Skip to main content

Concurrent-safe Jupyter KernelClient

Project description

conkernelclient

Background

Jupyter’s KernelClient is designed around a simple request-reply pattern: you send one message on the shell channel, wait for its reply, then send the next. This works fine for a single-threaded notebook, but falls apart when you need concurrent execution. For instance, running multiple cells in parallel, or letting an LLM tool loop fire off code while a long-running computation is still in flight. The underlying ZMQ socket isn’t safe to share across tasks, and there’s no built-in mechanism to route replies back to the correct caller when multiple requests are outstanding.

conkernelclient solves this with ConKernelClient, a drop-in replacement for AsyncKernelClient that makes concurrent execute() calls safe. It patches Session.send to synchronise with the ZMQ I/O thread (preventing a race where two sends interleave), and spins up a dedicated reader task on the shell channel that demultiplexes incoming replies by message ID. Each execute(..., reply=True) call gets its own asyncio.Queue, so multiple coroutines can await their replies independently without interfering with each other.

Installation

Install from pypi

$ pip install conkernelclient

How to use

from conkernelclient import *

The main entry point is ConKernelManager, a drop-in replacement for AsyncKernelManager that creates ConKernelClient instances. Start a kernel and connect a client in the usual way:

import asyncio
from jupyter_client.session import Session
km = ConKernelManager(session=Session(key=b'x'))
await km.start_kernel()
kc = await km.client().start_channels()
await kc.is_alive()
True

Once connected, execute() works like the standard client. Pass reply=True to await the shell reply, or reply=False (the default) to fire-and-forget and collect results later via get_pubs:

r = await kc.execute('2+1', timeout=1, reply=True)
r['content']['status']
'ok'

The key feature is safe concurrent execution. Multiple execute(..., reply=True) calls can be outstanding simultaneously — each gets its own asyncio.Queue, and a background reader task routes replies by message ID:

from fastcore.test import test_eq
a = kc.execute('x=2', reply=True)
b = kc.execute('y=3', reply=True)
r = await asyncio.wait_for(asyncio.gather(a, b), timeout=2)
test_eq(len(r), 2)
r[0]['parent_header']['msg_id']
'dab23f68-96c28dd9c776844176afdff1_66028_2'

Both replies arrive independently, each routed to the correct caller. Without ConKernelClient, the second execute would either block waiting for the first to finish, or the replies would get crossed.

As usual, we clean up when we’re done:

if await km.is_alive():
    kc.stop_channels()
    await km.shutdown_kernel()

Project details


Download files

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

Source Distribution

conkernelclient-0.0.13.tar.gz (14.8 kB view details)

Uploaded Source

Built Distribution

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

conkernelclient-0.0.13-py3-none-any.whl (14.7 kB view details)

Uploaded Python 3

File details

Details for the file conkernelclient-0.0.13.tar.gz.

File metadata

  • Download URL: conkernelclient-0.0.13.tar.gz
  • Upload date:
  • Size: 14.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.2

File hashes

Hashes for conkernelclient-0.0.13.tar.gz
Algorithm Hash digest
SHA256 1378c5da3e986e40e3f19c9af9a355d598d0b9c8cfdfeb18d9f2b4de797987d3
MD5 54a143fe46bbf24738c72c697c1554b9
BLAKE2b-256 f3d6a3daa21c75387a061d0527bcb52a3192f476342acaa2bb361bc7ebb99a93

See more details on using hashes here.

File details

Details for the file conkernelclient-0.0.13-py3-none-any.whl.

File metadata

File hashes

Hashes for conkernelclient-0.0.13-py3-none-any.whl
Algorithm Hash digest
SHA256 df9da159bbae06793c5c3baa3eeaf8601169e2483bba08175a69d3ae5514c193
MD5 7e5f5a2f2e4283e846ca7f343a23f2cf
BLAKE2b-256 4e9e12520d357dff1a28bd087498f333813acc0d5d068e1c0c2b9996e9f29222

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