Regex for accent insensitive replacement in python

Question

In Python 3, I'd like to be able to use re.sub() in an "accent-insensitive" way, as we can do with the re.I flag for case-insensitive substitution.

Could be something like a re.IGNOREACCENTS flag:

original_text = "¿It's 80°C, I'm drinking a café in a cafe with Chloë。"
accent_regex = r'a café'
re.sub(accent_regex, 'X', original_text, flags=re.IGNOREACCENTS)

This would lead to "¿It's 80°C, I'm drinking X in X with Chloë。" (note that there's still an accent on "Chloë") instead of "¿It's 80°C, I'm drinking X in a cafe with Chloë。" in real python.

I think that such a flag doesn't exist. So what would be the best option to do this? Using re.finditer and unidecode on both original_text and accent_regex and then replace by splitting the string? Or modifying all characters in the accent_regex by their accented variants, for instance: r'[cç][aàâ]f[éèêë]'?

Answer 1

unidecode is often mentioned for removing accents in Python, but it also does more than that : it converts '°' to 'deg', which might not be the desired output.

unicodedata seems to have enough functionality to remove accents.

With any pattern

This method should work with any pattern and any text.

You can temporarily remove the accents from both the text and regex pattern. The match information from re.finditer() (start and end indices) can be used to modify the original, accented text.

Note that the matches must be reversed in order to not modify the following indices.

import re
import unicodedata

original_text = "I'm drinking a 80° café in a cafe with Chloë, François Déporte and Francois Deporte."

accented_pattern = r'a café|François Déporte'

def remove_accents(s):
    return ''.join((c for c in unicodedata.normalize('NFD', s) if unicodedata.category(c) != 'Mn'))

print(remove_accents('äöüßéèiìììíàáç'))
# aoußeeiiiiiaac

pattern = re.compile(remove_accents(accented_pattern))

modified_text = original_text
matches = list(re.finditer(pattern, remove_accents(original_text)))

for match in matches[::-1]:
    modified_text = modified_text[:match.start()] + 'X' + modified_text[match.end():]

print(modified_text)
# I'm drinking a 80° café in X with Chloë, X and X.

If pattern is a word or a set of words

You could :

• remove the accents out of your pattern words and save them in a set for fast lookup
• look for every word in your text with \w+
• remove the accents from the word:
  • If it matches, replace by X
  • If it doesn't match, leave the word untouched

---

import re
from unidecode import unidecode

original_text = "I'm drinking a café in a cafe with Chloë."

def remove_accents(string):
    return unidecode(string)

accented_words = ['café', 'français']

words_to_remove = set(remove_accents(word) for word in accented_words)

def remove_words(matchobj):
    word = matchobj.group(0)
    if remove_accents(word) in words_to_remove:
        return 'X'
    else:
        return word

print(re.sub('\w+', remove_words, original_text))
# I'm drinking a X in a X with Chloë.

Answer 2

You can use Unidecode:

$ pip install unidecode

In your program:

from unidecode import unidecode

original_text = "I'm drinking a café in a cafe."
unidecoded_text = unidecode(original_text)
regex = r'cafe'
re.sub(regex, 'X', unidecoded_text)

Answer 3

Instead of removing accents, I needed to preserve accents on the text, then I used the following code:

accents_dic = {
'A': '(A|Á|À|Â|Ã)',
'E': '(E|É|È)',
'I': '(I|Í|Ï)',
'O': '(O|Ó|Ô|Õ|Ö)',
'U': '(U|Ú|Ü)',
'C': '(C|Ç)'
}
def define_regex_name(name):
    for i, j in accents_dic.items():
        name = re.sub(i,j,name)
    return re.compile(name, re.IGNORECASE)