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A library to normalize Unicode emoji sequencies. Currently broken for some cases, needs more fixing and testing. Use with care.
Does emoji normalization
- remove redundant zero-width-joiners;
- add missing zero-width joiners;
- add emoji presentation selectors where they are needed.
normalizeEmoji('☑') # ☑️
Issues:
- some compound emoji (i.e.
"👩🏿\u200d❤\ufe0f\ufe0f\u200d👨🏻"
) contain a sequence of 2 presentation selectors right after each other (\ufe0f\ufe0f
). This function breaks those emoji since it first strips all emoji presentation selectors, and then generates them from scratch. It seems that for those emoji the only way is to remember that they are constructed this way. Currently I'm not sure how to handle them, so they are broken.
Counts graphemes. Emoji must contain of 1.
o = '🚴️♂'
print(graphemeCount(o)) # 2
r = normalizeEmoji(o)
print(r, graphemeCount(r)) # 🚴♂️ 1
Strips skin tone, hair style modifiers and gender (not all, only deity-based (Venus/Mars)) zwj seqs.
print(*stripDiversity("👩🏻❤︎️👨🏿")) # 👩❤︎👨 {'skin': ('🏻', '🏿')}
print(*stripDiversity("👩🏻🦰")) # 👩 {'hair': ('🦰',), 'skin': ('🏻',)}
print(*stripDiversity("🚵♂️")) # 🚵 {'genderDeity': ('♂',)}
Replaces man
/woman
code points with person
ones.
print(*stripDiversityPerson("👨🚒")) # 🧑🚒 {'genderPerson': ('👨',)} (male firefighter to just firefighter)