⚡ Performance Optimization

Content Outline

Comprehensive guide to optimizing PyMapGIS performance:

1. Performance Philosophy

• Performance-first design principles
• Benchmarking and measurement strategies
• Performance vs. functionality trade-offs
• Continuous performance monitoring
• Performance regression prevention

2. Profiling and Measurement

• Python Profiling: cProfile, line_profiler, py-spy
• Memory Profiling: memory_profiler, tracemalloc
• I/O Profiling: Monitoring disk and network operations
• Custom Metrics: PyMapGIS-specific performance metrics
• Benchmarking: Automated performance testing

3. Data Loading Optimization

• Lazy loading strategies
• Streaming data processing
• Parallel data loading
• Cache optimization
• Format-specific optimizations

4. Memory Optimization

• Memory usage profiling and analysis
• Memory-efficient data structures
• Garbage collection optimization
• Memory mapping for large files
• Memory leak detection and prevention

5. Spatial Operation Optimization

• Spatial indexing optimization (R-tree, Grid)
• Algorithm selection and tuning
• Parallel spatial processing
• Chunked processing for large datasets
• GPU acceleration opportunities

6. Caching Optimization

• Cache hit ratio optimization
• Cache size and eviction strategies
• Multi-level caching optimization
• Cache warming and preloading
• Distributed caching performance

7. I/O Performance

• Disk I/O optimization
• Network I/O optimization
• Asynchronous I/O implementation
• Batch processing strategies
• Connection pooling and reuse

8. Visualization Performance

• Large dataset visualization strategies
• Level-of-detail (LOD) implementation
• Progressive rendering techniques
• Memory management for interactive maps
• Export performance optimization

9. Parallel Processing

• Multi-threading strategies
• Multi-processing implementation
• Async/await patterns
• Dask integration for distributed computing
• GPU acceleration with CuPy/RAPIDS

10. Database and Storage Optimization

• Query optimization strategies
• Index usage and optimization
• Connection pooling
• Batch operations
• Storage format optimization

11. Network and API Optimization

• Request batching and optimization
• Connection reuse and pooling
• Compression and encoding
• CDN and edge caching
• Rate limiting and throttling

12. Performance Monitoring

• Real-time performance monitoring
• Performance metrics collection
• Alerting and notification systems
• Performance dashboard creation
• Automated performance testing

13. Optimization Tools and Utilities

• Custom profiling utilities
• Performance testing frameworks
• Optimization scripts and tools
• Automated optimization recommendations
• Performance regression detection

14. Best Practices

• Performance-oriented coding practices
• Architecture decisions for performance
• Performance testing in CI/CD
• Performance documentation
• Performance culture and mindset

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This guide will provide detailed performance optimization techniques, tools, and strategies specifically for PyMapGIS and geospatial applications.