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Use queues to limit concurrent workflow executions.
Define queues
from polos import queue
# Limit concurrent API calls
api_queue = queue("api-calls", concurrency_limit=5)
# Limit database connections
db_queue = queue("database-ops", concurrency_limit=10)
# Limit CPU-intensive work
heavy_queue = queue("heavy-processing", concurrency_limit=2)
Assign workflows to queues
from polos import workflow, WorkflowContext
@workflow(id="api_call", queue=api_queue)
async def api_call(ctx: WorkflowContext, payload):
return await ctx.step.run("request", make_api_request, payload)
@workflow(id="db_read", queue=db_queue)
async def db_read(ctx: WorkflowContext, payload):
return await ctx.step.run("query", execute_query, payload)
# Multiple workflows can share the same queue
@workflow(id="db_write", queue=db_queue)
async def db_write(ctx: WorkflowContext, payload):
return await ctx.step.run("insert", insert_data, payload)
Inline queue config
@workflow(id="inline_queue", queue={"concurrency_limit": 3})
async def inline_queue(ctx: WorkflowContext, payload):
return {"message": "Processed"}
@workflow(id="named_queue", queue="my-queue")
async def named_queue(ctx: WorkflowContext, payload):
return {"message": "Processed"}
Run it
git clone https://github.com/polos-dev/polos.git
cd polos/python-examples/12-shared-queues
cp .env.example .env # Add your POLOS_PROJECT_ID and API key
uv sync
python main.py
