Hello, world!

The basics: run functions locally, remotely, and in parallel.

The code

import sys
import openmodal

app = openmodal.App("example-hello-world")

@app.function()
def f(i):
    if i % 2 == 0:
        print("hello", i)
    else:
        print("world", i, file=sys.stderr)
    return i * i

@app.local_entrypoint()
def main():
    print(f.local(1000))     # runs on your machine
    print(f.remote(1000))    # runs in a container
    total = 0
    for ret in f.map(range(200)):  # 200 calls in parallel
        total += ret
    print(total)

Run it

Local (Docker)GCP

openmodal --local run examples/hello_world.py

✓ Initialized.
✓ Created objects.
✓ Container created. (local CPU • localhost • 0s)
✓ Container ready. (2s total)
hello 1000
1000000
1000000
2646700
✓ Containers cleaned up.
✓ App completed.

openmodal run examples/hello_world.py

✓ Initialized.
✓ Created objects.
✓ Container created. (2 vCPU, 2 GB RAM • 34.135.113.28 • 14s)
✓ Container ready. (60s total)
hello 1000
1000000
1000000
2646700
✓ Containers cleaned up.
✓ App completed.

What happened?

1. f.local(1000) ran on your machine — returned 1000000
2. f.remote(1000) ran inside a container (Docker or cloud VM) — same result
3. f.map(range(200)) sent 200 calls to the container in parallel

The container was automatically cleaned up when the script finished.