colour python - Brave Search

colour-science.org

Colour Science for Python | Colour Science

Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.

pypi.org › project › colour

converts and manipulates various color representation (HSL, RVB, web, X11, ...)

Videos

This Python Color Library Does Everything - YouTube

December 22, 2025

Print Colorful Text in Python – Easy Terminal Styling with Colorama ...

Make Your Python Code POP With Amazing Colors in 2 Minutes - YouTube

Python Console Colors - Easy Tutorial - YouTube

How To Print Colored Text in Python (Colorama Tutorial)

December 21, 2020

colour.readthedocs.io › en › v0.3.11

Colour Science for Python — Colour 0.3.11 documentation

Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.

matplotlib.org › stable › gallery › color › named_colors.html

List of named colors — Matplotlib 3.11.2 documentation

Download Python source code: named_colors.py · Download zipped: named_colors.zip · Gallery generated by Sphinx-Gallery ·

matplotlib.org › stable › users › explain › colors › colors.html

Specifying colors — Matplotlib 3.11.2 documentation

import matplotlib.colors as mcolors import matplotlib.patches as mpatch overlap = {name for name in mcolors.CSS4_COLORS if f'xkcd:{name}' in mcolors.XKCD_COLORS} fig = plt.figure(figsize=[9, 5]) ax = fig.add_axes((0, 0, 1, 1)) n_groups = 3 n_rows = len(overlap) // n_groups + 1 for j, color_name in enumerate(sorted(overlap)): css4 = mcolors.CSS4_COLORS[color_name] xkcd = mcolors.XKCD_COLORS[f'xkcd:{color_name}'].upper() # Pick text colour based on perceived luminance.

github.com › colour-science › colour

GitHub - colour-science/colour: Colour Science for Python · GitHub

Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science.

Author: colour-science

Python Graph Gallery

python-graph-gallery.com › python-colors

Tips about colors with Python

Matplotlib only offers about a dozen qualitative palettes. So we've just created pypalettes, a python library that offers 2500+ color palettes.

sites.google.com › view › paztronomer › blog › basic › python-colors

paztronomer - python colors

Python's most used plotting library is matplotlib. With it you can do most of the visualizations, and if stuff gets complicated you can turn to other libraries (build on top of matplotlib) as seaborn, bokeh, vaex, and others. That being said, the named colors we are going to "unveil" here can be used across most (if not all) the available plotting libraries.

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colour.readthedocs.io › en › v0.3.8

Colour Science for Python — Colour 0.3.8 documentation

Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.

Invent with Python

inventwithpython.com › blog › complete-list-tkinter-colors-valid-and-tested.html

A Complete List of Python Tkinter Colors, Valid and Tested - Invent with Python

Here's a list of all 760 color names (valid and personally tested) for Python Tkinter.

developer.rhino3d.com › guides › rhinopython › python-rhinoscriptsyntax-color

Rhino - Colors in Python

December 5, 2018 - Colors in Python · Guides / Rhino.Python Guides / Colors in Python · by Scott Davidson (Last updated: Wednesday, December 5, 2018) Colors in Rhino are represented as zero-based, one-dimensional arrays that contain four values. The first 3 values are the Red, Green and Blue channels.

discuss.python.org › python help

Color a list or a string - Python Help - Discussions on Python.org

April 2, 2023 - Hi everyone, Is there a way to color a string or a list/tuple ? for example something that we can do is the following: H = 'hello' res = '' for i in range(len(H)): res += f'\033[0;33m{H[i]}' print(res) This will …

kaggle.com › code › asimislam › python-colors-color-cmap-palette

Python Colors for COLOR, CMAP and PALETTE

2 weeks ago - Checking your browser before accessing www.kaggle.com · Click here if you are not automatically redirected after 5 seconds

geeksforgeeks.org › python › print-colors-python-terminal

Print Colors in Python terminal - GeeksforGeeks

June 20, 2025 - We can print colored text in the terminal using ANSI escape codes. These codes tell the terminal to render specific foreground colors (like red or green), background colors, and text styles (like bold or underline). Here’s a simple implementation using Python functions for each color.

Python Graph Gallery

python-graph-gallery.com › color-palette-finder

Python Color Palette Finder

Browse 2500+ color palette. Find the perfect match for your Python Chart. Get the matplotlib code.

colour.readthedocs.io › en › v0.3.12

Colour Science for Python — Colour 0.3.12 documentation

Colour is a Python colour science package implementing a comprehensive number of colour theory transformations and algorithms.

wikipython.com › tkinter-ttk-tix › summary-information › colors

COLORS – wikiPython

March 22, 2022 - Python has a great many named colors you can choose by using the color’s name. A condensed list of officially recognized symbolic color names can be found in the program below. The page “… more Colors” shows another view, compliments of PySimpleGUI.

zeileis.org › news › python_colorspace

colorspace: A Python toolbox for colors and palettes

July 30, 2024 - The Python colorspace package provides a toolbox for mapping between different color spaces which can then be used to generate a wide range of perceptually-based color palettes for qualitative or quantitative (sequential or diverging) information.

docs.python.org › 3 › library › colorsys.html

colorsys — Conversions between color systems

Source code: Lib/colorsys.py The colorsys module defines bidirectional conversions of color values between colors expressed in the RGB (Red Green Blue) color space used in computer monitors and thr...

stackoverflow.com › questions › 22408237 › named-colors-in-matplotlib

python - Named colors in matplotlib - Stack Overflow

I constantly forget the names of the colors I want to use and keep coming back to this question =)

The previous answers are great, but I find it a bit difficult to get an overview of the available colors from the posted image. I prefer the colors to be grouped with similar colors, so I slightly tweaked the matplotlib answer that was mentioned in a comment above to get a color list sorted in columns. The order is not identical to how I would sort by eye, but I think it gives a good overview.

I updated the image and code to reflect that 'rebeccapurple' has been added and the three sage colors have been moved under the 'xkcd:' prefix since I posted this answer originally.

I really didn't change much from the matplotlib example, but here is the code for completeness.

import matplotlib.pyplot as plt
from matplotlib import colors as mcolors


colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)

# Sort colors by hue, saturation, value and name.
by_hsv = sorted((tuple(mcolors.rgb_to_hsv(mcolors.to_rgba(color)[:3])), name)
                for name, color in colors.items())
sorted_names = [name for hsv, name in by_hsv]

n = len(sorted_names)
ncols = 4
nrows = n // ncols

fig, ax = plt.subplots(figsize=(12, 10))

# Get height and width
X, Y = fig.get_dpi() * fig.get_size_inches()
h = Y / (nrows + 1)
w = X / ncols

for i, name in enumerate(sorted_names):
    row = i % nrows
    col = i // nrows
    y = Y - (row * h) - h

    xi_line = w * (col + 0.05)
    xf_line = w * (col + 0.25)
    xi_text = w * (col + 0.3)

    ax.text(xi_text, y, name, fontsize=(h * 0.8),
            horizontalalignment='left',
            verticalalignment='center')

    ax.hlines(y + h * 0.1, xi_line, xf_line,
              color=colors[name], linewidth=(h * 0.8))

ax.set_xlim(0, X)
ax.set_ylim(0, Y)
ax.set_axis_off()

fig.subplots_adjust(left=0, right=1,
                    top=1, bottom=0,
                    hspace=0, wspace=0)
plt.show()

Additional named colors

Updated 2017-10-25. I merged my previous updates into this section.

xkcd

If you would like to use additional named colors when plotting with matplotlib, you can use the xkcd crowdsourced color names, via the 'xkcd:' prefix:

plt.plot([1,2], lw=4, c='xkcd:baby poop green')

Now you have access to a plethora of named colors!

Tableau

The default Tableau colors are available in matplotlib via the 'tab:' prefix:

plt.plot([1,2], lw=4, c='tab:green')

There are ten distinct colors:

HTML

You can also plot colors by their HTML hex code:

plt.plot([1,2], lw=4, c='#8f9805')

This is more similar to specifying and RGB tuple rather than a named color (apart from the fact that the hex code is passed as a string), and I will not include an image of the 16 million colors you can choose from...

For more details, please refer to the matplotlib colors documentation and the source file specifying the available colors, _color_data.py.

Matplotlib uses a dictionary from its colors.py module.

To print the names use:

# python2:

import matplotlib
for name, hex in matplotlib.colors.cnames.iteritems():
    print(name, hex)

# python3:

import matplotlib
for name, hex in matplotlib.colors.cnames.items():
    print(name, hex)

This is the complete dictionary:

cnames = {
'aliceblue':            '#F0F8FF',
'antiquewhite':         '#FAEBD7',
'aqua':                 '#00FFFF',
'aquamarine':           '#7FFFD4',
'azure':                '#F0FFFF',
'beige':                '#F5F5DC',
'bisque':               '#FFE4C4',
'black':                '#000000',
'blanchedalmond':       '#FFEBCD',
'blue':                 '#0000FF',
'blueviolet':           '#8A2BE2',
'brown':                '#A52A2A',
'burlywood':            '#DEB887',
'cadetblue':            '#5F9EA0',
'chartreuse':           '#7FFF00',
'chocolate':            '#D2691E',
'coral':                '#FF7F50',
'cornflowerblue':       '#6495ED',
'cornsilk':             '#FFF8DC',
'crimson':              '#DC143C',
'cyan':                 '#00FFFF',
'darkblue':             '#00008B',
'darkcyan':             '#008B8B',
'darkgoldenrod':        '#B8860B',
'darkgray':             '#A9A9A9',
'darkgreen':            '#006400',
'darkkhaki':            '#BDB76B',
'darkmagenta':          '#8B008B',
'darkolivegreen':       '#556B2F',
'darkorange':           '#FF8C00',
'darkorchid':           '#9932CC',
'darkred':              '#8B0000',
'darksalmon':           '#E9967A',
'darkseagreen':         '#8FBC8F',
'darkslateblue':        '#483D8B',
'darkslategray':        '#2F4F4F',
'darkturquoise':        '#00CED1',
'darkviolet':           '#9400D3',
'deeppink':             '#FF1493',
'deepskyblue':          '#00BFFF',
'dimgray':              '#696969',
'dodgerblue':           '#1E90FF',
'firebrick':            '#B22222',
'floralwhite':          '#FFFAF0',
'forestgreen':          '#228B22',
'fuchsia':              '#FF00FF',
'gainsboro':            '#DCDCDC',
'ghostwhite':           '#F8F8FF',
'gold':                 '#FFD700',
'goldenrod':            '#DAA520',
'gray':                 '#808080',
'green':                '#008000',
'greenyellow':          '#ADFF2F',
'honeydew':             '#F0FFF0',
'hotpink':              '#FF69B4',
'indianred':            '#CD5C5C',
'indigo':               '#4B0082',
'ivory':                '#FFFFF0',
'khaki':                '#F0E68C',
'lavender':             '#E6E6FA',
'lavenderblush':        '#FFF0F5',
'lawngreen':            '#7CFC00',
'lemonchiffon':         '#FFFACD',
'lightblue':            '#ADD8E6',
'lightcoral':           '#F08080',
'lightcyan':            '#E0FFFF',
'lightgoldenrodyellow': '#FAFAD2',
'lightgreen':           '#90EE90',
'lightgray':            '#D3D3D3',
'lightpink':            '#FFB6C1',
'lightsalmon':          '#FFA07A',
'lightseagreen':        '#20B2AA',
'lightskyblue':         '#87CEFA',
'lightslategray':       '#778899',
'lightsteelblue':       '#B0C4DE',
'lightyellow':          '#FFFFE0',
'lime':                 '#00FF00',
'limegreen':            '#32CD32',
'linen':                '#FAF0E6',
'magenta':              '#FF00FF',
'maroon':               '#800000',
'mediumaquamarine':     '#66CDAA',
'mediumblue':           '#0000CD',
'mediumorchid':         '#BA55D3',
'mediumpurple':         '#9370DB',
'mediumseagreen':       '#3CB371',
'mediumslateblue':      '#7B68EE',
'mediumspringgreen':    '#00FA9A',
'mediumturquoise':      '#48D1CC',
'mediumvioletred':      '#C71585',
'midnightblue':         '#191970',
'mintcream':            '#F5FFFA',
'mistyrose':            '#FFE4E1',
'moccasin':             '#FFE4B5',
'navajowhite':          '#FFDEAD',
'navy':                 '#000080',
'oldlace':              '#FDF5E6',
'olive':                '#808000',
'olivedrab':            '#6B8E23',
'orange':               '#FFA500',
'orangered':            '#FF4500',
'orchid':               '#DA70D6',
'palegoldenrod':        '#EEE8AA',
'palegreen':            '#98FB98',
'paleturquoise':        '#AFEEEE',
'palevioletred':        '#DB7093',
'papayawhip':           '#FFEFD5',
'peachpuff':            '#FFDAB9',
'peru':                 '#CD853F',
'pink':                 '#FFC0CB',
'plum':                 '#DDA0DD',
'powderblue':           '#B0E0E6',
'purple':               '#800080',
'red':                  '#FF0000',
'rosybrown':            '#BC8F8F',
'royalblue':            '#4169E1',
'saddlebrown':          '#8B4513',
'salmon':               '#FA8072',
'sandybrown':           '#FAA460',
'seagreen':             '#2E8B57',
'seashell':             '#FFF5EE',
'sienna':               '#A0522D',
'silver':               '#C0C0C0',
'skyblue':              '#87CEEB',
'slateblue':            '#6A5ACD',
'slategray':            '#708090',
'snow':                 '#FFFAFA',
'springgreen':          '#00FF7F',
'steelblue':            '#4682B4',
'tan':                  '#D2B48C',
'teal':                 '#008080',
'thistle':              '#D8BFD8',
'tomato':               '#FF6347',
'turquoise':            '#40E0D0',
'violet':               '#EE82EE',
'wheat':                '#F5DEB3',
'white':                '#FFFFFF',
'whitesmoke':           '#F5F5F5',
'yellow':               '#FFFF00',
'yellowgreen':          '#9ACD32'}

You could plot them like this:

import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.colors as colors
import math


fig = plt.figure()
ax = fig.add_subplot(111)

ratio = 1.0 / 3.0
count = math.ceil(math.sqrt(len(colors.cnames)))
x_count = count * ratio
y_count = count / ratio
x = 0
y = 0
w = 1 / x_count
h = 1 / y_count

for c in colors.cnames:
    pos = (x / x_count, y / y_count)
    ax.add_patch(patches.Rectangle(pos, w, h, color=c))
    ax.annotate(c, xy=pos)
    if y >= y_count-1:
        x += 1
        y = 0
    else:
        y += 1

plt.show()