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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 combine(items, k=None):
 """ Create a matrix in wich each row is a tuple containing one of solutions or solution k-esima. """

    length_items = len(items)
    lengths = [len(i) for i in items]
    length = reduce(lambda x, y: x * y, lengths)
    repeats = [reduce(lambda x, y: x * y, lengths[i:])
               for i in range(1, length_items)] + [1]
    if k is not None:
        k = k % length
        # Python division by default is integer division (~ floor(a/b))
        indices = [old_div((k % (lengths[i] * repeats[i])), repeats[i])
                   for i in range(length_items)]
        return [items[i][indices[i]] for i in range(length_items)]
    else:
        matrix = []
        for i, item in enumerate(items):
            row = []
            for subset in item:
                row.extend([subset] * repeats[i])
            times = old_div(length, len(row))
            matrix.append(row * times)
        # Transpose the matrix or return the columns instead rows
        return list(zip(*matrix))