帮我用python写一个用邻接表储存的图的Dijkstra算法

以下是使用邻接表储存图的Dijkstra算法的Python代码：

import heapq


class Graph:
    def __init__(self):
        self.nodes = {}
        
    def add_node(self, node):
        self.nodes[node] = []
        
    def add_edge(self, node1, node2, distance):
        self.nodes[node1].append((node2, distance))
        self.nodes[node2].append((node1, distance))


def dijkstra_shortest_path(graph, start_node):
    heap = [(0, start_node)]
    visited = set()
    shortest_distance = {start_node: 0}
    
    while heap:
        (distance, current_node) = heapq.heappop(heap)
        if current_node in visited:
            continue
            
        visited.add(current_node)
        
        for (neighbor, edge_length) in graph.nodes[current_node]:
            if neighbor not in visited:
                new_distance = shortest_distance[current_node] + edge_length
                if new_distance < shortest_distance.get(neighbor, float('inf')):
                    shortest_distance[neighbor] = new_distance
                    heapq.heappush(heap, (new_distance, neighbor))
    
    return shortest_distance


# example usage

g = Graph()

g.add_node('A')
g.add_node('B')
g.add_node('C')
g.add_node('D')
g.add_node('E')

g.add_edge('A', 'B', 1)
g.add_edge('A', 'C', 4)
g.add_edge('B', 'C', 2)
g.add_edge('B', 'D', 5)
g.add_edge('C', 'D', 1)
g.add_edge('C', 'E', 6)
g.add_edge('D', 'E', 3)

shortest_distances = dijkstra_shortest_path(g, 'A')
print(shortest_distances)

对于给定的图，该代码将输出以下内容：

{'A': 0, 'B': 1, 'C': 3, 'D': 4, 'E': 7}

这表示从节点'A'出发，到达所有其他节点的最短距离分别为0、1、3、4和7。