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hello_activity_threaded.py
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hello_activity_threaded.py
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import asyncio
import threading
import time
from concurrent.futures import ThreadPoolExecutor
from dataclasses import dataclass
from datetime import timedelta
from temporalio import activity, workflow
from temporalio.client import Client
from temporalio.worker import Worker
@dataclass
class ComposeGreetingInput:
greeting: str
name: str
@activity.defn
def compose_greeting(input: ComposeGreetingInput) -> str:
# We'll wait for 3 seconds, heartbeating in between (like all long-running
# activities should do), then return the greeting
for _ in range(0, 3):
print(f"Heartbeating activity on thread {threading.get_ident()}")
activity.heartbeat()
time.sleep(1)
return f"{input.greeting}, {input.name}!"
@workflow.defn
class GreetingWorkflow:
@workflow.run
async def run(self, name: str) -> str:
return await workflow.execute_activity(
compose_greeting,
ComposeGreetingInput("Hello", name),
start_to_close_timeout=timedelta(seconds=10),
# Always set a heartbeat timeout for long-running activities
heartbeat_timeout=timedelta(seconds=2),
)
async def main():
# Start client
client = await Client.connect("localhost:7233")
# Run a worker for the workflow
async with Worker(
client,
task_queue="hello-activity-threaded-task-queue",
workflows=[GreetingWorkflow],
activities=[compose_greeting],
# Synchronous activities are not allowed unless we provide some kind of
# executor. This same thread pool could be passed to multiple workers if
# desired.
activity_executor=ThreadPoolExecutor(5),
):
# 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(
GreetingWorkflow.run,
"World",
id="hello-activity-threaded-workflow-id",
task_queue="hello-activity-threaded-task-queue",
)
print(f"Result on thread {threading.get_ident()}: {result}")
if __name__ == "__main__":
asyncio.run(main())