def distance(source_value, reference_value, task=None, **kw):
threshold = float(task.get('threshold', 0.2))
source_value_norm = text.normalize_plain(source_value)
reference_value_norm = text.normalize_plain(reference_value)
length = max([len(source_value_norm), len(reference_value_norm)])
max_distance = int(length * threshold) + 1
#print [max_distance]
return Levenshtein.distance(reference_value_norm, source_value_norm) \
< max_distance
def distance(source_value, reference_value, task=None, **kw):
threshold = float(task.get('threshold', 0.2))
source_value_norm = text.normalize_plain(source_value)
reference_value_norm = text.normalize_plain(reference_value)
length = max([len(source_value_norm), len(reference_value_norm)])
max_distance = int(length * threshold) + 1
#print [max_distance]
return Levenshtein.distance(reference_value_norm, source_value_norm) \
< max_distance
def contains(source_value, reference_value, **kw):
source_value_norm = text.normalize_plain(source_value)
reference_value_norm = text.normalize_plain(reference_value)
return reference_value_norm in source_value_norm
def contains(source_value, reference_value, **kw):
source_value_norm = text.normalize_plain(source_value)
reference_value_norm = text.normalize_plain(reference_value)
return reference_value_norm in source_value_norm
