基于python模拟bfs和dfs代码实例
BFS
"""
#@Time:2020/11/8
#@Author:JimouChen
"""
#广搜
defbfs(graph,start):
queue=[start]#先把起点入队列
visited=set()#访问国的点加入
visited.add(start)
whilelen(queue):
vertex=queue.pop(0)
#找到队列首元素的连接点
forvingraph[vertex]:
ifvnotinvisited:
queue.append(v)
visited.add(v)
#打印弹出队列的该头元素
print(vertex,end='')
if__name__=='__main__':
graph={
'A':['B','D','I'],
'B':['A','F'],
'C':['D','E','I'],
'D':['A','C','F'],
'E':['C','H'],
'F':['B','H'],
'G':['C','H'],
'H':['E','F','G'],
'I':['A','C']
}
bfs(graph,'A')
ABDIFCHEG
Processfinishedwithexitcode0
DFS
"""
#@Time:2020/11/8
#@Author:JimouChen
"""
#深搜
defdfs(graph,start):
stack=[start]
visited=set()
visited.add(start)
whilelen(stack):
vertex=stack.pop()#找到栈顶元素
forvingraph[vertex]:
ifvnotinvisited:
stack.append(v)
visited.add(v)
print(vertex,end='')
if__name__=='__main__':
graph={
'A':['B','D','I'],
'B':['A','F'],
'C':['D','E','I'],
'D':['A','C','F'],
'E':['C','H'],
'F':['B','H'],
'G':['C','H'],
'H':['E','F','G'],
'I':['A','C']
}
dfs(graph,'E')
EHGFBAIDC
Processfinishedwithexitcode0
总结
很明显一个用了队列，一个用了栈
利用python语言优势，只需改动pop即可
以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持毛票票。
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