# Copyright (c) 2018 luozhouyang # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from enum import IntEnum from .cosine import Cosine from .damerau import Damerau from .jaccard import Jaccard from .jarowinkler import JaroWinkler from .levenshtein import Levenshtein from .longest_common_subsequence import LongestCommonSubsequence from .metric_lcs import MetricLCS from .ngram import NGram from .normalized_levenshtein import NormalizedLevenshtein from .optimal_string_alignment import OptimalStringAlignment from .qgram import QGram from .sorensen_dice import SorensenDice from .weighted_levenshtein import WeightedLevenshtein class Algorithm(IntEnum): COSINE = 1 DAMERAU = 2 JACCARD = 3 JARO_WINKLE = 4 LEVENSHTEIN = 5 LCS = 6 METRIC_LCS = 7 N_GRAM = 8 NORMALIZED_LEVENSHTEIN = 9 OPTIMAL_STRING_ALIGNMENT = 10 Q_GRAM = 11 SORENSEN_DICE = 12 WEIGHTED_LEVENSHTEIN = 13 class Factory: @staticmethod def get_algorithm(algorithm: Algorithm, k=3): if algorithm == Algorithm.COSINE: return Cosine(k) elif algorithm == Algorithm.DAMERAU: return Damerau() elif algorithm == Algorithm.JACCARD: return Jaccard(k) elif algorithm == Algorithm.JARO_WINKLE: return JaroWinkler() elif algorithm == Algorithm.LEVENSHTEIN: return Levenshtein() elif algorithm == Algorithm.LCS: return LongestCommonSubsequence() elif algorithm == Algorithm.METRIC_LCS: return MetricLCS() elif algorithm == Algorithm.N_GRAM: return NGram() elif algorithm == Algorithm.NORMALIZED_LEVENSHTEIN: return NormalizedLevenshtein() elif algorithm == Algorithm.OPTIMAL_STRING_ALIGNMENT: return OptimalStringAlignment() elif algorithm == Algorithm.Q_GRAM: return QGram() elif algorithm == Algorithm.SORENSEN_DICE: return SorensenDice(k) elif algorithm == Algorithm.WEIGHTED_LEVENSHTEIN: raise TypeError("This method does not support create weighted_levenshtein algorithm.") else: return Cosine(k) @staticmethod def get_weighted_levenshtein(char_sub, char_change): return WeightedLevenshtein(char_sub, char_change) if __name__ == "__main__": a = Factory().get_algorithm(Algorithm.LEVENSHTEIN) distance_format = "distance: {:.4} between {} and {}" s0 = "你好" s1 = "你好啊" print(distance_format.format(str(a.distance(s0, s1)), s0, s1))