深度优先搜索 搜索求解

def dfs(graph, start, end, visited=[], path=[]):
    visited.append(start)  # 将当前节点标记为已访问
    path.append(start)  # 将当前节点添加到路径中

    if start == end:  # 如果当前节点是终点，返回路径
        return path

    for neighbor in graph[start]:  # 遍历当前节点的邻居节点
        if neighbor not in visited:  # 如果邻居节点未被访问过
            new_path = dfs(graph, neighbor, end, visited, path)  # 递归调用深度优先搜索
            if new_path:  # 如果找到路径
                return new_path

    # 如果没有找到路径，将当前节点从路径中移除
    path.pop()

# 调用深度优先搜索算法，并打印结果
graph = { 'A': ['B', 'C'],
          'B': ['A', 'D', 'E'],
          'C': ['A', 'F'],
          'D': ['B'],
          'E': ['B', 'F'],
          'F': ['C', 'E', 'G'],
          'G': ['F'] }

start_point = 'A'
end_point = 'G'

path = dfs(graph, start_point, end_point)
print("从起点到终点的路径为:", path)

从起点到终点的路径为: ['A', 'B', 'D', 'E', 'F', 'G']