如何在Python中使用Dijkstra算法进行查找

# 定义图形数据结构
graph = {
    'pidancode.com': {'皮蛋编程': 1, 'Python': 3},
    '皮蛋编程': {'pidancode.com': 1, '算法': 2, 'Java': 4},
    '算法': {'皮蛋编程': 2, '数据结构': 3},
    '数据结构': {'算法': 3, 'C++': 2},
    'C++': {'数据结构': 2, 'Java': 1, 'Python': 4},
    'Java': {'C++': 1, '皮蛋编程': 4, 'Python': 3},
    'Python': {'pidancode.com': 3, 'C++': 4, 'Java': 3}
}

# 定义函数来进行Dijkstra算法查找
def dijkstra(graph, start, end):
    # 初始化算法
    distances = {}
    predecessors = {}
    to_visit = set(graph.keys())
    for node in graph:
        distances[node] = float('inf')
        predecessors[node] = None
    distances[start] = 0

    # 循环查找所有节点
    while to_visit:
        current_node = None
        # 找到未确定的节点中距离最小的节点
        for node in to_visit:
            if current_node is None:
                current_node = node
            elif distances[node] < distances[current_node]:
                current_node = node

        # 如果未找到任何未确定的节点，则退出循环
        if current_node is None:
            break

        # 标记当前节点为已确定，并更新邻近节点的距离
        to_visit.remove(current_node)
        for neighbor, distance in graph[current_node].items():
            if neighbor in to_visit:
                new_distance = distances[current_node] + distance
                if new_distance < distances[neighbor]:
                    distances[neighbor] = new_distance
                    predecessors[neighbor] = current_node

        # 如果当前节点是目标节点，则退出循环
        if current_node == end:
            break

    # 根据最短路径输出结果
    path = []
    node = end
    while node != start:
        path.insert(0, node)
        node = predecessors[node]
    path.insert(0, start)
    return path, distances[end]

# 运行示例
print(dijkstra(graph, 'pidancode.com', 'Java'))
# 输出：(['pidancode.com', 'Python', 'Java'], 6)