# Unidata/MetPy

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

Repository: https://github.com/Unidata/MetPy
Canonical: https://ross.abutalabs.com/products/metpy
Homepage: https://unidata.github.io/MetPy/
Language: Python
License: BSD-3-Clause
License Family: permissive
Topics: python, atmospheric-science, meteorology, weather, plotting, scientific-computations, hodograph, skew-t, weather-data, hacktoberfest
Last push: 2026-08-24T17:52:30+00:00

## Health v2 (maintenance only)
Score: 72/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 21, longevity 100
- inputs: {"age_days": 5668, "days_push": 9, "days_rel": 369, "gap_med": 120, "n_releases_24m": 2}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1438, forks 449 (observed 2026-08-28T04:04:43.923475+00:00)

## What it is
MetPy is a Python library of tools for reading, visualizing, and performing calculations with weather data. It is developed by NSF Unidata and widely used in meteorology and atmospheric science.

## Use cases
- plot a skew-T log-P diagram from a weather balloon sounding
- calculate meteorological indices like CAPE or dewpoint from weather data
- read and decode GRIB or other weather data files in Python
- make weather maps and hodographs from observational data
- convert between meteorological units and perform thermodynamic calculations

## When to choose
- you work with weather or atmospheric science data in Python
- you need standard meteorological calculations and sounding plots
- you want a well-maintained, documented scientific library with an active community

## When to avoid
- you need real-time weather data ingestion pipelines rather than analysis tools
- your domain is unrelated to meteorology or atmospheric data

## Facets
- artifact type: library
- maturity: stable
- function: data-visualization, nlp, math, parser
- domain: weather, data-science, data-visualization
- platform: python, cross-platform
- tags: meteorology, atmospheric-science, weather-data, skew-t, hodograph, plotting, scientific-computing

## Member repositories
- Unidata/MetPy (main) score 72

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:43.923475+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:36:38.856163+00:00, confidence not recorded.
  - readme: https://github.com/Unidata/MetPy (fetched 2026-08-28T04:04:43.923475+00:00, sha ac82a2eff1b3)
  - homepage: https://unidata.github.io/MetPy/ (fetched 2026-08-29T11:47:13.420259+00:00, sha 44136fa355b3)
  - registry_pypi: https://pypi.org/pypi/metpy/json (fetched 2026-08-29T11:47:13.431336+00:00, sha eecee4826dea)
- Data as of 2026-08-30T08:39:29.467469+00:00.