tutorial-satpy-half-day
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Jupyter Notebook-based tutorial providing an overview of Satpy's features lasting about 4 hours
=================================== 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_ : |Binder|
.. _pangeo.binder.io: http://binder.pangeo.io/
.. |Binder| image:: http://binder.pangeo.io/badge.svg :target: http://binder.pangeo.io/v2/gh/pytroll/tutorial-satpy-half-day/main
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. 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 <https://github.com/pytroll/tutorial-satpy-half-day/blob/main/notebooks/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 <./INSTALL.md>_ 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.
.. code-block:: bash
jupyter notebook
Run individual code cells in the notebook by typing "Shift+Enter" for each cell.