BFS&DFS——Python实现

BFS ——队列

image-20210129115620630.png

步骤：1、首先A入队列，

2、A出队列时，A的邻接结点B，C相应进入队列

3、B出队列时，B的邻接结点A，C，D中未进过队列的D进入队列

4、C出队列时，C的邻接结点A，B，D，E中未进过队列的E进入队列

5、D出队列时，D的邻接结点B，C，E，F中未进过队列的F进入队列

6、E出队列，没有结点可再进队列

7、F出队列

graph=
{'A':['B','C'],'B':['A','C','D'],
'C':['A','B','D','E'],
'D':['B','C','E','F'],
'E':['D','C'],
'F':['D']}  

import queue
def BFS(graph, s):
    queue = []  #用数组表示队列
    queue.append(s)
    seen = set()  #存放已经遍历过的节点
    seen.add(s)
    while len(queue) > 0:
        vetex = queue.pop(0)  #区别：python中队列和栈都用数组表示，队列取队头pop(0)，弹栈为pop()
        nodes = graph[vetex]
        for w in nodes:
            if w not in seen:
                queue.append(w)
                seen.add(w)
        print(vetex)     
BFS(graph,"A")

DFS —— 栈

image-20210129120158011.png

步骤：1、首先A入栈，

​ 2、A出栈时，A的邻接结点B，C相应入栈 （这里假设C在下，B在上）

​ 3、B出栈时，B的邻接结点A，C，D中未进过栈的D入栈

​ 4、D出栈时，D的邻接结点B，C，E，F中未进过栈的E、F入栈（假设E在下，F在上）

​ 5、F出栈时，F没有邻接结点可入栈

​ 6、E出栈，E的邻接结点C，D已入过栈

​ 7、C出栈

def DFS(graph, s):
    stack = []
    stack.append(s)
    seen = set()
    seen.add(s)
    while len(stack) > 0:
        vetex = stack.pop()
        nodes = graph[vetex]
        for w in nodes:
            if w not in seen:
                stack.append(w)
                seen.add(w)
        print(vetex)