Which profiling tools does this skill support?

It supports a wide range of industry-standard tools including cProfile for CPU usage, line_profiler for line-by-line analysis, memory_profiler for tracking allocations, and py-spy for production environments.

Does it provide advice on algorithmic improvements?

Absolutely. It compares various implementation patterns like traditional loops vs. list comprehensions and dictionary lookups vs. list searches to provide the most efficient algorithmic approach.

Can this skill help detect Python memory leaks?

Yes, it provides specific patterns for memory profiling and optimization strategies, such as using generator expressions and the __slots__ attribute to identify and reduce memory bloat.

Is this suitable for optimizing data-heavy applications?

Yes, it includes advanced patterns for numerical operations using NumPy vectorization, which can provide massive speedups over pure Python for data-intensive tasks.

Python Performance Optimizer

Name: Python Performance Optimizer
Author: duanbiao2000

byduanbiao2000

0•

分析与监控

Profiles and optimizes Python applications to resolve performance bottlenecks and reduce resource consumption.

This skill provides comprehensive guidance for diagnosing and fixing performance issues in Python codebases. It enables Claude to implement advanced profiling techniques using tools like cProfile and memory_profiler, identify latency in CPU-bound or I/O-bound operations, and apply high-performance coding patterns such as vectorization with NumPy, efficient memory management with __slots__, and intelligent caching. Whether debugging slow production systems or optimizing data pipelines, this skill ensures Python applications run at peak efficiency by replacing inefficient loops with optimized alternatives and identifying memory leaks.

主要功能

01Memory footprint reduction using __slots__ and efficient data structures

02Production-safe profiling with py-spy for real-time process monitoring

03CPU and memory profiling using cProfile, line_profiler, and memory_profiler

04Advanced optimization techniques including NumPy vectorization and LRU caching

05Implementation of high-performance patterns like list comprehensions and generators

060 GitHub stars

使用场景

01Identifying and fixing slow functions in large-scale Python web applications

02Optimizing data processing pipelines for faster execution and lower memory overhead

03Reducing latency in production systems through non-invasive profiling and algorithmic improvements

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add duanbiao2000/obsidiandoc26 python-performance-optimization

For use in Claude.ai and ChatGPT

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