docstr: Uses the tree to proactively generate a starting sequence of bytes
  that we haven't explored yet for this test.
  
  When this method is called, we assume that there must be at
  least one novel prefix left to find. If there were not, then the
  test run should have already stopped due to tree exhaustion.
code: def generate_novel_prefix(self):
      """Uses the tree to proactively generate a starting sequence of bytes
      that we haven't explored yet for this test.
  
      When this method is called, we assume that there must be at
      least one novel prefix left to find. If there were not, then the
      test run should have already stopped due to tree exhaustion.
      """
      return self.tree.generate_novel_prefix(self.random)
  
imports: from __future__ import absolute_import, division, print_function
  from collections import Counter, defaultdict
  from enum import Enum
  from random import Random, getrandbits
  from weakref import WeakKeyDictionary
  import attr
  from hypothesis import HealthCheck, Phase, Verbosity, settings
  from hypothesis._settings import local_settings
  from hypothesis.internal.cache import LRUReusedCache
  from hypothesis.internal.compat import ceil, hbytes, int_from_bytes
  from hypothesis.internal.conjecture.data import ConjectureData, ConjectureResult, DataObserver, Overrun, Status, StopTest
  from hypothesis.internal.conjecture.datatree import DataTree, PreviouslyUnseenBehaviour, TreeRecordingObserver
  from hypothesis.internal.conjecture.junkdrawer import clamp
  from hypothesis.internal.conjecture.pareto import NO_SCORE, ParetoFront, ParetoOptimiser
  from hypothesis.internal.conjecture.shrinker import Shrinker, sort_key
  from hypothesis.internal.healthcheck import fail_health_check
  from hypothesis.reporting import base_report
label_desc: Use image node_id 7 for calling the ConjectureRunner obj's underlying member method code with example usage: obj.generate_novel_prefix() and returns: self