class_docstr: This implements a lazily calculated DFA where states
  are labelled by some string that reaches them, and are
  distinguished by a membership test and a set of experiments.
code: def label(self, i):
      self.__check_changed()
      return self.__lstar.label(i)
  
imports: from bisect import bisect_right, insort
  from collections import Counter
  import attr
  from hypothesis.errors import InvalidState
  from hypothesis.internal.conjecture.dfa import DFA, cached
  from hypothesis.internal.conjecture.junkdrawer import IntList, NotFound, SelfOrganisingList, find_integer
label_desc: Use image node_id 3 for calling the LearnedDFA obj's underlying member method code with example usage: obj.label(i) and returns: self