
    Given a grid of delivery zones where each cell represents the packages delivered per hour across different time slots and areas, determine if the workload distribution is perfectly balanced by checking if the sum of packages in each row, column, and diagonal is equal. The balanced distribution would mean each route and time slot handles an equal load, optimizing fleet efficiency and delivery times.
    

    
def magic_square_test(my_matrix):
    """
    Given a grid of delivery zones where each cell represents the packages delivered per hour across different time slots and areas, determine if the workload distribution is perfectly balanced by checking if the sum of packages in each row, column, and diagonal is equal. The balanced distribution would mean each route and time slot handles an equal load, optimizing fleet efficiency and delivery times.
    

    """
def magic_square_test(my_matrix):
    """
    Given a grid of delivery zones where each cell represents the packages delivered per hour across different time slots and areas, determine if the workload distribution is perfectly balanced by checking if the sum of packages in each row, column, and diagonal is equal. The balanced distribution would mean each route and time slot handles an equal load, optimizing fleet efficiency and delivery times.
    

    """
    iSize = len(my_matrix[0])
    sum_list = []
    sum_list.extend([sum(lines) for lines in my_matrix])
    for col in range(iSize):
        sum_list.append(sum((row[col] for row in my_matrix)))
    result1 = 0
    for i in range(0, iSize):
        result1 += my_matrix[i][i]
    sum_list.append(result1)
    result2 = 0
    for i in range(iSize - 1, -1, -1):
        result2 += my_matrix[i][i]
    sum_list.append(result2)
    if len(set(sum_list)) > 1:
        return False
    return True