hello_parallel_activity.py

import asyncio
from concurrent.futures import ThreadPoolExecutor
from datetime import timedelta
from typing import List

from temporalio import activity, workflow
from temporalio.client import Client
from temporalio.envconfig import ClientConfig
from temporalio.worker import Worker


@activity.defn
def say_hello_activity(name: str) -> str:
    return f"Hello, {name}!"


@workflow.defn
class SayHelloWorkflow:
    @workflow.run
    async def run(self) -> List[str]:
        # Run 5 activities at the same time
        results = await asyncio.gather(
            workflow.execute_activity(
                say_hello_activity, "user1", start_to_close_timeout=timedelta(seconds=5)
            ),
            workflow.execute_activity(
                say_hello_activity, "user2", start_to_close_timeout=timedelta(seconds=5)
            ),
            workflow.execute_activity(
                say_hello_activity, "user3", start_to_close_timeout=timedelta(seconds=5)
            ),
            workflow.execute_activity(
                say_hello_activity, "user4", start_to_close_timeout=timedelta(seconds=5)
            ),
            workflow.execute_activity(
                say_hello_activity, "user5", start_to_close_timeout=timedelta(seconds=5)
            ),
        )
        # Sort the results because they can complete in any order
        return list(sorted(results))


async def main():
    # Start client
    config = ClientConfig.load_client_connect_config()
    config.setdefault("target_host", "localhost:7233")
    client = await Client.connect(**config)

    # Run a worker for the workflow
    async with Worker(
        client,
        task_queue="hello-parallel-activity-task-queue",
        workflows=[SayHelloWorkflow],
        activities=[say_hello_activity],
        activity_executor=ThreadPoolExecutor(10),
    ):
        # While the worker is running, use the client to run the workflow and
        # print out its result. Note, in many production setups, the client
        # would be in a completely separate process from the worker.
        result = await client.execute_workflow(
            SayHelloWorkflow.run,
            id="hello-parallel-activity-workflow-id",
            task_queue="hello-parallel-activity-task-queue",
        )
        print(f"Result: {result}")


if __name__ == "__main__":
    asyncio.run(main())