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-2.0.5a202603271758-cp39-abi3-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.9+Windows x86-64

runtimed-2.0.5a202603271758-cp39-abi3-manylinux_2_39_x86_64.whl (4.3 MB view details)

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

runtimed-2.0.5a202603271758-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-2.0.5a202603271758-cp39-abi3-win_amd64.whl.

File metadata

  • Download URL: runtimed-2.0.5a202603271758-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/0.11.2 {"installer":{"name":"uv","version":"0.11.2","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-2.0.5a202603271758-cp39-abi3-win_amd64.whl
Algorithm Hash digest
SHA256 ebe2a939209252478513777d81294f04f8ca5c1aa511d8552f44bdb2949ef50f
MD5 0848fd6c3e34a9f634c2dcb29ee29840
BLAKE2b-256 db721d626b594fcd2b8f2c75126c0f1e2856193855c3ac72c36fbe2ea2a2af60

See more details on using hashes here.

File details

Details for the file runtimed-2.0.5a202603271758-cp39-abi3-manylinux_2_39_x86_64.whl.

File metadata

  • Download URL: runtimed-2.0.5a202603271758-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/0.11.2 {"installer":{"name":"uv","version":"0.11.2","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-2.0.5a202603271758-cp39-abi3-manylinux_2_39_x86_64.whl
Algorithm Hash digest
SHA256 da1dab57471d7d371d7c04da98990b2ee1670e687986bc96ad5c554addfd43d5
MD5 927665aeca02eba2a27523e783da4ecb
BLAKE2b-256 24c0084ff536f5785691f431465fa1dd67afadfc882e8f509612f2d6c444c79a

See more details on using hashes here.

File details

Details for the file runtimed-2.0.5a202603271758-cp39-abi3-macosx_11_0_arm64.whl.

File metadata

  • Download URL: runtimed-2.0.5a202603271758-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/0.11.2 {"installer":{"name":"uv","version":"0.11.2","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-2.0.5a202603271758-cp39-abi3-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 1aa090e31b8a68cc6ddb514cdce5302869c2f3c06d84b865fc464a75aac930ea
MD5 0b60420754e6c0b69b16bb63122a7339
BLAKE2b-256 0406df5fe1ef24fc1358677e3c49d1e9676e66d0e491c6e7b66e47f15d275a30

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