python-performance-optimization
Profilez et optimisez le code Python en utilisant cProfile, les profileurs mémoire et les meilleures pratiques de performance. Utilisez lors du débogage du code Python lent, de l'optimisation des goulots d'étranglement ou de l'amélioration des performances des applications.
Le contenu de ce skill est dans sa langue d’origine (souvent l’anglais).
Python Performance Optimization
Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.
Use this skill when
- Identifying performance bottlenecks in Python applications
- Reducing application latency and response times
- Optimizing CPU-intensive operations
- Reducing memory consumption and memory leaks
- Improving database query performance
- Optimizing I/O operations
- Speeding up data processing pipelines
- Implementing high-performance algorithms
- Profiling production applications
Do not use this skill when
- The task is unrelated to python performance optimization
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.