Generalized data analysis workflow via a consistent easy to use interface.
The Python Satellite Data Analysis Toolkit (pysat) provides a simple and flexible interface for robust data analysis from beginning to end - including downloading, loading, cleaning, managing, processing, and analyzing data. Pysat's plug-in design allows analysis support for any data, including user provided data sets. The pysat team provides a variety of plug-ins to support public scientific data sets in packages such as pysatNASA, pysatMadrigal, and more, available as part of the general pysat ecosystem.
Full Documentation
JGR-Space Physics Publication
Pysat Ecosystem Publication
Come join us on Slack! An invitation to the pysat workspace is available in the 'About' section of the pysat GitHub Repository. Development meetings are generally held fortnightly.
The following instructions provide a guide for installing pysat and give some examples on how to use the routines.
pysat uses common Python modules, as well as modules developed by and for the Space Physics community. This module officially supports Python 3.X+.
Common modules | Community modules |
---|---|
dask | netCDF4 |
numpy >= 1.12 | |
pandas | |
portalocker | |
pytest | |
scipy | |
toolz | |
xarray |
pip install pysat
git clone https://github.com/pysat/pysat.git
Change directories into the repository folder and run the pyproject.toml or setup.py file. For a local install use the "--user" flag after "install".
cd pysat/
python -m build .
pip install .
pysat.params['data_dirs'] = 'path/to/directory/that/may/or/may/not/exist'
Detailed examples and tutorials for using pysat are available in the documentation.