qualpal 1.1.0

Automatically generate qualitative color palettes with distinct colors

Qualpal

Automatically generate qualitative color palettes with distinct, perceptually uniform colors.

Installation

Qualpal will soon be available on PyPI. In the meantime, you can install it directly from source, but note that this requires a C++ compiler.

# Core functionality
pip install git+https://github.com/jolars/qualpal-py

# With visualization support
pip install git+https://github.com/jolars/qualpal-py[viz]

Quick Start

from qualpal import Qualpal

# Generate 6 distinct colors
qp = Qualpal()
palette = qp.generate(6)

# Display colors
print(palette.hex())
# ['#f68ec8', '#233604', '#15045a', '#13cbf6', '#ebf919', '#e84123']

# Export for CSS
css = palette.to_css(prefix="theme")
# ['--theme-1: #f68ec8;', '--theme-2: #233604;', ...]

# Visualize (requires matplotlib)
palette.show(labels=True)

Key Features

• 🎨 Smart Color Generation - Automatically selects maximally distinct colors
• 🎯 Customizable - Control hue, saturation, lightness ranges
• ♿ Accessible - CVD (color vision deficiency) simulation and optimization
• 📊 Analysis - Measure perceptual distances between colors
• 📤 Export - CSS, JSON, and matplotlib visualization
• 📓 Jupyter - Rich HTML display in notebooks
• 🚀 Fast - C++ backend with Python interface

Examples

Customize Color Space

# Pastel colors
qp = Qualpal(colorspace={"h": (0, 360), "s": (0.3, 0.6), "l": (0.7, 0.9)})
pastels = qp.generate(5)

CVD-Aware Palettes

# Generate palette safe for deuteranomaly
qp = Qualpal(cvd={"deutan": 0.7})
accessible = qp.generate(6)

Color Operations

from qualpal import Color

# Create and convert colors
color = Color("#ff0000")
print(color.rgb())  # (1.0, 0.0, 0.0)
print(color.hsl())  # (0.0, 1.0, 0.5)
print(color.lab())  # (53.24, 80.09, 67.20)

# Measure perceptual distance
red = Color("#ff0000")
orange = Color("#ff6600")
distance = red.distance(orange)  # 33.42

Documentation

The full documentation is available at https://jolars.github.io/qualpal-py/.

Contributing

Contributions are welcome!

Note that the main functionality comes from the underlying C++ library, which is developed and maintained at https://github.com/jolars/qualpal. So if you want to contribute to the core algorithms, please do so there.

License

Qualpal is licensed under the MIT license

Citation

If you use Qualpal in your research, please cite the following paper:

Larsson, J. (2025). Qualpal: Qualitative Color Palettes for Everyone. Journal of Open Source Software, 10(114), 8936. https://doi.org/10.21105/joss.08936