This repository contains tutorials on a Micro-Project within Humane-AI on defining an AIDDL-based implementation for the Moving Targets method.

The tutorials can be accessed in three different ways:

• As static pages on github
• As interactive notebooks running on a remote machine (via Binder)
• As interactive notebooks running on your local machine (via Docker)

And they are built using Jupyter notebooks as a main interface.

The simplest approach for accessing a tutorial is simply to use github, which allows one to visualize markdown files (such as this README.md) and Jupyter notebooks as nicely formatted web pages. Try inspecting the code of the "Example notebook.ipynb" file to see an example.

This is enough to view the text and code content of a tutorial, but it does not enable executing the code and checking the results.

Binder is a system that enables running repositories containing Jupyter notebooks in Docker containers on a remote machine. Accessing a tutorial in this way is actually very simple, since it involve just clicking a link such as this one:

When you click the link, the Binder system will spawn a Docker container running a Jupyter server, configure an environment for the tutorial, and allow you to run it as if on a local machine. This means you can execute code, as well as displaying the tutorial content. It's an extremely convenient way to make tutorials accessible, with no setup required on the user part.

More advanced use cases may benefit from running everything on a local machine. In an effort to improve portability and to avoid messing up with the local environment we will rely on Docker for local execution.

Doing this will require to:

• Install Docker, by following the online instructions.
• Install Docker Compose, by following the online instructions
• Clone the repository with the tutorial, in this case via the command:

git clone https://github.com/lompabo/tutorial-template-python.git

• Start the container via Docker Compose, from the main directory of the tutorial:

docker-compose up

On linux systems, you may need to start the docker service first.

The first execution of this process will be fairly long, since Docker will need to download a base image for the container (think of a virtual machine disk) and then some boilerplate configuration steps will need to be performed (e.g. installing jupyter in the container). Subsequent runs will be much faster.

The process will end with a message such as this one:

To access the notebook, open this file in a browser:
    file:https:///home/lompa/.local/share/jupyter/runtime/nbserver-1-open.html
Or copy and paste this URL:
    https://127.0.0.1:39281/?token=0cd92163797c3b3abe67c2b0aea57939867477d6068708a2

Copying one of the two addresses in a file browser file provide access to the Jupyter server running in the spawned container.

Once you are done, pressing CTRL+C on the terminal will close the Docker container.

For more information about how Docker works (such as the difference between images and containers, or how to get rid of all of them once you are done with the tutorial), you can check the Docker documentation.