图的广度优先遍历算法实现

以下是图的广度优先遍历算法实现的Python代码：

from collections import deque

# 定义图类
class Graph:
    def __init__(self, graph_dict=None):
        if graph_dict is None:
            graph_dict = {}
        self.__graph_dict = graph_dict

    # 添加节点
    def add_node(self, node):
        if node not in self.__graph_dict:
            self.__graph_dict[node] = []

    # 添加边
    def add_edge(self, edge):
        edge = set(edge)
        (node1, node2) = tuple(edge)
        if node1 in self.__graph_dict:
            self.__graph_dict[node1].append(node2)
        else:
            self.__graph_dict[node1] = [node2]

    # 广度优先遍历
    def bfs(self, start_node):
        visited = [start_node]
        queue = deque([start_node])
        while queue:
            node = queue.popleft()
            for neighbor in self.__graph_dict[node]:
                if neighbor not in visited:
                    visited.append(neighbor)
                    queue.append(neighbor)
        return visited

# 创建图实例
graph = Graph()

# 添加节点
graph.add_node('A')
graph.add_node('B')
graph.add_node('C')
graph.add_node('D')
graph.add_node('E')

# 添加边
graph.add_edge(('A', 'B'))
graph.add_edge(('B', 'C'))
graph.add_edge(('B', 'D'))
graph.add_edge(('D', 'E'))

# 广度优先遍历
print(graph.bfs('A')) # 输出：['A', 'B', 'C', 'D', 'E']