# Jupyter Docker Image

This directory contains build files for a complete jupyter environment. It is based off the following repositories:

 - https://github.com/jupyter/docker-stacks
 - https://github.com/rgriffogoes/scraper-notebook
 - https://github.com/sharpTrick/sage-notebook

The images these files produce contain everything you could possibly want in a jupyter notebook. Additional packages can be installed in notebooks with `%%bash` magic.


## Building the Image

To build this image, run `build/build.fish.` Edit the script to customize the image.

## Configuration

Change the permissions on the configuration volume (see `docker-compose.yml`) if you get errors.

You may want to add the following lines to `jupyter_notebook_config.py`:

```python
c.ServerApp.local_hostnames = ["localhost", "0.0.0.0"]
c.ServerApp.token = "a_long_random_string"

c.TagRemovePreprocessor.enabled = True
c.TagRemovePreprocessor.remove_cell_tags = ("hide_cell",)
c.TagRemovePreprocessor.remove_all_outputs_tags = ("hide_output",)
c.TagRemovePreprocessor.remove_input_tags = ("hide_input",)
```

The first sets `0.0.0.0` to the allowed local hostname list. This prevents a possible "connection reset" when connecting to the docker container. Opens jupyter up to the outside internet, but you should have your inbound ports firewalled off anyway.

The second line sets a persistent token. If this config value is unset, jupyter will generate a new one on each run, making it hard to make a one-click bookmark.


## Image contents
 - jupyterlab, jupyterhub, notebook
   - latex + pandoc for exporting
   - mamba for packages
 - Python
   - Scrape tools (bs4, requests)
   - scipy, scikit-learn, scikit-image
   - tensorflow
   - sympy
   - numpy
   - matplotlib
   - pandas
   - manim
 - Octave
 - R
 - Julia


## TODO
 - Auto dark theme
 - Fix sage
 - GPU support ([source](https://github.com/iot-salzburg/gpu-jupyter))
 - Haskell ([source](https://github.com/IHaskell/ihaskell-notebook))
 - Rust Kernel
 - C++ Kernel
 - Perl Kernel
 - Maxima Kernel