Python - Find the closest color to a color, from giving list of colors

You want to find the sum of the absolute difference between the red, green and blue numbers and choose the smallest one.

from math import sqrt

COLORS = (
    (181, 230, 99),
    (23, 186, 241),
    (99, 23, 153),
    (231, 99, 29),
)

def closest_color(rgb):
    r, g, b = rgb
    color_diffs = []
    for color in COLORS:
        cr, cg, cb = color
        color_diff = sqrt((r - cr)**2 + (g - cg)**2 + (b - cb)**2)
        color_diffs.append((color_diff, color))
    return min(color_diffs)[1]

closest_color((12, 34, 156))
# => (99, 23, 153)

closest_color((23, 145, 234))
# => (23, 186, 241)

EDIT: Improved code and used Euclidian distance calculation Sven mentioned above instead of basic diff sum.

Fast, efficient and clean solution

Lets say we have:

list_of_colors = [[255,0,0],[150,33,77],[75,99,23],[45,88,250],[250,0,255]]

For fast processing use numpy and transform into numpy array

import numpy as np

desired color

color = [155,155,155]

Complete code

import numpy as np

list_of_colors = [[255,0,0],[150,33,77],[75,99,23],[45,88,250],[250,0,255]]
color = [155,155,155]

def closest(colors,color):
    colors = np.array(colors)
    color = np.array(color)
    distances = np.sqrt(np.sum((colors-color)**2,axis=1))
    index_of_smallest = np.where(distances==np.amin(distances))
    smallest_distance = colors[index_of_smallest]
    return smallest_distance 

closest_color = closest(list_of_colors,color)
print(closest_color )

This algorithm is without loops and is super fast as it uses numpy