project-guidelines

What problem does it solve?

This Skill eliminates the struggle of inconsistent Python project setups, complex dependency management, and manual quality checks. It provides a clear, automated path to a well-structured and maintainable data analysis project, saving you time and reducing setup headaches.

Core Features & Use Cases

• Standardized Python Setup: Ensures consistent project structure and best practices for Python 3.12+ with uv and Jupyter.
• Jupyter Integration: Guides on effectively using Jupyter notebooks for data exploration, separating exploratory code from reusable modules.
• Automated Quality Checks: Integrates pytest, mypy, and ruff for automated testing, type checking, and linting, reducing manual review effort.
• Use Case: When starting a new data analysis project, this Skill provides instant, tailored guidance on setting up your Python environment, structuring your code, and ensuring quality, allowing you to immediately focus on the analysis itself.

Quick Start

Help me set up a new Python data analysis project using uv and Jupyter. Provide the initial directory structure and key configuration files.