Paano co-run robust background jobs (Celery/ARQ)?

Question

Accepted Answer

Kanggo **robust, durable background jobs** (ngliwati lightweight `BackgroundTasks` FastAPI), sampeyan nggunakne real task queue: **Celery** (standard established) utawa **ARQ** (modern async-native queue). Iki ngjalanke heavy, retryable, scheduled work ing proses worker pisah, diganti dening broker kaya Redis.

## Napa iku penting

```text
BackgroundTasks runs in the web process → NO persistence (lost on crash), NO retries,
NO scheduling, and heavy work ties up the worker. Fine only for quick fire-and-forget.
For durable/critical/heavy/scheduled jobs → use a real task queue (Celery / ARQ).
```

## Celery — define lan queue tasks

```python
# tasks.py
from celery import Celery
celery_app = Celery("tasks", broker="redis://localhost:6379")

@celery_app.task(bind=True, max_retries=3)
def process_video(self, video_id: int):
    try:
        do_heavy_processing(video_id)        # runs in a WORKER, not the web process
    except Exception as exc:
        raise self.retry(exc=exc, countdown=60)   # automatic retry on failure
```

```python
# in a FastAPI endpoint — QUEUE the task, return immediately
@app.post("/videos/{id}/process")
def process(id: int):
    process_video.delay(id)                  # enqueue → returns at once (doesn't block)
    return {"status": "processing started"}
# run workers separately: celery -A tasks worker
```

Endpoint ngikutne job lan mbalas seketika; proses **worker** pisah ngjalanke karo persistence lan retries.

## ARQ — async-native (cocog karo model async FastAPI)

```python
# ARQ is built on asyncio — a natural fit for async FastAPI codebases
async def process_video(ctx, video_id: int):
    await do_async_processing(video_id)

# enqueue from an endpoint
await redis.enqueue_job("process_video", video_id)
```

ARQ iku lighter, async-first alternative — narik manawa codebase sampeyan wis async.

## Apa sing diwenehne real task queue

```text
✓ Persistence — jobs survive crashes/restarts (stored in the broker)
✓ Retries with backoff — resilience against transient failures
✓ Scheduling — periodic/cron-like jobs (Celery Beat)
✓ Distribution & scaling — workers scale independently of the web servers
✓ Concurrency & rate limiting, task routing/priorities, result tracking
```

## Napa iku penting

Ngjalanke robust background jobs iku essential kanggo nggawe production-grade FastAPI applications sing nangani heavy utawa deferred work kanthi reliable — lan ngerti kapan lan carane nggunakne real task queue iku penting senior-level knowledge.

Core judgment iku ngenali **limits saka `BackgroundTasks`** (ora ana persistence, retries, utawa scheduling — alus mung kanggo quick, non-critical work) lan nggayuh **Celery utawa ARQ** nalika work kudu durable, retryable, scheduled, heavy, utawa distributed (processing files/videos, sending bulk emails, data syncing, generating reports).

Queues iki nawakne critical production capabilities: **persistence** (jobs uwal crash via broker, dadi work ora ilang), **automatic retries** (resilience ngadhepi transient failures), **scheduling** (periodic jobs), lan **independent scaling** saka workers saka web servers.

Ngerti carane define lan enqueue tasks (Celery `.delay()`, ARQ async-native API), architecture (broker + workers), lan utamane **decision nalika nggunakne real queue versus BackgroundTasks**, iku valuable kanggo architect reliable applications sing offload heavy work tanpa ilang — requirement umum, penting sing mbedakne robust production systems saka fragile ones.