django-celery

What this skill does

When applied, it prepends a system prompt before your request is sent — no extra calls and no change to how you are billed beyond the added tokens.

---
name: django-celery
description: Django + Celery async task patterns — configuration, task design, beat scheduling, retries, canvas workflows, monitoring, and testing. Use when adding background jobs, scheduled tasks, or async processing to a Django app.
origin: ECC
---

# Django + Celery Async Task Patterns

Production-grade patterns for background task processing in Django using Celery with Redis or RabbitMQ.

## When to Activate

- Adding background jobs or async processing to a Django app
- Implementing periodic/scheduled tasks
- Offloading slow operations (email, PDF generation, API calls) from request cycle
- Setting up Celery Beat for cron-like scheduling
- Debugging task failures, retries, or queue backlogs
- Writing tests for Celery tasks

## Project Setup

### Installation

```bash
pip install 'celery[redis]' django-celery-results django-celery-beat
```

### `celery.py` — App Entrypoint

```python
# config/celery.py
import os
from celery import Celery

os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'config.settings.development')

app = Celery('myproject')
app.config_from_object('django.conf:settings', namespace='CELERY')
app.autodiscover_tasks()  # Discovers tasks.py in each INSTALLED_APP

@app.task(bind=True, ignore_result=True)
def debug_task(self):
    print(f'Request: {self.request!r}')
```

```python
# config/__init__.py
from .celery import app as celery_app

__all__ = ('celery_app',)
```

### Django Settings

```python
# config/settings/base.py

# Broker (Redis recommended for production)
CELERY_BROKER_URL = env('CELERY_BROKER_URL', default='redis://localhost:6379/0')
CELERY_RESULT_BACKEND = env('CELERY_RESULT_BACKEND', default='django-db')

# Serialization
CELERY_ACCEPT_CONTENT = ['json']
CELERY_TASK_SERIALIZER = 'json'
CELERY_RESULT_SERIALIZER = 'json'

# Task behavior
CELERY_TASK_TRACK_STARTED = True
CELERY_TASK_TIME_LIMIT = 30 * 60        # Hard limit: 30 min
CELERY_TASK_SOFT_TIME_LIMIT = 25 * 60   # Soft limit: sends SoftTimeLimitExceeded
C

Use this skill

{
  "model": "gpt-4o-mini",
  "skill": "imp-100eb9b8-fde0-45ef-be5e-cfa849c47d16",
  "messages": [{ "role": "user", "content": "…" }]
}

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