How to use the fuzzywuzzy.fuzz.WRatio function in fuzzywuzzy

def testQRatioForceAscii(self):
        s1 = "ABCD\u00C1"
        s2 = "ABCD"

        score = fuzz.WRatio(s1, s2, force_ascii=True)
        self.assertEqual(score, 100)

        score = fuzz.WRatio(s1, s2, force_ascii=False)
        self.assertLess(score, 100)

def testWRatioMisorderedMatch(self):
        # misordered full matches are scaled by .95
        self.assertEqual(fuzz.WRatio(self.s4, self.s5), 95)

def testWRatioPartialMatch(self):
        # a partial match is scaled by .9
        self.assertEqual(fuzz.WRatio(self.s1, self.s3), 90)

def testWRatioUnicode(self):
        self.assertEqual(fuzz.WRatio(unicode(self.s1), unicode(self.s1a)), 100)

def refresh(self):
        # TODO optimize
        self.search_results = sorted(filter(lambda x: x[0], (
                (entry, fuzzywuzzy.fuzz.WRatio(self.query, entry.key)
                        if self.query else 0)
                    for entry in self.session.entries)),
                        key=lambda x: (100 - x[1], x[0].key))

def fuzzy(s1, s2):
    return [fuzz.ratio(s1, s2) / 100,
            fuzz.partial_ratio(s1, s2) / 100,
            fuzz.token_sort_ratio(s1, s2) / 100,
            fuzz.partial_token_sort_ratio(s1, s2) / 100,
            fuzz.token_set_ratio(s1, s2) / 100,
            fuzz.partial_token_set_ratio(s1, s2) / 100,
            fuzz.QRatio(s1, s2) / 100,
            fuzz.WRatio(s1, s2) / 100]

data['fuzz_WRatio'] = data.apply(lambda x: fuzz.WRatio(str(x['question1']), str(x['question2'])), axis=1)
data['fuzz_partial_ratio'] = data.apply(lambda x: fuzz.partial_ratio(str(x['question1']), str(x['question2'])), axis=1)

#!/usr/bin/env python
# encoding: utf-8
from . import fuzz
from . import utils
import heapq
import logging
from functools import partial


default_scorer = fuzz.WRatio


default_processor = utils.full_process


def extractWithoutOrder(query, choices, processor=default_processor, scorer=default_scorer, score_cutoff=0):
    """Select the best match in a list or dictionary of choices.

    Find best matches in a list or dictionary of choices, return a
    generator of tuples containing the match and its score. If a dictionary
    is used, also returns the key for each match.

    Arguments:
        query: An object representing the thing we want to find.
        choices: An iterable or dictionary-like object containing choices
            to be matched against the query. Dictionary arguments of