celery.py

"""
Why use Celery instead of Redis directly:

1. Abstraction & Task Management:
   - Celery provides a high-level task queue system
   - Handles task scheduling, retries, and monitoring
   - Manages worker processes automatically

2. Flexibility:
   - Can use different message brokers (Redis, RabbitMQ, etc.)
   - Supports multiple result backends
   - Easy to switch between brokers without code changes

3. Features:
   - Built-in task scheduling (like cron)
   - Task prioritization
   - Error handling and retries
   - Task chaining and workflows
   - Task monitoring and inspection
   - Rate limiting

4. Integration:
   - Seamless integration with web frameworks
   - Built-in Django/Flask support
   - Distributed task execution

5. Production Ready:
   - Battle-tested in production
   - Scalable architecture
   - Monitoring tools (Flower)
   - Logging and debugging features

While Redis is an excellent message broker and can be used directly,
Celery provides a robust task queue framework built on top of it,
saving development time and providing enterprise-ready features.
"""


"""
Why use RabbitMQ over Redis as a message broker:

1. Message Persistence & Durability:
   - RabbitMQ persists messages to disk by default
   - Better guarantees for message delivery
   - Survives broker restarts without data loss
   - Redis is primarily in-memory with optional persistence

2. Advanced Message Routing:
   - Complex routing patterns with exchanges and queues
   - Topic exchanges for flexible message routing
   - Fan-out capabilities for broadcasting
   - Better message filtering options

3. Back-pressure Handling:
   - Built-in flow control mechanisms
   - Better handling of high message volumes
   - Prevents memory overflow issues
   - Redis requires manual implementation

4. Protocol Support:
   - Native AMQP protocol support
   - Industry standard messaging protocol
   - Better interoperability with other systems
   - Multiple protocol plugins available

5. Queue Management:
   - Sophisticated queue management
   - Dead letter exchanges
   - Message TTL and queue limits
   - Priority queues

6. Clustering:
   - Native clustering support
   - High availability configurations
   - Better for distributed systems
   - More robust failover mechanisms

While Redis is excellent for simpler use cases and as a cache,
RabbitMQ is purpose-built for message queuing and provides
more robust features for complex messaging requirements.
"""