from .string_distance import NormalizedStringDistance
from .string_similarity import NormalizedStringSimilarity
from .levenshtein import Levenshtein


class NormalizedLevenshtein(NormalizedStringDistance, NormalizedStringSimilarity):

    def __init__(self):
        self.levenshtein = Levenshtein()

    def distance(self, s0, s1):
        if s0 is None:
            raise TypeError("Argument s0 is NoneType.")
        if s1 is None:
            raise TypeError("Argument s1 is NoneType.")
        if s0 == s1:
            return 0.0
        m_len = max(len(s0), len(s1))
        if m_len == 0:
            return 0.0
        return self.levenshtein.distance(s0, s1) / m_len

    def similarity(self, s0, s1):
        return 1.0 - self.distance(s0, s1)