---
id: colour-science
version: "0.4.7"
license: BSD-3-Clause
license_treatment: permissive
maintenance: active
---

# colour-science — Colour Science for Python

License: permissive · Maintenance: active · Downloads: 508.9K/mo

## 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 above — verify before relying.

Colour provides algorithms and datasets for colour science tasks including colour space conversions, chromatic adaptation, colour appearance models, and colour blindness simulation.

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

pip install colour-science
uv add colour-science
poetry add colour-science

## Installing colour-science

Before you install: Low install friction with only numpy as a runtime dependency. Active maintenance with recent commits and steady releases since 2014.

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")

Requires Python 3.11 or later (supports current versions, <3.15).

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_current
- Install friction: low
- Maintenance: active
- Downloads: 508.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

color space conversion, colour science algorithms, spectral data analysis, chromatic adaptation, colour appearance models, color blindness simulation, CIE color standards, color-science, spectral-data, colorimetry

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