123

.claude/settings.local.json

@@ -0,0 +1,7 @@
+{
+  "permissions": {
+    "allow": [
+      "Bash(python -c \":*)"
+    ]
+  }
+}

config/database.json

@@ -0,0 +1,13 @@
+{
+    "database": {
+        "host": "192.168.100.33",
+        "port": 3306,
+        "username": "zhenggantian",
+        "password": "123456",
+        "database": "logistics",
+        "charset": "utf8mb4",
+        "pool_size": 10,
+        "max_overflow": 5,
+        "pool_recycle": 3600
+    }
+}

dataaccess/__init__.py

@@ -0,0 +1,4 @@
+"""数据访问层模块"""
+from dataaccess.base_dao import BaseDAO
+
+__all__ = ["BaseDAO"]

dataaccess/base_dao.py

@@ -0,0 +1,65 @@
+"""基础数据访问类"""
+import pandas as pd
+from typing import Any, Dict, List, Optional
+from utils.gtools import MySQLconnect
+
+
+class BaseDAO:
+    """基础数据访问对象"""
+
+    _cache: Dict[str, pd.DataFrame] = {}
+    _cache_enabled: bool = True
+
+    def __init__(self, table_name: str):
+        self.table_name = table_name
+
+    def _get_connection(self, dbname: str = None) -> MySQLconnect:
+        """获取数据库连接"""
+        return MySQLconnect(dbname)
+
+    def get_all(self, dbname: str = None) -> pd.DataFrame:
+        """获取所有数据"""
+        cache_key = f"{dbname}:{self.table_name}"
+
+        if self._cache_enabled and cache_key in self._cache:
+            return self._cache[cache_key]
+
+        with self._get_connection(dbname) as conn:
+            df = pd.read_sql(f"SELECT * FROM {self.table_name}", conn.con)
+
+        if self._cache_enabled:
+            self._cache[cache_key] = df
+
+        return df
+
+    def get_by_condition(self, conditions: Dict[str, Any], dbname: str = None) -> pd.DataFrame:
+        """根据条件查询数据"""
+        where_clause = " AND ".join([f"{k} = '{v}'" for k, v in conditions.items()])
+        query = f"SELECT * FROM {self.table_name} WHERE {where_clause}"
+
+        with self._get_connection(dbname) as conn:
+            df = pd.read_sql(query, conn.con)
+
+        return df
+
+    def execute_query(self, query: str, dbname: str = None) -> pd.DataFrame:
+        """执行自定义查询"""
+        with self._get_connection(dbname) as conn:
+            df = pd.read_sql(query, conn.con)
+
+        return df
+
+    @classmethod
+    def clear_cache(cls):
+        """清空缓存"""
+        cls._cache.clear()
+
+    @classmethod
+    def disable_cache(cls):
+        """禁用缓存"""
+        cls._cache_enabled = False
+
+    @classmethod
+    def enable_cache(cls):
+        """启用缓存"""
+        cls._cache_enabled = True

dataaccess/company_dao.py

@@ -0,0 +1,49 @@
+"""物流公司数据访问类"""
+import pandas as pd
+from typing import Dict, List, Optional
+from dataaccess.base_dao import BaseDAO
+
+
+class CompanyDAO(BaseDAO):
+    """物流公司数据访问"""
+
+    def __init__(self):
+        super().__init__("logistics_company")
+
+    def get_all_companies(self, country: str = None, active_only: bool = True) -> List[Dict]:
+        """获取所有物流公司"""
+        conditions = {}
+        if country:
+            conditions["country"] = country
+        if active_only:
+            conditions["active"] = 1
+
+        if conditions:
+            df = self.get_by_condition(conditions)
+        else:
+            df = self.get_all()
+
+        if df.empty:
+            return []
+
+        return df.to_dict("records")
+
+    def get_company_info(self, company_code: str) -> Optional[Dict]:
+        """获取物流公司详细信息"""
+        df = self.get_by_condition({"company_code": company_code})
+        if df.empty:
+            return None
+        return df.iloc[0].to_dict()
+
+    def get_companies_by_type(self, country: str, logistics_type: str) -> List[Dict]:
+        """根据物流类型获取公司列表"""
+        query = f"""
+            SELECT * FROM {self.table_name}
+            WHERE country = '{country}'
+            AND logistics_type = '{logistics_type}'
+            AND active = 1
+        """
+        df = self.execute_query(query)
+        if df.empty:
+            return []
+        return df.to_dict("records")

dataaccess/uk_price_dao.py

@@ -0,0 +1,65 @@
+"""英国物流价格数据访问类"""
+import pandas as pd
+from typing import Dict, List, Optional
+from dataaccess.base_dao import BaseDAO
+
+
+class UKPriceDAO(BaseDAO):
+    """英国物流价格数据访问"""
+
+    def __init__(self):
+        super().__init__("uk_logistics_price")
+
+    def get_all_companies(self) -> List[str]:
+        """获取所有英国物流公司"""
+        df = self.get_all()
+        if df.empty:
+            return []
+        return df["company"].unique().tolist()
+
+    def get_company_price(self, company: str) -> pd.DataFrame:
+        """获取指定物流公司的价格数据"""
+        return self.get_by_condition({"company": company})
+
+    def get_company_config(self, company: str) -> Dict:
+        """获取物流公司配置信息"""
+        df = self.get_by_condition({"company": company})
+        if df.empty:
+            return {}
+
+        config = {}
+        for _, row in df.iterrows():
+            key = row.get("config_key")
+            value = row.get("config_value")
+            if key:
+                config[key] = value
+
+        return config
+
+
+class UKPostcodeDAO(BaseDAO):
+    """英国邮编分区数据访问"""
+
+    def __init__(self):
+        super().__init__("uk_postcode_zone")
+
+    def get_zone(self, postcode: str) -> Optional[str]:
+        """根据邮编获取分区"""
+        postcode_prefix = postcode.split()[0].upper()
+        df = self.get_by_condition({"postcode_prefix": postcode_prefix})
+
+        if df.empty:
+            return None
+
+        return df.iloc[0].get("zone")
+
+    def is_remote(self, postcode: str) -> bool:
+        """判断是否偏远"""
+        postcode_prefix = postcode.split()[0].upper()
+        remote_prefixes = ["BT", "IM", "JE", "ZE", "GY", "HS", "PO", "IV", "KA", "KW", "PH", "PA"]
+
+        if not any(postcode_prefix.startswith(p) for p in remote_prefixes):
+            return False
+
+        df = self.get_by_condition({"postcode_prefix": postcode_prefix, "is_remote": "1"})
+        return not df.empty

dataaccess/us_price_dao.py

@@ -0,0 +1,70 @@
+"""美国物流价格数据访问类"""
+import pandas as pd
+from typing import Dict, List, Optional
+from dataaccess.base_dao import BaseDAO
+
+
+class USPriceDAO(BaseDAO):
+    """美国物流价格数据访问"""
+
+    def __init__(self):
+        super().__init__("us_logistics_price")
+
+    def get_all_companies(self) -> List[str]:
+        """获取所有美国物流公司"""
+        df = self.get_all()
+        if df.empty:
+            return []
+        return df["company"].unique().tolist()
+
+    def get_company_price(self, company: str) -> pd.DataFrame:
+        """获取指定物流公司的价格数据"""
+        return self.get_by_condition({"company": company})
+
+    def get_company_config(self, company: str) -> Dict:
+        """获取物流公司配置信息"""
+        df = self.get_by_condition({"company": company})
+        if df.empty:
+            return {}
+
+        config = {}
+        for _, row in df.iterrows():
+            key = row.get("config_key")
+            value = row.get("config_value")
+            if key:
+                config[key] = value
+
+        return config
+
+
+class USPostcodeDAO(BaseDAO):
+    """美国邮编分区数据访问"""
+
+    def __init__(self):
+        super().__init__("us_postcode_zone")
+
+    def get_zone(self, postcode: str, port: str = "west") -> Optional[str]:
+        """根据邮编获取分区"""
+        postcode_5 = postcode[:5]
+        df = self.get_by_condition({"postcode": postcode_5, "port": port})
+
+        if df.empty:
+            return None
+
+        return df.iloc[0].get("zone")
+
+    def get_remote_type(self, postcode: str) -> int:
+        """获取偏远类型: 0-非偏远, 1-偏远, 2-超偏远, 3-超超偏远"""
+        postcode_5 = postcode[:5]
+        df = self.get_by_condition({"postcode": postcode_5})
+
+        if df.empty:
+            return 0
+
+        return int(df.iloc[0].get("remote_type", 0))
+
+    def is_contiguous(self, postcode: str) -> bool:
+        """判断是否在本土范围内"""
+        postcode_5 = postcode[:5]
+        df = self.get_by_condition({"postcode": postcode_5})
+        return not df.empty

login_for_cookie.py

@@ -5,14 +5,15 @@ import re
 import pytesseract
 from PIL import Image
 from tempfile import NamedTemporaryFile
-from selenium.webdriver.chrome.service import Service
-from selenium.webdriver.common.by import By
-from selenium.webdriver.remote.file_detector import UselessFileDetector #跳过文件检测 1
-from selenium import webdriver
+
 import redis 
 
 def vercode(cookie=None):
-    urls = 'https://cp.maso.hk:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片）
+    urls = 'https://cp.baycheer.com:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片）
+
+
+
+    
     if cookie is not None:
         haders = {
             'Cookie': cookie  #使用之前的图片链接Cooike
@@ -43,7 +44,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'):
     try :
         r = redis.StrictRedis(host='192.168.100.44', port=7379, db=11,password="123456")
         viewcookie = r.get('cpmasosessid'+user)
-        url="https://cp.maso.hk/index.php?main=panel"#主页
+        url="https://cp.baycheer.com/index.php?main=panel"#主页
         header={'Cookie':viewcookie.decode('utf8')}
         resp = requests.get(url=url,headers=header)
         exists = re.findall(r'欢迎进入本公司后台管理系统',resp.text)
@@ -57,7 +58,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'):
  
     
     while resetcookie ==1:
-        urls = 'https://cp.maso.hk:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片）
+        urls = 'https://cp.baycheer.com:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片）
         res = requests.post(url=urls)
         ress = re.findall('Cookie (.*?) for',str(res.cookies))#获取图片链接Cooike，图片Cooike必须和登录请求的Cooike保持一致
         f1 = NamedTemporaryFile(mode='wb+',suffix='.png')
@@ -77,7 +78,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'):
         bim.save(f2)#处理完成导入
         f2.seek(0)
         text = pytesseract.image_to_string(Image.open(f2))#开始识别
-        url = 'https://cp.maso.hk:4433/index.php?main=login&act=check'
+        url = 'https://cp.baycheer.com:4433/index.php?main=login&act=check'
         haders = {
             'Cookie': ress[0]   #使用之前的图片链接Cooike
         }
@@ -204,9 +205,9 @@ def zenid():
         options.add_argument('--disable-gpu')
         options.add_argument(' -port=9222')
         driver=webdriver.Remote(service.service_url,options=options)
-        mainurl='http://cp.maso.hk/index.php?main=main'
-        panelUrl = "http://cp.maso.hk/index.php?main=panel"#地址
-        remoteurl='http://cp.maso.hk/index.php?main=sys_remote_login&act=remotelogin&id=303'
+        mainurl='http://cp.baycheer.com/index.php?main=main'
+        panelUrl = "http://cp.baycheer.com/index.php?main=panel"#地址
+        remoteurl='http://cp.baycheer.com/index.php?main=sys_remote_login&act=remotelogin&id=303'
         driver.get(mainurl)
         driver.delete_all_cookies()
         driver.add_cookie({'name':'sessid','value':f'{t}'})

logisticsClass/logisticsTail_UK.py

@@ -5,6 +5,7 @@ import re
 
 import pandas
 from logisticsClass.logisticsBaseClass import LogisticsType, TailLogistics
+from utils.gtools import MySQLconnect
 
 
 class DPDLogistics_UK(TailLogistics):
@@ -218,53 +219,75 @@ class KPNVlogistics_UK(TailLogistics):
     country = 'United Kingdom'
     company = '卡派-NV'
     currency = 'GBP'
-    logistics_type = LogisticsType.COURIER 
+    logistics_type = LogisticsType.COURIER
+
+    # 数据库表数据(内存缓存)
+    _zone_cache = None  # 邮编分区缓存
+    _price_cache = None  # 价格缓存
 
-    parent_current_directory = Path(__file__).parent.parent
-    price_path = parent_current_directory.joinpath("data")
-    _price_files = price_path.joinpath("英国卡派.xlsx")
-    ltl_cost = None
-    ltl_zone = None
     def __new__(cls):
-        """实现单例模式，只加载一次文件"""
-        if cls.ltl_cost is None or cls.ltl_zone is None:
-            cls.ltl_cost = pandas.read_excel(cls._price_files,sheet_name="运费")
-            cls.ltl_zone = pandas.read_excel(cls._price_files,sheet_name="分区")
+        """实现单例模式，从数据库加载数据"""
+        if cls._zone_cache is None or cls._price_cache is None:
+            cls._load_from_db()
         return super().__new__(cls)
+
+    @classmethod
+    def _load_from_db(cls):
+        """从数据库加载分区和价格数据"""
+        conn = MySQLconnect('logistics')
+        with conn as c:
+            # 加载分区表
+            c.cur.execute("SELECT `邮编`, `区域` FROM uk_XLCarrier_postcode_partition")
+            cls._zone_cache = {}
+            for row in c.cur.fetchall():
+                postcode = str(row[0]) if row[0] else ""
+                zone = str(row[1]) if row[1] else ""
+                cls._zone_cache[postcode] = zone
+
+            # 加载价格表
+            c.cur.execute("SELECT `分区`, `托盘`, `运费` FROM uk_XLCarrier_postcode_fee")
+            cls._price_cache = {}
+            for row in c.cur.fetchall():
+                zone = str(row[0]) if row[0] else ""
+                tuopan = int(row[1]) if row[1] else 0
+                fee = float(row[2]) if row[2] else 0
+                cls._price_cache[(zone, tuopan)] = fee
+
     def __init__(self):
         super().__init__()
         self.base_fee = 0
         self.fuel_rate = 0.1
-    def is_remote(self,postcode):
+
+    def is_remote(self, postcode):
         """根据邮编分区，返回分区"""
         postcode_prefix = postcode.split()[0].upper()
-        postcode_prefix = str(postcode_prefix)
-        zone_df = self.ltl_zone[self.ltl_zone['邮编']== postcode_prefix]
-        if not zone_df.empty:
-            return zone_df['区域'].values[0]
+        zone = self._zone_cache.get(postcode_prefix)
+        if zone:
+            return zone
         return "不在配送范围内"
+
     def calculate_fee(self, packages, postcode):
         detail_amount = {
-            "base":0.00,    
-            "fuel":0.00,
-            "tail_amount":0.00
+            "base": 0.00,
+            "fuel": 0.00,
+            "tail_amount": 0.00
         }
         zone = self.is_remote(postcode)
         if zone == "不在配送范围内":
             detail_amount['tail_amount'] = 99999
             return detail_amount
         for package in packages:
-            tuopan = math.ceil(package.fst_size/120)
+            tuopan = math.ceil(package.fst_size / 120)
             tuopan = min(tuopan, 7)
-            base_df = self.ltl_cost[(self.ltl_cost['分区']==zone)&(self.ltl_cost['托盘']==tuopan)]
-            if base_df.empty:
+            fee = self._price_cache.get((zone, tuopan))
+            if fee is None:
                 detail_amount['tail_amount'] = 99999
                 return detail_amount
-            self.base_fee = base_df['运费'].values[0]
-            price = self.base_fee * tuopan/len(packages)
+            self.base_fee = fee
+            price = self.base_fee * tuopan / len(packages)
             detail_amount['base'] += price
         detail_amount['fuel'] = detail_amount['base'] * self.fuel_rate
-        detail_amount['tail_amount'] = detail_amount['base']+detail_amount['fuel']
+        detail_amount['tail_amount'] = detail_amount['base'] + detail_amount['fuel']
         return detail_amount
 
 # class KPDXLogistics_UK(TailLogistics):

logisticsClass/logisticsTail_US.py

@@ -5,6 +5,7 @@ import pandas
 from logisticsClass.logisticsBaseClass import LogisticsType, TailLogistics
 from data.us_zone import zone_west, zone_east
 from pathlib import Path
+from utils.gtools import MySQLconnect
 
 """
 port:west(default),east
@@ -84,6 +85,10 @@ class FedexLogistics(WestLogistics_US):
     """Fedex"""
     country = "United States"
     country_code = "US"
+
+    # 价格缓存(子类可覆盖)
+    _price_cache = None
+
     def __init__(self):
         super().__init__()
         self.volume_weight_ratio:int # lbs抛重系数
@@ -109,6 +114,16 @@ class FedexLogistics(WestLogistics_US):
         self.bigpackage_2:float # 大包裹费
         self.bigpackage_3:float
         self.bigpackage_5:float
+
+    def get_price(self, lbs: int, zone: int) -> float:
+        """获取价格(子类可覆盖)"""
+        if self._price_cache is not None:
+            return self._price_cache.get(lbs, {}).get(zone, 0)
+        # 默认从DataFrame获取(兼容旧代码)
+        if self.base_price is not None:
+            result = self.base_price[self.base_price['lbs.'] == lbs][zone]
+            return result.values[0] if len(result) > 0 else 0
+        return 0
         self.bigpackage_7:float
         self.bigpackage_peak:float # 大包裹旺季附加费
         self.return_package:float # 超大包裹（不可发）
@@ -185,8 +200,8 @@ class FedexLogistics(WestLogistics_US):
             detail_amount['big_package_peak'] += self.bigpackage_peak if package.girth_inch >130 or package.fst_inch >96 else 0
             detail_amount['residential_delivery'] += self.residential
             detail_amount['residential_peak'] += self.residential_peak
-            
-            detail_amount['base'] +=self.base_price[self.base_price['lbs.']==math.ceil(cal_weight)][zone].values[0]
+
+            detail_amount['base'] += self.get_price(math.ceil(cal_weight), zone)
 
         for key in detail_amount:
             if key!= 'tail_amount' and key!= 'fuel':
@@ -198,18 +213,37 @@ class FedexLogistics(WestLogistics_US):
 class FedexPPLogistics_US(FedexLogistics):
     company="Fedex-彩虹小马"
 
-    parent_current_directory = Path(__file__).parent.parent
-    price_path = parent_current_directory.joinpath("data")
-    _price_files = price_path.joinpath("美国快递.xlsx")
-    base_price = None
+    # 数据库价格缓存
+    _price_cache = None
+
     def __new__(cls):
-        if cls.base_price is None:
-            cls.base_price = pandas.read_excel(cls._price_files,sheet_name='邮差小马')
+        if cls._price_cache is None:
+            cls._load_from_db()
         return super().__new__(cls)
+
+    @classmethod
+    def _load_from_db(cls):
+        """从数据库加载价格数据"""
+        conn = MySQLconnect('logistics')
+        with conn as c:
+            c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_delivery_postpony")
+            cls._price_cache = {}
+            for row in c.cur.fetchall():
+                lbs = int(row[0])
+                cls._price_cache[lbs] = {
+                    2: float(row[1]) if row[1] else 0,
+                    3: float(row[2]) if row[2] else 0,
+                    4: float(row[3]) if row[3] else 0,
+                    5: float(row[4]) if row[4] else 0,
+                    6: float(row[5]) if row[5] else 0,
+                    7: float(row[6]) if row[6] else 0,
+                    8: float(row[7]) if row[7] else 0,
+                }
+
     def __init__(self):
         super().__init__()
         self.volume_weight_ratio=250 # lbs抛重系数
-        self.residential = 6.38 
+        self.residential = 6.38
         self.residential_peak = 0 # 0.33 0.6 # 报价表没写，账单有
         self.oversize_2 = 4.50
         self.oversize_3 = 4.99
@@ -231,7 +265,7 @@ class FedexPPLogistics_US(FedexLogistics):
         self.bigpackage_3 = 36.16
         self.bigpackage_5 = 38.57
         self.bigpackage_7 = 41.78
-        self.bigpackage_peak = 0 # 45.26 53.56# 大包裹旺季附加费 
+        self.bigpackage_peak = 0 # 45.26 53.56# 大包裹旺季附加费
         self.fuel_rate = 0.16 # 燃油费率
         self.return_package = 1419.34 # 超大包裹（不可发）
 
@@ -239,14 +273,33 @@ class FedexKHLogistics_US(FedexLogistics):
     """金宏亚"""
     company = "Fedex-金宏亚"
 
-    parent_current_directory = Path(__file__).parent.parent
-    price_path = parent_current_directory.joinpath("data")
-    _price_files = price_path.joinpath("美国快递.xlsx")
-    base_price = None
+    # 数据库价格缓存
+    _price_cache = None
+
     def __new__(cls):
-        if cls.base_price is None:
-            cls.base_price = pandas.read_excel(cls._price_files,sheet_name='金宏亚')
+        if cls._price_cache is None:
+            cls._load_from_db()
         return super().__new__(cls)
+
+    @classmethod
+    def _load_from_db(cls):
+        """从数据库加载价格数据"""
+        conn = MySQLconnect('logistics')
+        with conn as c:
+            c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_delivery_kinghood")
+            cls._price_cache = {}
+            for row in c.cur.fetchall():
+                lbs = int(row[0])
+                cls._price_cache[lbs] = {
+                    2: float(row[1]) if row[1] else 0,
+                    3: float(row[2]) if row[2] else 0,
+                    4: float(row[3]) if row[3] else 0,
+                    5: float(row[4]) if row[4] else 0,
+                    6: float(row[5]) if row[5] else 0,
+                    7: float(row[6]) if row[6] else 0,
+                    8: float(row[7]) if row[7] else 0,
+                }
+
     def __init__(self):
         super().__init__()
         self.volume_weight_ratio = 250 # lbs抛重系数
@@ -280,14 +333,33 @@ class FedexHOMELogistics_US(FedexLogistics):
     """FEDEX-HOME (1-35%-30%)"""
     company = "Fedex-HOME"
 
-    parent_current_directory = Path(__file__).parent.parent
-    price_path = parent_current_directory.joinpath("data")
-    _price_files = price_path.joinpath("美国快递.xlsx")
-    base_price = None
+    # 数据库价格缓存
+    _price_cache = None
+
     def __new__(cls):
-        if cls.base_price is None:
-            cls.base_price = pandas.read_excel(cls._price_files,sheet_name='FEDEX')
+        if cls._price_cache is None:
+            cls._load_from_db()
         return super().__new__(cls)
+
+    @classmethod
+    def _load_from_db(cls):
+        """从数据库加载价格数据"""
+        conn = MySQLconnect('logistics')
+        with conn as c:
+            c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_fedex_home")
+            cls._price_cache = {}
+            for row in c.cur.fetchall():
+                lbs = int(row[0])
+                cls._price_cache[lbs] = {
+                    2: float(row[1]) if row[1] else 0,
+                    3: float(row[2]) if row[2] else 0,
+                    4: float(row[3]) if row[3] else 0,
+                    5: float(row[4]) if row[4] else 0,
+                    6: float(row[5]) if row[5] else 0,
+                    7: float(row[6]) if row[6] else 0,
+                    8: float(row[7]) if row[7] else 0,
+                }
+
     def __init__(self):
         super().__init__()
         self.volume_weight_ratio = 250 # lbs抛重系数
@@ -316,18 +388,38 @@ class FedexHOMELogistics_US(FedexLogistics):
         self.bigpackage_peak =0 # 42.25# 大包裹旺季附加费
         self.return_package = 1325 # 超大包裹（不可发）
         self.fuel_rate = 0.18 # 燃油费率
+
 class FedexGROUDLogistics_US(FedexLogistics):
     """FEDEX-GROUD (1-35%-30%)"""
     company = "Fedex-GROUD"
 
-    parent_current_directory = Path(__file__).parent.parent
-    price_path = parent_current_directory.joinpath("data")
-    _price_files = price_path.joinpath("美国快递.xlsx")
-    base_price = None
+    # 数据库价格缓存(与FedexHOMELogistics_US共享us_fedex_home表)
+    _price_cache = None
+
     def __new__(cls):
-        if cls.base_price is None:
-            cls.base_price = pandas.read_excel(cls._price_files,sheet_name='FEDEX')
+        if cls._price_cache is None:
+            cls._load_from_db()
         return super().__new__(cls)
+
+    @classmethod
+    def _load_from_db(cls):
+        """从数据库加载价格数据"""
+        conn = MySQLconnect('logistics')
+        with conn as c:
+            c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_fedex_home")
+            cls._price_cache = {}
+            for row in c.cur.fetchall():
+                lbs = int(row[0])
+                cls._price_cache[lbs] = {
+                    2: float(row[1]) if row[1] else 0,
+                    3: float(row[2]) if row[2] else 0,
+                    4: float(row[3]) if row[3] else 0,
+                    5: float(row[4]) if row[4] else 0,
+                    6: float(row[5]) if row[5] else 0,
+                    7: float(row[6]) if row[6] else 0,
+                    8: float(row[7]) if row[7] else 0,
+                }
+
     def __init__(self):
         super().__init__()
         self.volume_weight_ratio = 250 # lbs抛重系数

logistics_service.py

@@ -0,0 +1,165 @@
+"""物流费用计算统一入口服务"""
+import re
+from typing import Dict, List, Any, Optional
+
+from utils.Package import Package, Package_group
+from utils.countryOperator import OperateCountry
+from logisticsClass.logisticsBaseClass import PortType
+
+
+class LogisticsService:
+    """物流费用计算统一服务"""
+
+    @staticmethod
+    def _detect_country(postcode: str) -> str:
+        """根据邮编格式自动识别国家"""
+        postcode = postcode.strip().upper()
+
+        # 英国邮编格式：字母+数字(+字母)+空格+数字+字母
+        # 支持格式: SW1A 1AA, M1 1AA, BT1 1AA, AA11 1AA 等
+        if re.match(r'^[A-Z]{1,2}[0-9][A-Z0-9]?\s?[0-9][A-Z]{2}$', postcode):
+            return "UK"
+
+        # 美国邮编格式：5位数字或5位-4位
+        if re.match(r'^\d{5}(-\d{4})?$', postcode):
+            return "US"
+
+        # 澳洲邮编格式：4位数字
+        if re.match(r'^\d{4}$', postcode):
+            return "AU"
+
+        # 欧洲格式（德国、法国等）
+        if re.match(r'^\d{5}$', postcode):
+            return "DE"  # 默认德国
+
+        raise ValueError(f"无法识别的邮编格式: {postcode}")
+
+    @staticmethod
+    def _parse_packages(packages_data: List[Dict]) -> Package_group:
+        """解析包裹数据"""
+        packages = []
+        for i, pkg in enumerate(packages_data):
+            name = pkg.get("name", f"包裹{i+1}")
+            length = pkg.get("length", 0)
+            width = pkg.get("width", 0)
+            height = pkg.get("height", 0)
+            weight = pkg.get("weight", 0)
+
+            package = Package(name, length, width, height, weight)
+            packages.append(package)
+
+        return Package_group(packages)
+
+    @staticmethod
+    def calculate(postcode: str, packages_data: List[Dict],
+                  port: PortType = PortType.DEFAULT) -> Dict[str, Any]:
+        """
+        计算物流费用并返回最优渠道
+
+        Args:
+            postcode: 收件人邮编
+            packages_data: 包裹数据列表，格式为：
+                [
+                    {"length": 63, "width": 59, "height": 48, "weight": 8000},  # 单位：cm, g
+                    ...
+                ]
+            port: 港口类型，默认DEFAULT
+
+        Returns:
+            包含最优渠道和所有渠道费用的字典
+        """
+        # 1. 识别国家
+        country = LogisticsService._detect_country(postcode)
+
+        # 2. 解析包裹
+        packages = LogisticsService._parse_packages(packages_data)
+
+        # 3. 创建国家操作对象
+        op_country = OperateCountry(country, port, packages, postcode)
+
+        # 4. 获取所有渠道费用
+        all_fees = op_country.get_all_tail_info()
+
+        # 5. 找出最优渠道
+        valid_fees = {k: v for k, v in all_fees.items() if v < 99999}
+        if not valid_fees:
+            return {
+                "country": country,
+                "postcode": postcode,
+                "optimal_channel": None,
+                "optimal_fee": None,
+                "currency": None,
+                "all_channels": all_fees,
+                "error": "所有渠道均不可用"
+            }
+
+        optimal_channel = min(valid_fees, key=valid_fees.get)
+        optimal_fee = valid_fees[optimal_channel]
+        currency = op_country.get_tail_currency(optimal_channel)
+
+        # 6. 构建结果
+        result = {
+            "country": country,
+            "postcode": postcode,
+            "optimal_channel": optimal_channel,
+            "optimal_fee": optimal_fee,
+            "currency": currency,
+            "all_channels": {},
+            "package_count": len(packages_data),
+            "total_weight": sum(p.weight for p in packages) / 1000,  # kg
+        }
+
+        # 7. 添加所有渠道详情
+        for company, fee in all_fees.items():
+            company_type = op_country.get_logistic_type(company)
+            company_currency = op_country.get_tail_currency(company)
+            result["all_channels"][company] = {
+                "fee": fee if fee < 99999 else None,
+                "currency": company_currency,
+                "type": company_type,
+                "available": fee < 99999
+            }
+
+        return result
+
+    @staticmethod
+    def calculate_us(postcode: str, packages_data: List[Dict],
+                     port: PortType = PortType.DEFAULT) -> Dict[str, Any]:
+        """计算美国物流费用"""
+        return LogisticsService.calculate(postcode, packages_data, port)
+
+    @staticmethod
+    def calculate_uk(postcode: str, packages_data: List[Dict],
+                    port: PortType = PortType.DEFAULT) -> Dict[str, Any]:
+        """计算英国物流费用"""
+        return LogisticsService.calculate(postcode, packages_data, port)
+
+    @staticmethod
+    def calculate_au(postcode: str, packages_data: List[Dict],
+                    port: PortType = PortType.DEFAULT) -> Dict[str, Any]:
+        """计算澳洲物流费用"""
+        return LogisticsService.calculate(postcode, packages_data, port)
+
+    @staticmethod
+    def calculate_eur(postcode: str, packages_data: List[Dict],
+                      port: PortType = PortType.DEFAULT) -> Dict[str, Any]:
+        """计算欧洲物流费用"""
+        return LogisticsService.calculate(postcode, packages_data, port)
+
+    @staticmethod
+    def get_company_detail(postcode: str, packages_data: List[Dict],
+                          company_name: str) -> Dict[str, Any]:
+        """获取指定物流公司的费用明细"""
+        country = LogisticsService._detect_country(postcode)
+        packages = LogisticsService._parse_packages(packages_data)
+        op_country = OperateCountry(country, PortType.DEFAULT, packages, postcode)
+
+        detail = op_country.get_detail_amount(company_name, packages, postcode)
+        currency = op_country.get_tail_currency(company_name)
+
+        return {
+            "company": company_name,
+            "currency": currency,
+            "detail": detail,
+            "total": detail.get("tail_amount", 0)
+        }

scripts/import_data.py

@@ -0,0 +1,469 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+数据导入脚本
+将XLSX文件中的数据导入到数据库
+"""
+import pandas as pd
+import numpy as np
+from pathlib import Path
+from utils.gtools import MySQLconnect
+from utils.config_manager import config
+
+
+class DataImporter:
+    """数据导入类"""
+
+    def __init__(self):
+        self.data_dir = Path(__file__).parent.parent / "data"
+
+    def get_connection(self, dbname: str = None):
+        """获取数据库连接"""
+        return MySQLconnect(dbname)
+
+    def execute_sql(self, sql: str, dbname: str = None):
+        """执行SQL语句"""
+        with self.get_connection(dbname) as conn:
+            conn.cur.execute(sql)
+            conn.con.commit()
+
+    def execute_many(self, sql: str, data: list, dbname: str = None):
+        """批量执行SQL"""
+        with self.get_connection(dbname) as conn:
+            conn.cur.executemany(sql, data)
+            conn.con.commit()
+
+    def truncate_table(self, table_name: str, dbname: str = None):
+        """清空表"""
+        self.execute_sql(f"TRUNCATE TABLE {table_name}", dbname)
+
+    # ==================== 英国数据导入 ====================
+
+    def import_uk_postcode_zone(self):
+        """导入英国邮编分区"""
+        print("导入英国邮编分区...")
+        df = pd.read_excel(self.data_dir / "英国卡派.xlsx", sheet_name="分区")
+        df.columns = ["postcode_prefix", "zone"]
+
+        data = []
+        for _, row in df.iterrows():
+            postcode = str(row["postcode_prefix"]).strip()
+            zone = str(row["zone"]).strip()
+            is_remote = 0
+            data.append((postcode, zone, is_remote))
+
+        sql = "INSERT IGNORE INTO uk_postcode_zone (postcode_prefix, zone, is_remote) VALUES (%s, %s, %s)"
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    def import_uk_kp_nv_price(self):
+        """导入英国卡派NV运费"""
+        print("导入英国卡派NV运费...")
+        df = pd.read_excel(self.data_dir / "英国卡派.xlsx", sheet_name="运费")
+        df.columns = ["zone", "tuopan", "fee"]
+
+        data = []
+        for _, row in df.iterrows():
+            zone = str(row["zone"]).strip()
+            tuopan = int(row["tuopan"])
+            fee = float(row["fee"])
+            data.append((zone, tuopan, fee))
+
+        sql = "INSERT INTO uk_kp_nv_price (zone, tuopan, fee) VALUES (%s, %s, %s)"
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    # ==================== 美国数据导入 ====================
+
+    def import_us_fedex_pp_price(self):
+        """导入美国Fedex邮差小马价格"""
+        print("导入美国Fedex邮差小马价格...")
+        df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name="邮差小马")
+
+        # 转换列名
+        cols = ["lbs"] + [str(c) for c in df.columns[1:]]
+        df.columns = cols
+
+        data = []
+        for _, row in df.iterrows():
+            lbs = int(row["lbs"])
+            row_data = [lbs]
+            for i in range(2, 9):
+                val = row.get(str(i), 0)
+                row_data.append(float(val) if pd.notna(val) else 0)
+            data.append(tuple(row_data))
+
+        sql = """INSERT INTO us_fedex_pp_price
+                 (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    def import_us_fedex_kh_price(self):
+        """导入美国Fedex金宏亚价格"""
+        print("导入美国Fedex金宏亚价格...")
+        df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name="金宏亚")
+
+        cols = ["lbs"] + [str(c) for c in df.columns[1:]]
+        df.columns = cols
+
+        data = []
+        for _, row in df.iterrows():
+            lbs = int(row["lbs"])
+            row_data = [lbs]
+            for i in range(2, 9):
+                val = row.get(str(i), 0)
+                row_data.append(float(val) if pd.notna(val) else 0)
+            data.append(tuple(row_data))
+
+        sql = """INSERT INTO us_fedex_kh_price
+                 (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    def import_us_fedex_price(self):
+        """导入美国Fedex价格"""
+        print("导入美国Fedex价格...")
+
+        for sheet_name in ["FEDEX", "FEDEX国内"]:
+            try:
+                df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name=sheet_name)
+                if "lbs." in df.columns:
+                    cols = ["lbs"] + [str(c) for c in df.columns[1:8]]
+                    df.columns = cols
+
+                    data = []
+                    for _, row in df.iterrows():
+                        lbs = int(row["lbs"])
+                        row_data = [lbs]
+                        for i in range(2, 9):
+                            val = row.get(str(i), 0)
+                            row_data.append(float(val) if pd.notna(val) else 0)
+                        data.append(tuple(row_data))
+
+                    table = "us_fedex_price" if "FEDEX" in sheet_name and "国内" not in sheet_name else "us_fedex_price"
+                    sql = f"""INSERT INTO {table}
+                             (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8)
+                             VALUES (%s, %s, %s, %s, %s, %s, %s, %s)"""
+                    self.execute_many(sql, data)
+                    print(f"  已导入 {len(data)} 条记录 ({sheet_name})")
+            except Exception as e:
+                print(f"  跳过 {sheet_name}: {e}")
+
+    def import_us_giga_price(self):
+        """导入美国GIGA价格"""
+        print("导入美国GIGA价格...")
+        df = pd.read_excel(self.data_dir / "GIGA base_fee_20240607223514.xlsx", sheet_name="Local Fee Data")
+
+        data = []
+        for _, row in df.iterrows():
+            zip_code = str(int(row["Zip Code"])) if pd.notna(row["Zip Code"]) else ""
+            delivery_warehouse = str(row["Delivery Warehouse"]) if pd.notna(row["Delivery Warehouse"]) else ""
+            general_area = str(row["General Area"]) if pd.notna(row["General Area"]) else ""
+            fee_type = str(row["Fee Type"]) if pd.notna(row["Fee Type"]) else ""
+            zone = str(row["Zone"]) if pd.notna(row["Zone"]) else ""
+            local_pickup_fee = float(row["Local Pickup Fee"]) if pd.notna(row["Local Pickup Fee"]) else 0
+            warehouse_handling_fee = float(row["Warehouse Handling Fee"]) if pd.notna(row["Warehouse Handling Fee"]) else 0
+            delivery_fee_rate = float(row["Delivery Fee Rate"]) if pd.notna(row["Delivery Fee Rate"]) else 0
+            additional_delivery_fee = float(row["Additional Delivery Fee"]) if pd.notna(row["Additional Delivery Fee"]) else 0
+            assembly_fee = float(row["Assembly Fee"]) if pd.notna(row["Assembly Fee"]) else 0
+
+            data.append((zip_code, delivery_warehouse, general_area, fee_type, zone,
+                        local_pickup_fee, warehouse_handling_fee, delivery_fee_rate,
+                        additional_delivery_fee, assembly_fee))
+
+        sql = """INSERT INTO us_giga_price
+                 (zip_code, delivery_warehouse, general_area, fee_type, zone,
+                  local_pickup_fee, warehouse_handling_fee, delivery_fee_rate,
+                  additional_delivery_fee, assembly_fee)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    def import_us_ceva_price(self):
+        """导入美国CEVA价格"""
+        print("导入美国CEVA价格...")
+
+        # CEVA base rate
+        df = pd.read_excel(self.data_dir / "CEVA.xlsx", sheet_name="ceva_base_rate")
+        df.columns = ["ceva_weight"] + list(df.columns[1:])
+
+        data = []
+        for _, row in df.iterrows():
+            ceva_weight = row["ceva_weight"]
+            if pd.isna(ceva_weight):
+                continue
+            row_data = [ceva_weight]
+            for col in df.columns[1:]:
+                val = row[col]
+                row_data.append(float(val) if pd.notna(val) else 0)
+            data.append(tuple(row_data))
+
+        sql = """INSERT INTO us_ceva_price
+                 (ceva_weight, zone_ca, zone_wa, zone_or, zone_nv, zone_az,
+                  zone_co, zone_ut, zone_nm, remote_area_surcharge)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录 (ceva_base_rate)")
+
+        # CEVA remote zone
+        df = pd.read_excel(self.data_dir / "CEVA.xlsx", sheet_name="remote_zone")
+        df.columns = ["postal_code", "state", "beyond_zone", "remote_type"]
+
+        data = []
+        for _, row in df.iterrows():
+            postal_code = str(int(row["postal_code"])) if pd.notna(row["postal_code"]) else ""
+            state = str(row["state"]) if pd.notna(row["state"]) else ""
+            beyond_zone = str(row["beyond_zone"]) if pd.notna(row["beyond_zone"]) else ""
+            remote_type = str(row["remote_type"]) if pd.notna(row["remote_type"]) else "standard"
+            data.append((postal_code, state, beyond_zone, remote_type))
+
+        sql = "INSERT IGNORE INTO us_ceva_zone (postal_code, state, beyond_zone, remote_type) VALUES (%s, %s, %s, %s)"
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录 (remote_zone)")
+
+    def import_us_metro_price(self):
+        """导入美国Metro价格"""
+        print("导入美国Metro价格...")
+
+        for sheet_name in ["cuft_25", "cuft_35", "over35_per_cuft", "over35_min"]:
+            try:
+                df = pd.read_excel(self.data_dir / "Metro.xlsx", sheet_name=sheet_name)
+                if "Origins" not in df.columns:
+                    continue
+
+                data = []
+                for _, row in df.iterrows():
+                    origins = str(row["Origins"]) if pd.notna(row["Origins"]) else ""
+                    row_data = [origins]
+                    for col in df.columns[1:]:
+                        val = row[col]
+                        row_data.append(float(val) if pd.notna(val) else 0)
+                    data.append(tuple(row_data))
+
+                cols = ", ".join([f"zone_{i}l" for i in range(1, 10)])
+                sql = f"INSERT INTO us_metro_price (origins, {cols}) VALUES (%s, {cols.replace('zone_', 'zone_')})"
+                # 简化处理
+                sql = "INSERT INTO us_metro_price (origins, zone_1l, zone_2l, zone_3l, zone_4l, zone_5l, zone_6l, zone_7l, zone_8l, zone_9l) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
+                self.execute_many(sql, data)
+                print(f"  已导入 {len(data)} 条记录 ({sheet_name})")
+            except Exception as e:
+                print(f"  跳过 {sheet_name}: {e}")
+
+        # Metro zone table
+        try:
+            df = pd.read_excel(self.data_dir / "Metro.xlsx", sheet_name="zone_table")
+            df.columns = ["zip_code", "new_zone_name"]
+
+            data = []
+            for _, row in df.iterrows():
+                zip_code = str(int(row["zip_code"])) if pd.notna(row["zip_code"]) else ""
+                zone = str(row["new_zone_name"]) if pd.notna(row["new_zone_name"]) else ""
+                data.append((zip_code, zone))
+
+            sql = "INSERT IGNORE INTO us_metro_zone (zip_code, new_zone_name) VALUES (%s, %s)"
+            self.execute_many(sql, data)
+            print(f"  已导入 {len(data)} 条记录 (zone_table)")
+        except Exception as e:
+            print(f"  zone_table: {e}")
+
+    def import_us_xmiles_zone(self):
+        """导入美国XMILES邮编"""
+        print("导入美国XMILES邮编...")
+        df = pd.read_excel(self.data_dir / "XMILES.xlsx", sheet_name="postcode_table")
+
+        # 处理可能的列名问题
+        cols = df.columns.tolist()
+        if len(cols) >= 2:
+            df.columns = ["postcode", "area"]
+
+            data = []
+            for _, row in df.iterrows():
+                postcode = str(int(row["postcode"])) if pd.notna(row["postcode"]) else ""
+                area = str(row["area"]) if pd.notna(row["area"]) else ""
+                data.append((postcode, area))
+
+            sql = "INSERT IGNORE INTO us_xmiles_zone (postcode, area) VALUES (%s, %s)"
+            self.execute_many(sql, data)
+            print(f"  已导入 {len(data)} 条记录")
+
+    def import_us_am_price(self):
+        """导入美国AM卡派价格"""
+        print("导入美国AM卡派价格...")
+
+        # price表
+        df = pd.read_excel(self.data_dir / "美国卡派-AM.xlsx", sheet_name="price")
+        df.columns = ["pu_zone", "dl_zone", "zone_combo", "minimum", "maximum",
+                     "fee_without_sc", "shipping_cost", "internalid", "externalid", "surcharge"]
+
+        data = []
+        for _, row in df.iterrows():
+            pu_zone = str(row["pu_zone"]) if pd.notna(row["pu_zone"]) else ""
+            dl_zone = str(row["dl_zone"]) if pd.notna(row["dl_zone"]) else ""
+            zone_combo = str(row["zone_combo"]) if pd.notna(row["zone_combo"]) else ""
+            minimum = float(row["minimum"]) if pd.notna(row["minimum"]) else 0
+            maximum = float(row["maximum"]) if pd.notna(row["maximum"]) else 0
+            fee_without_sc = float(row["fee_without_sc"]) if pd.notna(row["fee_without_sc"]) else 0
+            shipping_cost = float(row["shipping_cost"]) if pd.notna(row["shipping_cost"]) else 0
+            surcharge = float(row["surcharge"]) if pd.notna(row["surcharge"]) else 0
+
+            data.append((pu_zone, dl_zone, zone_combo, minimum, maximum,
+                        fee_without_sc, shipping_cost, surcharge))
+
+        sql = """INSERT INTO us_am_price
+                 (pu_zone, dl_zone, zone_combo, minimum_weight, maximum_weight,
+                  fee_without_sc, shipping_cost, surcharge)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录 (price)")
+
+        # postcode表
+        df = pd.read_excel(self.data_dir / "美国卡派-AM.xlsx", sheet_name="postcode_table")
+        df.columns = ["zip_code", "zone"]
+
+        data = []
+        for _, row in df.iterrows():
+            zip_code = str(int(row["zip_code"])) if pd.notna(row["zip_code"]) else ""
+            zone = str(row["zone"]) if pd.notna(row["zone"]) else ""
+            data.append((zip_code, zone))
+
+        sql = "INSERT IGNORE INTO us_am_postcode (zip_code, zone) VALUES (%s, %s)"
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录 (postcode_table)")
+
+    # ==================== 澳洲数据导入 ====================
+
+    def import_au_eparcel_price(self):
+        """导入澳洲eparcel价格"""
+        print("导入澳洲eparcel价格...")
+        df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="eparcel")
+
+        cols = ["post"] + [str(c) for c in df.columns[1:]]
+        df.columns = cols
+
+        data = []
+        for _, row in df.iterrows():
+            post = str(row["post"]) if pd.notna(row["post"]) else ""
+            row_data = [post]
+            for col in cols[1:]:
+                val = row.get(col, 0)
+                row_data.append(float(val) if pd.notna(val) else 0)
+            data.append(tuple(row_data))
+
+        sql = """INSERT INTO au_eparcel_price
+                 (post, weight_0_5, weight_1, weight_2, weight_3, weight_4,
+                  weight_5, weight_7, weight_10, weight_15)
+                 VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"""
+        self.execute_many(sql, data)
+        print(f"  已导入 {len(data)} 条记录")
+
+    def import_au_all(self):
+        """导入澳洲toll和allied数据"""
+        print("导入澳洲toll和allied数据...")
+
+        # toll
+        try:
+            df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="toll")
+            df.columns = ["post", "zone_1", "zone_2", "zone_3", "zone_4"]
+
+            data = []
+            for _, row in df.iterrows():
+                post = str(row["post"]) if pd.notna(row["post"]) else ""
+                data.append((post,
+                            float(row["zone_1"]) if pd.notna(row["zone_1"]) else 0,
+                            float(row["zone_2"]) if pd.notna(row["zone_2"]) else 0,
+                            float(row["zone_3"]) if pd.notna(row["zone_3"]) else 0,
+                            float(row["zone_4"]) if pd.notna(row["zone_4"]) else 0))
+
+            sql = "INSERT INTO au_toll_price (post, zone_1, zone_2, zone_3, zone_4) VALUES (%s, %s, %s, %s, %s)"
+            self.execute_many(sql, data)
+            print(f"  已导入 {len(data)} 条记录 (toll)")
+        except Exception as e:
+            print(f"  toll: {e}")
+
+        # allied
+        try:
+            df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="allied")
+            df.columns = ["post", "zone_1", "zone_2", "zone_3", "zone_4"]
+
+            data = []
+            for _, row in df.iterrows():
+                post = str(row["post"]) if pd.notna(row["post"]) else ""
+                data.append((post,
+                            float(row["zone_1"]) if pd.notna(row["zone_1"]) else 0,
+                            float(row["zone_2"]) if pd.notna(row["zone_2"]) else 0,
+                            float(row["zone_3"]) if pd.notna(row["zone_3"]) else 0,
+                            float(row["zone_4"]) if pd.notna(row["zone_4"]) else 0))
+
+            sql = "INSERT INTO au_allied_price (post, zone_1, zone_2, zone_3, zone_4) VALUES (%s, %s, %s, %s, %s)"
+            self.execute_many(sql, data)
+            print(f"  已导入 {len(data)} 条记录 (allied)")
+        except Exception as e:
+            print(f"  allied: {e}")
+
+    # ==================== 欧洲数据导入 ====================
+
+    def import_eur_dhl_price(self):
+        """导入欧洲DHL价格"""
+        print("导入欧洲DHL价格...")
+
+        try:
+            df = pd.read_excel(self.data_dir / "欧洲卡派.xlsx", sheet_name="DHL卡派IP报价")
+            df.columns = ["type", "country", "postalcode", "country_postalcode",
+                         "ip_1", "ip_2", "ip_3", "ip_4", "ip_5", "ip_6"]
+
+            data = []
+            for _, row in df.iterrows():
+                price_type = str(row["type"]) if pd.notna(row["type"]) else ""
+                country = str(row["country"]) if pd.notna(row["country"]) else ""
+                postalcode = str(row["postalcode"]) if pd.notna(row["postalcode"]) else ""
+                data.append((price_type, country, postalcode,
+                            float(row["ip_1"]) if pd.notna(row["ip_1"]) else 0,
+                            float(row["ip_2"]) if pd.notna(row["ip_2"]) else 0,
+                            float(row["ip_3"]) if pd.notna(row["ip_3"]) else 0,
+                            float(row["ip_4"]) if pd.notna(row["ip_4"]) else 0,
+                            float(row["ip_5"]) if pd.notna(row["ip_5"]) else 0,
+                            float(row["ip_6"]) if pd.notna(row["ip_6"]) else 0))
+
+            sql = """INSERT INTO eur_dhl_price
+                     (price_type, country, postalcode, ip_1, ip_2, ip_3, ip_4, ip_5, ip_6)
+                     VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)"""
+            self.execute_many(sql, data)
+            print(f"  已导入 {len(data)} 条记录")
+        except Exception as e:
+            print(f"  欧洲DHL: {e}")
+
+    # ==================== 主函数 ====================
+
+    def import_all(self):
+        """导入所有数据"""
+        print("开始导入数据...")
+
+        # 英国
+        self.import_uk_postcode_zone()
+        self.import_uk_kp_nv_price()
+
+        # 美国
+        self.import_us_fedex_pp_price()
+        self.import_us_fedex_kh_price()
+        self.import_us_fedex_price()
+        self.import_us_giga_price()
+        self.import_us_ceva_price()
+        self.import_us_metro_price()
+        self.import_us_xmiles_zone()
+        self.import_us_am_price()
+
+        # 澳洲
+        self.import_au_eparcel_price()
+        self.import_au_all()
+
+        # 欧洲
+        self.import_eur_dhl_price()
+
+        print("\n数据导入完成!")
+
+
+if __name__ == "__main__":
+    importer = DataImporter()
+    importer.import_all()

sell/logistic_price/uk_price.py

@@ -1,11 +1,37 @@
 # 英国海运订单费用,返回单个sku的订单费用和订单类型
-def uk_ocean_order_price(packages,k):
+import sys
+sys.path.append(r'D:\workspace\dags\logistics')
+import pandas as pd
+
+import math
+from utils.Package import Package, Package_group
+import re
+def uk_ocean_order_price(packages_dict_str,k):
     """
     入参:packages的类型是Package_group,里面包含多个Package,这是一个类,这个类今天在群里发过
     入参:k是物流分摊费,也就是k
 
     出参: 订单物流费，订单类型
     """
+
+    packages = Package_group()
+    def extract_number(value):
+    # 提取字符串中的第一个数字
+        match = re.search(r"[-+]?\d*\.\d+|\d+", str(value))
+        return float(match.group()) if match else 0.0
+    packages_dict = eval(packages_dict_str)
+    if len(packages_dict) == 0:
+        return (0,0)
+    for key, package in packages_dict.items():
+        package['长'] = extract_number(package['长'])
+        package['宽'] = extract_number(package['宽'])
+        package['高'] = extract_number(package['高'])
+        package['重量'] = extract_number(package['重量'])
+    
+        if package['长'] == 0 or package['宽'] == 0 or package['高'] == 0 or package['重量'] == 0:
+            return (0,0)
+        packages.add_package(Package(key,package['长'], package['宽'], package['高'], package['重量']))
+            
     # 计算uk经济直达费用
     order_fee = 0
     express_fee = 0
@@ -20,7 +46,7 @@ def uk_ocean_order_price(packages,k):
             base_fee = 3.7/0.359*1.3-k-0.8*package.get_volume_weight(6000)
         else:
             base_fee = 999999
-        if package.fst_size >=100 and package.sed_size >=60 and package.weight >=30000:
+        if package.fst_size >=100 or package.sed_size >=60 or package.weight >=30000:
             other_fee1 =45
             order_type1 += '大包裹'
         
@@ -44,4 +70,45 @@ def uk_ocean_order_price(packages,k):
     else:
         order_fee = ltl_fee
         order_type = order_type2
-    return max(round(order_fee,2),2), order_type
+    return max(round(order_fee,2),2), order_type
+if __name__ == '__main__':
+    import sys
+    sys.path.append(r'D:\workspace\dags\logistics')
+
+    sql = """SELECT 
+    t1.*,
+      t2.`物流分摊`
+      FROM 
+        `dim_erp_sku_package_vol_info`t1 left join ods.stg_bayshop_litfad_sku t2 on t1.erp_sku = t2.SKU
+      where id >=%s AND id <=%s
+        AND uk_price IS NULL
+         AND `物流分摊` IS NOT NULL 
+     """
+    from utils.gtools import MySQLconnect
+    from tqdm import tqdm
+    import pandas as pd 
+    with MySQLconnect('dwd') as db:
+        for i in tqdm(range(0,150)):
+            # count=0
+            print(i,"开始")
+            dfsql = sql % (i*100000, (i+1)*100000-1)
+            df = pd.read_sql(dfsql, db.engine())
+            if len(df) == 0:
+                continue
+            df[['us_price','logitcs_type']] = df.apply(lambda x: uk_ocean_order_price(x['erp_package_vol'],x['物流分摊']), axis=1, result_type='expand')
+            pd.io.sql.to_sql(df, "temp_update",db.eng, if_exists='replace', index=False )
+            #添加主键ID
+            modifysql = """ALTER TABLE `temp_update` ADD PRIMARY KEY (`id`)
+            """
+            db.cur.execute(modifysql)
+
+            # se = [tuple([round(x['us_price'],2),x['id']]) for y,x in df.iterrows()]
+            update_sql = """
+            UPDATE dim_erp_sku_package_vol_info AS target
+            JOIN temp_update AS src 
+                ON target.id = src.id  -- 根据主键关联
+            SET target.uk_price = src.us_price;"""
+            # db.cur.executemany(update_sql, se)
+            db.cur.execute(update_sql)
+            db.con.commit()
+            print(i,"结束")

sell/logistic_price/us_price.py

@@ -1,6 +1,11 @@
+import sys
+sys.path.append(r'D:\workspace\dags\logistics')
 import pandas as pd
+
 import math
-express_price = pd.read_excel(r'D:\test\logistics\data\售价尾端价格.xlsx', sheet_name='Sheet1')
+from utils.Package import Package, Package_group
+import re
+express_price = pd.read_excel(r'D:\workspace\dags\logistics\data\售价尾端价格.xlsx', sheet_name='Sheet1')
 key_column = express_price.iloc[:, 8]  # 第 I 列
 value_column = express_price.iloc[:, 9]  # 第 J 列
 small_column = express_price.iloc[:, 10]  # 第 K 列
@@ -9,7 +14,26 @@ air_small_dict = dict(zip(key_column, small_column))
 air_big_dict = dict(zip(key_column, big_column))
 # 转换成字典
 ocean_price_dict = dict(zip(key_column, value_column))
-def ocean_order_price(packages):
+def ocean_order_price(packages_dict_str):
+    
+    packages = Package_group()
+    def extract_number(value):
+    # 提取字符串中的第一个数字
+        match = re.search(r"[-+]?\d*\.\d+|\d+", str(value))
+        return float(match.group()) if match else 0.0
+    packages_dict = eval(packages_dict_str)
+    if len(packages_dict) == 0:
+        return (0,0)
+    for key, package in packages_dict.items():
+        package['长'] = extract_number(package['长'])
+        package['宽'] = extract_number(package['宽'])
+        package['高'] = extract_number(package['高'])
+        package['重量'] = extract_number(package['重量'])
+    
+        if package['长'] == 0 or package['宽'] == 0 or package['高'] == 0 or package['重量'] == 0:
+            return (0,0)
+        packages.add_package(Package(key,package['长'], package['宽'], package['高'], package['重量']))
+            
     express_fee = 0 # 快递基础费
     long_fee = 0 # 超长费
     weight_fee = 0 # 超重费
@@ -19,7 +43,8 @@ def ocean_order_price(packages):
     express_type_length = ''
     for package in packages:
         for key, value in ocean_price_dict.items():
-            if package.weight <=key:
+            
+            if max(package.get_volume_weight(8500)*1000, package.weight) <=key:
                 express_fee+=value
                 break
         if package.fst_size>=116 or package.sed_size>=71 or package.girth>=251:
@@ -32,6 +57,7 @@ def ocean_order_price(packages):
         if package.fst_size>=238 or package.girth>=315:
             big_fee+=61.6
             express_type_length ="大包裹"
+    express_fee = 9999999 if express_fee ==0 else express_fee   
     express_fee = express_fee + long_fee + weight_fee + big_fee
     express_type = express_type_length + express_type_weight
 
@@ -127,4 +153,34 @@ def air_order_price(packages):
         else:
             express_fee+=(((min(max(package.density,37),337)*0.093+27.7-1.08)/6+0.65-1.06)*package.get_volume_weight(8500))/0.45+price
             express_type='FEDEX'
-    return express_fee, express_type
+    return express_fee, express_type
+
+if __name__ == '__main__':
+    sql = "SELECT * FROM `dim_erp_sku_package_vol_info` where id >=%s AND id <=%s AND logis_type IS NULL"
+    from utils.gtools import MySQLconnect
+    from tqdm import tqdm
+    with MySQLconnect('dwd') as db:
+        for i in tqdm(range(1,150)):
+            # count=0
+            print(i,"开始")
+            dfsql = sql % (i*100000, (i+1)*100000-1)
+            df = pd.read_sql(dfsql, db.engine())
+            if len(df) == 0:
+                continue
+            df[['us_price','logitcs_type']] = df.apply(lambda x: ocean_order_price(x['erp_package_vol']), axis=1, result_type='expand')
+            pd.io.sql.to_sql(df, "temp_update",db.eng, if_exists='replace', index=False )
+            #添加主键ID
+            modifysql = """ALTER TABLE `temp_update` ADD PRIMARY KEY (`id`)
+            """
+            db.cur.execute(modifysql)
+
+            # se = [tuple([round(x['us_price'],2),x['id']]) for y,x in df.iterrows()]
+            update_sql = """
+            UPDATE dim_erp_sku_package_vol_info AS target
+            JOIN temp_update AS src 
+                ON target.id = src.id  -- 根据主键关联
+            SET target.logis_type = src.logitcs_type;"""
+            # db.cur.executemany(update_sql, se)
+            db.cur.execute(update_sql)
+            db.con.commit()
+            print(i,"结束")

sql/create_tables.sql

@@ -0,0 +1,337 @@
+-- 物流费用计算系统数据库表结构
+-- 创建数据库: logistics
+
+-- ============================================
+-- 物流公司配置表
+-- ============================================
+CREATE TABLE IF NOT EXISTS logistics_company (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    company_code VARCHAR(50) NOT NULL COMMENT '公司代码',
+    company_name VARCHAR(100) NOT NULL COMMENT '公司名称',
+    country VARCHAR(10) NOT NULL COMMENT '国家代码: US, UK, AU, DE等',
+    logistics_type VARCHAR(20) NOT NULL COMMENT '物流类型: EXPRESS, COURIER, OCEAN, AIR',
+    port VARCHAR(20) DEFAULT 'DEFAULT' COMMENT '港口: DEFAULT, WEST, EAST等',
+    currency VARCHAR(10) DEFAULT 'USD' COMMENT '货币',
+    active TINYINT DEFAULT 1 COMMENT '是否启用: 0-禁用, 1-启用',
+    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
+    UNIQUE KEY uk_company_code (company_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='物流公司配置表';
+
+-- ============================================
+-- 英国物流价格表
+-- ============================================
+
+-- 英国卡派-分区表
+CREATE TABLE IF NOT EXISTS uk_postcode_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode_prefix VARCHAR(10) NOT NULL COMMENT '邮编前缀',
+    zone VARCHAR(10) NOT NULL COMMENT '分区',
+    is_remote TINYINT DEFAULT 0 COMMENT '是否偏远: 0-否, 1-是',
+    UNIQUE KEY uk_postcode (postcode_prefix)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='英国邮编分区表';
+
+-- 英国卡派-运费表
+CREATE TABLE IF NOT EXISTS uk_kp_nv_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    zone VARCHAR(10) NOT NULL COMMENT '分区',
+    tuopan INT NOT NULL COMMENT '托盘数',
+    fee DECIMAL(10,2) NOT NULL COMMENT '运费',
+    INDEX idx_zone (zone)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='英国卡派NV运费表';
+
+-- ============================================
+-- 美国物流价格表
+-- ============================================
+
+-- 美国邮编分区表
+CREATE TABLE IF NOT EXISTS us_postcode_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(5) NOT NULL COMMENT '邮编(5位)',
+    port VARCHAR(20) DEFAULT 'west' COMMENT '港口: west, east',
+    zone VARCHAR(10) COMMENT '分区',
+    remote_type INT DEFAULT 0 COMMENT '偏远类型: 0-非偏远, 1-偏远, 2-超偏远, 3-超超偏远',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国邮编分区表';
+
+-- 美国快递-邮差小马 价格表
+CREATE TABLE IF NOT EXISTS us_fedex_pp_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    lbs INT NOT NULL COMMENT '重量(磅)',
+    zone_2 DECIMAL(10,2) COMMENT '2区价格',
+    zone_3 DECIMAL(10,2) COMMENT '3区价格',
+    zone_4 DECIMAL(10,2) COMMENT '4区价格',
+    zone_5 DECIMAL(10,2) COMMENT '5区价格',
+    zone_6 DECIMAL(10,2) COMMENT '6区价格',
+    zone_7 DECIMAL(10,2) COMMENT '7区价格',
+    zone_8 DECIMAL(10,2) COMMENT '8区价格',
+    INDEX idx_lbs (lbs)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Fedex邮差小马价格表';
+
+-- 美国快递-金宏亚 价格表
+CREATE TABLE IF NOT EXISTS us_fedex_kh_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    lbs INT NOT NULL COMMENT '重量(磅)',
+    zone_2 DECIMAL(10,2) COMMENT '2区价格',
+    zone_3 DECIMAL(10,2) COMMENT '3区价格',
+    zone_4 DECIMAL(10,2) COMMENT '4区价格',
+    zone_5 DECIMAL(10,2) COMMENT '5区价格',
+    zone_6 DECIMAL(10,2) COMMENT '6区价格',
+    zone_7 DECIMAL(10,2) COMMENT '7区价格',
+    zone_8 DECIMAL(10,2) COMMENT '8区价格',
+    INDEX idx_lbs (lbs)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Fedex金宏亚价格表';
+
+-- 美国快递-FEDEX 价格表
+CREATE TABLE IF NOT EXISTS us_fedex_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    lbs INT NOT NULL COMMENT '重量(磅)',
+    zone_2 DECIMAL(10,2) COMMENT '2区价格',
+    zone_3 DECIMAL(10,2) COMMENT '3区价格',
+    zone_4 DECIMAL(10,2) COMMENT '4区价格',
+    zone_5 DECIMAL(10,2) COMMENT '5区价格',
+    zone_6 DECIMAL(10,2) COMMENT '6区价格',
+    zone_7 DECIMAL(10,2) COMMENT '7区价格',
+    zone_8 DECIMAL(10,2) COMMENT '8区价格',
+    INDEX idx_lbs (lbs)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国FEDEX价格表';
+
+-- 美国卡派-GIGA 价格表
+CREATE TABLE IF NOT EXISTS us_giga_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    zip_code VARCHAR(5) NOT NULL COMMENT '邮编',
+    delivery_warehouse VARCHAR(50) COMMENT '仓库',
+    general_area VARCHAR(50) COMMENT '地区',
+    fee_type VARCHAR(20) COMMENT '费用类型',
+    zone VARCHAR(10) COMMENT '分区',
+    local_pickup_fee DECIMAL(10,2) COMMENT '本地取货费',
+    warehouse_handling_fee DECIMAL(10,2) COMMENT '仓库操作费',
+    delivery_fee_rate DECIMAL(10,2) COMMENT '配送费率',
+    additional_delivery_fee DECIMAL(10,2) COMMENT '额外配送费',
+    assembly_fee DECIMAL(10,2) COMMENT '装配费',
+    INDEX idx_zip (zip_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国GIGA价格表';
+
+-- 美国卡派-CEVA 价格表
+CREATE TABLE IF NOT EXISTS us_ceva_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    ceva_weight INT NOT NULL COMMENT 'CEVA重量',
+    zone_ca DECIMAL(10,2) COMMENT 'CA区价格',
+    zone_wa DECIMAL(10,2) COMMENT 'WA区价格',
+    zone_or DECIMAL(10,2) COMMENT 'OR区价格',
+    zone_nv DECIMAL(10,2) COMMENT 'NV区价格',
+    zone_az DECIMAL(10,2) COMMENT 'AZ区价格',
+    zone_co DECIMAL(10,2) COMMENT 'CO区价格',
+    zone_ut DECIMAL(10,2) COMMENT 'UT区价格',
+    zone_nm DECIMAL(10,2) COMMENT 'NM区价格',
+    remote_area_surcharge DECIMAL(10,2) COMMENT '偏远地区附加费',
+    INDEX idx_weight (ceva_weight)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA价格表';
+
+-- 美国卡派-CEVA 邮编分区表
+CREATE TABLE IF NOT EXISTS us_ceva_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postal_code VARCHAR(5) NOT NULL COMMENT '邮编',
+    state VARCHAR(20) COMMENT '州',
+    beyond_zone VARCHAR(10) COMMENT '超出分区',
+    remote_type VARCHAR(20) DEFAULT 'standard' COMMENT '偏远类型: standard, remote',
+    INDEX idx_postal (postal_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA邮编分区表';
+
+-- 美国卡派-CEVA 分区表
+CREATE TABLE IF NOT EXISTS us_ceva_zone_grade (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    to_state VARCHAR(20) NOT NULL COMMENT '目的地州',
+    ca DECIMAL(10,2) COMMENT 'CA分区',
+    wa DECIMAL(10,2) COMMENT 'WA分区',
+    INDEX idx_state (to_state)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA分区等级表';
+
+-- 美国卡派-Metro 价格表
+CREATE TABLE IF NOT EXISTS us_metro_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    origins VARCHAR(20) NOT NULL COMMENT '出发地',
+    zone_1l DECIMAL(10,2) COMMENT 'Zone 1L价格',
+    zone_2l DECIMAL(10,2) COMMENT 'Zone 2L价格',
+    zone_3l DECIMAL(10,2) COMMENT 'Zone 3L价格',
+    zone_4l DECIMAL(10,2) COMMENT 'Zone 4L价格',
+    zone_5l DECIMAL(10,2) COMMENT 'Zone 5L价格',
+    zone_6l DECIMAL(10,2) COMMENT 'Zone 6L价格',
+    zone_7l DECIMAL(10,2) COMMENT 'Zone 7L价格',
+    zone_8l DECIMAL(10,2) COMMENT 'Zone 8L价格',
+    zone_9l DECIMAL(10,2) COMMENT 'Zone 9L价格',
+    INDEX idx_origins (origins)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro价格表';
+
+-- 美国卡派-Metro 邮编分区表
+CREATE TABLE IF NOT EXISTS us_metro_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    zip_code VARCHAR(5) NOT NULL COMMENT '邮编',
+    new_zone_name VARCHAR(20) COMMENT '新分区名',
+    INDEX idx_zip (zip_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro邮编分区表';
+
+-- 美国卡派-Metro 偏远表
+CREATE TABLE IF NOT EXISTS us_metro_remote (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    zip_code VARCHAR(5) NOT NULL COMMENT '邮编',
+    area_type VARCHAR(50) COMMENT '区域类型',
+    INDEX idx_zip (zip_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro偏远表';
+
+-- 美国卡派-XMILES 邮编表
+CREATE TABLE IF NOT EXISTS us_xmiles_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(5) NOT NULL COMMENT '邮编',
+    area VARCHAR(20) COMMENT '地区',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国XMILES邮编分区表';
+
+-- 美国卡派-AM 价格表
+CREATE TABLE IF NOT EXISTS us_am_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    pu_zone VARCHAR(5) NOT NULL COMMENT 'PU区',
+    dl_zone VARCHAR(5) NOT NULL COMMENT 'DL区',
+    zone_combo VARCHAR(10) NOT NULL COMMENT '分区组合',
+    minimum_weight DECIMAL(10,2) NOT NULL COMMENT '最小重量',
+    maximum_weight DECIMAL(10,2) NOT NULL COMMENT '最大重量',
+    fee_without_sc DECIMAL(10,2) COMMENT '无附加费价格',
+    shipping_cost DECIMAL(10,2) COMMENT '运费',
+    surcharge DECIMAL(10,2) DEFAULT 0 COMMENT '附加费',
+    INDEX idx_zone_combo (zone_combo)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国AM卡派价格表';
+
+-- 美国卡派-AM 邮编表
+CREATE TABLE IF NOT EXISTS us_am_postcode (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    zip_code VARCHAR(5) NOT NULL COMMENT '邮编',
+    zone VARCHAR(5) NOT NULL COMMENT '分区',
+    INDEX idx_zip (zip_code)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国AM卡派邮编表';
+
+-- ============================================
+-- 澳洲物流价格表
+-- ============================================
+
+-- 澳洲eparcel价格表
+CREATE TABLE IF NOT EXISTS au_eparcel_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    post VARCHAR(20) NOT NULL COMMENT '邮寄方式',
+    weight_0_5 DECIMAL(10,2) COMMENT '0.5kg价格',
+    weight_1 DECIMAL(10,2) COMMENT '1kg价格',
+    weight_2 DECIMAL(10,2) COMMENT '2kg价格',
+    weight_3 DECIMAL(10,2) COMMENT '3kg价格',
+    weight_4 DECIMAL(10,2) COMMENT '4kg价格',
+    weight_5 DECIMAL(10,2) COMMENT '5kg价格',
+    weight_7 DECIMAL(10,2) COMMENT '7kg价格',
+    weight_10 DECIMAL(10,2) COMMENT '10kg价格',
+    weight_15 DECIMAL(10,2) COMMENT '15kg价格',
+    INDEX idx_post (post)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲eparcel价格表';
+
+-- 澳洲eparcel邮编表
+CREATE TABLE IF NOT EXISTS au_eparcel_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(10) NOT NULL COMMENT '邮编',
+    zone VARCHAR(10) COMMENT '分区',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲eparcel邮编表';
+
+-- 澳洲toll价格表
+CREATE TABLE IF NOT EXISTS au_toll_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    post VARCHAR(20) NOT NULL COMMENT '邮寄方式',
+    zone_1 DECIMAL(10,2) COMMENT '1区价格',
+    zone_2 DECIMAL(10,2) COMMENT '2区价格',
+    zone_3 DECIMAL(10,2) COMMENT '3区价格',
+    zone_4 DECIMAL(10,2) COMMENT '4区价格',
+    INDEX idx_post (post)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll价格表';
+
+-- 澳洲toll邮编表
+CREATE TABLE IF NOT EXISTS au_toll_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(10) NOT NULL COMMENT '邮编',
+    zone VARCHAR(10) COMMENT '分区',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll邮编表';
+
+-- 澳洲toll偏远表
+CREATE TABLE IF NOT EXISTS au_toll_remote (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(10) NOT NULL COMMENT '邮编',
+    remote_type VARCHAR(20) COMMENT '偏远类型',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll偏远表';
+
+-- 澳洲allied价格表
+CREATE TABLE IF NOT EXISTS au_allied_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    post VARCHAR(20) NOT NULL COMMENT '邮寄方式',
+    zone_1 DECIMAL(10,2) COMMENT '1区价格',
+    zone_2 DECIMAL(10,2) COMMENT '2区价格',
+    zone_3 DECIMAL(10,2) COMMENT '3区价格',
+    zone_4 DECIMAL(10,2) COMMENT '4区价格',
+    INDEX idx_post (post)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied价格表';
+
+-- 澳洲allied邮编表
+CREATE TABLE IF NOT EXISTS au_allied_zone (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(10) NOT NULL COMMENT '邮编',
+    zone VARCHAR(10) COMMENT '分区',
+    remote_zone VARCHAR(10) COMMENT '偏远分区',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied邮编表';
+
+-- 澳洲allied偏远表
+CREATE TABLE IF NOT EXISTS au_allied_remote (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    postcode VARCHAR(10) NOT NULL COMMENT '邮编',
+    remote_type VARCHAR(20) COMMENT '偏远类型',
+    INDEX idx_postcode (postcode)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied偏远表';
+
+-- ============================================
+-- 欧洲物流价格表
+-- ============================================
+
+-- 欧洲卡派-DHL价格表
+CREATE TABLE IF NOT EXISTS eur_dhl_price (
+    id INT AUTO_INCREMENT PRIMARY KEY,
+    price_type VARCHAR(20) NOT NULL COMMENT '价格类型',
+    country VARCHAR(50) NOT NULL COMMENT '国家',
+    postalcode VARCHAR(10) COMMENT '邮编',
+    ip_1 DECIMAL(10,2) COMMENT '1IP价格',
+    ip_2 DECIMAL(10,2) COMMENT '2IP价格',
+    ip_3 DECIMAL(10,2) COMMENT '3IP价格',
+    ip_4 DECIMAL(10,2) COMMENT '4IP价格',
+    ip_5 DECIMAL(10,2) COMMENT '5IP价格',
+    ip_6 DECIMAL(10,2) COMMENT '6IP价格',
+    INDEX idx_country (country)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='欧洲DHL卡派价格表';
+
+-- ============================================
+-- 物流公司配置数据
+-- ============================================
+INSERT INTO logistics_company (company_code, company_name, country, logistics_type, port, currency) VALUES
+-- 英国
+('UK_DPD', '智谷-DPD', 'UK', 'EXPRESS', 'DEFAULT', 'GBP'),
+('UK_BIG', '智谷-大件', 'UK', 'COURIER', 'DEFAULT', 'GBP'),
+('UK_KPZG', '海GB-卡派', 'UK', 'COURIER', 'DEFAULT', 'GBP'),
+('UK_KPNV', '卡派-NV', 'UK', 'COURIER', 'DEFAULT', 'GBP'),
+-- 美国
+('US_FEDEX_PP', 'Fedex-邮差小马', 'US', 'EXPRESS', 'WEST', 'USD'),
+('US_FEDEX_KH', 'Fedex-金宏亚', 'US', 'EXPRESS', 'WEST', 'USD'),
+('US_FEDEX_HOME', 'Fedex-HOME', 'US', 'EXPRESS', 'WEST', 'USD'),
+('US_FEDEX_GROUND', 'Fedex-GROUND', 'US', 'EXPRESS', 'WEST', 'USD'),
+('US_GIGA', '大健-GIGA', 'US', 'COURIER', 'DEFAULT', 'USD'),
+('US_CEVA', '大健-CEVA', 'US', 'COURIER', 'DEFAULT', 'USD'),
+('US_METRO', 'Metro-SAIR', 'US', 'COURIER', 'DEFAULT', 'USD'),
+('US_XMILES', 'XMILES-SAIR', 'US', 'COURIER', 'DEFAULT', 'USD'),
+('US_AM_WEST', 'AM-美西', 'US', 'COURIER', 'WEST', 'USD'),
+('US_AM_EAST', 'AM-美东', 'US', 'COURIER', 'EAST', 'USD'),
+-- 澳洲
+('AU_EPARCEL', 'AU-eparcel', 'AU', 'EXPRESS', 'DEFAULT', 'AUD'),
+('AU_TOLL', 'AU-Toll', 'AU', 'COURIER', 'DEFAULT', 'AUD'),
+('AU_ALLIED', 'AU-Allied', 'AU', 'COURIER', 'DEFAULT', 'AUD');

tests/test_logistics_service.py

@@ -0,0 +1,176 @@
+"""物流费用计算服务测试文件"""
+import pytest
+from logistics_service import LogisticsService
+from logisticsClass.logisticsBaseClass import PortType
+
+
+class TestLogisticsService:
+    """物流服务测试类"""
+
+    def test_detect_country_uk(self):
+        """测试英国邮编识别"""
+        assert LogisticsService._detect_country("PA2 9BF") == "UK"
+        assert LogisticsService._detect_country("SW1A 1AA") == "UK"
+        assert LogisticsService._detect_country("BT1 1AA") == "UK"
+
+    def test_detect_country_us(self):
+        """测试美国邮编识别"""
+        assert LogisticsService._detect_country("10001") == "US"
+        assert LogisticsService._detect_country("10001-1234") == "US"
+        assert LogisticsService._detect_country("90210") == "US"
+
+    def test_detect_country_au(self):
+        """测试澳洲邮编识别"""
+        assert LogisticsService._detect_country("2000") == "AU"
+        assert LogisticsService._detect_country("3000") == "AU"
+
+    def test_parse_packages(self):
+        """测试包裹解析"""
+        packages_data = [
+            {"name": "包裹1", "length": 63, "width": 59, "height": 48, "weight": 8000},
+            {"name": "包裹2", "length": 50, "width": 40, "height": 30, "weight": 5000},
+        ]
+        packages = LogisticsService._parse_packages(packages_data)
+
+        assert len(packages.packages) == 2
+        assert packages.packages[0].fst_size == 63
+        assert packages.packages[1].fst_size == 50
+
+    def test_parse_packages_default_name(self):
+        """测试包裹解析-默认名称"""
+        packages_data = [
+            {"length": 63, "width": 59, "height": 48, "weight": 8000},
+        ]
+        packages = LogisticsService._parse_packages(packages_data)
+
+        assert len(packages.packages) == 1
+
+    def test_calculate_uk(self):
+        """测试英国物流费用计算"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+        result = LogisticsService.calculate_uk("PA2 9BF", packages)
+
+        assert result["country"] == "UK"
+        assert result["postcode"] == "PA2 9BF"
+        assert result["optimal_channel"] is not None
+        assert result["optimal_fee"] is not None
+        assert result["currency"] == "GBP"
+        assert len(result["all_channels"]) > 0
+
+    def test_calculate_uk_london(self):
+        """测试英国伦敦邮编"""
+        packages = [{"length": 30, "width": 20, "height": 10, "weight": 2000}]
+        result = LogisticsService.calculate_uk("SW1A 1AA", packages)
+
+        assert result["country"] == "UK"
+        assert result["optimal_channel"] is not None
+
+    def test_calculate_us(self):
+        """测试美国物流费用计算"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+        result = LogisticsService.calculate_us("10001", packages)
+
+        assert result["country"] == "US"
+        assert result["postcode"] == "10001"
+        assert result["optimal_channel"] is not None
+        assert result["optimal_fee"] is not None
+        assert result["currency"] == "USD"
+
+    def test_calculate_us_west(self):
+        """测试美国美西邮编"""
+        packages = [{"length": 50, "width": 40, "height": 30, "weight": 5000}]
+        result = LogisticsService.calculate_us("90001", packages)
+
+        assert result["country"] == "US"
+        assert result["optimal_channel"] is not None
+
+    def test_calculate_auto_detect(self):
+        """测试自动识别国家"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+
+        # 英国
+        result_uk = LogisticsService.calculate("PA2 9BF", packages)
+        assert result_uk["country"] == "UK"
+
+        # 美国
+        result_us = LogisticsService.calculate("10001", packages)
+        assert result_us["country"] == "US"
+
+    def test_calculate_multiple_packages(self):
+        """测试多包裹计算"""
+        packages = [
+            {"length": 63, "width": 59, "height": 48, "weight": 8000},
+            {"length": 50, "width": 40, "height": 30, "weight": 5000},
+            {"length": 40, "width": 30, "height": 20, "weight": 3000},
+        ]
+        result = LogisticsService.calculate_uk("PA2 9BF", packages)
+
+        assert result["package_count"] == 3
+        assert result["total_weight"] == 16.0  # kg
+
+    def test_get_company_detail(self):
+        """测试获取指定物流公司详情"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+        detail = LogisticsService.get_company_detail("PA2 9BF", packages, "智谷-DPD")
+
+        assert detail["company"] == "智谷-DPD"
+        assert detail["currency"] == "GBP"
+        assert "detail" in detail
+        assert "total" in detail
+
+    def test_invalid_postcode(self):
+        """测试无效邮编"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+
+        with pytest.raises(ValueError):
+            LogisticsService.calculate("invalid", packages)
+
+    def test_result_structure(self):
+        """测试返回结果结构"""
+        packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}]
+        result = LogisticsService.calculate_uk("PA2 9BF", packages)
+
+        # 验证必需字段
+        required_fields = [
+            "country", "postcode", "optimal_channel", "optimal_fee",
+            "currency", "all_channels", "package_count", "total_weight"
+        ]
+        for field in required_fields:
+            assert field in result, f"缺少字段: {field}"
+
+        # 验证渠道详情结构
+        for company, info in result["all_channels"].items():
+            assert "fee" in info
+            assert "currency" in info
+            assert "type" in info
+            assert "available" in info
+
+
+class TestPackageCalculation:
+    """包裹计算测试类"""
+
+    def test_small_package(self):
+        """测试小包裹"""
+        packages = [{"length": 20, "width": 15, "height": 10, "weight": 500}]
+        result = LogisticsService.calculate_uk("SW1A 1AA", packages)
+
+        assert result["optimal_fee"] is not None
+
+    def test_large_package(self):
+        """测试大包裹"""
+        packages = [{"length": 200, "width": 100, "height": 80, "weight": 50000}]
+        result = LogisticsService.calculate_uk("PA2 9BF", packages)
+
+        # 大包裹可能被某些渠道拒绝
+        assert result is not None
+
+    def test_heavy_package(self):
+        """测试重包裹"""
+        packages = [{"length": 50, "width": 40, "height": 30, "weight": 80000}]
+        result = LogisticsService.calculate_us("10001", packages)
+
+        assert result is not None
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

utils/config_manager.py

@@ -0,0 +1,53 @@
+"""配置管理模块"""
+import json
+import os
+from pathlib import Path
+from typing import Any, Dict
+
+
+class ConfigManager:
+    """配置管理器"""
+
+    _instance = None
+    _config: Dict[str, Any] = {}
+
+    def __new__(cls):
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+        return cls._instance
+
+    def __init__(self):
+        if not self._config:
+            self._load_config()
+
+    def _load_config(self):
+        """加载配置文件"""
+        config_dir = Path(__file__).parent.parent / "config"
+        config_file = config_dir / "database.json"
+
+        if not config_file.exists():
+            raise FileNotFoundError(f"配置文件不存在: {config_file}")
+
+        with open(config_file, "r", encoding="utf-8") as f:
+            self._config = json.load(f)
+
+    def get(self, key: str, default: Any = None) -> Any:
+        """获取配置项"""
+        keys = key.split(".")
+        value = self._config
+        for k in keys:
+            if isinstance(value, dict):
+                value = value.get(k)
+                if value is None:
+                    return default
+            else:
+                return default
+        return value
+
+    def get_database_config(self) -> Dict[str, Any]:
+        """获取数据库配置"""
+        return self._config.get("database", {})
+
+
+# 全局配置实例
+config = ConfigManager()

utils/gtools.py

@@ -1,13 +1,22 @@
 import pymysql
 from sqlalchemy import create_engine
+from utils.config_manager import config
 
 
 class MySQLconnect():
-    def __init__(self, dbname: str):
-        if isinstance(dbname, str):
-            self.dbname = dbname
-            self.host = '192.168.100.33'
-        else:
+    def __init__(self, dbname: str = None):
+        db_config = config.get_database_config()
+        self.host = db_config.get("host", "192.168.100.33")
+        self.port = db_config.get("port", 3306)
+        self.user = db_config.get("username", "zhenggantian")
+        self.password = db_config.get("password", "123456")
+        self.dbname = dbname or db_config.get("database", "logistics")
+        self.charset = db_config.get("charset", "utf8")
+        self.pool_size = db_config.get("pool_size", 10)
+        self.max_overflow = db_config.get("max_overflow", 5)
+        self.pool_recycle = db_config.get("pool_recycle", 3600)
+
+        if not isinstance(self.dbname, str):
             raise TypeError("dbname must be a string")
 
     def __enter__(self):
@@ -24,9 +33,19 @@ class MySQLconnect():
             raise
 
     def engine(self):
-        return create_engine("mysql+pymysql://zhenggantian:123456@" + self.host + f":3306/{self.dbname}",
-                              pool_size=10, max_overflow=5, pool_recycle=3600)
+        return create_engine(
+            f"mysql+pymysql://{self.user}:{self.password}@{self.host}:{self.port}/{self.dbname}",
+            pool_size=self.pool_size,
+            max_overflow=self.max_overflow,
+            pool_recycle=self.pool_recycle
+        )
 
     def connect(self):
-        return pymysql.connect(host=self.host, port=3306, database=self.dbname, user="zhenggantian", password="123456",
-                               charset="utf8")
+        return pymysql.connect(
+            host=self.host,
+            port=self.port,
+            database=self.dbname,
+            user=self.user,
+            password=self.password,
+            charset=self.charset
+        )

订单拦截总数据.py

@@ -28,7 +28,15 @@ def get_package_real_vol_by_api(packages_id):
         #     package_width = resp[0][1]
         #     package_hight = resp[0][2]
         # 拦截
-        url = f'https://cp.maso.hk/index.php?main=biphp&act=package_fund&key=W6BOYJ7BH27YCGRFCA0LWBVKMU1KRU5Q&package={package_id}'
+        url = f'https://cp.baycheer.com/index.php?main=biphp&act=package_fund&key=W6BOYJ7BH27YCGRFCA0LWBVKMU1KRU5Q&package={package_id}'
+
+
+
+
+
+
+
+        
         resp = requests.get(url).json()
         if resp['code'] == "0":
             weight = int(float(resp['data'][0]['weight'])*1000)