9 min read
Note: This post was updated with additional details regarding AWS Lambda.
Last year we announced basic support for Python Workers , allowing Python developers to ship Python to region: Earth in a single command and take advantage of the Workers platform .
Since then, we’ve been hard at work making the Python experience on Workers feel great. We’ve focused on bringing package support to the platform, a reality that’s now here — with exceptionally fast cold starts and a Python-native developer experience.
This means a change in how packages are incorporated into a Python Worker. Instead of offering a limited set of built-in packages, we now support any package supported by Pyodide , the WebAssembly runtime powering Python Workers. This includes all pure Python packages, as well as many packages that rely on dynamic libraries. We also built tooling around uv to make package installation easy.
We’ve also implemented dedicated memory snapshots to reduce cold start times. These snapshots result in serious speed improvements over other serverless Python vendors. In cold start tests using common packages, Cloudflare Workers start over 2.4x faster than AWS Lambda without SnapStart and 3x faster than Google Cloud Run.
In this blog post, we’ll explain what makes Python Workers unique and share some of the technical details of how we’ve achieved the wins described above. But first, for those who may not be familiar with Workers or serverless platforms – and especially those coming from a Python background — let us share why you might want to use Workers at all.
Deploying Python globally in 2 minutes
Part of the magic of Workers is simple code and easy global deployments. Let's start by showing how you can deploy a FastAPI app across the world with fast cold starts in less than two minutes.
A simple Worker using FastAPI can be implemented in a handful of lines:
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