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@@ -1,140 +1,208 @@
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from house.db_operation import read_houses, write_houses
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def get_next_house_id():
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"""
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生成下一个房源ID（保证ID唯一）
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时间复杂度：O(n)（遍历所有房源找最大ID）
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return: 下一个可用的ID（整数）
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"""
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houses = read_houses()
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if not houses:
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return 1 # 无房源时，第一个ID为1
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# 找到最大ID，加1作为新ID
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max_id = max(house["id"] for house in houses)
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return max_id + 1
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def add_house(address, price, area, house_type):
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"""
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新增房源（线性表的尾部插入操作）
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时间复杂度：O(n)（read/write各O(n)，整体O(n)）
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空间复杂度：O(n)（存储所有房源数据）
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param address: 房源地址（字符串）
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param price: 租金（整数/浮点数）
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param area: 面积（整数/浮点数）
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param house_type: 户型（字符串，如"一居室"）
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return: 新增成功返回True，失败返回False
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"""
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# 基础数据校验（非空+数值合法性）
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if not address or not house_type:
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print("错误：地址和户型不能为空！")
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return False
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if not isinstance(price, (int, float)) or price <= 0:
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print("错误：租金必须是正数！")
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return False
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if not isinstance(area, (int, float)) or area <= 0:
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print("错误：面积必须是正数！")
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return False
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# 构建新房源字典（线性表的元素）
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new_house = {
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"id": get_next_house_id(),
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"address": address,
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"price": price,
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"area": area,
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"house_type": house_type
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}
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# 读取现有房源（线性表），新增元素（尾部插入）
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houses = read_houses()
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houses.append(new_house) # 线性表append操作，时间复杂度O(1)
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# 写入文件
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write_houses(houses)
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print(f"房源新增成功！房源ID：{new_house['id']}")
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return True
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def delete_house(house_id):
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"""
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删除房源（线性表的指定位置删除操作）
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时间复杂度：O(n)（遍历找ID+写入文件，整体O(n)）
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空间复杂度：O(n)（存储所有房源数据）
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param house_id: 要删除的房源ID（整数）
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return: 删除成功返回True，失败返回False
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"""
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houses = read_houses()
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# 遍历线性表，找到对应ID的房源
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for index, house in enumerate(houses):
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if house["id"] == house_id:
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del houses[index] # 线性表删除操作，时间复杂度O(n)（后续元素前移）
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write_houses(houses)
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print(f"房源ID {house_id} 删除成功！")
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return True
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print(f"错误：未找到房源ID {house_id}！")
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return False
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def update_house(house_id, new_info):
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"""
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修改房源信息（线性表的指定元素更新操作）
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时间复杂度：O(n)（遍历找ID+写入文件，整体O(n)）
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空间复杂度：O(n)（存储所有房源数据）
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param house_id: 要修改的房源ID（整数）
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param new_info: 要修改的字段字典（如{"price": 5500, "area": 85}）
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return: 修改成功返回True，失败返回False
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"""
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houses = read_houses()
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# 遍历线性表，找到对应ID的房源
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for house in houses:
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if house["id"] == house_id:
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# 仅更新传入的有效字段
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for key, value in new_info.items():
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if key in ["address", "price", "area", "house_type"]:
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# 校验数值字段合法性
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if key in ["price", "area"]:
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if not isinstance(value, (int, float)) or value <= 0:
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print(f"错误：{key}必须是正数！")
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return False
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house[key] = value
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write_houses(houses)
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print(f"房源ID {house_id} 修改成功！")
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return True
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print(f"错误：未找到房源ID {house_id}！")
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return False
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def query_house(condition_type, condition_value):
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"""
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查询房源（线性表的遍历筛选操作）
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时间复杂度：O(n)（遍历所有房源，n为房源数）
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空间复杂度：O(k)（k为符合条件的房源数，最坏O(n)）
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param condition_type: 查询条件类型（"id"/"address"/"price"/"house_type"）
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param condition_value: 查询条件值
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return: 符合条件的房源列表
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"""
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houses = read_houses()
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result = []
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# 按条件遍历筛选
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for house in houses:
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# 处理ID查询（整数匹配）
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if condition_type == "id":
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if house["id"] == int(condition_value):
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result.append(house)
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# 处理地址查询（模糊匹配）
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elif condition_type == "address":
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if condition_value in house["address"]:
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result.append(house)
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# 处理户型查询（精确匹配）
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elif condition_type == "house_type":
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if house["house_type"] == condition_value:
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result.append(house)
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# 处理租金查询（数值匹配，示例：查询等于该价格的房源）
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elif condition_type == "price":
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if house["price"] == float(condition_value):
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result.append(house)
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else:
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print("错误：不支持的查询条件类型！")
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return []
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return result
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from house_operation import *
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from datetime import datetime
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def get_next_house_id():
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houses = read_houses()
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if not houses:
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return 1
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max_id = max(house["id"] for house in houses)
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return max_id + 1
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def add_house(address, price, area, house_type):
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if not address or not house_type:
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print("错误：地址和户型不能为空！")
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return False
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if not isinstance(price, (int, float)) or price <= 0:
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print("错误：租金必须是正数！")
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return False
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if not isinstance(area, (int, float)) or area <= 0:
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print("错误：面积必须是正数！")
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return False
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new_house = {
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"id": get_next_house_id(),
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"address": address,
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"price": price,
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"area": area,
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"house_type": house_type
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}
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houses = read_houses()
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houses.append(new_house)
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write_houses(houses)
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print(f"房源新增成功！房源ID：{new_house['id']}")
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return True
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def delete_house(house_id):
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houses = read_houses()
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for index, house in enumerate(houses):
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if house["id"] == house_id:
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del houses[index]
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write_houses(houses)
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print(f"房源ID {house_id} 删除成功！")
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return True
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print(f"错误：未找到房源ID {house_id}！")
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return False
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def update_house(house_id, new_info):
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houses = read_houses()
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for house in houses:
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if house["id"] == house_id:
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for key, value in new_info.items():
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if key in ["address", "price", "area", "house_type"]:
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if key in ["price", "area"]:
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if not isinstance(value, (int, float)) or value <= 0:
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print(f"错误：{key}必须是正数！")
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return False
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house[key] = value
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write_houses(houses)
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print(f"房源ID {house_id} 修改成功！")
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return True
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print(f"错误：未找到房源ID {house_id}！")
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return False
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def query_house(condition_type, condition_value):
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houses = read_houses()
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result = []
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for house in houses:
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if condition_type == "id":
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if house["id"] == int(condition_value):
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result.append(house)
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elif condition_type == "address":
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if condition_value in house["address"]:
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result.append(house)
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elif condition_type == "house_type":
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if house["house_type"] == condition_value:
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result.append(house)
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elif condition_type == "price":
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if house["price"] == float(condition_value):
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result.append(house)
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else:
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print("错误：不支持的查询条件类型！")
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return []
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return result
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MAX_STACK_LENGTH = 100
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def push_operation_stack(operation_info):
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time_str = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
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full_info = f"[{time_str}] {operation_info}"
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stack = read_stack("operation")
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stack.append(full_info)
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if len(stack) > MAX_STACK_LENGTH:
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stack.pop(0)
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write_stack("operation", stack)
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def push_browse_stack(house_id):
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stack = read_stack("browse")
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if stack and stack[-1] == house_id:
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return
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stack.append(house_id)
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if len(stack) > MAX_STACK_LENGTH:
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stack.pop(0)
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write_stack("browse", stack)
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def pop_operation_stack():
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stack = read_stack("operation")
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if not stack:
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return None
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latest_op = stack.pop()
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write_stack("operation", stack)
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return latest_op
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def pop_browse_stack():
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stack = read_stack("browse")
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if not stack:
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return None
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latest_hid = stack.pop()
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write_stack("browse", stack)
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return latest_hid
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def get_recent_records(stack_type, limit=10):
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stack = read_stack(stack_type)
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return stack[-limit:][::-1]
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def clear_stack(stack_type):
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write_stack(stack_type, [])
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print(f"{stack_type}记录已清空！")
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def parse_address_string(full_address):
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# 字符串分割（串操作核心）
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parts = full_address.split("市")
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province_city = parts[0] + "市" if "市" in full_address else parts[0]
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if "省" in province_city:
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province, city = province_city.split("省")
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province += "省"
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city += "市"
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else:
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province = "未知省份"
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city = province_city
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# 继续拆分区县
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if len(parts) > 1:
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district_part = parts[1]
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if "区" in district_part or "县" in district_part:
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district, community = district_part.split("区") if "区" in district_part else district_part.split("县")
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district += "区" if "区" in district_part else "县"
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else:
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district = "未知区县"
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community = district_part
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else:
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district = "未知区县"
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community = "未知小区"
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return {
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"province": province,
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"city": city,
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"district": district,
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"community": community
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}
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def fuzzy_query_by_district(keyword):
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houses = read_houses()
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result = []
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for house in houses:
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addr_info = parse_address_string(house["address"])
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# 字符串包含匹配
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if keyword in addr_info["district"] or keyword in addr_info["community"]:
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result.append(house)
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return result
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def init_community_matrix(community_name_list):
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"""
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【V3.0新增 二维数组知识点：邻接矩阵初始化】
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根据小区列表生成距离邻接矩阵，初始化距离为无穷大，自己到自己为0
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时间复杂度：O(N²)，N为小区数量
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空间复杂度：O(N²)
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"""
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INF = float("inf")
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n = len(community_name_list)
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# 二维数组初始化（邻接矩阵）
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distance_matrix = [[INF]*n for _ in range(n)]
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for i in range(n):
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distance_matrix[i][i] = 0 # 自己到自己距离为0
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# 保存到数据文件
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matrix_data = {
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"community_list": community_name_list,
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"distance_matrix": distance_matrix
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}
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write_matrix_data(matrix_data)
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print("邻接矩阵初始化完成！")
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def update_matrix_distance(community_a, community_b, distance):
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matrix_data = read_matrix_data()
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community_list = matrix_data["community_list"]
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distance_matrix = matrix_data["distance_matrix"]
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try:
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idx_a = community_list.index(community_a)
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idx_b = community_list.index(community_b)
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distance_matrix[idx_a][idx_b] = distance
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distance_matrix[idx_b][idx_a] = distance
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write_matrix_data(matrix_data)
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print(f"{community_a} <-> {community_b} 距离更新成功！")
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except ValueError:
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print("小区名称不存在！")
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