Celery Distributed Task Queue

Celery is a simple, flexible, and reliable distributed task queue system for Python, designed to process vast amounts of messages asynchronously. Created by Ask Solem in 2009, Celery is used by Instagram, Mozilla, Reddit, and OpenStack for background job processing. Key features: asynchronous task execution where Python functions are defined as tasks using the task decorator and executed on worker processes with results collected via AsyncResult. Broker support for Redis, RabbitMQ, Amazon SQS, and Apache Kafka with broker-specific optimizations. Pluggable result backend including Redis, RabbitMQ RPC, SQLAlchemy, MongoDB, Django ORM, Elasticsearch, and Amazon S3. Canvas system for composing complex workflows including chains for sequential execution, groups for parallel, chords for fan-out-fan-in with callback, and chunks for batch processing. celery beat scheduler for periodic task execution via crontab or interval schedules with timezone awareness. Flexible task routing to specific queues based on task name, arguments, or custom logic. Worker processes with concurrency via prefork pool, eventlet, or gevent with autoscaling and remote control. Flower real-time web monitor showing task progress and worker status plus Prometheus integration. Automatic task retry with configurable retry delays, max retries, and exponential backoff. Soft and hard time limits per task for preventing runaway processes. Task states (PENDING, STARTED, SUCCESS, FAILURE, RETRY, REVOKED) with custom state tracking.