def match_value(self, source: List[str], match: List[str], start_pos: int) -> float:
matched = 0
total_deviation = 0
for match_token in match:
pos = StringUtility.index_of(source, match_token, start_pos)
if pos >= 0:
distance = pos - start_pos if matched > 0 else 0
if distance <= self.config.max_distance:
matched = matched + 1
total_deviation = total_deviation + distance
start_pos = pos + 1
score = 0.0
if matched > 0 and (matched == len(match) or self.config.allow_partial_match):
completeness = matched / len(match)
accuracy = completeness * (matched / (matched + total_deviation))
initial_score = accuracy * (matched / len(source))
score = 0.4 + (0.6 * initial_score)
return score
def __tokenize(self, source: str) -> List[str]:
tokens = []
chars = slice(source)
token: str = ''
pattern = regex.compile(self.config.token_regex)
for char in chars:
if StringUtility.is_emoji(char):
tokens.append(char)
if not (token is None or token.strip() == ''):
tokens.append(token)
token = ''
elif not (pattern.search(char) is not None or chars.strip() == ''):
token = token + char
elif token != '' or token.strip() != '':
tokens.append(token)
token = ''
if token != '' or token.strip() != '':
tokens.append(token)
token = ''
return tokens
def __get_matches(regexp: Pattern, source: str) -> []:
py_regex = StringUtility.remove_unicode_matches(regexp)
matches = list(regex.finditer(py_regex, source))
return list(filter(None, map(lambda m: m.group().lower(), matches)))