37 lines
1.3 KiB
Markdown
37 lines
1.3 KiB
Markdown
---
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name: python-performance-optimization
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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.
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---
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# Python Performance Optimization
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Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.
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## Use this skill when
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- Identifying performance bottlenecks in Python applications
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- Reducing application latency and response times
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- Optimizing CPU-intensive operations
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- Reducing memory consumption and memory leaks
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- Improving database query performance
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- Optimizing I/O operations
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- Speeding up data processing pipelines
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- Implementing high-performance algorithms
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- Profiling production applications
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## Do not use this skill when
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- The task is unrelated to python performance optimization
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- You need a different domain or tool outside this scope
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## Instructions
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- Clarify goals, constraints, and required inputs.
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- Apply relevant best practices and validate outcomes.
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- Provide actionable steps and verification.
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- If detailed examples are required, open `resources/implementation-playbook.md`.
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## Resources
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- `resources/implementation-playbook.md` for detailed patterns and examples.
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