Files
sientia-dataops-scouter_tem…/scouter/worker/prepare_worker.py
vitor-aignosi 5e2403090b SIENTIAPDE-1441
Refactor prepare_worker function to return a single Worker instance instead of a list, streamlining worker configuration and improving code clarity.
2025-12-16 15:43:01 -03:00

58 lines
2.2 KiB
Python

from typing import Sequence, Type, Any
from temporalio.worker import Worker, PollerBehaviorAutoscaling
from temporalio.client import Client
import os
parameters = [
('MAX_CONCURRENT_WORKFLOW_TASKS', '200'),
('MAX_CONCURRENT_ACTIVITIES', '200'),
('MAX_CONCURRENT_LOCAL_ACTIVITIES', '200'),
('MAX_CACHED_WORKFLOWS', '200'),
('WORKFLOW_POLLER_BEHAVIUR_MINIMUM', '10'),
('WORKFLOW_POLLER_BEHAVIUR_INITIAL', '100'),
('WORKFLOW_POLLER_BEHAVIUR_MAXIMUM', '200'),
('ACTIVITY_POLLER_BEHAVIUR_MINIMUM', '10'),
('ACTIVITY_POLLER_BEHAVIUR_INITIAL', '100'),
('ACTIVITY_POLLER_BEHAVIUR_MAXIMUM', '200'),
]
def prepare_worker(
main_workflow: Type,
other_workflows: Sequence[Type],
activities: Sequence[Any],
temporal_client: Client,
) -> Worker:
main_workflow_name = main_workflow.__name__.upper()
local_workflow_parameters = {}
for parameter in parameters:
local_workflow_parameters[parameter[0]] = int(
os.getenv(main_workflow_name + '_' + parameter[0], parameter[1]))
return Worker(
temporal_client,
task_queue='scouter-queue',
workflows=[main_workflow, *other_workflows],
activities=[*activities],
max_concurrent_workflow_tasks=local_workflow_parameters['MAX_CONCURRENT_WORKFLOW_TASKS'],
max_concurrent_activities=local_workflow_parameters['MAX_CONCURRENT_ACTIVITIES'],
max_concurrent_local_activities=local_workflow_parameters['MAX_CONCURRENT_LOCAL_ACTIVITIES'],
max_cached_workflows=local_workflow_parameters['MAX_CACHED_WORKFLOWS'],
workflow_task_poller_behavior=PollerBehaviorAutoscaling(
minimum=local_workflow_parameters['WORKFLOW_POLLER_BEHAVIUR_MINIMUM'],
initial=local_workflow_parameters['WORKFLOW_POLLER_BEHAVIUR_INITIAL'],
maximum=local_workflow_parameters['WORKFLOW_POLLER_BEHAVIUR_MAXIMUM'],
),
activity_task_poller_behavior=PollerBehaviorAutoscaling(
minimum=local_workflow_parameters['ACTIVITY_POLLER_BEHAVIUR_MINIMUM'],
initial=local_workflow_parameters['ACTIVITY_POLLER_BEHAVIUR_INITIAL'],
maximum=local_workflow_parameters['ACTIVITY_POLLER_BEHAVIUR_MAXIMUM'],
),
)