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this may be helpful dictionary to get color tuple code, I generated this using my very own algo using your colors.csv file by applying pandas inbuilt function.
I request you to please merge my pull request in your repo. !!!

algo is:

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/codebrainz/color-names/master/output/colors.csv')
dbox, rbox = {}, []

for i in range(df.shape[0]):
row = list(df.iloc[i])
crgb = c, rgb = row[0], (row[3], row[4], row[5])
rbox.append(rgb)
dbox.update({rgb : c})
rbox.sort()

cbox = []
for m in range(len(rbox)):
cbox.append(dbox.get(rbox[m]))

fdict = {}
for n in range(len(rbox)):
fdict.update({cbox[n] : rbox[n]})

print(fdict)

this may be helpful dictionary to get color tuple code, I generated this using my very own algo using your colors.csv file by applying pandas inbuilt function.
I request you to please merge my pull request in your repo. !!!

algo is:

import pandas as pd
df = pd.read_csv('https://raw.githubusercontent.com/codebrainz/color-names/master/output/colors.csv') 
dbox, rbox = {}, []

for i in range(df.shape[0]):
    row = list(df.iloc[i])
    crgb = c, rgb = row[0], (row[3], row[4], row[5])
    rbox.append(rgb)
    dbox.update({rgb : c})
rbox.sort()

cbox = []
for m in range(len(rbox)):
    cbox.append(dbox.get(rbox[m]))

fdict = {}
for n in range(len(rbox)):
    fdict.update({cbox[n] : rbox[n]})

print(fdict)
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