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MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.
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dopplershift Merge pull request #1161 from zbruick/standard_atmo
Update standard atmosphere reference to U.S. 1976
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.circleci Remove lat_lon_grid_spacing and the cdm module and related components Jun 18, 2019
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ci ENH: Add javacript to dynamically populate version chooser Oct 2, 2017
docs Update standard atmosphere reference to U.S. 1976 Sep 13, 2019
examples Remove extraneous u and v calculations in examples/tutorials Aug 29, 2019
metpy Update standard atmosphere reference to U.S. 1976 Sep 13, 2019
staticdata Fix Scipy 1.3 not-C-contiguous error Jun 6, 2019
talks MNT: Remove unnecessary use of keys(). Mar 20, 2018
tutorials Merge pull request #1140 from zbruick/calc_docs Sep 3, 2019
.appveyor.yml MNT: Pin coverage package version Jul 18, 2019
.codeclimate.yml MNT: Bump up complexity threshold for CodeClimate May 14, 2018
.codecov.yml MNT: Make sure counts as 100% coverage of test code Aug 15, 2019
.coveragerc ENH: Include tests as part of the coverage. Dec 9, 2016
.gitattributes MNT: Flag talks directory as docs for linguist Sep 27, 2017
.gitignore Add AMS talk (#745) Feb 21, 2018
.landscape.yml Upper air tutorial Feb 1, 2017
.lgtm.yml MNT: Add a configuration for LGTM May 11, 2018
.mailmap Updated contributors in AUTHORS.txt and .mailmap Jul 5, 2019
.stickler.yml Use Pooch to download sample data Aug 23, 2018
.travis.yml Bump pandas to 0.22.0 Aug 30, 2019
AUTHORS.txt Updated contributors in AUTHORS.txt and .mailmap Jul 5, 2019
CITATION.txt ENH: Add information for citing MetPy in publications Mar 31, 2017 MNT: Update CLA Sep 21, 2017 Create Dec 18, 2017 Use https for PEP8 link Apr 4, 2019
LICENSE Updated year in LICENSE Jul 5, 2019 Use Pooch to download sample data Aug 23, 2018
README Add stuff for putting packages on PyPI. Apr 22, 2015
README.rst Add pandas and xarray to README Aug 30, 2019 ENH: Add Stack Overflow information (Fixes #782) Mar 22, 2018 Add xarray to Aug 30, 2019
environment.yml ENH: Add flake8-rst-docstrings to our flake8 plugin collection Aug 20, 2019
setup.cfg ENH: Set numpy docstring convention for flake8 Aug 26, 2019 Bump pandas to 0.22.0 Aug 30, 2019 MNT: Bump to versioneer 0.17 Oct 26, 2016



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MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

MetPy follows semantic versioning in its version number. With our current 0.x version, that implies that MetPy's APIs (application programming interfaces) are still evolving (we won't break things just for fun, but many things are still changing as we work through design issues). Also, for a version 0.x.y, we change x when we release new features, and y when we make a release with only bug fixes.

For additional MetPy examples not included in this repository, please see the Unidata Python Gallery.

We support Python >= 3.6 and currently support Python 2.7.

NOTE: We are dropping support for Python 2.7 in Fall 2019. See here for more information.

Need Help?

Need help using MetPy? Found an issue? Have a feature request? Checkout our support page .

Important Links


Other required packages:

  • Numpy
  • Scipy
  • Matplotlib
  • Pandas
  • Pint
  • Xarray

Python 2.7 requires the enum34 package, which is a backport of the standard library enum module.

There is also an optional dependency on the pyproj library for geographic projections (used with cross sections, grid spacing calculation, and the GiniFile interface).

See the installation guide for more information.

Code of Conduct

We want everyone to feel welcome to contribute to MetPy and participate in discussions. In that spirit please have a look at our code of conduct.


Imposter syndrome disclaimer: We want your help. No, really.

There may be a little voice inside your head that is telling you that you're not ready to be an open source contributor; that your skills aren't nearly good enough to contribute. What could you possibly offer a project like this one?

We assure you - the little voice in your head is wrong. If you can write code at all, you can contribute code to open source. Contributing to open source projects is a fantastic way to advance one's coding skills. Writing perfect code isn't the measure of a good developer (that would disqualify all of us!); it's trying to create something, making mistakes, and learning from those mistakes. That's how we all improve, and we are happy to help others learn.

Being an open source contributor doesn't just mean writing code, either. You can help out by writing documentation, tests, or even giving feedback about the project (and yes - that includes giving feedback about the contribution process). Some of these contributions may be the most valuable to the project as a whole, because you're coming to the project with fresh eyes, so you can see the errors and assumptions that seasoned contributors have glossed over.

For more information, please read the see the contributing guide.


The space MetPy aims for is GEMPAK (and maybe NCL)-like functionality, in a way that plugs easily into the existing scientific Python ecosystem (numpy, scipy, matplotlib). So, if you take the average GEMPAK script for a weather map, you need to:

  • read data
  • calculate a derived field
  • show on a map/skew-T

One of the benefits hoped to achieve over GEMPAK is to make it easier to use these routines for any meteorological Python application; this means making it easy to pull out the LCL calculation and just use that, or re-use the Skew-T with your own data code. MetPy also prides itself on being well-documented and well-tested, so that on-going maintenance is easily manageable.

The intended audience is that of GEMPAK: researchers, educators, and any one wanting to script up weather analysis. It doesn't even have to be scripting; all python meteorology tools are hoped to be able to benefit from MetPy. Conversely, it's hoped to be the meteorological equivalent of the audience of scipy/scikit-learn/skimage.

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