MacOS Installation

If you want to install miniconda (recommended approach, go here.)

1. Installation


To be able to complete this guide, your machine will need to meet the following requirements:

  1. A stable internet connection
  2. ~10GB of space on your hard drive
  3. MacOS version 10.13 or newer i.e. High Sierra, Mojave or Catalina. If you are unsure what version you are running click on the Apple icon in the top left of the screen and then About this Mac.
  4. Mac hardware must be a 2010 model or newer

Docker install steps

  1. Go to the dockerhub website.

  2. Select the version according to your Apple chip.

  3. After you have installed the program and started it, the whale icon will appear in your taskbar as follows:

You have successfully downloaded Docker!

Using Docker

Now we have Docker installed we can use it to access Python and all the associated packages we need for the labs of this course.

Note: With this installation process, you will not be able to install other packages if you wish to experiment. However, this will be enough for the course.

Installing the GDS environment

  1. Access your terminal: Launchpad > Other > Terminal
  2. In a fresh line in the terminal type the following to install the GDS environment container:
docker pull darribas/gds:6.1

  1. This should now prompt a long download process that looks a bit like this:

Dont be alarmed if it seems to take a very long time.

Make sure you are connected to the internet and it is a stable connection. This step involves the download of large amounts of data (~ 10GB) so it might take a while. However, it only needs to run once.

Check success

You will know the process has completed successfully when each line says ‘Pull complete’ and the new line shows your machine name.

If everything has gone according to plan, you should see darribas/gds:6.1 show up on your terminal when you type docker image ls (note in the image below there are other containers that are not required, do not worry if you don’t have those or slightly different values on the ID and the “CREATED” columns, the important bit is having darribas/gds:6.1 listed):

NOTE: please ignore the version showing in the screenshot, follow that in the command below

2. Running Python

The following sections cover how to start a python session using the docker container image you just installed, use it, and shut it down when you are done.

Running the container

  1. In the new terminal line type the following command to run the container: docker run --rm -ti -p 8888:8888 -v ${PWD}:/home/jovyan/work darribas/gds:6.1

You have now started a Python session.

Please do NOT close the terminal window until you are finished in this Python session.
  1. To access this session go to your chosen web browser (e.g. Safari/Chrome) and type: localhost:8888 into the search bar
  1. The page that loads will prompt you for a password or a token. This can be found in the text in the terminal following the last command you ran (step 9). A long series of numbers and letters will be preceded by ?token=. Copy this long series of characters and paste into the password box in your browser.

  1. Now that you are in Jupyter Lab you can open up a Python 3 notebook

Using Jupyter Notebook

  • This notebook is where you will run your code. Each shaded box is called a kernel. To test this out you can type print('test') into one of these kernels. To run the code use the shortcut Ctrl + Enter.

Make sure you save files you want to keep ONLY within the work folder, as this will ensure they are saved on your machine.

Everything saved outside the work folder will be destroyed as soon as you shut down the session.

  • You can access other files on your machine through the work folder in the File Browser. From here you can navigate to your Documents and designated folder for this module. For example, see below (this will depend on where you have stored the lab notebooks/data/other material for this course)

Here I am navigating to the folder that I have created for this module in my Documents. You can replace this with the pathway to the folder you create for this module.

  • You can save your notebook here using File > Save notebook as

  • And you can create new folders to organise your work

Ending your session

  • Once you have finished in your Jupyter session and have saved all your work, you can end the session from the terminal.

  • Using Ctrl + C will prompt a y/n option. Either type y or Ctrl + C again to end the session.

  • You can now safely shut the terminal window.

Next time you go to run a Jupyter Notebook you will not need to repeat the whole process as you have already installed Docker and the GDS environment. Instead you can start from Running the container and carry on from there.