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Tutorial Contents, BiG CZ user workshop, Nov. 15-16, 2017


This repository contains tutorial (hands-on demos) materials (Jupyter notebooks, supporting code, data files, and conda environment files) for the 2017 BiG-CZ/ODM2 Hands-On Workshop. It is intended for git cloning into your personal JupyterHub user space or your local computer.

Access JupyterHub

Go to You'll need your github user name for access and to create your own user space on the server. Access validation will need to be done only once.

Once you're on JupyterHub, click on the "Start My Server" button and wait a bit until the Jupyter Notebooks is shown.

Load tutorial materials from github

  1. On the Jupyter Notebooks interface, on the upper right click on the "New" button and select Other: Terminal to start a terminal (shell) session. A new browser tab or window will be opened, and the terminal will start on your home account directory, /home/jovyan.
  2. "Clone" the github tutorial repository by entering the following command (you can copy and paste):
    git clone

A new directory will be created with the tutorial materials at the directory path /home/jovyan/wshp2017_tutorial_content. All tutorial work will be done under this directory. 3. Finally, exit the terminal by typing exit and closing the terminal browser tab or window.

On Jupyter Notebook you will now see a wshp2017_tutorial_content folder. Click on it, then click on the notebooks directory.

Updating or reloading tutorial materials from github

As you work with notebooks, you may make changes to the notebook or data files that you'd like to undo or can no longer fix. In addition, the tutorial github repository may be updated after you cloned it. To discard your tutorial files and reload from github:

  1. Open a terminal from Jupyter Notebooks.
  2. Change to the tutorial directory by typing this command:
    cd /home/jovyan/wshp2017_tutorial_content
  3. Update from github with these commands:
    git reset --hard && git clean -f
    git pull
  4. Exit the terminal window (see instructions above)

Docker (to be ignored by everyone but the JupyterHub admin)

Docker image of the jupyter notebook environment can be found here. This is only used by the JupyterHub admin to create the conda environments for everyone on JupyterHub.


Tutorial content (code, Jupyter notebooks, data files) for BiG CZ user workshop, November 15-16, 2017



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