actinia in jupyter notebooks

So far, examples used curl on the command line or a browser to interact with actinia. Another possibility is to create a Python script to interact with actinia. Jupyter notebooks are a convenient way to create Python scripts step-by-step.

The official actinia tutorials that also use curl commands have been converted to jupyter notebooks

Getting started with jupyter notebooks

There are generally two ways to work with jupyter notebooks * run a jupyter notebook on your local machine * use jupyter hub where you can upload jupyter notebooks

Running a jupyter notebook locally

Open a terminal in a folder with jupyter notebooks and start jupyter with

jupyter-notebook

This opens an instance in the default browser with a list of files:

Using some jupyterhub

An example for a jupyterhub is Google Colab where you can create, upload, and modify jupyter notebooks (a Google account is required).

In Google Colab, you can also load a jupyter notebook directly from some Github repo:

actinia jupyter notebooks

Ready to use jupyter notebooks for actinia based on the official tutorial are available on Github in the mundialis repo actinia-jupyter. You can download this repo with e.g.

git clone https://github.com/mundialis/actinia-jupyter.git

Here we will use the following notebooks

• Actinia database access
• Time-series sampling
• User defined processing

Ready to use Google Colab links:

• Actinia database access
• Time-series sampling
• User defined processing

Note that only a limited list of GRASS modules is allowed for the actinia demouser.