Python on Vercel is now generally available

Vercel has released Python support as generally available, allowing developers to build and run Python applications using familiar frameworks, libraries, and tools. The platform automatically detects supported frameworks such as FastAPI, Flask, Django, and FastHTML, configuring builds and deployments without manual setup. Applications run on Fluid compute, which handles concurrent requests and scales with traffic, while idiomatic Python SDKs provide access to storage, queues, durable workflows, and AI models directly from Python code.

For full-stack projects, Vercel enables a shared workflow where Python backends and JavaScript frontends can be developed, previewed, and deployed together. The platform’s Services feature consolidates both parts into a single project, allowing local development with vercel dev and unified preview deployments. Vercel Daemons ensures long-running workers remain active, supporting background tasks like queue processing or database polling alongside Python packages and system dependencies.

Python SDKs on Vercel cover storage, messaging, durable workflows, code execution, AI model interactions, and external API credential management. These SDKs follow Python conventions, including type annotations, async/await, and context managers, ensuring compatibility with the broader Python ecosystem. The runtime uses CPython on Linux to maintain compatibility with existing packages and tools developers rely on.

A practical example demonstrates how these components integrate in a full-stack application. A collaborative web app built with a Vite frontend, FastAPI backend, and PostgreSQL database uses Services for unified deployment and Vercel Queues for real-time updates. FastAPI manages isolated Jupyter sandboxes for code execution, while the browser connects directly to the sandbox and receives updates via WebSockets without page reloads.