Can I use it to format my code within cells?

Absolutely. It supports integration with formatting tools like Black and linters like nbqa to ensure your notebook follows PEP 8 standards.

Can this skill convert Jupyter notebooks to Python scripts?

Yes, it includes instructions and tools for extracting notebook logic into standalone .py files using nbconvert and jupytext.

How does it help with notebook organization?

It automatically identifies logical sections, adds markdown headers, generates a Table of Contents, and removes redundant empty cells for better flow.

Does it handle dependency management?

Yes, it can analyze your notebook's imports and generate a standardized requirements.txt file for your environment.

Jupyter Notebook Assistant

Name: Jupyter Notebook Assistant
Author: Dexploarer

byDexploarer

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Data Science & ML

Refactors, cleans, and optimizes Jupyter notebooks to improve code readability, maintainability, and reproducibility.

This skill transforms cluttered Jupyter notebooks into production-ready assets by automating common cleanup tasks such as removing empty cells, clearing outputs, and adding markdown structure. It goes beyond simple formatting by extracting reusable functions into utility files, generating requirements.txt from imports, and implementing best practices like random seed setting and memory management. Whether you need to prepare a notebook for team review, convert it into a clean Python script, or simply organize your exploratory data analysis, this assistant ensures your data science workflow remains efficient and well-documented.

Key Features

01Automated notebook cleanup including removing empty cells and clearing execution outputs.

02Dependency management through automated mapping of imports to requirements.txt packages.

03Integration with industry-standard tools like Black for formatting and Jupytext for version control.

04Structural enhancements like generating Tables of Contents and markdown section headers.

05Code refactoring to extract repetitive logic into reusable Python functions and utility modules.

062 GitHub stars

Use Cases

01Refactoring notebook logic into modular scripts to facilitate the transition from research to production.

02Ensuring reproducibility in data experiments by standardizing structure and documenting hyperparameters.

03Cleaning up messy exploratory notebooks before sharing with team members or stakeholders.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add dexploarer/claudius-skills jupyter-assistant

For use in Claude.ai and ChatGPT

Download Skill