In general, MetPy tries to support minor versions of dependencies released within the last two
years. For Python itself, that generally means supporting the last two minor releases; MetPy
currently supports Python >= 3.6.
matplotlib >= 2.1.0
numpy >= 1.16.0
pandas >= 0.24.0
pint >= 0.10.1
pooch >= 0.1
pyproj >= 2.3.0
scipy >= 1.0.0
traitlets >= 4.3.0
xarray >= 0.14.1
The easiest way to install MetPy is through pip:
pip install metpy
If you are a user of the Conda package manager, there are also
up-to-date packages for MetPy (as well as its dependencies) available from the
conda install -c conda-forge metpy
The source code can also be grabbed from GitHub. From
the base of the source directory, run:
pip install .
This will build and install MetPy into your current Python installation.
MetPy Monday videos #1, #2, and #3 demonstrate how to install the conda package
manager and Python packages, and how to work with conda environments.
The MetPy source comes with a set of example scripts in the examples
directory. These are also available as notebooks in the Example Gallery.