Python单源最短路径问题代码

Python中求解单源最短路径问题的常用算法是Dijkstra算法。下面是一个简单的Python代码示例：

import sys

# 定义一个图类
class Graph:
    def __init__(self, vertices):
        self.V = vertices
        self.graph = [[0 for _ in range(vertices)] for _ in range(vertices)]

    # 找到距离最小的节点
    def min_distance(self, dist, visited):
        min_dist = sys.maxsize
        min_index = -1
        for v in range(self.V):
            if dist[v] < min_dist and not visited[v]:
                min_dist = dist[v]
                min_index = v
        return min_index

    # 打印最短路径
    def print_solution(self, dist):
        print("节点\t距离")
        for node in range(self.V):
            print(node, "\t\t", dist[node])

    # 使用Dijkstra算法求解单源最短路径
    def dijkstra(self, src):
        dist = [sys.maxsize] * self.V  # 存储最短距离
        dist[src] = 0  # 源节点到自身的距离为0
        visited = [False] * self.V  # 记录节点是否已被访问

        for _ in range(self.V):
            u = self.min_distance(dist, visited)
            visited[u] = True

            for v in range(self.V):
                if (
                    self.graph[u][v] > 0
                    and not visited[v]
                    and dist[v] > dist[u] + self.graph[u][v]
                ):
                    dist[v] = dist[u] + self.graph[u][v]

        self.print_solution(dist)

# 示例代码
g = Graph(9)
g.graph = [
    [0, 4, 0, 0, 0, 0, 0, 8, 0],
    [4, 0, 8, 0, 0, 0, 0, 11, 0],
    [0, 8, 0, 7, 0, 4, 0, 0, 2],
    [0, 0, 7, 0, 9, 14, 0, 0, 0],
    [0, 0, 0, 9, 0, 10, 0, 0, 0],
    [0, 0, 4, 14, 10, 0, 2, 0, 0],
    [0, 0, 0, 0, 0, 2, 0, 1, 6],
    [8, 11, 0, 0, 0, 0, 1, 0, 7],
    [0, 0, 2, 0, 0, 0, 6, 7, 0],
]
g.dijkstra(0)

这段代码实现了一个Graph类，其中包含了Dijkstra算法的实现。首先定义了一个图的大小，然后通过二维数组`graph`表示图的邻接矩阵。在`dijkstra`方法中，通过遍历节点来计算源节点到其他节点的最短距离，并将结果存储在`dist`数组中。最后通过`print_solution`方法打印出最短路径的结果。