There's a dedicated virtual machine for Jupyter, accessible from our local network at
Organization of notebooks¶
The setup is organized in 2 parts, that are run with 2 instances of Jupyter for security reasons.
The notebooks in the admin are mostly for maintenance: operations on the database, etc.
The notebooks are organized in folders, all under Gisaf's source code git repository, except the "Sandbox" one.
This notebook server connects to the database with a specific user (
jupyter), which has been set on the database server with permissions to read all data (
readonly) plus has write access to some tables dedicated to store analysis results.
Integration with Gisaf¶
The notebook in
Templates demonstrates the usage of notebook in relation with Gisaf: mostly, how to use the
gisad.ipynb_tools module to access Gisaf models and the data from the database.
This module is part of gisaf: https://redmine.auroville.org.in/projects/gisaf/repository/revisions/master/entry/gisaf/ipynb_tools.py
Some nice examples of processing, using watershed and rain: https://geohackweek.github.io/vector/06-geopandas-advanced/
A good example of how a company has integrated the same tools: https://medium.com/netflix-techblog/scheduling-notebooks-348e6c14cfd6