Anurag Uniyal
Anurag Uniyal

Reputation: 88777

latin-1 to ascii

I have a unicode string with accented latin chars e.g.

n=unicode('Wikipédia, le projet d’encyclopédie','utf-8')

I want to convert it to plain ascii i.e. 'Wikipedia, le projet dencyclopedie', so all acute/accent,cedilla etc should get removed

What is the fastest way to do that, as it needed to be done for matching a long autocomplete dropdown list

Conclusion: As one my criteria is speed, Lennart's 'register your own error handler for unicode encoding/decoding' gives best result (see Alex's answer), speed difference increases further as more and more chars are latin.

Here is the translation table I am using, also modified error handler as it need to take care of whole range of un-encoded char from error.start to error.end

# -*- coding: utf-8 -*-
import codecs

"""
This is more of visual translation also avoiding multiple char translation
e.g. £ may be written as {pound}
"""
latin_dict = {
u"¡": u"!", u"¢": u"c", u"£": u"L", u"¤": u"o", u"¥": u"Y",
u"¦": u"|", u"§": u"S", u"¨": u"`", u"©": u"c", u"ª": u"a",
u"«": u"<<", u"¬": u"-", u"­": u"-", u"®": u"R", u"¯": u"-",
u"°": u"o", u"±": u"+-", u"²": u"2", u"³": u"3", u"´": u"'",
u"µ": u"u", u"¶": u"P", u"·": u".", u"¸": u",", u"¹": u"1",
u"º": u"o", u"»": u">>", u"¼": u"1/4", u"½": u"1/2", u"¾": u"3/4",
u"¿": u"?", u"À": u"A", u"Á": u"A", u"Â": u"A", u"Ã": u"A",
u"Ä": u"A", u"Å": u"A", u"Æ": u"Ae", u"Ç": u"C", u"È": u"E",
u"É": u"E", u"Ê": u"E", u"Ë": u"E", u"Ì": u"I", u"Í": u"I",
u"Î": u"I", u"Ï": u"I", u"Ð": u"D", u"Ñ": u"N", u"Ò": u"O",
u"Ó": u"O", u"Ô": u"O", u"Õ": u"O", u"Ö": u"O", u"×": u"*",
u"Ø": u"O", u"Ù": u"U", u"Ú": u"U", u"Û": u"U", u"Ü": u"U",
u"Ý": u"Y", u"Þ": u"p", u"ß": u"b", u"à": u"a", u"á": u"a",
u"â": u"a", u"ã": u"a", u"ä": u"a", u"å": u"a", u"æ": u"ae",
u"ç": u"c", u"è": u"e", u"é": u"e", u"ê": u"e", u"ë": u"e",
u"ì": u"i", u"í": u"i", u"î": u"i", u"ï": u"i", u"ð": u"d",
u"ñ": u"n", u"ò": u"o", u"ó": u"o", u"ô": u"o", u"õ": u"o",
u"ö": u"o", u"÷": u"/", u"ø": u"o", u"ù": u"u", u"ú": u"u",
u"û": u"u", u"ü": u"u", u"ý": u"y", u"þ": u"p", u"ÿ": u"y", 
u"’":u"'"}

def latin2ascii(error):
    """
    error is  protion of text from start to end, we just convert first
    hence return error.start+1 instead of error.end
    """
    return latin_dict[error.object[error.start]], error.start+1

codecs.register_error('latin2ascii', latin2ascii)

if __name__ == "__main__":
    x = u"¼ éíñ§ÐÌëÑ » ¼ ö ® © ’"
    print x
    print x.encode('ascii', 'latin2ascii')

Why I return error.start + 1:

error object returned can be multiple characters, and we convert only first of these e.g. if I add print error.start, error.end to error handler output is

¼ éíñ§ÐÌëÑ » ¼ ö ® © ’
0 1
2 10
3 10
4 10
5 10
6 10
7 10
8 10
9 10
11 12
13 14
15 16
17 18
19 20
21 22
1/4 einSDIeN >> 1/4 o R c '

so in second line we get chars from 2-10 but we convert only 2nd hence return 3 as continue point, if we return error.end output is

¼ éíñ§ÐÌëÑ » ¼ ö ® © ’
0 1
2 10
11 12
13 14
15 16
17 18
19 20
21 22
1/4 e >> 1/4 o R c '

As we can see 2-10 portion has been replaced by a single char. off-course it would be faster to just encode whole range in one go and return error.end, but for demonstration purpose I have kept it simple.

see http://docs.python.org/library/codecs.html#codecs.register_error for more details

Upvotes: 18

Views: 13539

Answers (6)

n611x007
n611x007

Reputation: 9272

Package unihandecode is

US-ASCII transliterations of Unicode text.
an improved version of Python unidecode, that is Python port of Text::Unidecode Perl module by Sean M. Burke .

pip install Unihandecode

then in python

import unihandecode
print(unihandecode.unidecode(u'Wikipédia, le projet d’encyclopédie'))

prints Wikipedia, le projet d'encyclopedie.

Upvotes: 1

jterrace
jterrace

Reputation: 67073

The awesome unidecode module does this for you:

>>> import unidecode
>>> n = unicode('Wikipédia, le projet d’encyclopédie','utf-8')
>>> unidecode.unidecode(n)
"Wikipedia, le projet d'encyclopedie"

Upvotes: 11

Alex Martelli
Alex Martelli

Reputation: 881805

So here are three approaches, more or less as given or suggested in other answers:

# -*- coding: utf-8 -*-
import codecs
import unicodedata

x = u"Wikipédia, le projet d’encyclopédie"

xtd = {ord(u'’'): u"'", ord(u'é'): u'e', }

def asciify(error):
    return xtd[ord(error.object[error.start])], error.end

codecs.register_error('asciify', asciify)

def ae():
  return x.encode('ascii', 'asciify')

def ud():
  return unicodedata.normalize('NFKD', x).encode('ASCII', 'ignore')

def tr():
  return x.translate(xtd)

if __name__ == '__main__':
  print 'or:', x
  print 'ae:', ae()
  print 'ud:', ud()
  print 'tr:', tr()

Run as main, this emits:

or: Wikipédia, le projet d’encyclopédie
ae: Wikipedia, le projet d'encyclopedie
ud: Wikipedia, le projet dencyclopedie
tr: Wikipedia, le projet d'encyclopedie

showing clearly that the unicodedata-based approach, while it does have the convenience of not needing a translation map xtd, can't translate all characters properly in an automated fashion (it works for accented letters but not for the reverse-apostrophe), so it would also need some auxiliary step to deal explicitly with those (no doubt before what's now its body).

Performance is also interesting. On my laptop with Mac OS X 10.5 and system Python 2.5, quite repeatably:

$ python -mtimeit -s'import a' 'a.ae()'
100000 loops, best of 3: 7.5 usec per loop
$ python -mtimeit -s'import a' 'a.ud()'
100000 loops, best of 3: 3.66 usec per loop
$ python -mtimeit -s'import a' 'a.tr()'
10000 loops, best of 3: 21.4 usec per loop

translate is surprisingly slow (relative to the other approaches). I believe the issue is that the dict is looked into for every character in the translate case (and most are not there), but only for those few characters that ARE there with the asciify approach.

So for completeness here's "beefed-up unicodedata" approach:

specstd = {ord(u'’'): u"'", }
def specials(error):
  return specstd.get(ord(error.object[error.start]), u''), error.end
codecs.register_error('specials', specials)

def bu():
  return unicodedata.normalize('NFKD', x).encode('ASCII', 'specials')

this gives the right output, BUT:

$ python -mtimeit -s'import a' 'a.bu()'
100000 loops, best of 3: 10.7 usec per loop

...speed isn't all that good any more. So, if speed matters, it's no doubt worth the trouble of making a complete xtd translation dict and using the asciify approach. When a few extra microseconds per translation are no big deal, one might want to consider the bu approach simply for its convenience (only needs a translation dict for, hopefully few, special characters that don't translate correctly with the underlying unicodedata idea).

Upvotes: 16

Tam&#225;s Szelei
Tam&#225;s Szelei

Reputation: 23941

Maketrans (and translate) then convert to ascii:

intab = u'áéí'  # extend as needed
outtab = u'aei' # as well as this one
table = maketrans(intab, outtab)

text = translate(u"Wikipédia, le projet d’encyclopédie", table)

try:
    temp = unicode(text, "utf-8")
    fixed = unicodedata.normalize('NFKD', temp).encode('ASCII', action)
    return fixed
except Exception, errorInfo:
    print errorInfo
    print "Unable to convert the Unicode characters to xml character entities"
    raise errorInfo

(from here)

Upvotes: 1

Lennart Regebro
Lennart Regebro

Reputation: 172269

The "correct" way to do this is to register your own error handler for unicode encoding/decoding, and in that error handler provide the replacements from è to e and ö to o, etc.

Like so:

# -*- coding: UTF-8 -*-
import codecs

map = {u'é': u'e',
       u'’': u"'",
       # ETC
       }

def asciify(error):
    return map[error.object[error.start]], error.end

codecs.register_error('asciify', asciify)

test = u'Wikipédia, le projet d’encyclopédie'
print test.encode('ascii', 'asciify')

You might also find something in IBM's ICU library and it's Python bindings PyICU, though, it might be less work.

Upvotes: 8

Martin v. L&#246;wis
Martin v. L&#246;wis

Reputation: 127467

Without measuring, I would expect that the .translate method of Unicode strings is the fastest solution. You should definitely make your own measurements, though.

Upvotes: 0

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