the data validation. It can handle a significant number of concurrent connections by using asynchronous programming techniques and is known for its performance and ease of use.
  4. Sanic: Sanic is an asynchronous web framework that’s designed for fast HTTP responses via asynchronous request handling. It is built on top of the Python 3.5+ async/await features and uses the uvloop library for efficient event loop handling, which enables it to handle a large number of concurrent connections.
  5. Gunicorn + Eventlet or Gevent: Gunicorn is a popular WSGI HTTP server that can be combined with asynchronous worker types like Eventlet or Gevent to handle many concurrent connections. Eventlet and Gevent are both concurrency libraries that use greenlets (lightweight, cooperative threads) to provide efficient asynchronous I/O handling.

When selecting a framework or library for your specific use case, consider factors like ease of use, performance, scalability, and community support. Note that the ability to handle millions of concurrent connections also depends on factors like server hardware, network infrastructure, and application architecture.

Photo by Brett Sayles