result-backend-patterns

# Result Backend Patterns

**Purpose:** Configure and optimize Celery result backends for reliable task result storage and retrieval.

**Activation Triggers:**
- Setting up result backend for first time
- Migrating from one backend to another
- Result retrieval failures or timeouts
- Serialization errors with complex objects
- Performance issues with result storage
- Expired result cleanup problems
- Custom serialization requirements

**Key Resources:**
- `templates/redis-backend.py` - Redis result backend configuration
- `templates/db-backend.py` - Database (SQLAlchemy) backend setup
- `templates/rpc-backend.py` - RPC (AMQP) backend configuration
- `templates/result-expiration.py` - Expiration and cleanup policies
- `templates/custom-serializers.py` - Custom serialization patterns
- `scripts/test-backend.sh` - Backend connection and functionality testing
- `scripts/migrate-backend.sh` - Safe backend migration with data preservation
- `examples/` - Complete setup guides for each backend type

## Backend Selection Guide

### Redis Backend (Recommended for Most Cases)
**Best for:**
- High-performance applications
- Frequent result access
- Short to medium result retention (minutes to days)
- Real-time status updates

**Characteristics:**
- Fast in-memory storage
- Automatic expiration support
- Connection pooling built-in
- TTL-based cleanup

**Use template:** `templates/redis-backend.py`

### Database Backend (PostgreSQL/MySQL)
**Best for:**
- Long-term result storage (weeks to months)
- Applications with existing database infrastructure
- Complex result queries and reporting
- Audit trail requirements

**Characteristics:**
- Persistent disk storage
- SQL query capabilities
- Automatic table creation
- Transaction support

**Use template:** `templates/db-backend.py`

### RPC Backend (Message Broker)
**Best for:**
- Transient results consumed immediately
- Microservice architectures
- Results used only by initiating client
- Minimal infrastructure requirements

**Char