runtimed 0.1.5a202603030913

Python toolkit for Jupyter runtimes, powered by runtimed Rust binaries

runtimed

Python bindings for the runtimed notebook daemon. Execute code, manage kernels, and interact with notebooks programmatically.

Installation

pip install runtimed

Quick Start

Synchronous API

import runtimed

with runtimed.Session() as session:
    session.start_kernel()
    result = session.run("print('hello')")
    print(result.stdout)  # "hello\n"

Async API

import asyncio
import runtimed

async def main():
    async with runtimed.AsyncSession() as session:
        await session.start_kernel()
        result = await session.run("print('hello async')")
        print(result.stdout)

asyncio.run(main())

Features

• Code execution via daemon-managed kernels
• Sync and async APIs for flexibility
• Document-first model with automerge sync
• Multi-client support for shared notebooks
• Rich output capture (stdout, stderr, display_data, errors)

Session API

session = runtimed.Session(notebook_id="my-notebook")
session.start_kernel()

# Simple execution
result = session.run("x = 42")

# Document-first pattern (for fine-grained control)
cell_id = session.create_cell("print(x)")
result = session.execute_cell(cell_id)

# Inspect results
print(result.success)
print(result.stdout)
print(result.error)

AsyncSession API

async with runtimed.AsyncSession(notebook_id="my-notebook") as session:
    await session.start_kernel()
    result = await session.run("x = 42")

    # Or document-first pattern
    cell_id = await session.create_cell("print(x)")
    result = await session.execute_cell(cell_id)

DaemonClient API

client = runtimed.DaemonClient()
client.ping()        # Health check
client.status()      # Pool statistics
client.list_rooms()  # Active notebooks

Requirements

• runtimed daemon running (runt daemon start)
• Python 3.9+

Documentation

See docs/python-bindings.md for full documentation.