图数据结构_广度优先搜索

图数据结构有两种经典的遍历方式: 广度优先搜索和深度优先搜索

这里以广度优先搜索为例

class Person:
    def __init__(self, name):
        self.name = name
        self.friends = []
        self.visited = False

    def add_friend(self, friend):
        self.friends.append(friend)

    def display_network(self):
        # 记下每个访问过的人, 以便算法完结后能重置他们的visited属性为false
        to_reset = [self]
        # 创建一个开始就含有根顶点的队列
        queue = [self]
        self.visited = True

        while len(queue):
            # 设出队的顶点为当前顶点
            current_vertex = queue.pop(0)
            print(current_vertex.name, end=' ')
            # 将当前顶点的所有未访问的邻接点加入队列
            for friend in current_vertex.friends:
                if not friend.visited:
                    to_reset.append(friend)
                    queue.append(friend)
                    friend.visited = True
            # 算法完结时，将访问过的结点的visited属性重置为false
        for node in to_reset:
            node.visited = False

if __name__ == '__main__':
    # 起步定点
    alice = Person('Alice')
    # 一度联系人
    bob = Person('Bob')
    candy = Person('Candy')
    derek = Person('Derek')
    elaine = Person('Elaine')
    # 二度联系人
    fred = Person('Fred')
    gina = Person('Gina')
    # 三度联系人
    helen = Person('Helen')
    irena = Person('Irena')

    alice.add_friend(bob)
    alice.add_friend(candy)
    alice.add_friend(derek)
    alice.add_friend(elaine)
    bob.add_friend(alice)
    bob.add_friend(fred)
    candy.add_friend(alice)
    derek.add_friend(alice)
    derek.add_friend(gina)
    elaine.add_friend(alice)
    fred.add_friend(bob)
    fred.add_friend(helen)
    gina.add_friend(derek)
    gina.add_friend(irena)
    helen.add_friend(fred)
    irena.add_friend(gina)

    alice.display_network()

# 打印结果：Alice Bob Candy Derek Elaine Fred Gina Helen Irena