No project description provided
Project description
Welcome to Jupyter-TinCan!
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
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 Distribution
Built Distribution
Hashes for jupyter_tincan-0.1.1-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1e0f15217d5e8b5267923e9938b898c771a0b8e017774c585faf4bc5488c350d |
|
MD5 | ceec6245e2ac87e42a88ac4d13bb7f2b |
|
BLAKE2b-256 | 4ed2bb834d15db38ed4a6f224071187fcab802b2ae1c66ccf11d2764df87dac6 |