python-performance-optimization

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

38 stars

Best use case

python-performance-optimization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Teams using python-performance-optimization should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/python-performance-optimization/SKILL.md --create-dirs "https://raw.githubusercontent.com/lingxling/awesome-skills-cn/main/antigravity-awesome-skills/plugins/antigravity-awesome-skills-claude/skills/python-performance-optimization/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/python-performance-optimization/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How python-performance-optimization Compares

Feature / Agentpython-performance-optimizationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Related Skills

zarr-python

38
from lingxling/awesome-skills-cn

Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.

web-performance-optimization

38
from lingxling/awesome-skills-cn

Optimize website and web application performance including loading speed, Core Web Vitals, bundle size, caching strategies, and runtime performance

temporal-python-testing

38
from lingxling/awesome-skills-cn

Comprehensive testing approaches for Temporal workflows using pytest, progressive disclosure resources for specific testing scenarios.

temporal-python-pro

38
from lingxling/awesome-skills-cn

Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment.

swiftui-performance-audit

38
from lingxling/awesome-skills-cn

Audit SwiftUI performance issues from code review and profiling evidence.

sql-optimization-patterns

38
from lingxling/awesome-skills-cn

Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.

spark-optimization

38
from lingxling/awesome-skills-cn

Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.

react-component-performance

38
from lingxling/awesome-skills-cn

Diagnose slow React components and suggest targeted performance fixes.

python-testing-patterns

38
from lingxling/awesome-skills-cn

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

python-pro

38
from lingxling/awesome-skills-cn

Master Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI.

python-pptx-generator

38
from lingxling/awesome-skills-cn

Generate complete Python scripts that build polished PowerPoint decks with python-pptx and real slide content.

python-patterns

38
from lingxling/awesome-skills-cn

Python development principles and decision-making. Framework selection, async patterns, type hints, project structure. Teaches thinking, not copying.