Python
Cloudflare Workers provides first-class support for Python, including support for:
- The majority of Python’s Standard library
- All bindings, including Workers AI, Vectorize, R2, KV, D1, Queues, Durable Objects, Service Bindings and more.
- Environment Variables, and Secrets
- A robust foreign function interface (FFI) that lets you use JavaScript objects and functions directly from Python — including all Runtime APIs
- Built-in packages, including FastAPI, Langchain, httpx and more.
Get started
git clone https://github.com/cloudflare/python-workers-examplescd 01-hellonpx wrangler@latest dev
A Python Worker can be as simple as three lines of code:
index.pyfrom js import Response
def on_fetch(request): return Response.new("Hello World!")
Similar to Workers written in JavaScript, TypeScript, or Rust, the main entry point for a Python worker is the fetch
handler. In a Python Worker, this handler is named on_fetch
.
To run a Python Worker locally, you use Wrangler, the CLI for Cloudflare Workers:
npx wrangler@latest dev
To deploy a Python Worker to Cloudflare, run wrangler deploy
:
npx wrangler@latest deploy
Modules
Python workers can be split across multiple files. Let’s create a new Python file, called hello.py
:
index.pydef hello(name): return "Hello, " + name + "!"
Now, we can modify entry.py
to make use of the new module.
index.pyfrom hello import hellofrom js import Response
def on_fetch(request): return Response.new(hello("World"))
Once you edit entry.py
, Wrangler will automatically detect the change and
reload your Worker.
The Request
Interface
The request
parameter passed to your fetch
handler is a JavaScript Request object, exposed via the foreign function interface, allowing you to access it directly from your Python code.
Let’s try editing the worker to accept a POST request. We know from the
documentation for Request
that we can call
await request.json()
within an async
function to parse the request body as
JSON. In a Python Worker, you would write:
index.pyfrom js import Responsefrom hello import hello
async def on_fetch(request): name = (await request.json()).name return Response.new(hello(name))
Once you edit the entry.py
, Wrangler should automatically restart the local
development server. Now, if you send a POST request with the appropriate body,
your Worker should respond with a personalized message.
$ curl --header "Content-Type: application/json" \ --request POST \ --data '{"name": "Python"}' http://localhost:8787# Hello, Python!
The env
Parameter
In addition to the request
parameter, the env
parameter is also passed to
the Python fetch
handler and can be used to access
environment variables,
secrets,and
bindings.
For example, let’s try setting and using an environment variable in a Python
Worker. First, add the environment variable to your Worker’s wrangler.toml
:
wrangler.tomlname = "hello-python-worker"
main = "entry.py"
compatibility_flags = ["python_workers"]
compatibility_date = "2024-03-20"
[vars]
API_HOST = "example.com"
Then, you can access the API_HOST
environment varialbe via the env
parameter:
index.pyfrom js import Response
async def on_fetch(request, env): return Response.new(env.API_HOST)
Further Reading
- Understand which parts of the Python Standard Library are supported in Python Workers.
- Learn about Python Workers’ foreign function interface (FFI), and how to use it to work with bindings and Runtime APIs.
- Explore the Built-in Python packages that the Workers runtime provides.