图的常用算法的 python 实现—邻接表表示法

#图的邻接链表表示法
graph = {'A': ['B', 'C'],
             'B': ['C', 'D'],
             'C': ['D'],
             'D': ['C','G','H'],
             'E': ['F'],
             'F': ['C']}

#从图中找出任意一条从起始顶点到终止顶点的路径
def find_path(graph, start, end, path=[]):
    if start == end:
        print "path", path
        return True
    if not graph.get(start):
        path.pop()
        return False
    for v in graph[start]:
        if v not in path:
            path.append(v)
            if find_path(graph,v,end,path):
                return True
    return False

path = []
if find_path(graph, 'A', 'C', path=path):
    print(path)
else:
    print(1)


#从图中找出从起始顶点到终止顶点的所有路径
import copy

def find_path_all(curr, end, path):
    '''
    :param curr: 当前顶点
    :param end: 要到达的顶点
    :param path: 当前顶点的一条父路径
    :return:
    '''
    if curr == end:
        path_tmp = copy.deepcopy(path)
        path_all.append(path_tmp)
        return
    if not graph.get(curr):
        return
    for v in graph[curr]:
        #一个顶点在当前递归路径中只能出现一次，否则会陷入死循环。
        if v in path:
            print("v %s in path %s" %(v, path))
            continue
        #构造下次递归的父路径
        path.append(v)
        find_path_all(v,end,path)
        path.pop()

path_all = []
find_path_all('A', 'G',path=['A'])
print path_all


#遍历图中所有顶点，按照遍历顺序将顶点添加到列表中
vertex = []
def dfs(v):
    if v not in graph:
        return
    for vv in graph[v]:
        if vv not in vertex:
            vertex.append(vv)
            dfs(vv)

for v in graph:
    if v not in vertex:
        vertex.append(v)
        dfs(v)
print(vertex)