1 python rules available
Browse optimized GitHub Copilot rules specifically designed for Python development. These rules help GitHub Copilot's AI understand Python best practices and patterns.
Python's flexibility means AI-generated code can vary widely in style. Rules that specify PEP 8 compliance, type hints (Python 3.9+), and your preferred async patterns help maintain consistency. Whether you're building Django applications, FastAPI services, or data science pipelines, proper rules ensure idiomatic Python code.
When configuring GitHub Copilot for Python development, consider these recommendations:
Python rules commonly cover type hints with modern syntax, proper project structure with __init__.py files, and framework-specific patterns. Data science rules often include NumPy/Pandas conventions, while web development rules focus on Django or FastAPI patterns.
Most general Python rules work for any framework, but for best results, look for framework-specific rules. Django rules include model patterns and ORM usage, while FastAPI rules focus on Pydantic models and dependency injection.
Modern Python rules typically expect type hints using the latest syntax (list[str] instead of List[str]). They guide the AI to use proper return types, Optional types, and Union types for comprehensive type coverage.
Yes, look for rules tagged with 'data-science', 'pandas', or 'jupyter'. These include patterns for notebook cell organization, DataFrame operations, and visualization with matplotlib or plotly.
Create your own GitHub Copilot rules for Python and share with the community.