# Source code for py_stringmatching.similarity_measure.jaccard

    from py_stringmatching import utils
    from py_stringmatching.similarity_measure.token_similarity_measure import \
                                                        TokenSimilarityMeasure

    class Jaccard(TokenSimilarityMeasure):
        """Computes Jaccard measure.

         For two sets X and Y, the Jaccard similarity score is:

            :math:`jaccard(X, Y) = \\frac{|X \\cap Y|}{|X \\cup Y|}`

         Note:
             In the case where both X and Y are empty sets, we define their Jaccard score to be 1.
        """

        def __init__(self):
            super(Jaccard, self).__init__()

        def get_raw_score(self, set1, set2):
            """Computes the raw Jaccard score between two sets.

            Args:
                set1,set2 (set or list): Input sets (or lists). Input lists are converted to sets.

            Returns:
                Jaccard similarity score (float).

            Raises:
                TypeError : If the inputs are not sets (or lists) or if one of the inputs is None.

            Examples:
                >>> jac = Jaccard()
                >>> jac.get_raw_score(['data', 'science'], ['data'])
                0.5
                >>> jac.get_raw_score({1, 1, 2, 3, 4}, {2, 3, 4, 5, 6, 7, 7, 8})
                0.375
                >>> jac.get_raw_score(['data', 'management'], ['data', 'data', 'science'])
                0.3333333333333333
            """

            # input validations
            utils.sim_check_for_none(set1, set2)
            utils.sim_check_for_list_or_set_inputs(set1, set2)

            # if exact match return 1.0
            if utils.sim_check_for_exact_match(set1, set2):
                return 1.0

            # if one of the strings is empty return 0
            if utils.sim_check_for_empty(set1, set2):
                return 0

            if not isinstance(set1, set):
                set1 = set(set1)
            if not isinstance(set2, set):
                set2 = set(set2)

            return float(len(set1 & set2)) / float(len(set1 | set2))

        def get_sim_score(self, set1, set2):
            """Computes the normalized Jaccard similarity between two sets. Simply call get_raw_score.

            Args:
                set1,set2 (set or list): Input sets (or lists). Input lists are converted to sets.

            Returns:
                Normalized Jaccard similarity (float).

            Raises:
                TypeError : If the inputs are not sets (or lists) or if one of the inputs is None.

            Examples:
                >>> jac = Jaccard()
                >>> jac.get_sim_score(['data', 'science'], ['data'])
                0.5
                >>> jac.get_sim_score({1, 1, 2, 3, 4}, {2, 3, 4, 5, 6, 7, 7, 8})
                0.375
                >>> jac.get_sim_score(['data', 'management'], ['data', 'data', 'science'])
                0.3333333333333333
            """
            return self.get_raw_score(set1, set2)