MetPy is a collection of tools in Python for reading, visualizing, and performing calculations with weather data. MetPy aims to mesh well with the rest of the scientific Python ecosystem, including the Numpy, Scipy, and Matplotlib projects, adding functionality specific to meteorology.

MetPy aims to provide GEMPAK- (and maybe NCL)-like functionality within the existing scientific Python ecosystem including projects like Numpy, Scipy, and Matplotlib. Part of MetPy's design philosophy is to make it easy to use its 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 easy to manage.

MetPy's current features include:

• meteorology-focused plotting (e.g. skew-T, hodograph, station plot)
• unit-aware meteorological calculations (e.g. vorticity, dewpoint, CAPE, cross-sections)
• reading common meteorological file formats (e.g. GINI satellite images, NEXRAD Level 2 and 3)
• gridding and interpolation tools, including isentropic interpolation
• simplified, GEMPAK-like plotting syntax
• support for xarray with coordinate and projection interpretation