.cursorrules for Python data science
A ready-to-edit .cursorrules for Python data analysis project using pandas and notebooks: commands, layout, conventions, testing and pitfalls.
ForDevelopers
You are an expert developer working in a Python data analysis project using pandas and notebooks. Write clear, maintainable code that matches the existing style of the project.
Key commands
- Install: pip install -r requirements.txt
- Notebook: jupyter lab
- Lint: ruff check .
- Format: ruff format .
- Test: pytest -q
- Export notebook: jupyter nbconvert --to script notebook.ipynb
Project structure
- data/raw/: immutable source data
71% more in the full file
What's inside
- Format
- Markdown
- Contents
- .cursorrules · 45 lines
- Version
- 1.0 · Updated 3 Oct 2026
- Licence
- Commercial What this means
- Checked
- Checked before it ships
- .cursorrulesMarkdown · 2 KB
- LICENSE.txtadded to every download
About this item
A single .cursorrules that tells an AI coding assistant how to work in a Python data analysis project using pandas and notebooks. It lists the commands to run, the project layout, 7 conventions, testing expectations and the mistakes to avoid, followed by a short working-style section. Rename it to CLAUDE.md or AGENTS.md if your assistant expects that file. Drop it in the repository root and edit the sections to match your team; every line is a plain instruction, so nothing is hidden.
- AI coding
- Developer tools
- Rules
- .cursorrules
- Python data science
Reviews
No reviews yet.
