Celery is an asynchronous task queue that enables you to execute long-running or background tasks in a distributed, scalable, and reliable way. It is particularly useful for CPU-intensive tasks, I/O-bound jobs, or distributed workloads.
🔹 Why Use Celery?
Asynchronous Execution: Run tasks in the background while your main application continues processing.
Distributed Processing: Tasks can be executed on multiple worker machines.
Scalability: Add more workers as load increases.
Reliability: Supports automatic task retries, error handling, and result persistence.
Periodic Tasks: Schedule tasks like a cron job using celery beat.
Integration with Django, Flask, FastAPI: Works seamlessly with web frameworks.
Multiple Broker Support: Redis, RabbitMQ, Amazon SQS, etc.
🔹 Celery Architecture
Celery consists of four main components:
Broker (Message Queue)
The "middleman" that queues tasks before they reach the workers.
Examples: Redis, RabbitMQ, Amazon SQS, Kafka.
Workers
Execute the tasks asynchronously.
Multiple workers can run in parallel across machines.
Task Queue (Backend)
Stores the task state & results.
Examples: Redis, Database (PostgreSQL, MySQL).
Client (Producer)
The application (e.g., Flask/Django) that sends tasks to the broker.
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