64 lines
2.0 KiB
Markdown
64 lines
2.0 KiB
Markdown
# Jupyter Docker Image
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This directory contains build files for a complete jupyter environment. It is based off the following repositories:
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- https://github.com/jupyter/docker-stacks
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- https://github.com/rgriffogoes/scraper-notebook
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- https://github.com/sharpTrick/sage-notebook
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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.
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## Building the Image
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To build this image, run `build/build.fish.` Edit the script to customize the image.
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## Configuration
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Change the permissions on the configuration volume (see `docker-compose.yml`) if you get errors.
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You may want to add the following lines to `jupyter_notebook_config.py`:
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```python
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c.ServerApp.local_hostnames = ["localhost", "0.0.0.0"]
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c.ServerApp.token = "a_long_random_string"
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c.TagRemovePreprocessor.enabled = True
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c.TagRemovePreprocessor.remove_cell_tags = ("hide_cell",)
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c.TagRemovePreprocessor.remove_all_outputs_tags = ("hide_output",)
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c.TagRemovePreprocessor.remove_input_tags = ("hide_input",)
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```
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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.
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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.
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## Image contents
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- jupyterlab, jupyterhub, notebook
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- latex + pandoc for exporting
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- mamba for packages
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- Python
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- Scrape tools (bs4, requests)
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- scipy, scikit-learn, scikit-image
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- tensorflow
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- sympy
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- numpy
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- matplotlib
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- pandas
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- manim
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- Octave
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- R
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- Julia
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## TODO
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- Auto dark theme
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- Fix sage
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- GPU support ([source](https://github.com/iot-salzburg/gpu-jupyter))
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- Haskell ([source](https://github.com/IHaskell/ihaskell-notebook))
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- Rust Kernel
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- C++ Kernel
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- Perl Kernel
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- Maxima Kernel
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