python实现dijkstra最短路由算法

# dijkstra算法实现，有向图和路由的源点作为函数的输入，最短路径最为输出
def dijkstra(graph,src):
 # 判断图是否为空，如果为空直接退出
 if graph is None:
 return None
 nodes = [i for i in range(len(graph))] # 获取图中所有节点
 visited=[] # 表示已经路由到最短路径的节点集合
 if src in nodes:
 visited.append(src)
 nodes.remove(src)
 else:
 return None
 distance={src:0} # 记录源节点到各个节点的距离
 for i in nodes:
 distance[i]=graph[src][i] # 初始化
 # print(distance)
 path={src:{src:[]}} # 记录源节点到每个节点的路径
 k=pre=src
 while nodes:
 mid_distance=float('inf')
 for v in visited:
  for d in nodes:
  new_distance = graph[src][v]+graph[v][d]
  if new_distance < mid_distance:
   mid_distance=new_distance
   graph[src][d]=new_distance # 进行距离更新
   k=d
   pre=v
 distance[k]=mid_distance # 最短路径
 path[src][k]=[i for i in path[src][pre]]
 path[src][k].append(k)
 # 更新两个节点集合
 visited.append(k)
 nodes.remove(k)
 print(visited,nodes) # 输出节点的添加过程
 return distance,path
if __name__ == '__main__':
 graph_list = [ [0, 2, 1, 4, 5, 1],
  [1, 0, 4, 2, 3, 4],
  [2, 1, 0, 1, 2, 4],
  [3, 5, 2, 0, 3, 3],
  [2, 4, 3, 4, 0, 1],
  [3, 4, 7, 3, 1, 0]]

 distance,path= dijkstra(graph_list, 0) # 查找从源点0开始带其他节点的最短路径
 print(distance,path)