from colorsys import rgb_to_hsv colors = dict(( ((196, 2, 51), "RED"), ((255, 165, 0), "ORANGE"), ((255, 205, 0), "YELLOW"), ((0, 128, 0), "GREEN"), ((0, 0, 255), "BLUE"), ((127, 0, 255), "VIOLET"), ((0, 0, 0), "BLACK"), ((255, 255, 255), "WHITE"),)) def to_hsv( color ):     """ converts color tuples to floats and then to hsv """     return rgb_to_hsv(*[x/255.0 for x in color]) #rgb_to_hsv wants floats! def color_dist( c1, c2):     """ returns the squared euklidian distance between two color vectors in hsv space """     return sum( (a-b)**2 for a,b in zip(to_hsv(c1),to_hsv(c2)) ) def min_color_diff( color_to_match, colors):     """ returns the `(distance, color_name)` with the minimal distance to `colors`"""     return min( # overal best is the best match to any color:         (color_dist(color_to_match, test), colors[test]) # (distance to `test` color, color name)         for test in colors) color_to_match = (255,255,0) print min_color_diff( color_to_match, colors)