domains / families / software-engineering / python-performance-optimization

python-performance-optimization

combined

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.

When to use

• 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

When not to use

• The task is unrelated to python performance optimization
• You need a different domain or tool outside this scope
• 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.

Skill page

Conflict

The first two copies are nearly identical stubs that point to a resources/implementation-playbook.md file, while the third copy (LeoYeAI/openclaw-master-skills) contains the actual detailed procedure, including specific profiling tools (cProfile, line_profiler, memory_profiler, py-spy) and optimization patterns. Because the first two copies lack the substantive steps found in the third, and the third lacks the specific 'Limitations' and 'Do not use' sections found in the second, no single copy is a complete superset of the others. Combining them yields a skill that has both the safety/scope constraints and the detailed technical instructions.