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colorcet

Collection of perceptually uniform colormaps

Worth itPyPI GraphicsReleased Apr 20262.6M downloads / moCC-BY-4.0Pure Python

Decision gist · record as of 2026-08-14

pure-Python wheel — colorcet-3.2.1-py3-none-any.whl
v3.2.1 · released 2026-04-28 · Python >=3.10

Yes. Colorcet is actively maintained, has zero known vulnerabilities, installs with no dependencies, and supports current Python versions. The only caveat is verifying CC-BY-4.0 licensing terms for your specific use case—if you're using it for visualization in research, education, or open-source work, it's a straightforward choice.AI-flagged interpretation of the facts on this page — verify before relying

Before you install

  • Requires Python 3.10 or greater.
  • Low install friction with no runtime dependencies.
  • Active maintenance with a recent release 108 days ago and ongoing commits; supports current Python versions 3.10 through 3.14.

License · maintenance · safety

CC-BY-4.0 (unclear) — Licensed under CC-BY-4.0 (Creative Commons Attribution 4.0). The license treatment is marked unclear in the metadata, so you should verify the specific terms for your use case, particularly if redistributing or modifying the colormaps.

last release 2026-04-28 (108 days) · last repo commit 2026-05-13 · 751 stars

0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,592,884 downloads/mo, #2,978 on PyPI

Verify before relying

pip install colorcet

import colorcet as cc
# Access a colormap by name
colormap = cc.cm.viridis
  • Whether CC-BY-4.0 licensing applies to the colormap data itself or only to documentation/code, and what attribution is required for use in applications
Same gist for agents: .md · .json

What it is and what it does

Colorcet is a curated library of perceptually uniform colormaps built on research by Peter Kovesi at the Center for Exploration Targeting. It provides over 100 named colormaps optimized for scientific visualization, where color perception remains consistent across the full range of values—avoiding the perceptual distortions that can mislead viewers in standard colormaps.

The package integrates directly with popular Python plotting libraries (matplotlib, bokeh, holoviews, datashader) and requires no external dependencies beyond Python itself. It's actively maintained, supports modern Python versions, and is designed as a drop-in replacement for standard colormap collections when perceptual uniformity matters for your visualization.

Use it for

  • Create scientific plots where color gradients must represent data magnitude accurately without perceptual bias.
  • Build interactive dashboards with bokeh or holoviews using consistent, research-backed color schemes.
  • Visualize large datasets with datashader using colormaps optimized for high-density point rendering.
  • Generate publication-quality figures in matplotlib where colormap choice affects reader interpretation.
  • Ensure accessibility in visualizations by selecting colormaps designed for perceptual uniformity across viewers.

Worth the install?

AI-flagged interpretation of the facts on this page. Verify before relying on it.

Worth it

Yes.

Colorcet is actively maintained, has zero known vulnerabilities, installs with no dependencies, and supports current Python versions. The only caveat is verifying CC-BY-4.0 licensing terms for your specific use case—if you're using it for visualization in research, education, or open-source work, it's a straightforward choice.

Install

colorcet on PyPI

Before you install

Low install friction with no runtime dependencies. Active maintenance with a recent release 108 days ago and ongoing commits; supports current Python versions 3.10 through 3.14.

Requires Python 3.10 or greater.

License in practice

Licensed under CC-BY-4.0 (Creative Commons Attribution 4.0). The license treatment is marked unclear in the metadata, so you should verify the specific terms for your use case, particularly if redistributing or modifying the colormaps.

Quickstart

pip install colorcet

import colorcet as cc
# Access a colormap by name
colormap = cc.cm.viridis

Verify before relying

  • Whether CC-BY-4.0 licensing applies to the colormap data itself or only to documentation/code, and what attribution is required for use in applications

Package facts

LicenseCC-BY-4.0 unclear
Python supportSupports the current Python release >=3.10
Install frictionLow. Pure-Python wheel
Runtime dependenciesNone
MaintenanceActively maintained 108 days since the last release
Last repo commit
First released
Downloads2,592,884 / month, #2,978 on PyPI 30-day window, as of 2026-08-14
Known vulnerabilitiesNone known OSV.dev, checked 2026-08-14
Classifiers
Development Status :: 5 - Production/StableOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Typing :: Typed

Evidence: colorcet-3.2.1-py3-none-any.whl

Tags

Capabilities
perceptually uniform colormapsscientific visualization colorsmatplotlib colormap collectionbokeh color schemesdatashader colormapsuniform color palettesvisualization color maps
Topics
visualizationscientific-computingcolor-science

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See also cmcrameri · cmocean · datashader · cycler · cmap · cmweather · distinctipy · colourmap · scikit-misc · holoviews