class_docstr: Does as little as possible, returns random actions
  
  :param observation_space: The observation space for the environment (in the state to observation interface)
docstr: :param maze_action: Environment MazeAction to take.
  :return: state, reward, done, info
docstr_tok: [":","param","maze_action",":","Environment","MazeAction","to","take",".",":","return",":","state",",","reward",",","done",",","info"]
code: def step(
      self, maze_action: Dict
  ) -> Tuple[Dict[str, np.ndarray], float, bool, Optional[Dict]]:
      """
      :param maze_action: Environment MazeAction to take.
      :return: state, reward, done, info
      """
  
      self.dummy_core_events.twice_per_step(3)
      self.dummy_core_events.twice_per_step(7)
  
      return (
          self.get_maze_state(),
          self.reward_aggregator.summarize_reward(),
          False,
          {},
      )
  
imports: from typing import Tuple, Dict, Any, Optional
  import gym
  import numpy
  from maze.core.env.core_env import CoreEnv
  from maze.core.env.structured_env import StepKeyType, ActorID
  from maze.core.events.pubsub import Pubsub
  from maze.core.rendering.renderer import Renderer
  from maze.test.shared_test_utils.dummy_env.dummy_renderer import DummyMatplotlibRenderer
  from maze.test.shared_test_utils.dummy_env.reward.base import RewardAggregator, DummyEnvEvents
label_desc: Use image node_id 2 for calling the DummyCoreEnvironment obj's underlying member method code with example usage: obj.step(maze_action) and returns: self,  self,  False,  dict