A MinGW-specific version is provided for Docker Toolbox users, and a batch file is provided for Windows 10 users.

A Docker container functions like a separate OS that you can safely make modifications to without modifying your computers native OS.

We will distribute a Docker image that sets up this virtual OS to a configuration that we know will work well with Drake, so that you dont have to do that setup yourself -- and so that if things break, we have a better chance of reproducing your issues.

MITs Athena cluster machines running these OSs are only experimentally supported, and offer a very poor user experience, so we recommend running your own machine.

Other platforms that can run Docker (e.g.

Debian, CentOS, Fedora) might work but we cant promise support.

If getting access to a suitable machine is difficult for you, let us know and we can work with you to find a solution.

A single complete Drake image is around 2GB in size (since it contains an entire OS, and a lot of support software), and you may maintain duplicate images, so to be safe, keep around 10GB free.

Youll be sad if youre on slow internet and waiting for a couple gigabytes to download.

If you havent used one before, you will want to take a few minutes to learn the basics of using one.

You can read up on details about what that means here, but you dont really need to know it in-depth.

The gist of it is that well mostly interact with PyDrake through a web page on which you can edit and run Python code interactively.

We will only officially support Ubuntu 16.04 but you can probably get other systems working too.

Without XQuartz, you will only be able to run examples with visualizations through iPython notebooks.

It will open a terminal and take a few moments, but will present you with a terminal from which you can run Docker.

Unlike other OSs, you can only run Docker from this particular terminal when using Docker Toolbox Windows 7.).

These instructions apply for either Windows 10 or 7, and are required if you want graphical windows to appear when using the command line (when invoking Python scripts, for example) within the Docker container.

If you only view results through the Jupyter notebooks, you can skip this step.

Click through, accepting the default options, until you get the option to enable no access control.

Open your favorite terminal (unless youre on Windows 7 yall have to use the Docker Quickstart terminal) and type.

Both of these scripts rely on the idea of mounting a shared directory -- that is, sharing files between your host OS and the OS within the docker container.

Specifically, both scripts take as their second argument a directory that you can edit from both outside the container, as well as inside it at path notebooks.

This way, work you do inside the container within that directory is saved.

Youll usually want to point this path to whatever directory contains your homework code.

You can use this to, e.g., run python scripts from the command line.

Is Docker For Mac Safe