Question

我想就如何构建我的功能评论提出建议。我目前的描述是否过于深入？

以下代码用于解决n-queens问题的算法。

def hill_climbing(initial_board):
    """
    While the current Board object has lower heuristic value successors, neighbour is randomly assigned to one.
    If the current Board's heuristic value is less than or equal to its neighbour's, the current Board object is
    returned. Else, the current variable is assigned the neighbour Board object and the while loop continues until
    either the current Board has no better successors, or current's h value is less than or equal to all of its
    successors.

    :param initial_board: A Board object with a randomly generated state, and successor_type of "best".
                          i.e. a start state
    :return: A Board object that has no further successors. i.e. a goal state (Local/Global Minimum)
    """
    current = initial_board
    while current.has_successors():
        neighbour = Board(current.get_random_successor(), "best")
        if neighbour.value() >= current.value():
            return current
        current = neighbour
    return current

Answer 1

感谢Alexey的建议，我遵循了PEP，他们为评论提供了很好的指导。

https://www.python.org/dev/peps/pep-0008/

https://www.python.org/dev/peps/pep-0257/

我的结果评论：

def hill_climbing(initial_board):
""" Hill Climbing Algorithm.

Performs a hill climbing search on initial_board and returns a Board
object representing a goal state (local/global minimum).

Attributes:
    current: A Board object
    neighbour: A Board object that is a successor of current

:param initial_board: A Board object with a randomly generated state, and successor_type of "best".
                      i.e. a start state
:return: A Board object that has no further successors. i.e. a goal state (Local/Global Minimum)
"""

current = initial_board
while current.has_successors():
    neighbour = Board(current.get_random_successor(), "best")
    if neighbour.value() >= current.value():
        return current
    current = neighbour
return current

如何在Python中正确地评论函数

1 个答案: