Will it suggest faster code alternatives for my scripts?

Absolutely. The skill contains benchmarked patterns for list comprehensions, generator expressions, and NumPy vectorization to replace slower traditional loops.

How do I profile Python code with this skill?

This skill provides integrated patterns for cProfile and line_profiler to help you identify specific functions or lines of code causing execution delays.

Is this skill useful for data science projects?

Yes, it features specific optimizations for numerical operations and data processing efficiency that are essential for large-scale data science and ML tasks.

Can this skill help with memory leaks?

Yes, it includes specialized memory_profiler patterns to track allocation and implementation strategies like using __slots__ to significantly reduce RAM consumption.

Does it support profiling in production environments?

Yes, it provides guidance for using py-spy, which allows you to profile running Python processes and generate flamegraphs without restarting the application.

Python Performance Optimization

Name: Python Performance Optimization
Author: GaitanS

byGaitanS

분석 및 모니터링

Profiles and optimizes Python codebases to eliminate bottlenecks, reduce memory usage, and improve execution speed.

소개

This skill provides a comprehensive toolkit for developers seeking to maximize the efficiency of their Python applications. It offers expert guidance on CPU and memory profiling using industry-standard tools like cProfile, line_profiler, and py-spy, while delivering actionable patterns for algorithmic and implementation-level optimizations. Whether you are troubleshooting slow API responses, managing high-memory data pipelines, or refining production code, this skill implements best practices for caching, vectorization, and resource-efficient coding to ensure your applications run at peak performance.

주요 기능

Production-safe profiling and flamegraph generation using py-spy
Memory footprint reduction via generator expressions and __slots__
0 GitHub stars
High-performance coding patterns for loops, string manipulation, and lookups
Advanced optimization using NumPy vectorization and functools caching
CPU and memory profiling with cProfile, line_profiler, and memory_profiler

사용 사례

Identifying and fixing memory leaks in long-running background processes
Accelerating data processing pipelines and heavy numerical computations
Reducing latency and response times in high-traffic Python web services

소개

주요 기능

Production-safe profiling and flamegraph generation using py-spy
Memory footprint reduction via generator expressions and __slots__
0 GitHub stars
High-performance coding patterns for loops, string manipulation, and lookups
Advanced optimization using NumPy vectorization and functools caching
CPU and memory profiling with cProfile, line_profiler, and memory_profiler

사용 사례

Identifying and fixing memory leaks in long-running background processes
Accelerating data processing pipelines and heavy numerical computations
Reducing latency and response times in high-traffic Python web services