aparo/pyes

class FuzzyQuery(Query):
    """
    A fuzzy based query that uses similarity based on Levenshtein (edit distance) algorithm.
    Note
        Warning: this query is not very scalable with its default prefix
        length of 0 - in this case, every term will be enumerated and cause an
        edit score calculation. Here is a simple example:
    """

    _internal_name = "fuzzy"

    def __init__(self, field, value, boost=None, min_similarity=0.5,
                 prefix_length=0, **kwargs):
        super(FuzzyQuery, self).__init__(**kwargs)
        self.field = field
        self.value = value
        self.boost = boost
        self.min_similarity = min_similarity
        self.prefix_length = prefix_length

    def _serialize(self):
        data = {
            'value': self.value,
            'min_similarity': self.min_similarity,
            'prefix_length': self.prefix_length,
            }
        if self.boost:
            data['boost'] = self.boost
        return {self.field: data}