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

This version

2.1.1

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-2.1.1-cp39-abi3-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9+Windows x86-64

runtimed-2.1.1-cp39-abi3-manylinux_2_39_x86_64.whl (3.1 MB view details)

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

runtimed-2.1.1-cp39-abi3-macosx_11_0_arm64.whl (2.7 MB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

File details

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

File metadata

  • Download URL: runtimed-2.1.1-cp39-abi3-win_amd64.whl
  • Upload date:
  • Size: 2.6 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-2.1.1-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 b71540c4604d4275a67bcb9801b0618c55be4b7139ab42f0724046e6b5aee522
MD5 764910a00d3a9c7b4ca4abd34e6bd14e
BLAKE2b-256 c9d42675511bf6ea317b9b86ab11b50daa7dc5575f063c42e7883fb9b5303bfc

See more details on using hashes here.

File details

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

File metadata

  • Download URL: runtimed-2.1.1-cp39-abi3-manylinux_2_39_x86_64.whl
  • Upload date:
  • Size: 3.1 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-2.1.1-cp39-abi3-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 c02fa1d5a2e8280b5169d90d1c8c0b66192c8b47bb4ddff13f3210a7dfd82ab4
MD5 bb59c905fa31298542f82a820936e013
BLAKE2b-256 f0ec7863cfc7985a2e293a2146287210740f938f2bd03dc0622cfbb02c983428

See more details on using hashes here.

File details

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

File metadata

  • Download URL: runtimed-2.1.1-cp39-abi3-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.7 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-2.1.1-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 ce8f935027bd2e3116890b851d001192e71c613adf31f3006322ca6cc1a0f641
MD5 73006692d579e3d1e4f8def873de1ec6
BLAKE2b-256 df3fcbf7deffdde4c5c882e2cc5761fedb8dd144627a0270e75494467970b6ab

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