class_docstr: Merges adjacent tokens into "bi-word" tokens, so that for example::
  
      "the", "sign", "of", "four"
  
  becomes::
  
      "the-sign", "sign-of", "of-four"
  
  This can be used to create fields for pseudo-phrase searching, where if
  all the terms match the document probably contains the phrase, but the
  searching is faster than actually doing a phrase search on individual word
  terms.
  
  The ``BiWordFilter`` is much faster than using the otherwise equivalent
  ``ShingleFilter(2)``.
code: def __init__(self, sep="-"):
      self.sep = sep
  
imports: import re
  from collections import deque
  from whoosh.compat import u, text_type
  from whoosh.compat import xrange
  from whoosh.analysis.filters import Filter
label_desc: Use image node_id 1 to create a new BiWordFilter object from inherited base classes: Filter with example: obj = BiWordFilter(sep)