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Community / AGENT SKILL
python-performance-optimization
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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.
Understand the trade-offs.
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# 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.