Generators

You may have noticed that whenever we get the results/files from a task, we use an async for loop. This is because tasks can produce multiple results/files over time, and using a generator allows us to process them as they become available without waiting for all of them to be ready.

from hyperscript import Hyperscript
from hyperscript.convergence import Convergence
import os


def output_multiple_results():
    import time
    for i in range(5):
        # Yield results one by one. We could also yield files here if needed.
        yield f"Result {i}"
        time.sleep(1)  # Simulate some delay

def multiply_by_3(value):
    return value * 3


async def main():
    # Set up Convergence as our backend
        convergence = Convergence(api_key=os.getenv("CONVERGENCE_API_KEY"))

    # Initialize Hyperscript with Convergence's storage and event systems
    async with Hyperscript(
        storage=convergence.storage, events=convergence.events
    ) as hs:
        # Run the hello_world function in the cloud
        task = await hs.run(
            fn=output_multiple_results,
            executor=convergence.executor)

        tasks = []

        # Now we can process results as they come in
        async for result in task.results():
            print(f"Got result: {result}")  # Should print the line count of the file
            # Now we can process each result further if needed
            processed_task = await hs.run(
                fn=multiply_by_3,
                args=[result],
                executor=convergence.executor)
            tasks.append(processed_task)

        # Retrieve processed results
        for t in tasks:
            async for processed_result in t.results():
                print(f"Processed result: {processed_result}")


if __name__ == "__main__":
    import asyncio

    asyncio.run(main())