cmweather
A library of useful colormaps when visualizing weather and climate data, with numerous color vision deficiency friendly options
Decision gist · record as of 2026-08-14
Yes, if you are working with weather or climate data visualization in Python. The low install friction, permissive MIT license, and stable dependency set (numpy, matplotlib) make it a safe addition. The dormant maintenance status is acceptable for a specialized, feature-complete library; however, do not expect active development or rapid bug fixes. Verify that the colormaps you need are included in version 0.3.2 before committing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires matplotlib and numpy; colormaps are accessed through matplotlib's colormap interface.
- Low install friction with a pure Python wheel.
- Maintenance is dormant—last release was 2024-01-04 and no commits for 953 days—but the repository remains active and the package is stable enough for its narrow purpose.
License · maintenance · safety
MIT license (permissive) — MIT license is permissive; you can use, modify, and distribute cmweather with minimal restrictions, making it suitable for both open and proprietary projects.
last release 2024-01-04 (953 days) · last repo commit 2025-01-22 · 56 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 97,987 downloads/mo, #13,119 on PyPI
Alternatives
Verify before relying
pip install cmweather
import cmweather.cmap as cmap
import matplotlib.pyplot as plt
plt.imshow(data, cmap=cmap.cmap_d['your_colormap_name'])- Which specific colormaps are included in version 0.3.2 and their names for programmatic access.
- Whether all colormaps are accessible via matplotlib's standard cmap registry or require direct import.
- Performance characteristics when rendering large datasets with these colormaps.
What it is and what it does
cmweather is a lightweight library that extends matplotlib with colormaps designed specifically for weather and climate visualization. It fills a gap left by core matplotlib by providing domain-specific colormaps used across the weather community, including options designed to be friendly to color vision deficiency. The package depends only on numpy and matplotlib, making it easy to integrate into existing scientific Python workflows.
The library is positioned as a community collaboration effort, with contributions from domain-specific packages like MetPy and GeoCAT. While marked as Pre-Alpha in development status and dormant in maintenance (last release January 2024), it remains archived-free and suitable for stable visualization tasks where weather-specific colormaps are needed.
Use it for
- Visualizing meteorological data (radar, satellite, model output) with colormaps optimized for weather interpretation.
- Creating climate analysis plots where standard matplotlib colormaps are inadequate for domain conventions.
- Building accessible weather visualizations using color vision deficiency friendly colormaps.
- Standardizing colormap choices across multiple weather-focused Python packages in a single project.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are working with weather or climate data visualization in Python.
The low install friction, permissive MIT license, and stable dependency set (numpy, matplotlib) make it a safe addition. The dormant maintenance status is acceptable for a specialized, feature-complete library; however, do not expect active development or rapid bug fixes. Verify that the colormaps you need are included in version 0.3.2 before committing.
Install
cmweather on PyPI
Before you install
Low install friction with a pure Python wheel. Maintenance is dormant—last release was 2024-01-04 and no commits for 953 days—but the repository remains active and the package is stable enough for its narrow purpose.
Requires matplotlib and numpy; colormaps are accessed through matplotlib's colormap interface.
License in practice
MIT license is permissive; you can use, modify, and distribute cmweather with minimal restrictions, making it suitable for both open and proprietary projects.
Quickstart
pip install cmweather
import cmweather.cmap as cmap
import matplotlib.pyplot as plt
plt.imshow(data, cmap=cmap.cmap_d['your_colormap_name'])Verify before relying
- Which specific colormaps are included in version 0.3.2 and their names for programmatic access.
- Whether all colormaps are accessible via matplotlib's standard cmap registry or require direct import.
- Performance characteristics when rendering large datasets with these colormaps.
Package facts
| License | MIT license permissive |
| Python support | Supports the current Python release >=3.6 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 2 packagesnumpymatplotlib |
| Maintenance | Dormant 953 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 97,987 / month, #13,119 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 2 - Pre-AlphaIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: Python :: 3Programming Language :: Python :: 3.6Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Topic :: Scientific/Engineering |
Evidence: cmweather-0.3.2-py3-none-any.whl
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