python-string-similarity/similarity/normalized_levenshtein_test.py

import unittest

from .normalized_levenshtein import NormalizedLevenshtein


class TestNormalizedLevenshtein(unittest.TestCase):

    def test_normalized_levenshtein(self):
        a = NormalizedLevenshtein()
        s0 = ""
        s1 = ""
        s2 = "上海"
        s3 = "上海市"
        distance_format = "distance: {:.4}\t between {} and {}"
        similarity_format = "similarity: {:.4}\t between {} and {}"
        print(distance_format.format(str(a.distance(s0, s1)), s0, s1))
        print(distance_format.format(str(a.distance(s0, s2)), s0, s2))
        print(distance_format.format(str(a.distance(s0, s3)), s0, s3))
        print(distance_format.format(str(a.distance(s1, s2)), s1, s2))
        print(distance_format.format(str(a.distance(s1, s3)), s1, s3))
        print(distance_format.format(str(a.distance(s2, s3)), s2, s3))

        print(similarity_format.format(str(a.similarity(s0, s1)), s0, s1))
        print(similarity_format.format(str(a.similarity(s0, s2)), s0, s2))
        print(similarity_format.format(str(a.similarity(s0, s3)), s0, s3))
        print(similarity_format.format(str(a.similarity(s1, s2)), s1, s2))
        print(similarity_format.format(str(a.similarity(s1, s3)), s1, s3))
        print(similarity_format.format(str(a.similarity(s2, s3)), s2, s3))


if __name__ == "__main__":
    unittest.main()