DestinE Jupyter Notebook Tutorials for the Insula's Code Lab

This set of Jupyter Notebook tutorials equips users with the skills to access and exploit Digital Twin data from DestinE for the Insula Code Lab. Examples are all written in Python.
Tutorials are seamlessly integrated into the Insula Code Lab Python environment for all users.

• DestinE Platform CacheB data access: this example supports the user in accessing the DESP Data CacheB Service and work with Climate Adaptation DT data.
• How to access LUMI's Extremes Digital Twin data using earthkit and the Polytope API: this example supports the user to retrieve Weather Extremes DT data from Polytope and visualize it.
• How to discover and access data from DestinE Platform: this example supports the user in discover and access DestinE data through EDEN Service.
• DestinE Data Streaming: this example supports the user in the discovery of DestinE data streams through the DestinE Streamer Service.
• Drought Assessment using Insula: this example demonstrates how to use Insula Code on DestinE through the "Standard Evapotranspiration (preview)" service outputs.

Notebook templates are all a quickstart to DestinE Platform services, including EDEN, Earth Data Hub, the Data Cache Services (Cache-A and Cache-B), DestinE Streamer, DEA, Polytope, HDA, and more! Stay tuned for more contents and feel free to contribute!

⚠️ Warning: Authorized Access Only

The usage of Insula Code Lab and these example notebooks is reserved only to authorized DestinE user groups.
➡️ Register on the Destination Earth Platform

Credits

• Cache-B notebooks original content created by B-Open (Earth Data Hub).
• Earth Data Hub tutorials created by B-Open.
• polytope-earthkit.ipynb and desp-authentication.py are a slightly modified version of the examples available at Destination Earth Digital Twins's polytope examples by ECMWF.
• EDEN notebooks original content created by MEEO (EDEN).
• DestineStreamer original contents created by GeoVille (DestinE Streamer)
• DEA and Cache-A original contents created by Alia Space Systems
• Insula original contents created by Bea07 from CGI

Installation

The CodeLab environment includes some Python packages pre-installed in the user's environment. The overall list of dependencies is provided in the file requirements.txt.

Note: Pre-installed Python packages listed in this file provide a snapshot of dependencies needed to run the example notebooks provided in this repository.

To install new packages persistently in the coding environment, users can create their own virtual environment in Insula Code Lab by following the guidelines below.

How to create a virtual environment

Open a Terminal window and create a virtual environment named my_env:

python -m venv /home/jovyan/my_env

Activate it:

source /home/jovyan/my_env/bin/activate

Install dependencies

Install Python dependencies in the virtual environment as follows.

• Open a terminal window and install a single module singularly:

pip install <package>

Or install modules in batch by means of a requirements file:

• Open a terminal window and type:

pip install -r requirements.txt

Install the kernel

Install the Jupyter kernel my_env:

ipython kernel install --user --name=my_env

Note: Do not forget to change the kernel to my_env using the upper-right button within the Jupyter user interface every time you want to run your code. Occasionally, a stop/start of the service is required to apply environment changes. Users can manage the server stop/start commands via the File dropdown menu under Hub Control Panel.

Contact

If you have questions or need support with these examples, contact the support at https://platform.destine.eu/support.