Skip to main content

Dockernel

Makes it possible to utilize arbitrary docker images as Jupyter kernels.

Installation, prerequisites

You will need Docker (obviously). For detailed instructions on how to install it, see Get Docker page.

To install Dockernel, use Pip.

pip install dockernel

Make sure that the jupyter installation you wish to use with dockerized kernels is in the same environment as dockernel. Keep in mind, that kernels installed with Dockernel in one version may not necessarily work with a different one.

Usage

First, create a docker image that will host your kernel. This will require a proper dockerfile. An example can be seen here.

To build your image, use docker build. E.g. to build the example mentioned above:

sudo docker build --tag my_kernel - < example_dockerfile

After that, use Dockernel to install the docker image as a Jupyter kernel:

dockernel install my_kernel --name dockerized_kernel

... and you should be ready to go! Fire up jupyter notebook and you should see dockerized_kernel under "New" menu, or in the "Notebook" section of the Launcher tab in jupyter lab.

Issues or questions?

Post a new issue in the Dockernell Issue Tracker at GitHub.

Metadata

Release files for dockernel 1.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dockernel 1.0.2
File Size Uploaded Provenance Actions
dockernel-1.0.2.tar.gz 12.2 kB Without provenance Details for dockernel-1.0.2.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for dockernel 1.0.2
File Interpreter ABI Platform Actions
dockernel-1.0.2-py3-none-any.whl Python 3 none any Details for dockernel-1.0.2-py3-none-any.whl

Total release size: 20.9 kB

Release files / dockernel-1.0.2.tar.gz

Download URL dockernel-1.0.2.tar.gz
Size 12.2 kB
Tags Source
SHA-256 checksum
How to use checksums
d9d5aa7d470743e60a9afb0dacd41094ec3532f4811ab74cc1580859515e3439
BLAKE2b-256 checksum
How to use checksums
5b824e5254996336d176eee580d37e61398af3ff76a8d807f9fcb56f2c42f54e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Release files / dockernel-1.0.2-py3-none-any.whl

Download URL dockernel-1.0.2-py3-none-any.whl
Size 8.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
2d2ce5f1dd38cf632bbf816053fbcf6faa9f9a80f24ba17e4a926436d7d37cd9
BLAKE2b-256 checksum
How to use checksums
5565ae80cf3de93b330b3513b34f4e75b06c4d4ce936e3b2cd968ac6b65b7a5d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/3.7.3 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

Security for dockernel 1.0.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page