Cloudflare's Python Workers reach general availability

Cloudflare has announced that Python Workers are now generally available (GA), two years after the capability was introduced as a way to run Python applications in the Cloudflare Workers runtime. The company describes the release as making Python a first-class, fully supported language on its developer platform.

A Pythonic path to Cloudflare services

Previously, using Cloudflare bindings from Python required converting Python objects into TypeScript objects explicitly at the RPC boundary: sending a dictionary to a Queue, for instance, needed glue code built on Pyodide's to_js helper. That type conversion now lives inside the Workers runtime and the Python SDK, so no JavaScript has to be written. Workers connect directly to Workers AI, R2, D1, Hyperdrive, Durable Objects, Queues and Workflows.

Frameworks, WASM packages and databases

Python Workers can now run FastAPI, Django and Flask through the new workers.asgi and workers.wsgi connectors, which translate an incoming JavaScript request into the WSGI/ASGI structures Python frameworks expect; the Workers platform itself acts as the web server, so no separate uvicorn or Gunicorn process is needed. Because Python runs in a WebAssembly sandbox through Pyodide, Cloudflare proposed PEP 783, accepted after more than a year of discussion, which standardizes a package platform called PyEmscripten; support for it was also added to cibuildwheel. Socket system calls implemented on the Workers connect API unblocked TCP-based database drivers such as aiomysql and asyncpg, enabling Hyperdrive integration for PostgreSQL and MySQL, and let HTTP clients used by openai, langchain and mcp work.

Examples and what comes next

Cloudflare published production-ready patterns in a python-workers-examples repository, among them an image-to-image generator combining Queues, Workflows, Workers AI and R2, a Bluesky Jetstream WebSocket consumer kept alive by a Durable Object, an MCP server and a RAG system built on Workers AI and Vectorize. The documentation now offers Python snippets alongside TypeScript across products. The company says further work on performance, memory efficiency and package support is planned.