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-2.1.1a202604021312-cp39-abi3-win_amd64.whl (2.3 MB view details)

Uploaded CPython 3.9+Windows x86-64

runtimed-2.1.1a202604021312-cp39-abi3-manylinux_2_39_x86_64.whl (4.8 MB view details)

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

runtimed-2.1.1a202604021312-cp39-abi3-macosx_11_0_arm64.whl (2.2 MB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

File details

Details for the file runtimed-2.1.1a202604021312-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604021312-cp39-abi3-win_amd64.whl
  • Upload date:
  • Size: 2.3 MB
  • Tags: CPython 3.9+, Windows x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.3 {"installer":{"name":"uv","version":"0.11.3","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-2.1.1a202604021312-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 7e0214abccc4a4b1d33e5fce79cad08122abacb50e7a76e4bae1e58b9565fc43
MD5 39518315b6ab499cab5e5cada58c4741
BLAKE2b-256 0b42431225f88693dd761d38760c93573342a2c04a04a1d2b496ada39a7d00f0

See more details on using hashes here.

File details

Details for the file runtimed-2.1.1a202604021312-cp39-abi3-manylinux_2_39_x86_64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604021312-cp39-abi3-manylinux_2_39_x86_64.whl
  • Upload date:
  • Size: 4.8 MB
  • Tags: CPython 3.9+, manylinux: glibc 2.39+ x86-64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.3 {"installer":{"name":"uv","version":"0.11.3","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-2.1.1a202604021312-cp39-abi3-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 99b8e183cfdf09887233cffe32e253c60b1505bd2a5e69e0a42a7442cb74fe7f
MD5 e8d211e304eeb911168276aa4dd11586
BLAKE2b-256 390897bdea5df05500111f814ac02776cf3c1d47425330f3ea9a378dc72d8bb8

See more details on using hashes here.

File details

Details for the file runtimed-2.1.1a202604021312-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604021312-cp39-abi3-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.9+, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.3 {"installer":{"name":"uv","version":"0.11.3","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-2.1.1a202604021312-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 d3cb9d0132e14ae1baff51730b90ed222a8d7a8c099612bf1766ad81cf22c71c
MD5 5e382a607d0213a7ecd57898beec0f50
BLAKE2b-256 db2f64bd4a624b3988a2d054b4483ed6b9663fbcc9355f27d82d68baf850e8e3

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