input: Write a function to create an algorithm in Python to determine the most efficient order of tasks from an array of given tasks. The function should take a list of tasks and produce the most efficient order for completing the tasks. If the list of tasks is empty, return an empty list.
  def most_efficient_order(tasks):
      """
      This method takes a list of tasks and produces the most efficient order for completing the tasks.
  
      Parameters
      ----------
      tasks: List
          A list of tasks to be performed.
  
      Returns
      -------
      List
          An ordered list of tasks representing the most efficient order for completing the tasks.
      """
      tasks_to_complete = tasks.copy()
      order = [] 
      while tasks_to_complete:
          min_time = float("inf")
          task_index = None
          for i, task in enumerate(tasks_to_complete):
              if task.get_time() < min_time:
                  min_time = task.get_time()
                  task_index = i
          order.append(tasks_to_complete.pop(task_index))
      return order
  assert most_efficient_order([])==[]
  assert most_efficient_order([Task("Task1", 5), Task("Task2", 3), Task("Task3", 2)])==[Task("Task3", 2), Task("Task2", 3), Task("Task1", 5)]
  assert most_efficient_order([Task("Task4", 1), Task("Task5", 4)])==[Task("Task4", 1), Task("Task5", 4)]
  assert most_efficient_order([Task("Task6", 6)])==[Task("Task6", 6)]
  assert most_efficient_order([Task("Task7", 7), Task("Task8", 9), Task("Task9", 8)])==[Task("Task7", 7), Task("Task9", 8), Task("Task8", 9)]
output: def most_efficient_order(tasks):
      tasks_to_complete = tasks.copy()
      order = [] 
      while tasks_to_complete:
          min_time = float("inf")
          task_index = None
          for i, task in enumerate(tasks_to_complete):
              if task.get_time() < min_time:
                  min_time = task.get_time()
                  task_index = i
          order.append(tasks_to_complete.pop(task_index))
      return order