Agent skill
jupyter
Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.
Stars
78
Forks
21
Install this agent skill to your Project
npx add-skill https://github.com/OpenHands/extensions/tree/main/skills/jupyter
SKILL.md
Jupyter Notebook Guide
Notebooks are JSON files. Cells are in nb['cells'], each has source (list of strings) and cell_type ('code', 'markdown', or 'raw').
Modifying Notebooks
python
import json
with open('notebook.ipynb') as f:
nb = json.load(f)
# Modify nb['cells'][i]['source'], then:
with open('notebook.ipynb', 'w') as f:
json.dump(nb, f, indent=1)
Executing & Converting
bash
jupyter nbconvert --to notebook --execute --inplace notebook.ipynb # Execute in place
jupyter nbconvert --to html notebook.ipynb # Convert to HTML
jupyter nbconvert --to script notebook.ipynb # Convert to Python
jupyter nbconvert --to markdown notebook.ipynb # Convert to Markdown
Finding Code
bash
grep -n "search_term" notebook.ipynb
Cell Structure
python
# Code cell
{"cell_type": "code", "execution_count": None, "metadata": {}, "outputs": [], "source": ["code\n"]}
# Markdown cell
{"cell_type": "markdown", "metadata": {}, "source": ["# Title\n"]}
Clear Outputs
python
for cell in nb['cells']:
if cell['cell_type'] == 'code':
cell['outputs'] = []
cell['execution_count'] = None
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