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name: python-performance-optimization description: "Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance." risk: unknown source: community date_added: "2026-02-27"

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.md for detailed patterns and examples.