class_docstr: Object that can be used to control a number of feature flags for a
  given test run.
  
  This enables an approach to data generation called swarm testing (
  see Groce, Alex, et al. "Swarm testing." Proceedings of the 2012
  International Symposium on Software Testing and Analysis. ACM, 2012), in
  which generation is biased by selectively turning some features off for
  each test case generated. When there are many interacting features this can
  find bugs that a pure generation strategy would otherwise have missed.
  
  FeatureFlags are designed to "shrink open", so that during shrinking they
  become less restrictive. This allows us to potentially shrink to smaller
  test cases that were forbidden during the generation phase because they
  required disabled features.
code: def __repr__(self):
      enabled = []
      disabled = []
      for name, is_disabled in self.__is_disabled.items():
          if is_disabled:
              disabled.append(name)
          else:
              enabled.append(name)
      return f"FeatureFlags({enabled=}, {disabled=})"
  
file_path: catboost/contrib/python/hypothesis/py3/hypothesis/strategies/_internal/featureflags.py
imports: from hypothesis.internal.conjecture import utils
  from hypothesis.strategies._internal.strategies import SearchStrategy
label_desc: Use image node_id 3 for calling the FeatureFlags obj's underlying member method code with example usage: obj.__repr__() and returns: str, enabled, str, disabled, str