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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

Note
Initialize Once. Call init() once at startup, then stage changes with data.update() and apply them with dcupl.update(). Re-initialization is expensive.
Note
Use Specific Types. Define properties with specific types like int, float, boolean instead of storing everything as string.
Note
Reuse Lists. Create lists once and reuse them with query.clear(). Creating new lists has overhead.
Note
Limit Reference Depth. Keep reference chains to 2-3 levels. Use derived properties for frequently-accessed deep data.