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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 crossover(self, donor, random_state):
 """Perform the crossover genetic operation on the program. Crossover selects a random subtree from the embedded program to be replaced. A donor also has a subtree selected at random and this is inserted into the original parent to form an offspring. Parameters donor : list The flattened tree representation of the donor program. random_state : RandomState instance The random number generator. Returns ------- program : list The flattened tree representation of the program. """

        # Get a subtree to replace
        start, end = self.get_subtree(random_state)
        removed = range(start, end)
        # Get a subtree to donate
        donor_start, donor_end = self.get_subtree(random_state, donor)
        donor_removed = list(set(range(len(donor))) -
                             set(range(donor_start, donor_end)))
        # Insert genetic material from donor
        return (self.program[:start] +
                donor[donor_start:donor_end] +
                self.program[end:]), removed, donor_removed