class_docstr: Suggests corrections based on the content of a field in a reader.
  
  Ranks suggestions by the edit distance, then by highest to lowest
  frequency.
class_docstr_tok: ["Suggests","corrections","based","on","the","content","of","a","field","in","a","reader",".","Ranks","suggestions","by","the","edit","distance",",","then","by","highest","to","lowest","frequency","."]
code: def __init__(self, reader, fieldname, fieldobj):
      self.reader = reader
      self.fieldname = fieldname
      self.fieldobj = fieldobj
  
imports: from bisect import bisect_left
  from heapq import heappush, heapreplace
  from whoosh import highlight
  from whoosh.compat import iteritems, xrange
label_desc: Use image node_id 1 to create a new ReaderCorrector object from inherited base classes: Corrector with example: obj = ReaderCorrector(reader, fieldname, fieldobj)