Metadata-Version: 2.1
Name: jupyter-tincan
Version: 0.1.1
Summary: 
License: MIT
Author: Roberto Abdelkader Martínez Pérez
Author-email: robertomartinezp@gmail.com
Requires-Python: >=3.10,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: beautifulsoup4 (>=4.12.2,<5.0.0)
Requires-Dist: pyzmq (>=25.1.1,<26.0.0)
Requires-Dist: tornado (>=6.4,<7.0)
Description-Content-Type: text/markdown

# Welcome to Jupyter-TinCan!

<img src="https://github.com/nilp0inter/jupyter-tincan/blob/main/art/jupyter-tincan-logo.png?raw=true" align="right"
     alt="Jupyter-Tincan logo" width="120">

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

```console
$ pip install jupyter-tincan
```

You also need nodejs and have text2svg available.

```console
$ 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:

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

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

```console
$ 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:

```console
$ jupyter kernelspec install python3-tincan
```

or

```console
$ 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.

