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.

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 celery.py — App Entrypoint Django Settings Running Workers Task Design Patterns Basic Task Retryable Task Idempotent Task Pattern Design tasks so they can safely run multiple times with the same inputs: Task with Soft Time Limit Calling Tasks Beat Scheduling (Periodic Tasks) Code Defined Schedule Database Defined Schedule (via django celery beat) Canvas: Chaining and Grouping Tasks Error Handling and Dead Letter Queue Testing Celery Tasks Unit Testing (No Broker) Integration Testing with CELERY TASK ALWAYS EAGER Testing Retries Monitoring Anti Patterns Production Checklist Check Setting Worker restarts on crash supervisord or systemd unit CELERY TASK ACKS LATE = True Re queue tasks on worker crash CELERY WORKER PREFETCH MULTIPLIER = 1 Fair distribution of long tasks Separate queues per priority Q default,high priority,low priority CELERY TASK SOFT TIME LIMIT set Graceful timeout before hard kill Sentry integration Capture all task failure signals Flower or other monitor Visibility into queue depths Beat runs on single node only Prevents duplicate scheduled task execution Related Skills django patterns — ORM, service layer, and project structure django tdd — Testing Django models, views, and services python testing — pytest configuration and fixtures

django-celery