fn_registry/python/functions/notebook/jupyter_read.md

---
name: jupyter_read
kind: function
lang: py
domain: notebook
version: "1.0.0"
purity: impure
signature: "def jupyter_read_cells(notebook_path: str, server_url: str = 'http://localhost:8888', token: str = '', cell_index: int | None = None) -> list[dict]"
description: "Lee celdas de un notebook Jupyter abierto via el protocolo de colaboracion en tiempo real (CRDT/Y.js). Devuelve el estado actual incluyendo cambios no guardados. Expone tambien jupyter_notebook_info() para metadata rapida."
tags: [jupyter, notebook, crdt, yjs, websocket, cells, read, realtime]
uses_functions: []
uses_types: []
returns: []
returns_optional: false
error_type: "error_go_core"
imports: [jupyter_nbmodel_client]
tested: false
tests: []
test_file_path: ""
file_path: "python/functions/notebook/jupyter_read.py"
---

## Funciones exportadas

### `jupyter_read_cells`

```python
def jupyter_read_cells(
    notebook_path: str,
    server_url: str = "http://localhost:8888",
    token: str = "",
    cell_index: int | None = None,
) -> list[dict]
```

Lee todas las celdas o una especifica de un notebook Jupyter en vivo.
Retorna lista de dicts:

```python
{"index": 0, "type": "code", "source": "import pandas as pd", "outputs": ["..."]}
```

- Para celdas markdown y raw, el campo `outputs` no se incluye.
- Para code cells, los outputs se convierten a texto legible:
  - `stream` -> texto plano
  - `display_data`/`execute_result` -> `text/plain`, o `[HTML Output]`, `[Image Output (PNG)]`
  - `error` -> traceback limpio (sin codigos ANSI)

### `jupyter_notebook_info`

```python
def jupyter_notebook_info(
    notebook_path: str,
    server_url: str = "http://localhost:8888",
    token: str = "",
) -> dict
```

Retorna metadata del notebook:

```python
{
    "notebook_path": "notebooks/analysis.ipynb",
    "server_url": "http://localhost:8888",
    "total_cells": 12,
    "cell_counts": {"code": 9, "markdown": 3}
}
```

## Ejemplo

```python
from notebook.jupyter_read import jupyter_read_cells, jupyter_notebook_info

# Leer todas las celdas
cells = jupyter_read_cells(
    "notebooks/analysis.ipynb",
    server_url="http://localhost:8888",
    token="mi-token",
)
for cell in cells:
    print(f"[{cell['index']}] {cell['type']}: {cell['source'][:60]}")

# Leer solo la celda 3
cell = jupyter_read_cells("notebooks/analysis.ipynb", token="mi-token", cell_index=3)

# Solo metadata
info = jupyter_notebook_info("notebooks/analysis.ipynb", token="mi-token")
print(f"Total celdas: {info['total_cells']}")
```

## CLI

```bash
# Ver todas las celdas (formato legible)
python jupyter_read.py notebooks/analysis.ipynb --token MI_TOKEN

# Ver solo la celda 5
python jupyter_read.py notebooks/analysis.ipynb --token MI_TOKEN --cell 5

# Solo metadata
python jupyter_read.py notebooks/analysis.ipynb --token MI_TOKEN --info

# Salida JSON (todas las celdas)
python jupyter_read.py notebooks/analysis.ipynb --token MI_TOKEN --json

# Servidor remoto
python jupyter_read.py notebooks/analysis.ipynb --server http://mi-servidor:8888 --token MI_TOKEN
```

## Notas

- Usa `NbModelClient` de `jupyter_nbmodel_client` con protocolo CRDT/Y.js.
- Las funciones internas son `async`; las publicas envuelven con `asyncio.run()` para ser sincronas.
- Lee el estado **en memoria del servidor**, no el archivo `.ipynb` en disco — captura cambios no guardados.
- `notebook_path` debe ser relativo a la raiz del servidor Jupyter, no al sistema de archivos local.
- Para servidores sin token, usar `token=""` (default).
- El CLI muestra preview de hasta 8 lineas de source y 4 lineas por output en modo legible.