Merge remote-tracking branch 'origin/main'

Reviewed-on: http://idiot.asia/wjy/house/pulls/1

address_operation.py

@@ -0,0 +1,125 @@
+import json
+import os
+from house.house_operation import read_houses
+
+# 地址数据文件
+ADDRESS_FILE = "./data/address_info.json"
+# 邻接矩阵数据文件
+GRAPH_FILE = "./data/adj_matrix.json"
+
+
+def init_address_db():
+    """初始化地址解析数据文件"""
+    os.makedirs("./data", exist_ok=True)
+    if not os.exists(ADDRESS_FILE):
+        with open(ADDRESS_FILE, 'w', encoding='utf-8') as f:
+            json.dump({}, f, ensure_ascii=False, indent=4)
+
+
+def init_graph_db():
+    """初始化小区邻接矩阵文件"""
+    os.makedirs("./data", exist_ok=True)
+    if not os.path.exists(GRAPH_FILE):
+        init_data = {
+            "communities": [],
+            "adj_matrix": []
+        }
+        with open(GRAPH_FILE, 'w', encoding='utf-8') as f:
+            json.dump(init_data, f, ensure_ascii=False, indent=4)
+
+
+# ==================== 串操作：地址解析 ====================
+def parse_address(address_str):
+    """
+    串操作：拆分地址为 省/市/区/小区
+    时间复杂度：O(L) L为字符串长度
+    """
+    address_str = address_str.strip()
+    # 按常见分隔符拆分
+    split_chars = ["省", "市", "区", "县", "街道", "路", "号", "小区"]
+    parts = []
+    temp = address_str
+    for char in split_chars:
+        if char in temp:
+            idx = temp.find(char)
+            parts.append(temp[:idx + 1])
+            temp = temp[idx + 1:]
+    if temp:
+        parts.append(temp)
+
+    # 标准化结构
+    result = {
+        "province": parts[0] if len(parts) >= 1 else "",
+        "city": parts[1] if len(parts) >= 2 else "",
+        "district": parts[2] if len(parts) >= 3 else "",
+        "community": parts[3] if len(parts) >= 4 else parts[-1] if parts else ""
+    }
+    return result
+
+
+def save_address_info(house_id, address_info):
+    """保存解析后的地址信息"""
+    init_address_db()
+    with open(ADDRESS_FILE, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+    data[str(house_id)] = address_info
+    with open(ADDRESS_FILE, 'w', encoding='utf-8') as f:
+        json.dump(data, f, ensure_ascii=False, indent=4)
+
+
+def get_address_info(house_id):
+    """获取房源解析后的地址"""
+    init_address_db()
+    with open(ADDRESS_FILE, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+    return data.get(str(house_id), {})
+
+
+# ==================== 数组操作：邻接矩阵 ====================
+def add_community(community_name):
+    """添加小区到图节点（数组维护）"""
+    init_graph_db()
+    with open(GRAPH_FILE, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+
+    if community_name in data["communities"]:
+        return False
+
+    data["communities"].append(community_name)
+    n = len(data["communities"])
+    # 初始化新行新列（无穷大用 9999 表示）
+    for row in data["adj_matrix"]:
+        row.append(9999)
+    data["adj_matrix"].append([9999] * n)
+    # 自己到自己距离为0
+    data["adj_matrix"][-1][-1] = 0
+
+    with open(GRAPH_FILE, 'w', encoding='utf-8') as f:
+        json.dump(data, f, ensure_ascii=False, indent=4)
+    return True
+
+
+def set_distance(community1, community2, distance):
+    """设置两个小区之间的距离（邻接矩阵赋值）"""
+    init_graph_db()
+    with open(GRAPH_FILE, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+
+    if community1 not in data["communities"] or community2 not in data["communities"]:
+        return False
+
+    i = data["communities"].index(community1)
+    j = data["communities"].index(community2)
+    data["adj_matrix"][i][j] = distance
+    data["adj_matrix"][j][i] = distance
+
+    with open(GRAPH_FILE, 'w', encoding='utf-8') as f:
+        json.dump(data, f, ensure_ascii=False, indent=4)
+    return True
+
+
+def get_adj_matrix():
+    """获取邻接矩阵与小区列表"""
+    init_graph_db()
+    with open(GRAPH_FILE, 'r', encoding='utf-8') as f:
+        return json.load(f)

house-main3.0优化版.py

@@ -0,0 +1,259 @@
+from house_service import (
+    add_house, delete_house, update_house, query_house,
+    push_operation_stack, push_browse_stack,
+    pop_operation_stack, pop_browse_stack,
+    get_recent_records, clear_stack, get_next_house_id,
+    query_by_area, add_community_distance, show_adj_matrix
+)
+# 引入上一轮优化后的数据保存方法
+from house.house_operation import save_all_data
+
+
+def get_valid_input(prompt, cast_type=str):
+    """通用输入工具：自动处理类型转换异常，输入为空时返回 None"""
+    value = input(prompt).strip()
+    if not value:
+        return None
+    try:
+        return cast_type(value)
+    except ValueError:
+        print(f"错误：输入内容必须是有效的{cast_type.__name__}！")
+        return False
+
+
+def print_house(house):
+    """统一房源信息的打印格式"""
+    print(
+        f"ID：{house['id']} | 地址：{house['address']} | 租金：{house['price']}元/月 | 面积：{house['area']}㎡ | 户型：{house['house_type']}")
+
+
+def print_house_list(result, is_browse_history=False):
+    """统一打印房源列表（支持普通列表和浏览历史记录）"""
+    if not result:
+        print("未找到相关记录！")
+        return
+    for i, item in enumerate(result, 1):
+        house = item if not is_browse_history else query_house("id", item)[0] if query_house("id", item) else None
+        if house:
+            prefix = f"{i}. " if not is_browse_history else ""
+            print(f"{prefix}ID:{house['id']} | 地址:{house['address']} | 租金:{house['price']}元/月")
+        elif is_browse_history:
+            print(f"{i}. ID:{item}（房源已删除）")
+
+
+# ==================== 业务功能模块拆分 ====================
+
+def handle_add_house():
+    """处理新增房源"""
+    print("\n----- 新增房源 -----")
+    address = input("请输入房源地址：").strip()
+    price = get_valid_input("请输入租金（元/月）：", float)
+    if price is False: return
+    area = get_valid_input("请输入面积（㎡）：", float)
+    if area is False: return
+    house_type = input("请输入户型（如：一居室、两居室）：").strip()
+
+    if add_house(address, price, area, house_type):
+        new_id = get_next_house_id() - 1
+        push_operation_stack(f"新增房源ID:{new_id}，地址:{address}")
+        print("房源新增成功！")
+
+
+def handle_delete_house():
+    """处理删除房源"""
+    print("\n----- 删除房源 -----")
+    house_id = get_valid_input("请输入要删除的房源ID：", int)
+    if house_id is False or house_id is None: return
+
+    house = query_house("id", house_id)
+    house_addr = house[0]["address"] if house else "未知地址"
+    if delete_house(house_id):
+        push_operation_stack(f"删除房源ID:{house_id}，地址:{house_addr}")
+        print("房源删除成功！")
+
+
+def handle_update_house():
+    """处理修改房源"""
+    print("\n----- 修改房源 -----")
+    house_id = get_valid_input("请输入要修改的房源ID：", int)
+    if house_id is False or house_id is None: return
+
+    new_info = {}
+    address = input("请输入新地址（不修改按回车）：").strip()
+    if address: new_info["address"] = address
+
+    price = get_valid_input("请输入新租金（不修改按回车）：", float)
+    if price is False: return
+    if price: new_info["price"] = price
+
+    area = get_valid_input("请输入新面积（不修改按回车）：", float)
+    if area is False: return
+    if area: new_info["area"] = area
+
+    house_type = input("请输入新户型（不修改按回车）：").strip()
+    if house_type: new_info["house_type"] = house_type
+
+    if new_info:
+        if update_house(house_id, new_info):
+            push_operation_stack(f"修改房源ID:{house_id}，修改内容:{new_info}")
+            print("房源修改成功！")
+    else:
+        print("未输入任何修改内容！")
+
+
+def handle_query_house():
+    """处理查询房源"""
+    print("\n----- 查询房源 -----")
+    cond_type_map = {"1": "id", "2": "address", "3": "price", "4": "house_type"}
+    print("查询条件类型：1-ID  2-地址  3-租金  4-户型")
+    cond_choice = input("请输入条件类型编号（1-4）：").strip()
+
+    if cond_choice not in cond_type_map:
+        print("错误：无效的条件类型！")
+        return
+
+    condition_type = cond_type_map[cond_choice]
+    condition_value = input(f"请输入{condition_type}查询值：").strip()
+    result = query_house(condition_type, condition_value)
+
+    if result:
+        print("\n查询结果：")
+        for house in result:
+            print_house(house)
+            if condition_type == "id":
+                push_browse_stack(house["id"])
+    else:
+        print("未找到符合条件的房源！")
+
+
+def handle_operation_records():
+    """处理操作记录管理"""
+    while True:
+        print("\n----- 操作记录管理 -----")
+        print("1. 查看最新10条操作记录\n2. 获取最新1条操作记录（并删除）\n3. 清空所有操作记录\n4. 返回主菜单")
+        c = input("请输入操作编号：").strip()
+        if c == "1":
+            records = get_recent_records("operation", 10)
+            if records:
+                print("\n最新10条操作记录（从新到旧）：")
+                for i, r in enumerate(records, 1): print(f"{i}. {r}")
+            else:
+                print("暂无操作记录！")
+        elif c == "2":
+            latest = pop_operation_stack()
+            print(latest if latest else "暂无操作记录！")
+        elif c == "3":
+            clear_stack("operation")
+            print("操作记录已清空！")
+        elif c == "4":
+            break
+
+
+def handle_browse_history():
+    """处理浏览历史管理"""
+    while True:
+        print("\n----- 浏览历史管理 -----")
+        print("1. 查看最新10条浏览历史\n2. 获取最新1条浏览房源（并删除）\n3. 清空所有浏览历史\n4. 返回主菜单")
+        c = input("请输入操作编号：").strip()
+        if c == "1":
+            ids = get_recent_records("browse", 10)
+            print_house_list(ids, is_browse_history=True)
+        elif c == "2":
+            hid = pop_browse_stack()
+            if hid:
+                h = query_house("id", hid)
+                if h:
+                    print(f"最新浏览：ID:{hid} | 地址:{h[0]['address']}")
+                else:
+                    print(f"最新浏览ID:{hid}（已删除）")
+            else:
+                print("暂无浏览历史！")
+        elif c == "3":
+            clear_stack("browse")
+            print("浏览历史已清空！")
+        elif c == "4":
+            break
+
+
+def handle_address_area():
+    """V3.0 处理地址解析与区域查询"""
+    while True:
+        print("\n----- 地址解析与区域查询 -----")
+        print("1. 按区域关键词查询房源\n2. 返回主菜单")
+        c = input("请输入操作编号：").strip()
+        if c == "1":
+            keyword = input("请输入区域关键词（如：朝阳、花园）：").strip()
+            res = query_by_area(keyword)
+            print_house_list(res)
+        elif c == "2":
+            break
+
+
+def handle_adj_matrix():
+    """V3.0 处理小区邻接矩阵管理"""
+    while True:
+        print("\n----- 小区邻接矩阵管理 -----")
+        print("1. 设置小区间距离\n2. 查看邻接矩阵\n3. 返回主菜单")
+        c = input("请输入操作编号：").strip()
+        if c == "1":
+            c1 = input("请输入小区1名称：").strip()
+            c2 = input("请输入小区2名称：").strip()
+            dis = get_valid_input("请输入距离（米）：", int)
+            if dis and dis is not False:
+                if add_community_distance(c1, c2, dis):
+                    print("距离设置成功！")
+                else:
+                    print("设置失败，请检查小区名称是否正确！")
+        elif c == "2":
+            show_adj_matrix()
+        elif c == "3":
+            break
+
+
+# ==================== 主程序 ====================
+
+def print_menu():
+    print("\n===== 房屋出租系统 V3.0 =====")
+    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. 地址解析与区域查询")
+    print("8. 小区邻接矩阵管理")
+    print("9. 退出系统")
+    print("==============================")
+
+
+def main():
+    action_map = {
+        "1": handle_add_house,
+        "2": handle_delete_house,
+        "3": handle_update_house,
+        "4": handle_query_house,
+        "5": handle_operation_records,
+        "6": handle_browse_history,
+        "7": handle_address_area,
+        "8": handle_adj_matrix,
+    }
+
+    while True:
+        print_menu()
+        choice = input("请输入操作编号（1-9）：").strip()
+
+        if choice == "9":
+            print("正在保存数据...")
+            save_all_data()  # 退出前保存内存中的数据到磁盘
+            print("感谢使用房屋出租系统 V3.0，再见！")
+            break
+
+        action = action_map.get(choice)
+        if action:
+            action()
+        else:
+            print("错误：请输入1-9之间的有效编号！")
+
+
+if __name__ == "__main__":
+    main()

house_operation.py

@@ -1,83 +1,77 @@
 import json
 import os
 
-# 以下为 V1.0 原有代码，完全未修改
+#v1
-
-# 定义数据文件路径
 HOUSE_FILE = "./data/houses.json"
 
 def init_db():
-    """
+    """初始化房源数据文件"""
-    初始化数据文件：如果houses.json不存在，创建并写入空列表
-    空间复杂度：O(1)（仅创建空文件）
-    """
-    # 确保data文件夹存在
     os.makedirs("./data", exist_ok=True)
-    # 如果文件不存在，创建并写入空列表
     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"""
-    读取所有房源数据
+    init_db()
-    时间复杂度：O(n)（n为房源数，JSON解析耗时与数据量正相关）
-    空间复杂度：O(n)（存储所有房源数据）
-    return: 房源列表（每个元素是字典）
-    """
-    init_db()  # 先确保文件存在
     with open(HOUSE_FILE, 'r', encoding='utf-8') as f:
         return json.load(f)
 
 def write_houses(houses):
-    """
+    """写入房源"""
-    写入房源数据到JSON文件
-    时间复杂度：O(n)（n为房源数，JSON序列化耗时与数据量正相关）
-    空间复杂度：O(1)（仅写入操作，无额外存储）
-    param houses: 要写入的房源列表
-    """
     with open(HOUSE_FILE, 'w', encoding='utf-8') as f:
         json.dump(houses, f, ensure_ascii=False, indent=4)
 
-# V2.0 新增代码：栈数据读写
+#v2
-
-#  V2.0 新增：栈数据文件配置
 STACK_FILE = "./data/stack_data.json"
 
-# V2.0 新增：栈数据初始化与读写
 def init_stack_db():
-    """
+    """初始化栈文件"""
-    初始化栈数据文件：若不存在则创建，区分操作记录栈/浏览历史栈
-    """
     os.makedirs("./data", exist_ok=True)
     if not os.path.exists(STACK_FILE):
-        init_data = {
+        init_data = {"operation_stack": [], "browse_stack": []}
-            "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"""
-    读取指定类型的栈数据
-    :param stack_type: operation（操作记录）/ browse（浏览历史）
-    """
     init_stack_db()
     with open(STACK_FILE, 'r', encoding='utf-8') as f:
         data = json.load(f)
-    stack_key = f"{stack_type}_stack"
+    return data.get(f"{stack_type}_stack", [])
-    return data.get(stack_key, [])
 
 def write_stack(stack_type, new_stack):
-    """
+    """写入指定栈"""
-    写入指定类型的栈数据到文件
-    """
     init_stack_db()
-    # 读取原有数据，避免覆盖另一个栈
     with open(STACK_FILE, 'r', encoding='utf-8') as f:
         data = json.load(f)
-    stack_key = f"{stack_type}_stack"
+    data[f"{stack_type}_stack"] = new_stack
-    data[stack_key] = 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)
+

house_operation4.0.py

@@ -0,0 +1,76 @@
+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)

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)
+

house_service.py

@@ -1,32 +1,17 @@
-from house.db_operation import read_houses, write_houses
+from house_operation import *
+from datetime import datetime
 
 
+# v1
 def get_next_house_id():
-    """
-    生成下一个房源ID（保证ID唯一）
-    时间复杂度：O(n)（遍历所有房源找最大ID）
-    return: 下一个可用的ID（整数）
-    """
     houses = read_houses()
     if not houses:
-        return 1  # 无房源时，第一个ID为1
+        return 1
-    # 找到最大ID，加1作为新ID
     max_id = max(house["id"] for house in houses)
     return max_id + 1
 
 
 def add_house(address, price, area, house_type):
-    """
-    新增房源（线性表的尾部插入操作）
-    时间复杂度：O(n)（read/write各O(n)，整体O(n)）
-    空间复杂度：O(n)（存储所有房源数据）
-    param address: 房源地址（字符串）
-    param price: 租金（整数/浮点数）
-    param area: 面积（整数/浮点数）
-    param house_type: 户型（字符串，如"一居室"）
-    return: 新增成功返回True，失败返回False
-    """
-    # 基础数据校验（非空+数值合法性）
     if not address or not house_type:
         print("错误：地址和户型不能为空！")
         return False
@@ -37,7 +22,6 @@ def add_house(address, price, area, house_type):
         print("错误：面积必须是正数！")
         return False
 
-    # 构建新房源字典（线性表的元素）
     new_house = {
         "id": get_next_house_id(),
         "address": address,
@@ -45,30 +29,18 @@ def add_house(address, price, area, house_type):
         "area": area,
         "house_type": house_type
     }
-
-    # 读取现有房源（线性表），新增元素（尾部插入）
     houses = read_houses()
-    houses.append(new_house)  # 线性表append操作，时间复杂度O(1)
+    houses.append(new_house)
-
-    # 写入文件
     write_houses(houses)
     print(f"房源新增成功！房源ID：{new_house['id']}")
     return True
 
 
 def delete_house(house_id):
-    """
-    删除房源（线性表的指定位置删除操作）
-    时间复杂度：O(n)（遍历找ID+写入文件，整体O(n)）
-    空间复杂度：O(n)（存储所有房源数据）
-    param house_id: 要删除的房源ID（整数）
-    return: 删除成功返回True，失败返回False
-    """
     houses = read_houses()
-    # 遍历线性表，找到对应ID的房源
     for index, house in enumerate(houses):
         if house["id"] == house_id:
-            del houses[index]  # 线性表删除操作，时间复杂度O(n)（后续元素前移）
+            del houses[index]
             write_houses(houses)
             print(f"房源ID {house_id} 删除成功！")
             return True
@@ -77,22 +49,11 @@ def delete_house(house_id):
 
 
 def update_house(house_id, new_info):
-    """
-    修改房源信息（线性表的指定元素更新操作）
-    时间复杂度：O(n)（遍历找ID+写入文件，整体O(n)）
-    空间复杂度：O(n)（存储所有房源数据）
-    param house_id: 要修改的房源ID（整数）
-    param new_info: 要修改的字段字典（如{"price": 5500, "area": 85}）
-    return: 修改成功返回True，失败返回False
-    """
     houses = read_houses()
-    # 遍历线性表，找到对应ID的房源
     for house in houses:
         if house["id"] == house_id:
-            # 仅更新传入的有效字段
             for key, value in new_info.items():
                 if key in ["address", "price", "area", "house_type"]:
-                    # 校验数值字段合法性
                     if key in ["price", "area"]:
                         if not isinstance(value, (int, float)) or value <= 0:
                             print(f"错误：{key}必须是正数！")
@@ -106,31 +67,18 @@ def update_house(house_id, new_info):
 
 
 def query_house(condition_type, condition_value):
-    """
-    查询房源（线性表的遍历筛选操作）
-    时间复杂度：O(n)（遍历所有房源，n为房源数）
-    空间复杂度：O(k)（k为符合条件的房源数，最坏O(n)）
-    param condition_type: 查询条件类型（"id"/"address"/"price"/"house_type"）
-    param condition_value: 查询条件值
-    return: 符合条件的房源列表
-    """
     houses = read_houses()
     result = []
-    # 按条件遍历筛选
     for house in houses:
-        # 处理ID查询（整数匹配）
         if condition_type == "id":
             if house["id"] == int(condition_value):
                 result.append(house)
-        # 处理地址查询（模糊匹配）
         elif condition_type == "address":
             if condition_value in house["address"]:
                 result.append(house)
-        # 处理户型查询（精确匹配）
         elif condition_type == "house_type":
             if house["house_type"] == condition_value:
                 result.append(house)
-        # 处理租金查询（数值匹配，示例：查询等于该价格的房源）
         elif condition_type == "price":
             if house["price"] == float(condition_value):
                 result.append(house)
@@ -138,3 +86,381 @@ def query_house(condition_type, condition_value):
             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

house_service4.0.py

@@ -0,0 +1,346 @@
+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

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

main.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()

main4.0.py

@@ -0,0 +1,262 @@
+from house_service import *
+
+def print_menu():
+    print("\n===== 房屋出租系统 V4.0 =====")
+    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")
+    # 【V4.0 新增菜单】
+    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）")
+    print("14. 退出系统")
+    print("============================")
+
+# V2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
+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
+        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
+        elif choice == "5":
+            op_record_menu()
+        elif choice == "6":
+            browse_history_menu()
+
+        #v3
+        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
+        elif choice == "11":
+            # 二叉树范围查询
+            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
+
+            # 读取所有房源，构建二叉树
+            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)
+            # 范围查询
+            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":
+            # 冒泡排序
+            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
+            # 冒泡排序
+            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":
+            # 快速排序
+            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
+            # 快速排序
+            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]}")
+
+        elif choice == "14":
+            print("系统退出成功！")
+            break
+        else:
+            print("请输入有效编号")
+
+
+if __name__ == "__main__":
+    main()

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()