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fn_registry/python/functions/notebook/jupyter_write.md
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egutierrez 988e901066 docs: params/output semántico en 506 funciones para composabilidad
Añade campos params y output al frontmatter YAML de las 506 funciones del registry.
Cada parámetro tiene descripción semántica (qué representa, unidades, rango típico)
y cada función describe qué produce su output. Permite a agentes razonar sobre
cadenas de composición (ej: prices → log_return → sharpe_ratio) sin leer código.
2026-04-05 18:45:16 +02:00

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---
name: jupyter_write
kind: function
lang: py
domain: notebook
version: "1.1.0"
purity: impure
signature: "def jupyter_append_code(notebook_path: str, source: str, server_url: str = 'http://localhost:8888', token: str = '') -> dict"
description: "Operaciones de escritura sobre celdas de un notebook Jupyter via colaboracion en tiempo real (WebSocket) y API REST. Expone siete operaciones: append_code, append_markdown, insert, edit, delete, create y batch. NO ejecuta celdas — solo modifica la estructura del notebook. create usa PUT /api/contents para crear notebooks nuevos sin necesidad de websocket. batch abre una unica conexion WebSocket para insertar N celdas en una sola operacion."
tags: [jupyter, notebook, websocket, cell, write, append, insert, edit, delete, create, batch, nbmodel, rest]
uses_functions: []
uses_types: []
returns: []
returns_optional: false
error_type: "error_go_core"
imports: [jupyter_nbmodel_client]
output: "Múltiples funciones para escribir en notebooks: append_code/markdown, insert, edit, delete, create, batch (retornan dicts con action y posición)"
tested: false
tests: []
test_file_path: ""
file_path: "python/functions/notebook/jupyter_write.py"
---
## Funciones expuestas
| Funcion | Descripcion |
|---------|-------------|
| `jupyter_append_code(notebook_path, source, server_url, token)` | Anade celda de codigo al final |
| `jupyter_append_markdown(notebook_path, source, server_url, token)` | Anade celda markdown al final |
| `jupyter_insert_cell(notebook_path, cell_index, source, cell_type, server_url, token)` | Inserta celda en posicion especifica |
| `jupyter_edit_cell(notebook_path, cell_index, source, server_url, token)` | Sobrescribe contenido de celda existente |
| `jupyter_delete_cell(notebook_path, cell_index, server_url, token)` | Elimina una celda |
| `jupyter_create_notebook(notebook_path, kernel_name, server_url, token, force)` | Crea un notebook vacio nbformat 4 via API REST |
| `jupyter_batch_write(notebook_path, cells, server_url, token)` | Anade N celdas en una sola conexion WebSocket |
## Ejemplo
```python
from notebook.jupyter_write import (
jupyter_append_code,
jupyter_append_markdown,
jupyter_insert_cell,
jupyter_edit_cell,
jupyter_delete_cell,
jupyter_create_notebook,
jupyter_batch_write,
)
# Crear notebook nuevo
result = jupyter_create_notebook(
notebook_path="notebooks/01_analisis.ipynb",
kernel_name="python3",
server_url="http://localhost:8888",
)
# {"action": "create", "notebook": "notebooks/01_analisis.ipynb", "created": true}
# Si ya existe, lanza FileExistsError. Usar force=True para sobreescribir:
result = jupyter_create_notebook("notebooks/01.ipynb", force=True)
# Anadir multiples celdas de golpe (una sola conexion WebSocket)
cells = [
{"type": "markdown", "source": "## Analisis inicial"},
{"type": "code", "source": "import pandas as pd"},
{"type": "code", "source": "df = pd.read_csv('data.csv')\ndf.head()"},
]
result = jupyter_batch_write(
notebook_path="notebooks/01_analisis.ipynb",
cells=cells,
server_url="http://localhost:8888",
)
# {"action": "batch", "cells_added": 3, "notebook": "notebooks/01_analisis.ipynb"}
# Anadir celda de codigo al final
result = jupyter_append_code(
notebook_path="notebooks/01_analisis.ipynb",
source="import pandas as pd\ndf = pd.read_csv('data.csv')",
)
# {"action": "append_code", "cell_index": 5, "notebook": "notebooks/01_analisis.ipynb"}
# Anadir celda markdown
result = jupyter_append_markdown(
notebook_path="notebooks/01_analisis.ipynb",
source="## Resultados\n\nAnalisis de los datos obtenidos.",
)
# {"action": "append_markdown", "cell_index": 6, "notebook": "..."}
# Insertar celda en posicion 2
result = jupyter_insert_cell(
notebook_path="notebooks/01_analisis.ipynb",
cell_index=2,
source="# celda insertada",
cell_type="code",
)
# {"action": "insert", "cell_index": 2, "cell_type": "code", "notebook": "..."}
# Editar celda existente (indice 0)
result = jupyter_edit_cell(
notebook_path="notebooks/01_analisis.ipynb",
cell_index=0,
source="# Titulo actualizado",
)
# {"action": "edit", "cell_index": 0, "notebook": "..."}
# Eliminar celda
result = jupyter_delete_cell(
notebook_path="notebooks/01_analisis.ipynb",
cell_index=3,
)
# {"action": "delete", "cell_index": 3, "notebook": "..."}
```
## CLI
```bash
# Crear notebook nuevo
python -m notebook.jupyter_write create notebooks/01.ipynb
python -m notebook.jupyter_write create notebooks/01.ipynb --kernel python3
python -m notebook.jupyter_write create notebooks/01.ipynb --force
# Anadir multiples celdas desde archivo JSON
python -m notebook.jupyter_write batch notebooks/01.ipynb --from cells.json
# O via stdin
cat cells.json | python -m notebook.jupyter_write batch notebooks/01.ipynb --from -
echo '[{"type":"code","source":"import pandas"}]' | python -m notebook.jupyter_write batch notebooks/01.ipynb
# Formato JSON de entrada para batch:
# [{"type": "markdown", "source": "# Titulo"}, {"type": "code", "source": "import pandas"}]
# Anadir celda de codigo
python -m notebook.jupyter_write append-code notebooks/01.ipynb "print('hola')" --server http://localhost:8888 --token mi-token
# Anadir celda markdown
python -m notebook.jupyter_write append-markdown notebooks/01.ipynb "## Titulo"
# Insertar en posicion 2
python -m notebook.jupyter_write insert notebooks/01.ipynb 2 "x = 42" --type code
# Editar celda 0
python -m notebook.jupyter_write edit notebooks/01.ipynb 0 "# Nuevo titulo"
# Eliminar celda 3
python -m notebook.jupyter_write delete notebooks/01.ipynb 3
```
## Notas
- Todas las funciones son sincronas publicamente. Internamente usan `asyncio.run()` sobre corutinas async que se comunican via WebSocket con `NbModelClient`.
- `create` es la excepcion: usa urllib (PUT /api/contents) sin WebSocket. Crea un nbformat 4 con celdas vacias. Lanza `FileExistsError` si el notebook ya existe y `force=False`.
- `batch` es mucho mas eficiente que N llamadas a `append-code`/`append-markdown`: abre una sola conexion WebSocket y hace un unico `asyncio.sleep(2)` de sincronizacion al final.
- El `notebook_path` es relativo al servidor Jupyter (no al filesystem local).
- Si el servidor no esta corriendo o el token es incorrecto, lanza excepcion de conexion de `jupyter_nbmodel_client`.
- NO ejecuta celdas — solo modifica la estructura. Para ejecutar, usar `jupyter_exec`.
- `server_url` y `token` tienen defaults convenientes para desarrollo local (`http://localhost:8888`, token vacio).
- El campo `cell_index` en el resultado refleja la posicion final de la celda en el notebook.
- Patron tipico: `create` para crear el notebook, luego `batch` para poblar las celdas iniciales.