class_docstr: Splits token text into N-grams.
  
  >>> rext = RegexTokenizer()
  >>> stream = rext("hello there")
  >>> ngf = NgramFilter(4)
  >>> [token.text for token in ngf(stream)]
  ["hell", "ello", "ther", "here"]
class_docstr_tok: ["Splits","token","text","into","N-grams",".",">",">",">","rext","=","RegexTokenizer","(",")",">",">",">","stream","=","rext","(","``","hello","there","''",")",">",">",">","ngf","=","NgramFilter","(","4",")",">",">",">","[","token.text","for","token","in","ngf","(","stream",")","]","[","``","hell","''",",","``","ello","''",",","``","ther","''",",","``","here","''","]"]
code: def __eq__(self, other):
      return (
          other
          and self.__class__ is other.__class__
          and self.min == other.min
          and self.max == other.max
      )
  
file_path: whoosh/src/whoosh/analysis/ngrams.py
imports: from whoosh.compat import text_type
  from whoosh.compat import xrange
  from whoosh.analysis.acore import Token
  from whoosh.analysis.filters import Filter, LowercaseFilter
  from whoosh.analysis.tokenizers import Tokenizer, RegexTokenizer
label_desc: Use image node_id 2 for calling the NgramFilter obj's underlying member method code with example usage: obj.__eq__(other) and returns: unknown