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python-performance-optimization

python-performance-optimization

github.com/rmyndharisDevelopment1.9k42 installsUpdated 2w ago
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About python-performance-optimization

A skill for profiling and optimizing Python application performance, covering CPU, memory, database, and I/O bottlenecks. It provides optimization guidance and points to `resources/implementation-playbook.md` for detailed patterns and examples.

Key features

  1. 01Analyze Python performance bottlenecks
  2. 02Optimize CPU-intensive operations
  3. 03Reduce memory use and investigate leaks
  4. 04Improve database queries and I/O
  5. 05Accelerate data pipelines and algorithms

Use cases

  1. 01Finding causes of application latency
  2. 02Reducing memory use in production applications
  3. 03Optimizing database query performance
  4. 04Speeding up data processing pipelines

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/rmyndharis/antigravity-skills --skill python-performance-optimization

After installing, type/python-performance-optimizationin Claude Code to confirm it loaded.

Bundled filesresources/implementation-playbook.md

Details

From the project README

Python Performance Optimization

Comprehensive guide to profiling, analyzing, and optimizing Python code for better performance, including CPU profiling, memory optimization, and implementation best practices.

Use this skill when

  • 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

Do not use this skill when

  • The task is unrelated to python performance optimization
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/implementation-playbook.md.

Resources

  • resources/implementation-playbook.md for detailed patterns and examples.

Comments

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