Skip to main content

No project description provided

Project description

Welcome to Jupyter-TinCan!

Jupyter-Tincan logo

In the realm of data science and software development, safeguarding sensitive information is paramount. Traditional approaches, such as using remote desktop interfaces to access Jupyter notebooks, offer security but at a cost to user experience. These methods typically involve a cumbersome 'browser within a browser' setup, leading to ergonomic challenges like conflicting keyboard shortcuts, noticeable latency, and a disconnect from local development tools like VSCode. Often, developers find themselves forced into less efficient workflows, such as committing code remotely instead of locally.

Jupyter-TinCan changes the game by offering a simpler, more intuitive solution. It transforms sensitive text in notebook cells into images, maintaining data security while enhancing user experience. No more cumbersome setups or workflow disruptions – just smooth, secure, and efficient development.

Installation

$ pip install jupyter-tincan

You also need nodejs and have text2svg available.

$ npm install -g text2svg

Usage

You can configure any pre-existing Jupyter kernel to use Jupyter-TinCan. First let's list the kernels we have installed:

$ jupyter kernelspec list
Available kernels:
  python3    /usr/local/share/jupyter/kernels/python3

Now let's put the python3 kernel into TinCan mode:

$ mkdir python3-tincan
$ jupyter tincan create-kernel /usr/local/share/jupyter/kernels/python3 > python3-tincan/kernel.json

This will create a new kernel spec file called tincan-python3.json in the current directory. You can now install this kernel spec into Jupyter:

$ jupyter kernelspec install python3-tincan

or

$ jupyter kernelspec install --user python3-tincan

Acknowledgments

"Jupyter" and the Jupyter logos are trademarks of the NumFOCUS foundation. Our use of these trademarks does not imply any endorsement by Project Jupyter or NumFOCUS. Jupyter-TinCan is an independent project developed to integrate with Jupyter software.

This project is not affiliated with Project Jupyter but is designed to be compatible with and enhance the Jupyter notebook experience.

Disclaimer

Jupyter-TinCan is experimental software provided 'as-is' without any express or implied warranties. By using this software, users acknowledge the potential risks, such as data loss or incorrect data transformations, and agree to bear full responsibility for any consequences arising from its use. The developers are not liable for any damages or losses incurred from the software's operation or failure.

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

jupyter_tincan-0.1.1.tar.gz (6.7 kB view hashes)

Uploaded Source

Built Distribution

jupyter_tincan-0.1.1-py3-none-any.whl (8.5 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page