fn_registry/python/functions/notebook/jupyter_write.md

name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, output, tested, tests, test_file_path, file_path

name	kind	lang	domain	version	purity	signature	description	tags	uses_functions	uses_types	returns	returns_optional	error_type	imports	output	tested	tests	test_file_path	file_path
jupyter_write	function	py	notebook	1.1.0	impure	def jupyter_append_code(notebook_path: str, source: str, server_url: str = 'http://localhost:8888', token: str = '') -> dict	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.	jupyter notebook websocket cell write append insert edit delete create batch nbmodel rest				false	error_go_core	jupyter_nbmodel_client	Múltiples funciones para escribir en notebooks: append_code/markdown, insert, edit, delete, create, batch (retornan dicts con action y posición)	false			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

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

# 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.