Skip to main content

Python toolkit for Jupyter runtimes, powered by runtimed Rust binaries

Project description

runtimed

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

Download the nteract desktop app — it ships the runtimed daemon and gives you a visual interface for your notebooks.

Using runtimed with agents? The nteract MCP server is built on runtimed and provides a ready-made agentic interface for AI assistants. It's also a great example of how to use runtimed in practice.

Installation

pip install runtimed

The stable release matches the nteract desktop stable app. If you're running the nightly desktop app, install the pre-release to match: pip install --pre runtimed (or uv pip install --prerelease allow runtimed). The nightly build automatically discovers the nightly daemon socket.

Client() and the high-level Python API use default_socket_path() by default. That helper respects RUNTIMED_SOCKET_PATH, so exported test or MCP sockets take precedence over the package's default channel.

Quick Start

All examples use await — run them inside asyncio.run(main()), a Jupyter notebook, or a Python REPL with top-level await (e.g. python -m asyncio).

import asyncio
import runtimed

async def main():
    client = runtimed.Client()
    notebook = await client.create_notebook()

    # Create and execute cells
    cell = await notebook.cells.create("print('hello')")
    result = await cell.run()
    print(result.stdout)  # "hello\n"

    # Read cell properties (sync — local CRDT replica)
    print(cell.source)      # "print('hello')"
    print(cell.cell_type)   # "code"

    # Edit cells
    await cell.set_source("x = 42")
    await cell.run()

    # Save the notebook
    path = await notebook.save_as("/tmp/my-notebook.ipynb")

asyncio.run(main())

Features

  • Document-first model with Automerge CRDT sync
  • Sync reads, async writes — reads from local replica, writes sync to peers
  • Multi-client support for shared notebooks
  • Rich output capture (stdout, stderr, display_data, errors)

API Overview

Client

client = runtimed.Client()

# Discover active notebooks
notebooks = await client.list_active_notebooks()
for info in notebooks:
    print(f"{info.name} [{info.status}] ({info.active_peers} peers)")

# Open, create, or join notebooks
notebook = await client.open_notebook("/path/to/notebook.ipynb")
notebook = await client.create_notebook(runtime="python")
notebook = await client.join_notebook(notebook_id)

If you need to target a specific release channel instead of the current process default:

import os
import runtimed

os.environ["RUNTIMED_SOCKET_PATH"] = runtimed.socket_path_for_channel("nightly")
client = runtimed.Client()

Use default_socket_path() for normal current-process behavior. Use socket_path_for_channel("stable"|"nightly") only for explicit channel targeting or cross-channel discovery because it intentionally ignores RUNTIMED_SOCKET_PATH.

Notebook

async with await client.create_notebook() as notebook:
    # Cells collection (sync reads, async writes)
    print(len(notebook.cells))
    for cell in notebook.cells:
        print(f"{cell.id[:8]}: {cell.source[:40]}")

    # Runtime state (sync read from local doc)
    print(notebook.runtime.kernel.status)

    # Runtime lifecycle
    await notebook.start(runtime="python")
    await notebook.restart()
    await notebook.interrupt()
    await notebook.save()
# Session closed automatically on exit

Cells

# Create cells
cell = await notebook.cells.create("import math")
cell = await notebook.cells.insert_at(0, "# Title", cell_type="markdown")

# Access cells
cell = notebook.cells.get_by_index(0)    # by position
cell = notebook.cells.get_by_id(cell_id) # by ID
matches = notebook.cells.find("import")  # search source

# Read properties (sync)
print(cell.source, cell.cell_type, cell.outputs)

# Mutate (async)
await cell.set_source("x = 2")
await cell.append("\ny = 3")
result = await cell.run()
await cell.delete()

Requirements

Documentation

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

runtimed-2.1.4a202604130934-cp39-abi3-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.9+Windows x86-64

runtimed-2.1.4a202604130934-cp39-abi3-manylinux_2_39_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9+manylinux: glibc 2.39+ x86-64

runtimed-2.1.4a202604130934-cp39-abi3-macosx_11_0_arm64.whl (1.7 MB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

File details

Details for the file runtimed-2.1.4a202604130934-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: runtimed-2.1.4a202604130934-cp39-abi3-win_amd64.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.9+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.6 {"installer":{"name":"uv","version":"0.11.6","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for runtimed-2.1.4a202604130934-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 ac82e322875b68836a437aabd98642ecaed4b087e0cda34cf44e408d561c9458
MD5 e1fb46752b7d1d5157f00ae17701bbe2
BLAKE2b-256 5a2419d6abf6c7833f75ca73992ba1107cb0dd453397ac1716dcf9df404abeda

See more details on using hashes here.

File details

Details for the file runtimed-2.1.4a202604130934-cp39-abi3-manylinux_2_39_x86_64.whl.

File metadata

  • Download URL: runtimed-2.1.4a202604130934-cp39-abi3-manylinux_2_39_x86_64.whl
  • Upload date:
  • Size: 4.3 MB
  • Tags: CPython 3.9+, manylinux: glibc 2.39+ x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.6 {"installer":{"name":"uv","version":"0.11.6","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for runtimed-2.1.4a202604130934-cp39-abi3-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 4b94827ee5b5649e9e6d43c0e61e485ef7f20592ed3756e7a27b24ca06b0fb7b
MD5 e3082c26fca670ad23901475e806497b
BLAKE2b-256 565d98ddbbacb81dee03f626ce794df33638bee8bb81ca5c9711554e8b59cd33

See more details on using hashes here.

File details

Details for the file runtimed-2.1.4a202604130934-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

  • Download URL: runtimed-2.1.4a202604130934-cp39-abi3-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 1.7 MB
  • Tags: CPython 3.9+, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.6 {"installer":{"name":"uv","version":"0.11.6","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for runtimed-2.1.4a202604130934-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 7f4fc2d50a05acf66e4c37a849a0305288232ce996e8a6947a10fdd11562c384
MD5 1c1e900b02d5bf1ffbe10987ea0fb9be
BLAKE2b-256 43a1132c42c05520a96c13465856f1b9557d06a03e39cc6115b377bdfbcdb33a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page