---
id: metpy
version: "1.7.1"
license: BSD-3-Clause
license_treatment: permissive
maintenance: active
---

# MetPy — Collection of tools for reading, visualizing and performing calculations with weather data.

License: permissive · Maintenance: active · Downloads: 221.4K/mo

## What it is and what it does

MetPy is a Python library for meteorological and atmospheric science workflows, designed to bring GEMPAK-like functionality into the scientific Python ecosystem. It handles the three core tasks of weather analysis: reading meteorological data, performing thermodynamic and kinematic calculations, and visualizing results on maps and specialized diagrams such as Skew-T plots. The library is built on top of numpy, scipy, matplotlib, and xarray, so it integrates naturally with existing scientific Python workflows.

MetPy is intended for researchers, educators, and operational meteorologists who want to script weather analysis and visualization. Its design emphasizes modularity—you can extract individual calculations and reuse them in your own applications—and it prioritizes clear documentation and test coverage to ensure long-term maintainability. The package has been actively maintained since its first release in 2015 and follows semantic versioning, so code written for version 1.y will work on future 1.x releases.

Use it for:

- Plot weather maps with geographic projections and overlay meteorological fields from gridded data
- Calculate thermodynamic indices from radiosonde or model output
- Create Skew-T log-P diagrams for analyzing atmospheric stability and convection
- Extract and reuse individual meteorological calculations in custom analysis scripts
- Visualize cross-sections of atmospheric data with proper coordinate transformations
- Process and analyze gridded datasets with numpy and xarray integration

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

MetPy provides tools for reading, visualizing, and performing calculations on weather data, integrating with the scientific Python ecosystem (NumPy, SciPy, Matplotlib).

Yes. MetPy is a mature, actively maintained library with no known vulnerabilities, low install friction, and a permissive license. It fills a clear niche for meteorological analysis in Python and integrates well with the broader scientific ecosystem. Install it if you work with weather or atmospheric data.

## Install

pip install metpy
uv add metpy
poetry add metpy

## Installing MetPy

Before you install: Low install friction with a pure-wheel distribution. Active maintenance with a recent release and ongoing repository activity. Supports current Python versions (3.10–3.13).

License in practice: BSD-3-Clause permissive license allows use in both open-source and commercial projects with minimal restrictions.

Quickstart:

pip install metpy

import metpy.calc as mpcalc
from metpy.units import units

# Calculate lifted condensation level
lcl_pressure, lcl_temperature = mpcalc.lcl(pressure, temperature, dewpoint)

Requires Python >= 3.10; nine runtime dependencies (matplotlib, numpy, pandas, pint, pooch, pyproj, scipy, traitlets, xarray) will be installed automatically.

Verify before relying:

- Whether pyproj is installed by default or only on demand for geographic projections
- Performance characteristics when working with large gridded datasets
- Specific example values for thermodynamic calculations in the library

## Package facts

- License: BSD-3-Clause (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 221.4K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

weather data analysis python, meteorological calculations, atmospheric science tools, weather visualization, meteorology library, skew-t diagrams, weather map plotting, atmospheric data processing, meteorology, atmospheric-science, geospatial

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