Python Performance Optimization
This walks you through the essential Python profiling toolkit, from cProfile for CPU bottlenecks to memory_profiler for tracking allocations and py-spy for production debugging. You'll learn to identify slow functions, optimize list comprehensions versus loops, fix string concatenation performance, and choose the right data structures. The patterns cover real optimization wins like switching from O(n) list searches to O(1) dictionary lookups, using generators to reduce memory usage, and leveraging local variables over globals. Solid for debugging sluggish applications or optimizing data processing pipelines before they hit production.
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- skills.sh installs
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- last updated
- Aug 21, 2026
Install
$ npx -y skills add wshobson/agents --skill python-performance-optimization --agent claude-codeInstalls into .claude/skills of the current project.
Files
Python Performance Optimization
Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.
When to Use This Skill
- 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
Core Concepts
1. Profiling Types
- CPU Profiling: Identify time-consuming functions
- Memory Profiling: Track memory allocation and leaks
- Line Profiling: Profile at line-by-line granularity
- Call Graph: Visualize function call relationships
2. Performance Metrics
- Execution Time: How long operations take
- Memory Usage: Peak and average memory consumption
- CPU Utilization: Processor usage patterns
- I/O Wait: Time spent on I/O operations
3. Optimization Strategies
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- Repository
- github.com/wshobson/agents
- Categories
- Debugging, Python
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