README.md

docker-for-data-scientists

From one data scientist to another on how to utilize docker to make your life easier.

You can view the auto-generated documentation here:

https://www.data-mining.co.nz/docker-for-data-scientists/

Installation

Best approach is to install mkdocs in a virtual environment (venv directory):

• Python 3

  virtualenv -p /usr/bin/python3 venv
  

• Install mkdocs and dependencies

  ./venv/bin/pip install mkdocs==1.6.1 jinja2==3.1.6 Markdown==3.10.2 MarkupSafe==3.0.3 mkdocs-material==9.7.6 mkdocs-material-extensions==1.3.1 Pygments==2.20.0 pymdown-extensions==10.21.2 click==8.2.1
  

Content

In order for content to show up, it needs to be added to the configuration, i.e., in the pages section of the mkdocs.yml file.

Some pointers:

• Images and media
• Linking
• mkdocs.yml

Build

mkdocs is used to generate HTML from the markdown documents and images:

./venv/bin/mkdocs build --clean

Testing

You can test what the site looks like, using the following command and opening a browser on localhost:8000:

mkdocs monitors setup and markdown files, so you can just add and edit them as you like, it will automatically rebuild and refresh the browser.

./venv/bin/mkdocs build --clean && ./venv/bin/mkdocs serve

Deploying

Any push will trigger a rebuild of the site on github via github actions:

.github/workflows/main.yml