Can I use this skill to find memory leaks?

Yes, it includes specific implementation patterns for memory_profiler to track object allocation and identify blocks of code causing excessive memory consumption.

Is it safe to profile code in a production environment?

The skill includes instructions for using py-spy, a sampling profiler that can attach to running Python processes with extremely low overhead, making it suitable for production debugging.

Does it provide actual code samples for optimization?

Yes, it features over 10 optimization patterns covering string concatenation, dictionary lookups, local variable access, and caching to replace inefficient code with high-performance alternatives.

How does this skill help identify slow Python code?

It provides standardized patterns for using cProfile and line_profiler to pinpoint exactly which functions or specific lines of code are consuming the most CPU time.

Python Performance Optimization

Name: Python Performance Optimization
Author: eroslifestyle

byeroslifestyle

0•

Developer Tools

Profiles and optimizes Python applications using industry-standard tools to identify bottlenecks, reduce memory usage, and improve execution speed.

This skill provides a comprehensive framework for diagnosing and resolving performance issues within Python codebases. It guides users through various profiling methodologies—including CPU, memory, and line-level analysis—using tools like cProfile and memory_profiler. Beyond diagnostics, it provides production-ready implementation patterns for common optimizations such as caching, vectorization with NumPy, and memory-efficient data structures, making it essential for developers building high-throughput or resource-constrained applications.

Key Features

01CPU and memory profiling using cProfile, line_profiler, and memory_profiler

02Production-grade sampling profiling with py-spy for running processes

03Algorithmic optimization patterns for loops, lookups, and string handling

040 GitHub stars

05Advanced memory management techniques using generators and __slots__

06Performance boosting via functools caching and NumPy vectorization

Use Cases

01Debugging memory leaks and high CPU utilization in long-running production applications

02Identifying and fixing performance bottlenecks in slow API endpoints or web services

03Optimizing data processing pipelines to handle larger datasets with lower memory overhead

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add eroslifestyle/claude-orchestrator-plugin python-performance-optimization

For use in Claude.ai and ChatGPT

Key Features

01CPU and memory profiling using cProfile, line_profiler, and memory_profiler

02Production-grade sampling profiling with py-spy for running processes

03Algorithmic optimization patterns for loops, lookups, and string handling

040 GitHub stars

05Advanced memory management techniques using generators and __slots__

06Performance boosting via functools caching and NumPy vectorization

Use Cases

01Debugging memory leaks and high CPU utilization in long-running production applications

02Identifying and fixing performance bottlenecks in slow API endpoints or web services

03Optimizing data processing pipelines to handle larger datasets with lower memory overhead

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add eroslifestyle/claude-orchestrator-plugin python-performance-optimization

For use in Claude.ai and ChatGPT