From 225f66a4909f63e309af36cd73f6054514acff6c Mon Sep 17 00:00:00 2001 From: WJY-1123 <1229483859@qq.com> Date: Tue, 30 Jun 2026 19:55:10 +0800 Subject: [PATCH] house_service3.0.py --- house_operation最终版本.py | 77 ++++++ house_service最终版.py | 466 +++++++++++++++++++++++++++++++++++++ main最终版.py | 287 +++++++++++++++++++++++ 3 files changed, 830 insertions(+) create mode 100644 house_operation最终版本.py create mode 100644 house_service最终版.py create mode 100644 main最终版.py diff --git a/house_operation最终版本.py b/house_operation最终版本.py new file mode 100644 index 0000000..3cc7734 --- /dev/null +++ b/house_operation最终版本.py @@ -0,0 +1,77 @@ +import json +import os + +#v1 +HOUSE_FILE = "./data/houses.json" + +def init_db(): + """初始化房源数据文件""" + os.makedirs("./data", exist_ok=True) + if not os.path.exists(HOUSE_FILE): + with open(HOUSE_FILE, 'w', encoding='utf-8') as f: + json.dump([], f, ensure_ascii=False, indent=4) + +def read_houses(): + """读取所有房源""" + init_db() + with open(HOUSE_FILE, 'r', encoding='utf-8') as f: + return json.load(f) + +def write_houses(houses): + """写入房源""" + with open(HOUSE_FILE, 'w', encoding='utf-8') as f: + json.dump(houses, f, ensure_ascii=False, indent=4) + +#v2 +STACK_FILE = "./data/stack_data.json" + +def init_stack_db(): + """初始化栈文件""" + os.makedirs("./data", exist_ok=True) + if not os.path.exists(STACK_FILE): + init_data = {"operation_stack": [], "browse_stack": []} + with open(STACK_FILE, 'w', encoding='utf-8') as f: + json.dump(init_data, f, ensure_ascii=False, indent=4) + +def read_stack(stack_type): + """读取指定栈""" + init_stack_db() + with open(STACK_FILE, 'r', encoding='utf-8') as f: + data = json.load(f) + return data.get(f"{stack_type}_stack", []) + +def write_stack(stack_type, new_stack): + """写入指定栈""" + init_stack_db() + with open(STACK_FILE, 'r', encoding='utf-8') as f: + data = json.load(f) + data[f"{stack_type}_stack"] = new_stack + with open(STACK_FILE, 'w', encoding='utf-8') as f: + json.dump(data, f, ensure_ascii=False, indent=4) + +# v3 +MATRIX_FILE = "./data/matrix.json" + +def init_matrix_db(): + """初始化小区邻接矩阵文件""" + os.makedirs("./data", exist_ok=True) + if not os.path.exists(MATRIX_FILE): + init_data = { + "community_list": [], # 小区名称列表(一维数组) + "distance_matrix": [] # 小区距离二维数组(邻接矩阵) + } + with open(MATRIX_FILE, 'w', encoding='utf-8') as f: + json.dump(init_data, f, ensure_ascii=False, indent=4) + +def read_matrix_data(): + """读取小区列表和距离邻接矩阵""" + init_matrix_db() + with open(MATRIX_FILE, 'r', encoding='utf-8') as f: + return json.load(f) + +def write_matrix_data(matrix_dict): + """保存小区列表和距离邻接矩阵""" + init_matrix_db() + with open(MATRIX_FILE, 'w', encoding='utf-8') as f: + json.dump(matrix_dict, f, ensure_ascii=False, indent=4) + diff --git a/house_service最终版.py b/house_service最终版.py new file mode 100644 index 0000000..29abab6 --- /dev/null +++ b/house_service最终版.py @@ -0,0 +1,466 @@ +from house_operation import * +from datetime import datetime + + +# v1 +def get_next_house_id(): + houses = read_houses() + if not houses: + return 1 + max_id = max(house["id"] for house in houses) + return max_id + 1 + + +def add_house(address, price, area, house_type): + if not address or not house_type: + print("错误:地址和户型不能为空!") + return False + if not isinstance(price, (int, float)) or price <= 0: + print("错误:租金必须是正数!") + return False + if not isinstance(area, (int, float)) or area <= 0: + print("错误:面积必须是正数!") + return False + + new_house = { + "id": get_next_house_id(), + "address": address, + "price": price, + "area": area, + "house_type": house_type + } + houses = read_houses() + houses.append(new_house) + write_houses(houses) + print(f"房源新增成功!房源ID:{new_house['id']}") + return True + + +def delete_house(house_id): + houses = read_houses() + for index, house in enumerate(houses): + if house["id"] == house_id: + del houses[index] + write_houses(houses) + print(f"房源ID {house_id} 删除成功!") + return True + print(f"错误:未找到房源ID {house_id}!") + return False + + +def update_house(house_id, new_info): + houses = read_houses() + for house in houses: + if house["id"] == house_id: + for key, value in new_info.items(): + if key in ["address", "price", "area", "house_type"]: + if key in ["price", "area"]: + if not isinstance(value, (int, float)) or value <= 0: + print(f"错误:{key}必须是正数!") + return False + house[key] = value + write_houses(houses) + print(f"房源ID {house_id} 修改成功!") + return True + print(f"错误:未找到房源ID {house_id}!") + return False + + +def query_house(condition_type, condition_value): + houses = read_houses() + result = [] + for house in houses: + if condition_type == "id": + if house["id"] == int(condition_value): + result.append(house) + elif condition_type == "address": + if condition_value in house["address"]: + result.append(house) + elif condition_type == "house_type": + if house["house_type"] == condition_value: + result.append(house) + elif condition_type == "price": + if house["price"] == float(condition_value): + result.append(house) + else: + print("错误:不支持的查询条件类型!") + return [] + return result + + +# v2 +MAX_STACK_LENGTH = 100 + + +def push_operation_stack(operation_info): + time_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S") + full_info = f"[{time_str}] {operation_info}" + stack = read_stack("operation") + stack.append(full_info) + if len(stack) > MAX_STACK_LENGTH: + stack.pop(0) + write_stack("operation", stack) + + +def push_browse_stack(house_id): + stack = read_stack("browse") + if stack and stack[-1] == house_id: + return + stack.append(house_id) + if len(stack) > MAX_STACK_LENGTH: + stack.pop(0) + write_stack("browse", stack) + + +def pop_operation_stack(): + stack = read_stack("operation") + if not stack: + return None + latest_op = stack.pop() + write_stack("operation", stack) + return latest_op + + +def pop_browse_stack(): + stack = read_stack("browse") + if not stack: + return None + latest_hid = stack.pop() + write_stack("browse", stack) + return latest_hid + + +def get_recent_records(stack_type, limit=10): + stack = read_stack(stack_type) + return stack[-limit:][::-1] + + +def clear_stack(stack_type): + write_stack(stack_type, []) + print(f"{stack_type}记录已清空!") + + +#v3 +def parse_address_string(full_address): + """解析完整地址字符串:拆分省、市、区、小区""" + parts = full_address.split("市") + province_city = parts[0] + "市" if "市" in full_address else parts[0] + if "省" in province_city: + province, city = province_city.split("省") + province += "省" + city += "市" + else: + province = "未知省份" + city = province_city + + if len(parts) > 1: + district_part = parts[1] + if "区" in district_part or "县" in district_part: + district, community = district_part.split("区") if "区" in district_part else district_part.split("县") + district += "区" if "区" in district_part else "县" + else: + district = "未知区县" + community = district_part + else: + district = "未知区县" + community = "未知小区" + + return { + "province": province, + "city": city, + "district": district, + "community": community + } + + +def fuzzy_query_by_district(keyword): + """根据区域关键词模糊匹配所有房源""" + houses = read_houses() + result = [] + for house in houses: + addr_info = parse_address_string(house["address"]) + if keyword in addr_info["district"] or keyword in addr_info["community"]: + result.append(house) + return result + + +def init_community_matrix(community_name_list): + """初始化小区距离邻接矩阵""" + INF = float("inf") + n = len(community_name_list) + distance_matrix = [[INF] * n for _ in range(n)] + for i in range(n): + distance_matrix[i][i] = 0 + + matrix_data = { + "community_list": community_name_list, + "distance_matrix": distance_matrix + } + write_matrix_data(matrix_data) + print("邻接矩阵初始化完成!") + + +def update_matrix_distance(community_a, community_b, distance): + """更新两个小区之间的距离""" + matrix_data = read_matrix_data() + community_list = matrix_data["community_list"] + distance_matrix = matrix_data["distance_matrix"] + + try: + idx_a = community_list.index(community_a) + idx_b = community_list.index(community_b) + distance_matrix[idx_a][idx_b] = distance + distance_matrix[idx_b][idx_a] = distance + write_matrix_data(matrix_data) + print(f"{community_a} <-> {community_b} 距离更新成功!") + except ValueError: + print("小区名称不存在!") +#v4 +class HouseBSTNode: + """ + 二叉查找树节点:按指定字段(租金/面积)作为键值 + """ + + def __init__(self, house_data, key_field="price"): + self.key = house_data[key_field] # 排序键(租金/面积) + self.house = house_data # 房源完整数据 + self.left = None # 左子节点(键值更小) + self.right = None # 右子节点(键值更大) + + +# V4.0 新增:二叉查找树核心操作 +def build_house_bst(houses, key_field="price"): + """ + 构建房源二叉查找树(按租金/面积) + 时间复杂度:O(n log n)(最优/平均),O(n²)(最坏,有序数据) + """ + if not houses: + return None + # 选第一个元素作为根节点 + root = HouseBSTNode(houses[0], key_field) + # 逐个插入剩余节点 + for house in houses[1:]: + insert_bst_node(root, house, key_field) + return root + + +def insert_bst_node(root, house_data, key_field="price"): + """ + 向二叉查找树插入节点 + 时间复杂度:O(log n)(平均),O(n)(最坏) + """ + current = root + while True: + # 键值小于当前节点,走左子树 + if house_data[key_field] < current.key: + if current.left is None: + current.left = HouseBSTNode(house_data, key_field) + break + else: + current = current.left + # 键值大于等于当前节点,走右子树 + else: + if current.right is None: + current.right = HouseBSTNode(house_data, key_field) + break + else: + current = current.right + + +def inorder_bst_traversal(root, result_list): + """ + 二叉查找树中序遍历(输出有序列表) + 时间复杂度:O(n)(遍历所有节点) + """ + if root is not None: + inorder_bst_traversal(root.left, result_list) + result_list.append(root.house) + inorder_bst_traversal(root.right, result_list) + + +def search_bst_range(root, min_val, max_val, key_field="price", result_list=None): + """ + 二叉查找树范围查询(如:租金5000-8000) + 时间复杂度:O(log n + k)(k为符合条件的节点数) + """ + if result_list is None: + result_list = [] + if root is None: + return result_list + + # 若当前键值大于最小值,遍历左子树 + if root.key > min_val: + search_bst_range(root.left, min_val, max_val, key_field, result_list) + # 若当前键值在范围内,加入结果 + if min_val <= root.key <= max_val: + result_list.append(root.house) + # 若当前键值小于最大值,遍历右子树 + if root.key < max_val: + search_bst_range(root.right, min_val, max_val, key_field, result_list) + return result_list + +def bubble_sort_houses(houses, sort_field="price", reverse=False): + """ + V4.0新增 排序知识点 + 冒泡排序:按指定字段(租金/面积)排序 + 时间复杂度:O(n²)(稳定排序) + """ + n = len(houses) + # 深拷贝避免修改原列表 + sorted_houses = [h.copy() for h in houses] + for i in range(n): + swapped = False + for j in range(0, n - i - 1): + if sorted_houses[j][sort_field] > sorted_houses[j + 1][sort_field]: + # 交换元素 + sorted_houses[j], sorted_houses[j + 1] = sorted_houses[j + 1], sorted_houses[j] + swapped = True + # 无交换则提前退出 + if not swapped: + break + # 降序反转 + if reverse: + sorted_houses = sorted_houses[::-1] + return sorted_houses + + +def quick_sort_houses(houses, sort_field="price", reverse=False): + """ + V4新增 排序知识点 + 快速排序:按指定字段(租金/面积)排序 + 时间复杂度:O(n log n)(平均),O(n²)(最坏) + """ + if len(houses) <= 1: + return houses + # 深拷贝避免修改原列表 + sorted_houses = [h.copy() for h in houses] + # 选第一个元素作为基准 + pivot = sorted_houses[0][sort_field] + left = [h for h in sorted_houses[1:] if h[sort_field] <= pivot] + right = [h for h in sorted_houses[1:] if h[sort_field] > pivot] + # 递归排序 + result = quick_sort_houses(left, sort_field) + [sorted_houses[0]] + quick_sort_houses(right, sort_field) + # 降序反转 + if reverse: + result = result[::-1] + return result + +#V5 +def print_community_graph(): + """ + 文本形式可视化小区图(邻接矩阵) + 时间复杂度:O(n²),n为小区数量 + """ + matrix_data = read_matrix_data() + community_list = matrix_data["community_list"] + distance_matrix = matrix_data["distance_matrix"] + + if not community_list: + print("暂无小区图数据!请先初始化邻接矩阵。") + return + + # 打印表头 + print("\n===== 小区距离图(邻接矩阵) =====") + print(" " + " ".join([c[:4].ljust(4) for c in community_list])) + # 打印每行数据 + for i, community in enumerate(community_list): + row_str = community[:4].ljust(4) + for j in range(len(community_list)): + val = distance_matrix[i][j] + if val == float("inf"): + row_str += " ∞ " + else: + row_str += f"{val:5.1f}" + print(row_str) + + +def dijkstra_shortest_path(start_community, end_community): + """ + Dijkstra算法:计算两个小区间的最短路径 + 时间复杂度:O(n²)(邻接矩阵实现),n为小区数量 + return: (最短距离, 路径列表) + """ + matrix_data = read_matrix_data() + community_list = matrix_data["community_list"] + distance_matrix = matrix_data["distance_matrix"] + + # 校验小区是否存在 + if start_community not in community_list or end_community not in community_list: + print("起始/目标小区不存在!") + return (None, None) + + n = len(community_list) + start_idx = community_list.index(start_community) + end_idx = community_list.index(end_community) + + # 初始化距离数组和前驱节点数组 + INF = float("inf") + dist = [INF] * n # 各节点到起点的距离 + visited = [False] * n # 节点是否已访问 + prev = [-1] * n # 前驱节点索引 + + dist[start_idx] = 0 # 起点到自己的距离为0 + + # 核心Dijkstra循环 + for _ in range(n): + # 找到未访问的距离最小节点 + min_dist = INF + u = -1 + for i in range(n): + if not visited[i] and dist[i] < min_dist: + min_dist = dist[i] + u = i + + if u == -1 or dist[u] == INF: + break # 无可达路径 + visited[u] = True + + # 松弛操作:更新邻接节点的距离 + for v in range(n): + if not visited[v] and distance_matrix[u][v] != INF: + if dist[v] > dist[u] + distance_matrix[u][v]: + dist[v] = dist[u] + distance_matrix[u][v] + prev[v] = u + + # 回溯路径 + if dist[end_idx] == INF: + print(f"{start_community} 到 {end_community} 无可达路径!") + return (None, None) + + # 从终点回溯到起点 + path = [] + current = end_idx + while current != -1: + path.append(community_list[current]) + current = prev[current] + path.reverse() # 反转得到正序路径 + + return (dist[end_idx], path) + + +def recommend_houses_by_path(target_community, max_distance): + """ + 推荐目标小区最短距离≤max_distance的周边房源 + """ + matrix_data = read_matrix_data() + community_list = matrix_data["community_list"] + if target_community not in community_list: + print("目标小区不存在!") + return [] + + # 计算目标小区到所有小区的最短路径 + recommend_communities = [] + for comm in community_list: + dist, _ = dijkstra_shortest_path(target_community, comm) + if dist is not None and dist <= max_distance: + recommend_communities.append(comm) + + # 查询这些小区的房源 + all_houses = read_houses() + recommend_houses = [] + for house in all_houses: + addr_info = parse_address_string(house["address"]) + if addr_info["community"] in recommend_communities: + recommend_houses.append(house) + + return recommend_houses \ No newline at end of file diff --git a/main最终版.py b/main最终版.py new file mode 100644 index 0000000..9081a5e --- /dev/null +++ b/main最终版.py @@ -0,0 +1,287 @@ +from house_service import * + +def print_menu(): + print("\n===== 房屋出租系统 V5.0 =====") + print("1. 新增房源") + print("2. 删除房源") + print("3. 修改房源") + print("4. 查询房源") + print("5. 查看/管理操作记录") + print("6. 查看/管理浏览历史") + print("7. 地址字符串解析测试") + print("8. 按区域关键词模糊查询") + print("9. 初始化小区邻接矩阵") + print("10. 更新小区间距离") + print("11. 房源二叉树范围查询(租金/面积)") + print("12. 房源冒泡排序(租金/面积)") + print("13. 房源快速排序(租金/面积)") + #V5.0 新增菜单 + print("14. 可视化小区距离图(邻接矩阵)") + print("15. 计算小区间最短路径(Dijkstra)") + print("16. 基于最短路径推荐房源") + print("17. 退出系统") + print("============================") + + +# V2原有操作记录子菜单 +def op_record_menu(): + while True: + print("\n----- 操作记录管理 -----") + print("1. 查看最近10条") + print("2. 取出最新一条") + print("3. 清空记录") + print("4. 返回") + c = input("请选择:") + if c == "1": + lst = get_recent_records("operation", 10) + print(lst if lst else "暂无记录") + elif c == "2": + print(pop_operation_stack() or "暂无记录") + elif c == "3": + clear_stack("operation") + elif c == "4": + break + else: + print("输入有误") + + +# V2浏览历史子菜单 +def browse_history_menu(): + while True: + print("\n----- 浏览历史管理 -----") + print("1. 查看最近10条") + print("2. 取出最新一条") + print("3. 清空历史") + print("4. 返回") + c = input("请选择:") + if c == "1": + id_list = get_recent_records("browse", 10) + if not id_list: + print("暂无浏览历史") + continue + for idx, hid in enumerate(id_list, 1): + info = query_house("id", hid) + if info: + h = info[0] + print(f"{idx}. ID:{hid} 地址:{h['address']}") + else: + print(f"{idx}. ID:{hid} 房源已不存在") + elif c == "2": + hid = pop_browse_stack() + if not hid: + print("暂无浏览历史") + continue + info = query_house("id", hid) + print(f"最近浏览ID:{hid}") + elif c == "3": + clear_stack("browse") + elif c == "4": + break + else: + print("输入有误") + +def main(): + while True: + print_menu() + choice = input("请输入功能编号:") + + # ========== V1 原有功能========== + if choice == "1": + addr = input("输入房源地址:") + try: + price = float(input("输入月租金:")) + area = float(input("输入面积:")) + except: + print("租金面积必须是数字!") + continue + htype = input("输入户型:") + if add_house(addr, price, area, htype): + new_id = get_next_house_id() - 1 + push_operation_stack(f"新增房源ID:{new_id} 地址:{addr}") + + elif choice == "2": + try: + hid = int(input("输入要删除房源ID:")) + res = query_house("id", hid) + addr = res[0]["address"] if res else "未知地址" + if delete_house(hid): + push_operation_stack(f"删除房源ID:{hid} 地址:{addr}") + except: + print("ID必须是整数") + + elif choice == "3": + try: + hid = int(input("输入要修改房源ID:")) + edit = {} + a = input("新地址(回车不修改):") + if a: edit["address"] = a + p = input("新租金(回车不修改):") + if p: edit["price"] = float(p) + ar = input("新面积(回车不修改):") + if ar: edit["area"] = float(ar) + t = input("新户型(回车不修改):") + if t: edit["house_type"] = t + if edit: + if update_house(hid, edit): + push_operation_stack(f"修改房源ID:{hid} 变更:{edit}") + else: + print("未填写任何修改内容") + except: + print("输入格式错误") + + elif choice == "4": + print("1-ID 2-地址 3-租金 4-户型") + sel = input("选择查询类型:") + map_dic = {"1": "id", "2": "address", "3": "price", "4": "house_type"} + if sel not in map_dic: + print("选择无效") + continue + val = input("输入查询值:") + res_list = query_house(map_dic[sel], val) + if not res_list: + print("未找到房源") + continue + for h in res_list: + print(f"ID:{h['id']} 地址:{h['address']} 租金:{h['price']}") + if map_dic[sel] == "id": + push_browse_stack(h["id"]) + + # ========== V2 原有功能 ========== + elif choice == "5": + op_record_menu() + elif choice == "6": + browse_history_menu() + + # ========== V3 原有功能========== + elif choice == "7": + full_addr = input("输入完整地址(如:四川省德阳市什邡市XX小区):") + res = parse_address_string(full_addr) + print("解析结果:", res) + + elif choice == "8": + keyword = input("输入区域关键词(如:什邡、德阳):") + res_list = fuzzy_query_by_district(keyword) + if not res_list: + print("未找到该区域房源") + else: + for h in res_list: + print(f"ID:{h['id']} 地址:{h['address']}") + + elif choice == "9": + community_input = input("输入所有小区名称,用英文逗号分隔:") + community_list = community_input.split(",") + init_community_matrix(community_list) + + elif choice == "10": + c1 = input("输入小区A名称:") + c2 = input("输入小区B名称:") + try: + dis = float(input("输入两小区距离:")) + update_matrix_distance(c1, c2, dis) + except: + print("距离必须是数字") + + # ========== V4 原有功能========== + elif choice == "11": + print("请选择查询维度:1-租金 2-面积") + dim_choice = input("输入维度编号:") + key_field = "price" if dim_choice == "1" else "area" + field_name = "租金" if dim_choice == "1" else "面积" + + try: + min_val = float(input(f"输入{field_name}最小值:")) + max_val = float(input(f"输入{field_name}最大值:")) + except: + print("数值必须是数字!") + continue + + all_houses = read_houses() + if not all_houses: + print("暂无房源数据!") + continue + bst_root = build_house_bst(all_houses, key_field) + result = search_bst_range(bst_root, min_val, max_val, key_field) + if not result: + print(f"未找到{field_name}在{min_val}-{max_val}之间的房源") + else: + print(f"\n{field_name}在{min_val}-{max_val}之间的房源:") + for h in result: + print(f"ID:{h['id']} 地址:{h['address']} {field_name}:{h[key_field]}") + + elif choice == "12": + print("请选择排序维度:1-租金 2-面积") + dim_choice = input("输入维度编号:") + sort_field = "price" if dim_choice == "1" else "area" + field_name = "租金" if dim_choice == "1" else "面积" + + print("请选择排序方式:1-升序 2-降序") + sort_way = input("输入方式编号:") + reverse = (sort_way == "2") + + all_houses = read_houses() + if not all_houses: + print("暂无房源数据!") + continue + sorted_houses = bubble_sort_houses(all_houses, sort_field, reverse) + print(f"\n按{field_name}{'降序' if reverse else '升序'}排序结果(冒泡排序):") + for h in sorted_houses: + print(f"ID:{h['id']} 地址:{h['address']} {field_name}:{h[sort_field]}") + + elif choice == "13": + print("请选择排序维度:1-租金 2-面积") + dim_choice = input("输入维度编号:") + sort_field = "price" if dim_choice == "1" else "area" + field_name = "租金" if dim_choice == "1" else "面积" + + print("请选择排序方式:1-升序 2-降序") + sort_way = input("输入方式编号:") + reverse = (sort_way == "2") + + all_houses = read_houses() + if not all_houses: + print("暂无房源数据!") + continue + sorted_houses = quick_sort_houses(all_houses, sort_field, reverse) + print(f"\n按{field_name}{'降序' if reverse else '升序'}排序结果(快速排序):") + for h in sorted_houses: + print(f"ID:{h['id']} 地址:{h['address']} {field_name}:{h[sort_field]}") + + # ========== V5 新增功能分支 ========== + elif choice == "14": + # 可视化小区图 + print_community_graph() + + elif choice == "15": + # 计算最短路径 + start_comm = input("输入起始小区名称:") + end_comm = input("输入目标小区名称:") + shortest_dist, shortest_path = dijkstra_shortest_path(start_comm, end_comm) + if shortest_dist is not None: + print(f"\n{start_comm} 到 {end_comm} 的最短距离:{shortest_dist:.1f}") + print(f"最短路径:{' -> '.join(shortest_path)}") + + elif choice == "16": + # 基于路径推荐房源 + target_comm = input("输入目标小区名称:") + try: + max_dist = float(input("输入最大推荐距离:")) + except: + print("距离必须是数字!") + continue + recommend_list = recommend_houses_by_path(target_comm, max_dist) + if not recommend_list: + print(f"未找到{target_comm}周边{max_dist}范围内的房源") + else: + print(f"\n{target_comm}周边{max_dist}范围内的推荐房源:") + for h in recommend_list: + print(f"ID:{h['id']} 地址:{h['address']} 租金:{h['price']} 面积:{h['area']}") + + elif choice == "17": + print("系统退出成功!") + break + else: + print("请输入有效编号") + + +if __name__ == "__main__": + main() \ No newline at end of file