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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(candidate):
 """Perform crossover action to candidates. For example, new gene = 60% sample_1 + 40% sample_2. Args: candidate: List of candidate genes (encodings). Examples: Returns: New gene (encoding) """

        sample_index1 = np.random.choice(len(candidate))
        sample_index2 = np.random.choice(len(candidate))
        sample_1 = candidate[sample_index1]
        sample_2 = candidate[sample_index2]
        cross_index = int(len(sample_1) * np.random.uniform(low=0.3, high=0.7))
        logger.info(
            LOGGING_PREFIX +
            "Perform crossover between %sth and %sth at index=%s",
            sample_index1, sample_index2, cross_index)

        next_gen = []
        for i in range(len(sample_1)):
            if i > cross_index:
                next_gen.append(sample_2[i])
            else:
                next_gen.append(sample_1[i])
        return next_gen