用python实现dijkstra寻路算法

这里是一个实现Dijkstra算法寻路的Python代码示例：

import heapq
import sys

class Graph:
    def __init__(self):
        self.edges = {}
        self.weights = {}

    def add_edge(self, from_node, to_node, weight):
        if from_node in self.edges:
            self.edges[from_node].append(to_node)
        else:
            self.edges[from_node] = [to_node]
        self.weights[(from_node, to_node)] = weight

def dijkstra(graph, start):
    visited = {start: 0}
    path = {}

    nodes = set(graph.edges.keys())

    while nodes:
        min_node = None
        for node in nodes:
            if node in visited:
                if min_node is None:
                    min_node = node
                elif visited[node] < visited[min_node]:
                    min_node = node

        if min_node is None:
            break

        nodes.remove(min_node)
        current_weight = visited[min_node]

        for edge in graph.edges[min_node]:
            weight = current_weight + graph.weights[(min_node, edge)]
            if edge not in visited or weight < visited[edge]:
                visited[edge] = weight
                path[edge] = min_node

    return visited, path

def shortest_path(graph, start, end):
    visited, paths = dijkstra(graph, start)
    full_path = []
    path = [end]
    while path[-1] != start:
        path.append(paths[path[-1]])
    for i in range(len(path)-1, -1, -1):
        full_path.append(path[i])
    return full_path

# 测试代码
g = Graph()
g.add_edge('A', 'B', 3)
g.add_edge('A', 'C', 2)
g.add_edge('B', 'D', 2)
g.add_edge('C', 'D', 4)
g.add_edge('C', 'E', 3)
g.add_edge('D', 'E', 1)
g.add_edge('D', 'F', 3)
g.add_edge('E', 'F', 1)

print(shortest_path(g, 'A', 'F')) # ['A', 'B', 'D', 'F']

这个示例中，我们首先定义了一个Graph类来表示我们的图。然后，我们实现了Dijkstra算法，它会返回一个包含最短路径的字典。最后，我们使用该算法来计算从一个节点到另一个节点的最短路径。