DeforestationFree

A JupyterLab and VS Code Open Source environment for internal use in Trase - powered by AWS SageMaker

If you have any issues or questions, write a message in the #data-systems channel on Slack.

How to access the shared instance

1. Click on "Take me to JupyterLab" and sign-in using your @trase.earth Google account.
2. Click on the JupyterLab application:

   

3. Click on the Run button associated with the trase-jupyterlab-shared instance, wait for approximately half a minute, and when the Open button appears, click on it:

   

   

You will then be taken to the main JupyterLab interface, as shown below

Within the ~/shared/SEI-PCS folder, you will find the contents of github.com/sei-international/TRASE/trase/models.

Changes made in the shared/SEI-PCS folder are synchronized from and to the online repository when an instance starts, when it automatically shuts down, or whenever you call the sync_with_github command (see instructions below).

Additional instructions on how to use and configure a shared instance can be found at trase/products/sagemaker/documentation/user_facing/jupyterlab_shared_space_README.md

In a shared instance multiple users can collaborate in real time on the same notebook. In a private instance, a user can have its own compute capacity for special workloads.

How to create a VS Code Open Source instance

How to create a private instance