colour-science
Colour Science for Python
Decision gist · record as of 2026-08-14
Yes. Colour is actively maintained, has no known vulnerabilities, low install friction, and offers a mature, well-documented implementation of colour science standards. Install it if you need colour space conversions, colour appearance modelling, or spectral data handling. The permissive license and NumFOCUS affiliation signal stability and community backing.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later (supports current versions, <3.15).
- Low install friction with only numpy as a runtime dependency.
- Active maintenance with recent commits and steady releases since 2014.
License · maintenance · safety
BSD-3-Clause (permissive) — BSD-3-Clause is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
last release 2025-12-06 (251 days) · last repo commit 2026-08-12 · 2,636 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 508,950 downloads/mo, #6,275 on PyPI
Alternatives
Verify before relying
pip install colour-science
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"]
colour.convert(sd, "Spectral Distribution", "sRGB")- Whether the package supports GPU acceleration or is CPU-only for large-scale colour conversions.
- Performance characteristics for real-time colour processing workflows.
- Completeness of spectral data coverage across different illuminant and observer standards.
What it is and what it does
Colour is a comprehensive Python library for colour science that implements algorithms for colour space conversions, chromatic adaptation, colour appearance models (CIECAM02, CIECAM16, CAM16, Hellwig2022, Kim2009, sCAM, ZCAM), and colour blindness simulation. It provides access to standardized datasets including colour checkers, illuminants, and display primaries, and includes tools like kernel and Sprague interpolation for spectral data.
The package is built on numpy and exposes most functionality through a unified namespace. It targets both developers and researchers working with colour science, offering implementations of CIE standards and modern colour appearance models. The library is actively maintained, affiliated with NumFOCUS, and released under a permissive BSD-3-Clause license.
Use it for
- Convert spectral distributions or RGB values between colour spaces (sRGB, XYZ, Lab, etc.) with automatic conversion path selection.
- Simulate colour blindness by computing anomalous trichromacy matrices for different types of colour vision deficiency.
- Calculate colour appearance attributes (lightness, chroma, hue) using standard models like CIECAM02 or CIECAM16.
- Perform chromatic adaptation between different illuminants using methods like Von Kries or CMCCAT2000.
- Interpolate spectral data using kernel or Sprague methods for incomplete or unevenly sampled measurements.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Colour is actively maintained, has no known vulnerabilities, low install friction, and offers a mature, well-documented implementation of colour science standards. Install it if you need colour space conversions, colour appearance modelling, or spectral data handling. The permissive license and NumFOCUS affiliation signal stability and community backing.
Install
colour-science on PyPI
Before you install
Low install friction with only numpy as a runtime dependency. Active maintenance with recent commits and steady releases since 2014.
Requires Python 3.11 or later (supports current versions, <3.15).
License in practice
BSD-3-Clause is permissive; you can use, modify, and distribute this package freely with minimal restrictions.
Quickstart
pip install colour-science
import colour
sd = colour.SDS_COLOURCHECKERS["ColorChecker N Ohta"]["dark skin"]
colour.convert(sd, "Spectral Distribution", "sRGB")Verify before relying
- Whether the package supports GPU acceleration or is CPU-only for large-scale colour conversions.
- Performance characteristics for real-time colour processing workflows.
- Completeness of spectral data coverage across different illuminant and observer standards.
Package facts
| License | BSD-3-Clause permissive |
| Python support | Supports the current Python release <3.15,>=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenumpy |
| Maintenance | Actively maintained 251 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 508,950 / month, #6,275 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 3 - AlphaEnvironment :: ConsoleIntended Audience :: DevelopersIntended Audience :: Science/ResearchLicense :: OSI ApprovedNatural Language :: EnglishOperating System :: OS IndependentProgramming Language :: Python :: 3Topic :: Scientific/EngineeringTopic :: Software Development |
Evidence: colour_science-0.4.7-py3-none-any.whl
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See also colormath · colorspacious · colour · colorzero · coloraide · distinctipy · colourmap · brewer2mpl · webcolors · colorlover