What is the best way to remove accents (normalize) in a Python unicode string?

Heavy-duty Unidecode (For the Monty Python and the Holy Grail of accent removal!)

Unidecode converts Unicode to ASCII, hurling diacritics away like the Black Knight's limbs:

from unidecode import unidecode

print(unidecode("Café Münchner"))  # 'Twas but a scratch!
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The different flavors of normalization (How spicy do you want your string?)

Python's unicodedata serves accents in two main courses: NFD and NFKD:

• NFD: As cool as an iceberg lettuce, decomposing characters into separate diacritical marks.
• NFKD: Like Jalapeno peppers, decomposing into compatibility equivalence, leaving no stone unturned.

But watch out! Language-specific requirements might favor one process over another!

The Swiss Army Knife function (For when you need a bottle opener too!)

This function can handle everything from Python version checks to bit encodings without dropping a sweat:

def robust_strip_accents(text):
    try:
        # Python 3 doesn't believe in magic, so no wands here!
        text = unicode(text, 'utf-8') if not isinstance(text, unicode) else text
    except NameError:  # Oops, we're in Python 3 land!
        pass

    # Poof! Accents begone!
    text = unicodedata.normalize('NFKD', text)
    return ''.join(c for c in text if unicodedata.category(c) != 'Mn')  # Megabytes or Munchkins, doesn't matter!
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Transliteration vs normalizing (Same dish, different recipes! Choose your chef.)

Both methods aim to simplify, but it's essential to balance text meaning preservation against simplification. What's your priority?

Language matters! (Lost in translation?)

Remember, different diacritics mean different things in different languages. So weigh up language-specific requirements carefully to avoid playing Chinese whispers with your text!

Beware of the Unicode boogeyman (Inconsistencies are lurking!)

Unicode can be slippery with unexpected character name and category discrepancies, leading you on a wild goose chase during normalization! Knowledge is power!

It's regex to the rescue! (A shining knight for your damsel in distress)

You can wield the mighty regular expressions to clean up spacing and strip non-alphanumeric characters:

import re

def clean_text(text):
    text = robust_strip_accents(text)
    # Shields up, punctuation down!
    return re.sub(r'[^\w\s]', '', text)
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Caution, edge cases! (Every road has a dead end)

Even the best functions can stumble over edge cases. Always stress test with diverse datasets!

Universal Python code (Travels back from Python 4!)

Ensure your code does not only cater to Python version elitism with backward compatibility if targeting diverse environments. Share the unicodedata love equally!