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-2.1.1a202604060404-cp39-abi3-win_amd64.whl (2.6 MB view details)

Uploaded CPython 3.9+Windows x86-64

runtimed-2.1.1a202604060404-cp39-abi3-manylinux_2_39_x86_64.whl (3.1 MB view details)

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

runtimed-2.1.1a202604060404-cp39-abi3-macosx_11_0_arm64.whl (2.6 MB view details)

Uploaded CPython 3.9+macOS 11.0+ ARM64

File details

Details for the file runtimed-2.1.1a202604060404-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604060404-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-2.1.1a202604060404-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 c31d06554ef3f9f8484915f2e3a3a0b5e18c45068f0a1f7b9af0709797754288
MD5 1880f6dbb54c52c80788930eb70d67f8
BLAKE2b-256 ba307e1978e68eb1f71fdad1445fbc22b50558599a808d6df22e0ea975f10b61

See more details on using hashes here.

File details

Details for the file runtimed-2.1.1a202604060404-cp39-abi3-manylinux_2_39_x86_64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604060404-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-2.1.1a202604060404-cp39-abi3-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 7f54b06f179f026712a2a004ebb0cdadbda1ba664b03561c7abefea0fbfd3b66
MD5 49837f2225c93d5c0a0017db1d6c881c
BLAKE2b-256 a16071ea89db6d9f95f120add3b69b999f9c62192a583661ea9e7317a5bfe9ec

See more details on using hashes here.

File details

Details for the file runtimed-2.1.1a202604060404-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

  • Download URL: runtimed-2.1.1a202604060404-cp39-abi3-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 2.6 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-2.1.1a202604060404-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0eb5a6dac533b31da5d1ccf430dba20a40ac667d08f0de6690536ef062702ece
MD5 99b903416e23bebfa1c80b913424ab07
BLAKE2b-256 75a7e199bca41c51304fdccb6d7ae9a73e547a3aa30843a0a64b65157ca6d211

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