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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def bandit(self, choice_rewards):
 """Return the choice to take next using multi-armed bandit Multi-armed bandit method. Accepts a mapping of choices to rewards which indicate their historical performance, and returns the choice that we should make next in order to maximize expected reward in the long term. The default implementation is to return the arm with the highest average score. Args: choice_rewards (Dict[object, List[float]]):
 maps choice IDs to lists of rewards. Returns: str: the name of the choice to take next. """

        return max(choice_rewards, key=lambda a: np.mean(choice_rewards[a]))