Documentation

Docs and examples

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Architecture diagrams

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Production layout: API, workers, Beat, Flower, brokers

Celery pipeline: API RL → enqueue → RabbitMQ → job RL + lock → side effect

Locks & rate limits: Redis beside the worker path

Transactional outbox: commit then publish safely

Observability: Flower, Prometheus, app metrics

Guides

20/20

Pseudocode snippets

5/5

Quick patterns. Full context lives in the guides above.

Enqueue + 202

async def enqueue_export(body, db, bus):
 job = await db.insert_job(type="export", status="pending", ...)
 await bus.publish("jobs.heavy", {"job_id": str(job.id), "type": "export"})
 return {"job_id": job.id} # HTTP 202

Idempotent worker

async def handle(message, db):
 job = await db.get_job(message["job_id"])
 if job.status == "succeeded":
 return
 await db.mark_running(job.id)
 await do_work(job)
 await db.mark_succeeded(job.id)

Transactional outbox

async with db.transaction():
 job = await db.insert_job(...)
 await db.insert_outbox(
 destination="jobs.default",
 payload={"job_id": str(job.id), "type": job.type},
 )

Lock + job rate limit

@celery_app.task(bind=True, max_retries=25)
def sync_account(self, job_id: str, account_id: str):
 if not take_token(redis, f"rl:vendor:{account_id}", rate=5, burst=10):
 raise self.retry(countdown=2)
 token = new_uuid()
 if not acquire_lock(redis, f"lock:account:{account_id}", token, ttl=300):
 raise self.retry(countdown=10)
 try:
 do_sync(account_id)
 finally:
 release_lock(redis, f"lock:account:{account_id}", token)

Job metrics sketch

metrics.incr("jobs_enqueued_total", tags={"type": job.type})
metrics.observe("job_runtime_seconds", elapsed, tags={"type": job.type})
# backlog: rabbitmq_queue_depth gauge per queue
# alerts: consumers==0 critical; dlq_depth>0 high

Machine-readable export

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Open llms-full.txt