Best Practices
Patterns and recommendations for building production-ready dcupl applications. These guides cover data modeling, performance optimization, and error handling strategies.
Data Modeling
Structure your data models effectively with proper types, references, and indexing strategies.
Performance
Optimize queries, updates, and memory usage for fast, efficient applications.
Error Handling
Handle errors gracefully with retry logic, fallbacks, and recovery strategies.
Quick Tips
Initialize Once
Call init() once at startup, then use data.update() for changes. Re-initialization is expensive.
Use Specific Types
Define properties with specific types like int, float, boolean instead of storing everything as string.
Reuse Lists
Create lists once and reuse them with query.clear(). Creating new lists has overhead.
Limit Reference Depth
Keep reference chains to 2-3 levels. Use derived properties for frequently-accessed deep data.
Related Documentation
- Performance Guide - Advanced performance optimization
- Caching - Caching strategies
- Quality Validation - Data validation and quality checks
- Debugging - Debug common issues