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Home - GCP - Getting started.

Creating a GCP Instance with Python and Jupyter Notebook

This note provides a step by step guide on setting up a Google Cloud Platform (GCP) virtual machine (VM) instance with most of the tools necessary for this class.

Before starting you will need to create a GCP account, and a GCP project with billing enabled. You may also redeem the GCP coupon provided by the professor. Instructions on getting started in GCP can be found here.

Creating the VM

  1. Open up the google developer console page: Google API Console
  2. Create new project by clicking on the "Project" drop-down. Provide a name and select the billing account.
  3. Navigate to the Compute Engine page and select "Create Instance"
  4. Provide a name for your new instance and setup the following properties:
    • Zone: one of the us-east options
    • Machine type: minimize the specs for a lower rate.
    • Boot disk: Ubuntu 16.04 LTS
    • Firewall: Allow HTTP/HTTPS traffic checked.
    • Hit "Create". The VM will then take a short time to be created and will then appear in the list of VM instances.
  5. Reserve a Static IP Address

Connect to your VM Instance

You can connect to your instance via browser through the instance listing page. Alternatively, you can connect from a third party SSH client which may have more features. We provide instructions for using third party clients.

Jupyter Notebook Setup with Anaconda

In this class, we will use Python 3. So, make sure you get the correct version.

  1. SSH to the VM (see above)
  2. Create a directory in your VM, say ~/Downloads
  3. Get the latest conda package:
    wget  https://repo.continuum.io/archive/Anaconda3-4.4.0-Linux-x86_64.sh
  1. Run the script: bash ~/Downloads/Anaconda3-4.4.0-Linux-x86_64.sh.
  2. Follow instructions https://www.continuum.io/downloads.
  3. Close and re-open SSH
  4. Update conda:
    conda update conda
    conda update anaconda

Jupyter Notebook with Pip

If you install Anaconda in the previous step, you can skip this step.
But, if you wish to install with pip3 instead of anaconda, do the following:

  1. Connect to your VM instance using SSH
  2. Install python 3 stuff:
    sudo apt install python3-pip
    pip3 install jupyter pandas numpy matplotlib

Modify Jupyter installation for external access

Some of the commands below will need to be changed if you used pip3 instead of anaconda.

  1. SSH into the VM
  2. [Optional] For security, you can add a password for access to Jupyter Notebook. But, if you do not use this, the system will automatically use a token. If you prefer a password, generate a sha1 hashed password:
    python3
    >>> from notebook.auth import passwd
    >>> passwd()

This will prompt you to enter a password and then will produce a long string like 'sha1:e079...' Once this is diplayed, type exit to exit the python shell.

  1. Modify jupyter config file. You can use any text editor. The code below assumes you use vi, but you can use any editor of your choice like nano.
   jupyter notebook --generate-config
   vi .jupyter/jupyter_notebook_config.py

  1. You will now be viewing the jupyter config file. Uncomment and modify existing lines, or add these new ones:

    • c.NotebookApp.ip = '0.0.0.0'
    • c.NotebookApp.port = 8888 # or some other custom port
    • c.NotebookApp.password = u'sha1:sdasd...' # sha1 hash generated from previous step
    • c.NotebookApp.open_browser = False

  2. Start the jupyter notebook server as a background process:

    jupyter notebook &

The jupyter notebook will remain active as long as the SSH remains open. Alternatively, in the previous step you can use nohup jupyter notebook& and then jupyter notebook will remain open even if you close the SSH session.

Open up the Firewall to Allow Outside Traffic

We need to modify the network settings to open up external access.

  1. Navigate to the Networking page on the Google Cloud console.
  2. Create a new firewall rule:
    • Source filter: Allow from any source.
    • Allowed protocols and ports: tcp:80, 8888 (or whatever custom port you used before)
    • Targets: All instances in the network. If you specify a target tag, your VM instance must have a matching network tag or the firewall rule will not apply.
  3. You should now be able to access the remote jupyter notebook GUI through your local browser. Just type your instance's external IP as the URL: [IP_ADDRESS]:[PORT#]