圖的常用算法的 python 實現—鄰接表表示法

#圖的鄰接鏈表表示法
graph = {'A': ['B', 'C'],
             'B': ['C', 'D'],
             'C': ['D'],
             'D': ['C','G','H'],
             'E': ['F'],
             'F': ['C']}

#從圖中找出任意一條從起始頂點到終止頂點的路徑
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)


#從圖中找出從起始頂點到終止頂點的所有路徑
import copy

def find_path_all(curr, end, path):
    '''
    :param curr: 當前頂點
    :param end: 要到達的頂點
    :param path: 當前頂點的一條父路徑
    :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]:
        #一個頂點在當前遞歸路徑中只能出現一次，否則會陷入死循環。
        if v in path:
            print("v %s in path %s" %(v, path))
            continue
        #構造下次遞歸的父路徑
        path.append(v)
        find_path_all(v,end,path)
        path.pop()

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


#遍歷圖中所有頂點，按照遍歷順序將頂點添加到列表中
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)