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Dynamic Performance Monitoring Decorator for Function Optimization

decorators performance monitoring profiling
Prompt
Design a Python decorator that automatically tracks and logs performance metrics for any function, including execution time, memory usage, and call frequency. The decorator should generate a detailed JSON report and support optional logging to a file or external monitoring system. Implement advanced features like threshold alerts, statistical aggregation, and the ability to selectively monitor specific function categories.
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Python
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Feb 28, 2026

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Use Cases
  • Optimizing function calls in a software application.
  • Tracking performance metrics in real-time systems.
  • Improving efficiency in data processing tasks.
Tips for Best Results
  • Use decorators selectively to avoid overhead.
  • Log performance data for analysis and improvement.
  • Test performance before and after applying decorators.

Frequently Asked Questions

What is performance monitoring?
Performance monitoring involves tracking system performance to optimize functionality.
How does a decorator enhance performance monitoring?
A decorator can modify functions to include performance tracking seamlessly.
Is it suitable for all programming languages?
Most modern programming languages support decorators for performance monitoring.
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