house_service3.0.py

address_operation.py

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+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)