Tutorial: Satpy Overview - Half day

This repository contains Jupyter notebooks to walk the user through the basic functionality of the Satpy Python library. The notebooks are meant to be stepped through in order as lessons in a tutorial. When lead by an instructor in a class, the lessons should take about 4 hours to complete.

In addition to the lessons in the notebooks/ directory, this repository is configured to run from Pangeo's binder instance. This allows users to run the notebook examples from the cloud, with no need to install software or download data to their local machine. See http://pangeo.io for more information.

Try these notebooks on pangeo.binder.io :

Prerequisites

This tutorial requires only basic python and numpy experience. Any additional experience with xarray or dask is not required but will make the lessons easier to understand and more effective.

System Requirements

It is recommended that anyone working through this tutorial have a minimum of 8GB of RAM memory and a CPU with at least 4 logical cores. A more powerful system is recommended for more responsive plotting and viewing of data.

Issues

Any difficulties installing or following these lessons should be filed as bugs on the [tutorial GitHub repository](https://github.com/pytroll/tutorial-satpy-half-day/issues). Create a new issue by clicking the "New issue" button near the top right of the linked page.

Lessons

All lesson notebooks are in the notebooks/ directory. See the first notebook, 01_introduction.ipynb, for details on the lessons as a whole and to start the tutorial.

Local Installation

Before attending an instructor led version of this tutorial where you will be executing the notebooks on your local machine (not in the cloud) the necessary software should be installed and test data downloaded into the correct locations. Follow the INSTALL instructions for how to create the proper conda environment. Once completed and your new environment is activated, verified, and test data downloaded you can open these lessons by starting Jupyter Notebook and navigating to the notebooks/ directory.

jupyter notebook

Run individual code cells in the notebook by typing "Shift+Enter" for each cell.