Add imports

strsim/__init__.py

@@ -18,4 +18,21 @@
 # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 # SOFTWARE.
 
+
+from .cosine import Cosine
+from .damerau import Damerau
+from .jaccard import Jaccard
+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 .shingle_based import ShingleBased
+from .sorensen_dice import SorensenDice
+from .string_distance import StringDistance
+from .string_similarity import StringSimilarity
+from .weighted_levenshtein import WeightedLevenshtein
+
 __name__ = 'strsim'

strsim/similarity.py

@@ -1,95 +0,0 @@
-# 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 .jaro_winkler 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))