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Run a Function in the Cloud

The simplest way to run code on Beam is to add the @function decorator to any Python function. Save this to app.py:
app.py
from beam import function


@function(cpu=1, memory="1Gi")
def square(x: int):
    return {"result": x**2}


if __name__ == "__main__":
    print(square.remote(x=12))
Run it like any other Python file: 
python app.py
Beam syncs your code, launches a container, runs the function, and streams the result back to your shell: 
=> Building image
=> Using cached image
=> Syncing files
=> Files synced
=> Running function: <app:square>
{'result': 144}
=> Function complete
The container spins up in seconds, runs your code, and shuts itself down. No idle costs, no infrastructure to clean up.

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Deploy a Web Endpoint

To turn your code into a live web API, swap @function for @endpoint. We’ll include numpy in the image to show how easily you can add Python packages.
  • Image() defines your container environment. You can add Python packages, system dependencies, or even custom Dockerfiles.
  • @endpoint turns your function into a real, live web API that runs in the cloud.
app.py
from beam import endpoint, Image


@endpoint(
    name="quickstart",
    cpu=1,
    memory="1Gi",
    image=Image().add_python_packages(["numpy"]),
)
def predict(**inputs):
    x = inputs.get("x", 256)
    return {"result": x**2}

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Deployment

Deploy the endpoint to the cloud: 
beam deploy app.py:predict

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Call the API

When the deploy finishes, Beam prints your endpoint URL along with a ready-to-run curl command. Replace [TOKEN] with your token and use the URL from your deploy output: 
curl -X POST 'https://app.beam.cloud/endpoint/quickstart' \
  -H 'Authorization: Bearer [TOKEN]' \
  -H 'Content-Type: application/json' \
  -d '{"x": 12}'
Either way, you’ll get back: 
{ "result": 144 }
The container spins up in seconds, runs your code, and shuts itself down. No idle costs. No infrastructure to clean up.

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What Next?

Here are some other things you can try: