我一直在尝试为流行的凯文培根游戏创建一个图形表示 . 我已经创建了图形和顶点类，但是在创建宽度第一搜索方法来遍历图形并找到从凯文培根到演员的最短路径时遇到了一些麻烦，并在路上打印出边缘 . 用户应该输入一个演员，程序应该找到从凯文培根到该演员的最短路径 . 然后用户将继续进入演员，并且将获取到该演员的最短路径，并打印出凯文培根数字，否则它将打印出来 .

有一个顶点和图表类 . 顶点类是一个字典，它包含它连接到的其他顶点和边 .

我正在使用的数据如下所示：

顶点：

[“凯文培根”，“演员1”，“演员2”，“演员3”，“演员4”，“演员5”，“演员6”]

边：

(“凯文培根”，“演员1”，“movie1”)

(“凯文培根”，“演员2”，“movie1”)

(“actor1”，“actor2”，“movie1”)

(“actor1”，“actor3”，“movie2”)

(“actor3”，“actor2”，“movie3”)

(“actor3”，“actor4”，“movie4”)

(“actor5”，“actor6”，“movie5”)

电影是边缘名称或权重，而元组的其他部分是顶点 . 我希望BFS算法打印出所有边缘和凯文培根数字，或打印出如果无法到达演员则不可能 .

这是迄今为止的代码 . 任何建议和帮助表示赞赏 .

感谢您的时间

class Vertex:

'''

keep track of the vertices to which it is connected, and the weight of each edge

'''

def __init__(self, key):

'''

'''

self.ID = key

self.connected_to = {}

def add_neighbor(self, neighbor, weight=0):

'''

add a connection from this vertex to anothe

'''

self.connected_to[neighbor] = weight

def __str__(self):

'''

returns all of the vertices in the adjacency list, as represented by the connectedTo instance variable

'''

return str(self.ID) + ' connected to: ' + str([x.ID for x in self.connected_to])

def get_connections(self):

'''

returns all of the connections for each of the keys

'''

return self.connected_to.keys()

def get_ID(self):

'''

returns the current key id

'''

return self.ID

def get_weight(self, neighbor):

'''

returns the weight of the edge from this vertex to the vertex passed as a parameter

'''

return self.connected_to[neighbor]

class Graph:

'''

contains a dictionary that maps vertex names to vertex objects.

'''

def __init__(self):

'''

'''

self.vert_list = {}

self.num_vertices = 0

def __str__(self):

'''

'''

edges = ""

for vert in self.vert_list.values():

for vert2 in vert.get_connections():

edges += "(%s, %s)\n" %(vert.get_ID(), vert2.get_ID())

return edges

def add_vertex(self, key):

'''

adding vertices to a graph

'''

self.num_vertices = self.num_vertices + 1

new_vertex = Vertex(key)

self.vert_list[key] = new_vertex

return new_vertex

def get_vertex(self, n):

'''

'''

if n in self.vert_list:

return self.vert_list[n]

else:

return None

def __contains__(self, n):

'''

in operator

'''

return n in self.vert_list

def add_edge(self, f, t, cost=0):

'''

connecting one vertex to another

'''

if f not in self.vert_list:

nv = self.add_vertex(f)

if t not in self.vert_list:

nv = self.add_vertex(t)

self.vert_list[f].add_neighbor(self.vert_list[t], cost)

def get_vertices(self):

'''

returns the names of all of the vertices in the graph

'''

return self.vert_list.keys()

def __iter__(self):

'''

for functionality

'''

return iter(self.vert_list.values())

def bfs(self):

'''

Needs to be implemented

'''

pass