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.
Quellinformationen
- Repository
- OpenHands/extensions
- Letzte Quellaktivität
- 1. Juli 2026 um 22:49
- Erkannte Sprache von SKILL.md
- Englisch
- Sterne
- 167
- Forks
- 114
Installationsoptionen
Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Quelldateien prüfen
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
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SKILL.md
Quellanweisungen · Schreibgeschützte Vorschau- name
- jupyter
- description
- 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.
- triggers
- ["ipynb","jupyter"]
# 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
```
PowerShell equivalent:
```powershell
Select-String -Path notebook.ipynb -Pattern "search_term"
```
## 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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