class_docstr: Transforms the text of the tokens using Lawrence Philips's Double
  Metaphone algorithm. This algorithm attempts to encode words in such a way
  that similar-sounding words reduce to the same code. This may be useful for
  fields containing the names of people and places, and other uses where
  tolerance of spelling differences is desireable.
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docstr: :param primary_boost: the boost to apply to the token containing the
      primary code.
  :param secondary_boost: the boost to apply to the token containing the
      secondary code, if any.
  :param combine: if True, the original unencoded tokens are kept in the
      stream, preceding the encoded tokens.
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code: def __init__(
      self, primary_boost=1.0, secondary_boost=0.5, combine=False
  ):
      """
      :param primary_boost: the boost to apply to the token containing the
          primary code.
      :param secondary_boost: the boost to apply to the token containing the
          secondary code, if any.
      :param combine: if True, the original unencoded tokens are kept in the
          stream, preceding the encoded tokens.
      """
  
      self.primary_boost = primary_boost
      self.secondary_boost = secondary_boost
      self.combine = combine
  
imports: from whoosh.analysis.filters import Filter
  from whoosh.compat import integer_types
  from whoosh.lang.dmetaphone import double_metaphone
  from whoosh.lang.porter import stem
  from whoosh.util.cache import lfu_cache, unbound_cache
label_desc: Use image node_id 1 to create a new DoubleMetaphoneFilter object from inherited base classes: Filter with example: obj = DoubleMetaphoneFilter(primary_boost, secondary_boost, combine)