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dff20ae83f
...
6e14684f5d
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@ -1,7 +0,0 @@
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{
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"permissions": {
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"allow": [
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"Bash(python -c \":*)"
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]
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}
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}
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@ -1,13 +0,0 @@
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{
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"database": {
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"host": "192.168.100.33",
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"port": 3306,
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"username": "zhenggantian",
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"password": "123456",
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"database": "logistics",
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"charset": "utf8mb4",
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"pool_size": 10,
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"max_overflow": 5,
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"pool_recycle": 3600
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}
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}
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BIN
data/售价尾端价格.xlsx (Stored with Git LFS)
BIN
data/售价尾端价格.xlsx (Stored with Git LFS)
Binary file not shown.
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@ -1,4 +0,0 @@
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"""数据访问层模块"""
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from dataaccess.base_dao import BaseDAO
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__all__ = ["BaseDAO"]
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@ -1,65 +0,0 @@
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"""基础数据访问类"""
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import pandas as pd
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from typing import Any, Dict, List, Optional
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from utils.gtools import MySQLconnect
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class BaseDAO:
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"""基础数据访问对象"""
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_cache: Dict[str, pd.DataFrame] = {}
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_cache_enabled: bool = True
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def __init__(self, table_name: str):
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self.table_name = table_name
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def _get_connection(self, dbname: str = None) -> MySQLconnect:
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"""获取数据库连接"""
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return MySQLconnect(dbname)
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def get_all(self, dbname: str = None) -> pd.DataFrame:
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"""获取所有数据"""
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cache_key = f"{dbname}:{self.table_name}"
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if self._cache_enabled and cache_key in self._cache:
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return self._cache[cache_key]
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with self._get_connection(dbname) as conn:
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df = pd.read_sql(f"SELECT * FROM {self.table_name}", conn.con)
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if self._cache_enabled:
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self._cache[cache_key] = df
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return df
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def get_by_condition(self, conditions: Dict[str, Any], dbname: str = None) -> pd.DataFrame:
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"""根据条件查询数据"""
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where_clause = " AND ".join([f"{k} = '{v}'" for k, v in conditions.items()])
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query = f"SELECT * FROM {self.table_name} WHERE {where_clause}"
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with self._get_connection(dbname) as conn:
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df = pd.read_sql(query, conn.con)
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return df
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def execute_query(self, query: str, dbname: str = None) -> pd.DataFrame:
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"""执行自定义查询"""
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with self._get_connection(dbname) as conn:
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df = pd.read_sql(query, conn.con)
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return df
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@classmethod
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def clear_cache(cls):
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"""清空缓存"""
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cls._cache.clear()
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@classmethod
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def disable_cache(cls):
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"""禁用缓存"""
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cls._cache_enabled = False
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@classmethod
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def enable_cache(cls):
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"""启用缓存"""
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cls._cache_enabled = True
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@ -1,49 +0,0 @@
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"""物流公司数据访问类"""
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import pandas as pd
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from typing import Dict, List, Optional
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from dataaccess.base_dao import BaseDAO
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class CompanyDAO(BaseDAO):
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"""物流公司数据访问"""
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def __init__(self):
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super().__init__("logistics_company")
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def get_all_companies(self, country: str = None, active_only: bool = True) -> List[Dict]:
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"""获取所有物流公司"""
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conditions = {}
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if country:
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conditions["country"] = country
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if active_only:
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conditions["active"] = 1
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if conditions:
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df = self.get_by_condition(conditions)
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else:
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df = self.get_all()
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if df.empty:
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return []
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return df.to_dict("records")
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def get_company_info(self, company_code: str) -> Optional[Dict]:
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"""获取物流公司详细信息"""
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df = self.get_by_condition({"company_code": company_code})
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if df.empty:
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return None
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return df.iloc[0].to_dict()
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def get_companies_by_type(self, country: str, logistics_type: str) -> List[Dict]:
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"""根据物流类型获取公司列表"""
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query = f"""
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SELECT * FROM {self.table_name}
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WHERE country = '{country}'
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AND logistics_type = '{logistics_type}'
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AND active = 1
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"""
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df = self.execute_query(query)
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if df.empty:
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return []
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return df.to_dict("records")
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@ -1,65 +0,0 @@
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"""英国物流价格数据访问类"""
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import pandas as pd
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from typing import Dict, List, Optional
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from dataaccess.base_dao import BaseDAO
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class UKPriceDAO(BaseDAO):
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"""英国物流价格数据访问"""
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def __init__(self):
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super().__init__("uk_logistics_price")
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def get_all_companies(self) -> List[str]:
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"""获取所有英国物流公司"""
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df = self.get_all()
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if df.empty:
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return []
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return df["company"].unique().tolist()
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def get_company_price(self, company: str) -> pd.DataFrame:
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"""获取指定物流公司的价格数据"""
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return self.get_by_condition({"company": company})
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def get_company_config(self, company: str) -> Dict:
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"""获取物流公司配置信息"""
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df = self.get_by_condition({"company": company})
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if df.empty:
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return {}
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config = {}
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for _, row in df.iterrows():
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key = row.get("config_key")
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value = row.get("config_value")
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if key:
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config[key] = value
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return config
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class UKPostcodeDAO(BaseDAO):
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"""英国邮编分区数据访问"""
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def __init__(self):
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super().__init__("uk_postcode_zone")
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def get_zone(self, postcode: str) -> Optional[str]:
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"""根据邮编获取分区"""
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postcode_prefix = postcode.split()[0].upper()
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df = self.get_by_condition({"postcode_prefix": postcode_prefix})
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if df.empty:
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return None
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return df.iloc[0].get("zone")
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def is_remote(self, postcode: str) -> bool:
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"""判断是否偏远"""
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postcode_prefix = postcode.split()[0].upper()
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remote_prefixes = ["BT", "IM", "JE", "ZE", "GY", "HS", "PO", "IV", "KA", "KW", "PH", "PA"]
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if not any(postcode_prefix.startswith(p) for p in remote_prefixes):
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return False
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df = self.get_by_condition({"postcode_prefix": postcode_prefix, "is_remote": "1"})
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return not df.empty
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@ -1,70 +0,0 @@
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"""美国物流价格数据访问类"""
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import pandas as pd
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from typing import Dict, List, Optional
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from dataaccess.base_dao import BaseDAO
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class USPriceDAO(BaseDAO):
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"""美国物流价格数据访问"""
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def __init__(self):
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super().__init__("us_logistics_price")
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def get_all_companies(self) -> List[str]:
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"""获取所有美国物流公司"""
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df = self.get_all()
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if df.empty:
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return []
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return df["company"].unique().tolist()
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def get_company_price(self, company: str) -> pd.DataFrame:
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"""获取指定物流公司的价格数据"""
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return self.get_by_condition({"company": company})
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def get_company_config(self, company: str) -> Dict:
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"""获取物流公司配置信息"""
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df = self.get_by_condition({"company": company})
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if df.empty:
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return {}
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config = {}
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for _, row in df.iterrows():
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||||
key = row.get("config_key")
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||||
value = row.get("config_value")
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if key:
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config[key] = value
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return config
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||||
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class USPostcodeDAO(BaseDAO):
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"""美国邮编分区数据访问"""
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def __init__(self):
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super().__init__("us_postcode_zone")
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def get_zone(self, postcode: str, port: str = "west") -> Optional[str]:
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"""根据邮编获取分区"""
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postcode_5 = postcode[:5]
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df = self.get_by_condition({"postcode": postcode_5, "port": port})
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if df.empty:
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return None
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return df.iloc[0].get("zone")
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def get_remote_type(self, postcode: str) -> int:
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"""获取偏远类型: 0-非偏远, 1-偏远, 2-超偏远, 3-超超偏远"""
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postcode_5 = postcode[:5]
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df = self.get_by_condition({"postcode": postcode_5})
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||||
if df.empty:
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||||
return 0
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||||
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return int(df.iloc[0].get("remote_type", 0))
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||||
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||||
def is_contiguous(self, postcode: str) -> bool:
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||||
"""判断是否在本土范围内"""
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||||
postcode_5 = postcode[:5]
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||||
df = self.get_by_condition({"postcode": postcode_5})
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return not df.empty
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@ -5,15 +5,14 @@ import re
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import pytesseract
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from PIL import Image
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||||
from tempfile import NamedTemporaryFile
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||||
|
||||
from selenium.webdriver.chrome.service import Service
|
||||
from selenium.webdriver.common.by import By
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from selenium.webdriver.remote.file_detector import UselessFileDetector #跳过文件检测 1
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from selenium import webdriver
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import redis
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|
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def vercode(cookie=None):
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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）
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||||
|
||||
|
||||
|
||||
|
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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）
|
||||
if cookie is not None:
|
||||
haders = {
|
||||
'Cookie': cookie #使用之前的图片链接Cooike
|
||||
|
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@ -44,7 +43,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'):
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try :
|
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r = redis.StrictRedis(host='192.168.100.44', port=7379, db=11,password="123456")
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viewcookie = r.get('cpmasosessid'+user)
|
||||
url="https://cp.baycheer.com/index.php?main=panel"#主页
|
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url="https://cp.maso.hk/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)
|
||||
|
|
@ -58,7 +57,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'):
|
|||
|
||||
|
||||
while resetcookie ==1:
|
||||
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）
|
||||
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）
|
||||
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')
|
||||
|
|
@ -78,7 +77,7 @@ 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.baycheer.com:4433/index.php?main=login&act=check'
|
||||
url = 'https://cp.maso.hk:4433/index.php?main=login&act=check'
|
||||
haders = {
|
||||
'Cookie': ress[0] #使用之前的图片链接Cooike
|
||||
}
|
||||
|
|
@ -205,9 +204,9 @@ def zenid():
|
|||
options.add_argument('--disable-gpu')
|
||||
options.add_argument(' -port=9222')
|
||||
driver=webdriver.Remote(service.service_url,options=options)
|
||||
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'
|
||||
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'
|
||||
driver.get(mainurl)
|
||||
driver.delete_all_cookies()
|
||||
driver.add_cookie({'name':'sessid','value':f'{t}'})
|
||||
|
|
|
|||
|
|
@ -5,7 +5,6 @@ import re
|
|||
|
||||
import pandas
|
||||
from logisticsClass.logisticsBaseClass import LogisticsType, TailLogistics
|
||||
from utils.gtools import MySQLconnect
|
||||
|
||||
|
||||
class ZGDPDLogistics_UK(TailLogistics):
|
||||
|
|
@ -292,75 +291,53 @@ class KPNVlogistics_UK(TailLogistics):
|
|||
country = 'United Kingdom'
|
||||
company = '卡派-NV'
|
||||
currency = 'GBP'
|
||||
logistics_type = LogisticsType.EXPRESS
|
||||
|
||||
# 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
|
||||
logistics_type = LogisticsType.LTL
|
||||
|
||||
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，从数据库加载数据"""
|
||||
if cls._zone_cache is None or cls._price_cache is None:
|
||||
cls._load_from_db()
|
||||
"""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="NV运费")
|
||||
cls.ltl_zone = pandas.read_excel(cls._price_files,sheet_name="NV分区")
|
||||
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()
|
||||
zone = self._zone_cache.get(postcode_prefix)
|
||||
if zone:
|
||||
return zone
|
||||
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]
|
||||
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)
|
||||
fee = self._price_cache.get((zone, tuopan))
|
||||
if fee is None:
|
||||
base_df = self.ltl_cost[(self.ltl_cost['分区']==zone)&(self.ltl_cost['托盘']==tuopan)]
|
||||
if base_df.empty:
|
||||
detail_amount['tail_amount'] = 99999
|
||||
return detail_amount
|
||||
self.base_fee = fee
|
||||
price = self.base_fee * tuopan / len(packages)
|
||||
self.base_fee = base_df['运费'].values[0]
|
||||
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 ZGbigLogistics_UK(TailLogistics):
|
||||
|
|
|
|||
|
|
@ -5,7 +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
|
||||
from utils.gtools import DBconnect
|
||||
"""
|
||||
port:west(default),east
|
||||
currency:str = 'USD'
|
||||
|
|
@ -83,10 +83,6 @@ 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
|
||||
|
|
@ -112,16 +108,6 @@ 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）
|
||||
|
|
@ -198,8 +184,8 @@ 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.get_price(math.ceil(cal_weight), zone)
|
||||
self.base_price.columns = self.base_price.columns.map(str)
|
||||
detail_amount['base'] +=self.base_price[self.base_price['lbs.']==math.ceil(cal_weight)][str(zone)].values[0]
|
||||
|
||||
for key in detail_amount:
|
||||
if key!= 'tail_amount' and key!= 'fuel':
|
||||
|
|
@ -211,37 +197,18 @@ class FedexLogistics(WestLogistics_US):
|
|||
class FedexPPLogistics_US(FedexLogistics):
|
||||
company="Fedex-彩虹小马"
|
||||
|
||||
# 数据库价格缓存
|
||||
_price_cache = None
|
||||
|
||||
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
|
||||
def __new__(cls):
|
||||
if cls._price_cache is None:
|
||||
cls._load_from_db()
|
||||
if cls.base_price is None:
|
||||
cls.base_price = pandas.read_excel(cls._price_files,sheet_name='邮差小马')
|
||||
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
|
||||
|
|
@ -263,7 +230,7 @@ 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）
|
||||
|
||||
|
|
@ -271,33 +238,14 @@ class FedexKHLogistics_US(FedexLogistics):
|
|||
"""金宏亚"""
|
||||
company = "Fedex-金宏亚"
|
||||
|
||||
# 数据库价格缓存
|
||||
_price_cache = None
|
||||
|
||||
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
|
||||
def __new__(cls):
|
||||
if cls._price_cache is None:
|
||||
cls._load_from_db()
|
||||
if cls.base_price is None:
|
||||
cls.base_price = pandas.read_excel(cls._price_files,sheet_name='金宏亚')
|
||||
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
|
||||
|
|
@ -331,32 +279,15 @@ class FedexHOMELogistics_US(FedexLogistics):
|
|||
"""FEDEX-HOME (1-35%-30%)"""
|
||||
company = "Fedex-HOME"
|
||||
|
||||
# 数据库价格缓存
|
||||
_price_cache = None
|
||||
|
||||
base_price = None
|
||||
_instance = None
|
||||
def __new__(cls):
|
||||
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,
|
||||
}
|
||||
if cls.base_price is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
with DBconnect() as db:
|
||||
cls.base_price = pandas.read_sql("SELECT * FROM us_fedex_home", db.engine())
|
||||
return cls._instance
|
||||
return cls._instance
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.volume_weight_ratio = 250 # lbs抛重系数
|
||||
|
|
@ -385,38 +316,18 @@ 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"
|
||||
|
||||
# 数据库价格缓存(与FedexHOMELogistics_US共享us_fedex_home表)
|
||||
_price_cache = None
|
||||
|
||||
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
|
||||
def __new__(cls):
|
||||
if cls._price_cache is None:
|
||||
cls._load_from_db()
|
||||
if cls.base_price is None:
|
||||
cls.base_price = pandas.read_excel(cls._price_files,sheet_name='FEDEX')
|
||||
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
|
||||
|
|
|
|||
|
|
@ -1,165 +0,0 @@
|
|||
"""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)
|
||||
}
|
||||
|
|
@ -1,469 +0,0 @@
|
|||
#!/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()
|
||||
|
|
@ -1,37 +1,11 @@
|
|||
# 英国海运订单费用,返回单个sku的订单费用和订单类型
|
||||
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):
|
||||
def uk_ocean_order_price(packages,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
|
||||
|
|
@ -70,45 +44,4 @@ def uk_ocean_order_price(packages_dict_str,k):
|
|||
else:
|
||||
order_fee = ltl_fee
|
||||
order_type = order_type2
|
||||
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")
|
||||
return max(round(order_fee,2),2), order_type
|
||||
|
|
@ -1,7 +1,4 @@
|
|||
import sys
|
||||
sys.path.append(r'D:\workspace\dags\logistics')
|
||||
import pandas as pd
|
||||
|
||||
import math
|
||||
from utils.gtools import MySQLconnect,DBconnect
|
||||
# 取计算订单物流费的参数
|
||||
|
|
@ -35,7 +32,6 @@ 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
|
||||
|
||||
|
|
@ -131,34 +127,4 @@ 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
|
||||
|
||||
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")
|
||||
return express_fee, express_type
|
||||
|
|
@ -1,517 +0,0 @@
|
|||
# -*- coding: utf-8 -*-
|
||||
"""
|
||||
美国售价模型 V2 (shopfad)
|
||||
通过输入多包裹体积和采购价格，快速计算售价
|
||||
规则版本: 2604
|
||||
"""
|
||||
import sys
|
||||
sys.path.append(r'D:\workspace\dags\logistics')
|
||||
|
||||
import math
|
||||
from utils.gtools import MySQLconnect
|
||||
import pandas as pd
|
||||
|
||||
|
||||
class USLogisticsPrice:
|
||||
"""美国物流价格查询"""
|
||||
|
||||
_instance = None
|
||||
|
||||
def __new__(cls):
|
||||
if cls._instance is None:
|
||||
cls._instance = super().__new__(cls)
|
||||
cls._instance._init_data()
|
||||
return cls._instance
|
||||
|
||||
def _init_data(self):
|
||||
"""从数据库加载价格数据"""
|
||||
conn = MySQLconnect('logistics')
|
||||
with conn as c:
|
||||
self.sell_usps = pd.read_sql("SELECT * FROM sell_usps", c.con)
|
||||
# 2604版本价格表 (表名按需修改)
|
||||
self.sell_uandf_2604 = pd.read_sql("SELECT * FROM sell_uandf_2604", c.con)
|
||||
self.sell_fedex_price_ref_2604 = pd.read_sql("SELECT * FROM sell_fedex_price_ref_2604", c.con)
|
||||
self.sell_fedex_order_ref_2604 = pd.read_sql("SELECT * FROM sell_fedex_order_ref_2604", c.con)
|
||||
# 物流比例限制表 (表名按需修改)
|
||||
self.logistics_ratio_limit = pd.read_sql("SELECT * FROM logistics_ratio_limit", c.con)
|
||||
|
||||
# ========== 包裹计费类型判断 ==========
|
||||
|
||||
def get_package_types(self, packages):
|
||||
"""
|
||||
USPS：默认
|
||||
UandF：最长边>50 或 次长边>40 或 最短边>30 或 实重>2718 或 体积重>4500
|
||||
FEDEX：最长边>264 或 实重>67000 或 体积重>95000 或 围长>391
|
||||
卡派：同FEDEX条件（或该SKU的其他包裹为卡派类型）
|
||||
"""
|
||||
types = []
|
||||
for pkg in packages:
|
||||
l, w, h, wt = pkg['length_cm'], pkg['width_cm'], pkg['height_cm'], pkg['weight_g']
|
||||
sizes = sorted([l, w, h], reverse=True)
|
||||
fst, sed, trd = sizes[0], sizes[1], sizes[2]
|
||||
vol_weight = l * w * h / 6
|
||||
girth = fst + sed * 2 + trd * 2
|
||||
|
||||
pkg_type = 'USPS'
|
||||
if fst > 50 or sed > 40 or trd > 30 or wt > 2718 or vol_weight > 4500:
|
||||
pkg_type = 'UandF'
|
||||
if fst > 264 or wt > 67000 or vol_weight > 95000 or girth > 391:
|
||||
pkg_type = 'FEDEX'
|
||||
types.append(pkg_type)
|
||||
|
||||
# FEDEX升级为卡派（同SKU联动）
|
||||
if 'FEDEX' in types:
|
||||
types = ['卡派' if t == 'FEDEX' else t for t in types]
|
||||
|
||||
return types
|
||||
|
||||
# ========== 快递费计算 ==========
|
||||
|
||||
def _lookup_express_base_fee(self, pkg_type, lbs_weight, oz_weight, profit_rate, fuel_rate):
|
||||
"""
|
||||
查表获取单个包裹的快递基础计费
|
||||
USPS/UandF: 直接查表
|
||||
FEDEX: FEDEX售价参考表 * (1+快递燃油费率) + 2.9
|
||||
"""
|
||||
if pkg_type == 'USPS':
|
||||
row = self.sell_usps[self.sell_usps['oz'] == oz_weight]
|
||||
if len(row) > 0:
|
||||
return row['最终费用_v2'].iloc[0] / profit_rate, 'USPS'
|
||||
else:
|
||||
return self._lookup_express_base_fee('UandF', lbs_weight, oz_weight, profit_rate, fuel_rate)
|
||||
|
||||
if pkg_type == 'UandF':
|
||||
row = self.sell_uandf_2604[self.sell_uandf_2604['lbs'] == lbs_weight]
|
||||
if len(row) > 0:
|
||||
return row['加权价格_v2'].iloc[0] / profit_rate, 'UandF'
|
||||
else:
|
||||
return self._lookup_express_base_fee('FEDEX', lbs_weight, oz_weight, profit_rate, fuel_rate)
|
||||
|
||||
if pkg_type in ('FEDEX', '卡派'):
|
||||
row = self.sell_fedex_price_ref_2604[self.sell_fedex_price_ref_2604['lbs'] == lbs_weight]
|
||||
if len(row) > 0:
|
||||
return row['售价尾端价格_v4'].iloc[0] * (1 + fuel_rate) + 2.9, 'FEDEX'
|
||||
else:
|
||||
return 99999, 'FEDEX'
|
||||
|
||||
return 0, pkg_type
|
||||
|
||||
def _calc_express_fee(self, packages, types, profit_rate, fuel_rate):
|
||||
"""
|
||||
快递费 = Σ(单包裹快递基础计费 + 大包裹费 + 超重费 + 超尺寸费)
|
||||
大包裹费: 最长边>238 或 围长>315 → 109.4
|
||||
超重费: 实重>21000 → 6.1
|
||||
超尺寸费: 最长边>116 或 围长>251 → 7.4
|
||||
"""
|
||||
total_fee = 0
|
||||
for i, pkg in enumerate(packages):
|
||||
l, w, h, wt = pkg['length_cm'], pkg['width_cm'], pkg['height_cm'], pkg['weight_g']
|
||||
sizes = sorted([l, w, h], reverse=True)
|
||||
fst, sed, trd = sizes[0], sizes[1], sizes[2]
|
||||
volume = l * w * h
|
||||
girth = fst + sed * 2 + trd * 2
|
||||
|
||||
lbs_weight = math.ceil(max(volume / 8500 / 0.453, wt / 453))
|
||||
oz_weight = math.ceil(wt / 28)
|
||||
|
||||
pkg_type = types[i]
|
||||
base_fee, actual_type = self._lookup_express_base_fee(
|
||||
pkg_type, lbs_weight, oz_weight, profit_rate, fuel_rate
|
||||
)
|
||||
|
||||
large_pkg_fee = 0
|
||||
overweight_fee = 0
|
||||
oversize_fee = 0
|
||||
|
||||
if actual_type in ('FEDEX', '卡派'):
|
||||
if fst > 238 or girth > 315:
|
||||
large_pkg_fee = 109.4
|
||||
if wt > 21000:
|
||||
overweight_fee = 6.1
|
||||
if fst > 116 or girth > 251:
|
||||
oversize_fee = 7.4
|
||||
|
||||
total_fee += base_fee + large_pkg_fee + overweight_fee + oversize_fee
|
||||
|
||||
return total_fee
|
||||
|
||||
# ========== 卡派费计算 ==========
|
||||
|
||||
def _calc_ltl_fee(self, packages, profit_rate):
|
||||
"""
|
||||
卡派费 = 卡派基础费 + 超长费 + 超重费
|
||||
合并体积 = ceil(长x宽x高/1000000 x 35.3) (立方英尺)
|
||||
"""
|
||||
total_cubic_feet = 0
|
||||
over_length_fee = 0
|
||||
over_weight_fee = 0
|
||||
|
||||
for pkg in packages:
|
||||
l, w, h, wt = pkg['length_cm'], pkg['width_cm'], pkg['height_cm'], pkg['weight_g']
|
||||
sizes = sorted([l, w, h], reverse=True)
|
||||
fst = sizes[0]
|
||||
volume = l * w * h
|
||||
|
||||
cubic_feet = math.ceil(volume / 1000000 * 35.3147)
|
||||
total_cubic_feet += cubic_feet
|
||||
|
||||
# 超长费: 最长边>250
|
||||
if fst > 250:
|
||||
over_length_fee = max(over_length_fee, round(130 / profit_rate - 118, 1))
|
||||
# 超重费
|
||||
if 130000 <= wt < 157000:
|
||||
over_weight_fee = max(over_weight_fee, round(130 / profit_rate - 118, 1))
|
||||
elif 111000 <= wt < 130000:
|
||||
over_weight_fee = max(over_weight_fee, round(80 / profit_rate - 78, 1))
|
||||
|
||||
# 卡派基础费
|
||||
v = total_cubic_feet
|
||||
if v < 25:
|
||||
base_fee = round(198 / profit_rate / 2, 2)
|
||||
elif v < 35:
|
||||
base_fee = round(231 / profit_rate / 2, 2)
|
||||
else:
|
||||
base_fee = round(max(231, 6.6 * v) / profit_rate / 2, 2)
|
||||
|
||||
ltl_fee = base_fee + over_length_fee + over_weight_fee
|
||||
return ltl_fee, total_cubic_feet
|
||||
|
||||
# ========== 初始前端展示物流费 ==========
|
||||
|
||||
def _calc_display_logistics_fee(self, packages, types, total_cubic_feet):
|
||||
"""
|
||||
卡派: v<25→90, v<35→90+(v-25)*3, 其他→99+(v-35)*5
|
||||
快递: FEDEX订单参考表查表
|
||||
"""
|
||||
has_ltl = '卡派' in types
|
||||
|
||||
if has_ltl:
|
||||
v = total_cubic_feet
|
||||
if v < 25:
|
||||
display = 90
|
||||
elif v < 35:
|
||||
display = 90 + (v - 25) * 3
|
||||
else:
|
||||
display = 99 + (v - 35) * 5
|
||||
print(f"[卡派展示物流费] 合并体积={v} cu ft, 展示费={display}")
|
||||
return display
|
||||
else:
|
||||
# 快递: FEDEX订单参考表查表
|
||||
total = 0
|
||||
for pkg in packages:
|
||||
l, w, h, wt = pkg['length_cm'], pkg['width_cm'], pkg['height_cm'], pkg['weight_g']
|
||||
volume = l * w * h
|
||||
lbs_weight = math.ceil(max(volume / 8500 / 0.453, wt / 453))
|
||||
row = self.sell_fedex_order_ref_2604[
|
||||
self.sell_fedex_order_ref_2604['lbs'] == lbs_weight
|
||||
]
|
||||
if len(row) > 0:
|
||||
total += row['售价尾端价格_v3'].iloc[0]
|
||||
return total
|
||||
|
||||
# ========== 物流比例限制查表 ==========
|
||||
|
||||
def _lookup_logistics_limit(self, category, price):
|
||||
"""通过条目和价格查表得到建议物流比例上限和建议物流绝对上限"""
|
||||
try:
|
||||
rows = self.logistics_ratio_limit[
|
||||
(self.logistics_ratio_limit['条目'] == category) &
|
||||
(self.logistics_ratio_limit['价格'] <= price)
|
||||
]
|
||||
if len(rows) > 0:
|
||||
row = rows.iloc[-1]
|
||||
return row['建议物流比例上限'], row['建议物流绝对上限']
|
||||
return 1.0, float('inf')
|
||||
except:
|
||||
return 1.0, float('inf')
|
||||
|
||||
# ========== 统一尾端费用接口 ==========
|
||||
|
||||
def get_tail_fee_info(self, packages, profit_rate=0.359, fuel_rate=0):
|
||||
"""
|
||||
尾端费用 = min(快递费, 卡派费)
|
||||
存在卡派类型包裹则强制使用卡派
|
||||
"""
|
||||
types = self.get_package_types(packages)
|
||||
has_ltl = '卡派' in types
|
||||
|
||||
express_fee = self._calc_express_fee(packages, types, profit_rate, fuel_rate)
|
||||
ltl_fee, total_cubic_feet = self._calc_ltl_fee(packages, profit_rate)
|
||||
|
||||
if has_ltl:
|
||||
tail_fee = ltl_fee
|
||||
else:
|
||||
tail_fee = min(express_fee, ltl_fee)
|
||||
|
||||
display_fee = self._calc_display_logistics_fee(packages, types, total_cubic_feet)
|
||||
|
||||
return {
|
||||
'tail_fee': tail_fee,
|
||||
'display_logistics_fee': display_fee,
|
||||
'express_fee': express_fee,
|
||||
'ltl_fee': ltl_fee,
|
||||
'types': types,
|
||||
'has_ltl': has_ltl,
|
||||
'total_cubic_feet': total_cubic_feet
|
||||
}
|
||||
|
||||
|
||||
class USSellPrice:
|
||||
"""
|
||||
美国售价计算器 V2 (shopfad)
|
||||
规则版本: 2604
|
||||
|
||||
使用示例:
|
||||
calculator = USSellPrice()
|
||||
result = calculator.calculate(
|
||||
packages=[{'length_cm': 30, 'width_cm': 20, 'height_cm': 10, 'weight_g': 500}],
|
||||
purchase_price_cny=100,
|
||||
preset='shopfad'
|
||||
)
|
||||
"""
|
||||
|
||||
PRESETS = {
|
||||
'shopfad': {
|
||||
'ocean_first_cny': 0.5,
|
||||
'ocean_first_usd': 0.7,
|
||||
'air_first_usd': 0.65,
|
||||
'air_cny_type': 0.093,
|
||||
'air_first_fix': 22.7,
|
||||
'exchange_rate': 6.5,
|
||||
'profit_rate': 0.38,
|
||||
'air_rate': 0.7,
|
||||
'tax_rate': 0.1,
|
||||
'fuel_rate': 0,
|
||||
'extra_rate': 0
|
||||
},
|
||||
'shopfad2': {
|
||||
'ocean_first_cny': 1,
|
||||
'ocean_first_usd': 1,
|
||||
'air_first_usd': 0.65,
|
||||
'air_cny_type': 0.093,
|
||||
'air_first_fix': 22.7,
|
||||
'exchange_rate': 6.5,
|
||||
'profit_rate': 0.38,
|
||||
'air_rate': 0.7,
|
||||
'tax_rate': 0.145,
|
||||
'fuel_rate': 0,
|
||||
'extra_rate': 0
|
||||
},
|
||||
'shopfad3': {
|
||||
'ocean_first_cny': 0.67,
|
||||
'ocean_first_usd': 0.7,
|
||||
'air_first_usd': 0.65,
|
||||
'air_cny_type': 0.093,
|
||||
'air_first_fix': 22.7,
|
||||
'exchange_rate': 6.5,
|
||||
'profit_rate': 0.3,
|
||||
'air_rate': 0.7,
|
||||
'tax_rate': 0.1,
|
||||
'fuel_rate': 0,
|
||||
'extra_rate': 0
|
||||
},
|
||||
'shopfad4': {
|
||||
'ocean_first_cny': 0.67,
|
||||
'ocean_first_usd': 0.7,
|
||||
'air_first_usd': 0.65,
|
||||
'air_cny_type': 0.093,
|
||||
'air_first_fix': 22.7,
|
||||
'exchange_rate': 6.5,
|
||||
'profit_rate': 0.3,
|
||||
'air_rate': 0.7,
|
||||
'tax_rate': 0.1,
|
||||
'fuel_rate': 0,
|
||||
'extra_rate': 0
|
||||
}
|
||||
}
|
||||
|
||||
def __init__(self):
|
||||
self.logistics = USLogisticsPrice()
|
||||
|
||||
def calculate(self, packages, purchase_price_cny, preset='shopfad', config=None, category=''):
|
||||
"""
|
||||
计算售价
|
||||
|
||||
Args:
|
||||
packages: 包裹列表 [{'length_cm', 'width_cm', 'height_cm', 'weight_g'}]
|
||||
purchase_price_cny: 采购价(CNY)
|
||||
preset: 预设配置名称
|
||||
config: 自定义配置 (优先使用)
|
||||
category: 条目 (用于物流比例限制查表)
|
||||
"""
|
||||
cfg = config or self.PRESETS.get(preset, self.PRESETS['shopfad'])
|
||||
|
||||
# 1. 获取尾端费用
|
||||
fuel_rate = cfg.get('fuel_rate', 0)
|
||||
tail_info = self.logistics.get_tail_fee_info(packages, cfg['profit_rate'], fuel_rate)
|
||||
tail_fee = tail_info['tail_fee']
|
||||
display_fee = tail_info['display_logistics_fee']
|
||||
|
||||
# 2. 判断SPU运输方式
|
||||
has_ltl = tail_info['has_ltl']
|
||||
shipping_type = '海运' if has_ltl else '空运'
|
||||
|
||||
# 3. 汇总体积重 (长x宽x高/6)
|
||||
total_volume_weight = sum(
|
||||
p['length_cm'] * p['width_cm'] * p['height_cm'] / 6 for p in packages
|
||||
)
|
||||
|
||||
tax_amount = purchase_price_cny * cfg['tax_rate'] / cfg['exchange_rate']
|
||||
|
||||
# 4. 根据运输方式计算调整前售价
|
||||
if shipping_type == '海运':
|
||||
pre_adjust_price = self._calc_ocean_price(
|
||||
total_volume_weight, purchase_price_cny, tax_amount, tail_fee, cfg
|
||||
)
|
||||
first_cny = cfg['ocean_first_cny'] / 1000 * total_volume_weight
|
||||
first_usd = cfg['ocean_first_usd'] / 1000 * total_volume_weight
|
||||
else:
|
||||
pre_adjust_price = self._calc_air_price(
|
||||
packages, purchase_price_cny, tax_amount, tail_fee, cfg
|
||||
)
|
||||
first_cny, first_usd = self._calc_air_first_leg(packages, cfg)
|
||||
|
||||
# 5. 最终修正 (仅海运)
|
||||
shared_tail_fee = 0
|
||||
final_price = pre_adjust_price
|
||||
|
||||
if shipping_type == '海运':
|
||||
final_price, shared_tail_fee = self._apply_ocean_adjustment(
|
||||
pre_adjust_price, display_fee, category
|
||||
)
|
||||
|
||||
# 头程费用 / 总物流费用
|
||||
head_fee = first_cny / cfg['exchange_rate'] + first_usd
|
||||
total_logistics_fee = head_fee + tail_fee
|
||||
|
||||
return {
|
||||
'sell_price_usd': round(final_price, 2),
|
||||
'sell_price_cny': round(final_price * cfg['exchange_rate'], 2),
|
||||
'purchase_price_cny': purchase_price_cny,
|
||||
'express_fee': round(tail_fee, 2),
|
||||
'first_cny': round(first_cny, 2),
|
||||
'first_usd': round(first_usd, 2),
|
||||
'tax_amount': round(tax_amount, 2),
|
||||
'shipping_type': shipping_type,
|
||||
'preset': preset,
|
||||
'pre_adjust_price': round(pre_adjust_price, 2),
|
||||
'display_logistics_fee': round(display_fee, 2),
|
||||
'shared_tail_fee': round(shared_tail_fee, 2),
|
||||
'head_fee': round(head_fee, 2),
|
||||
'total_logistics_fee': round(total_logistics_fee, 2),
|
||||
'package_types': tail_info['types'],
|
||||
}
|
||||
|
||||
# ========== 海运计费 ==========
|
||||
|
||||
def _calc_ocean_price(self, total_volume_weight, purchase_price_cny, tax_amount, tail_fee, cfg):
|
||||
"""
|
||||
调整前售价 = (((海运头程CNY总价 + 采购价格) / 汇率 + 海运头程USD总价)
|
||||
+ 采购价格 x 税金系数 / 汇率) / 利润系数 + 尾端费用
|
||||
"""
|
||||
ocean_first_cny_total = cfg['ocean_first_cny'] / 1000 * total_volume_weight
|
||||
ocean_first_usd_total = cfg['ocean_first_usd'] / 1000 * total_volume_weight
|
||||
|
||||
pre_adjust = (
|
||||
((ocean_first_cny_total + purchase_price_cny) / cfg['exchange_rate']
|
||||
+ ocean_first_usd_total + tax_amount) / cfg['profit_rate'] + tail_fee
|
||||
)
|
||||
return pre_adjust
|
||||
|
||||
# ========== 空运计费 ==========
|
||||
|
||||
def _calc_air_price(self, packages, purchase_price_cny, tax_amount, tail_fee, cfg):
|
||||
"""
|
||||
调整前售价 = (采购价格/汇率/利润系数
|
||||
+ ((空运头程CNY总价/汇率 + 空运头程USD总价 + 税金) / 利润系数 + 尾端费用)
|
||||
x 空运分配比例) x (1 + 附加费率)
|
||||
"""
|
||||
air_cny_total = 0
|
||||
air_usd_total = 0
|
||||
|
||||
for pkg in packages:
|
||||
volume = pkg['length_cm'] * pkg['width_cm'] * pkg['height_cm']
|
||||
volume_weight = volume / 6
|
||||
density = pkg['weight_g'] / (volume / 1000) if volume > 0 else 0
|
||||
type_weight = min(337, max(37, math.ceil(density)))
|
||||
|
||||
air_cny_unit = cfg['air_cny_type'] / 1000 * type_weight + cfg['air_first_fix'] / 1000
|
||||
air_cny_total += air_cny_unit * volume_weight
|
||||
air_usd_total += cfg['air_first_usd'] / 1000 * volume_weight
|
||||
|
||||
purchase_usd = purchase_price_cny / cfg['exchange_rate']
|
||||
|
||||
pre_adjust = (
|
||||
purchase_usd / cfg['profit_rate']
|
||||
+ ((air_cny_total / cfg['exchange_rate'] + air_usd_total + tax_amount)
|
||||
/ cfg['profit_rate'] + tail_fee) * cfg['air_rate']
|
||||
) * (1 + cfg.get('extra_rate', 0))
|
||||
|
||||
return pre_adjust
|
||||
|
||||
def _calc_air_first_leg(self, packages, cfg):
|
||||
"""计算空运头程费用 (CNY/USD)"""
|
||||
first_cny = 0
|
||||
first_usd = 0
|
||||
for pkg in packages:
|
||||
volume = pkg['length_cm'] * pkg['width_cm'] * pkg['height_cm']
|
||||
volume_weight = volume / 6
|
||||
density = pkg['weight_g'] / (volume / 1000) if volume > 0 else 0
|
||||
type_weight = min(337, max(37, math.ceil(density)))
|
||||
|
||||
air_cny_unit = cfg['air_cny_type'] / 1000 * type_weight + cfg['air_first_fix'] / 1000
|
||||
first_cny += air_cny_unit * volume_weight
|
||||
first_usd += cfg['air_first_usd'] / 1000 * volume_weight
|
||||
return first_cny, first_usd
|
||||
|
||||
# ========== 最终修正 (海运) ==========
|
||||
|
||||
def _apply_ocean_adjustment(self, pre_adjust_price, display_fee, category):
|
||||
"""
|
||||
前端展示物流费 = min(初始前端展示物流费, 调整前售价×比例上限, 绝对上限)
|
||||
if min == 初始前端展示物流费: 分摊尾端=0, 最终售价=调整前售价
|
||||
else: 分摊尾端=初始前端展示物流费-min, 最终售价=调整前售价+分摊尾端
|
||||
"""
|
||||
total = display_fee + pre_adjust_price
|
||||
if total <= 0:
|
||||
return pre_adjust_price, 0
|
||||
|
||||
ratio_limit, abs_limit = self.logistics._lookup_logistics_limit(category, pre_adjust_price)
|
||||
actual_display_fee = min(display_fee, pre_adjust_price * ratio_limit, abs_limit)
|
||||
|
||||
if actual_display_fee == display_fee:
|
||||
return pre_adjust_price, 0
|
||||
else:
|
||||
shared_tail = display_fee - actual_display_fee
|
||||
final_price = pre_adjust_price + shared_tail
|
||||
return final_price, shared_tail
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
calc = USSellPrice()
|
||||
|
||||
print("=== 单包裹测试 ===")
|
||||
result = calc.calculate(
|
||||
packages=[{'length_cm': 30, 'width_cm': 20, 'height_cm': 10, 'weight_g': 500}],
|
||||
purchase_price_cny=100,
|
||||
preset='shopfad'
|
||||
)
|
||||
print(f" 30x20x10cm 500g => ${result['sell_price_usd']}")
|
||||
print(f" 运输方式: {result['shipping_type']}")
|
||||
print(f" 包裹类型: {result['package_types']}")
|
||||
|
||||
print("\n=== 多包裹测试 ===")
|
||||
result = calc.calculate(
|
||||
packages=[
|
||||
{'length_cm': 30, 'width_cm': 20, 'height_cm': 10, 'weight_g': 500},
|
||||
{'length_cm': 40, 'width_cm': 30, 'height_cm': 15, 'weight_g': 1000},
|
||||
],
|
||||
purchase_price_cny=200,
|
||||
preset='shopfad'
|
||||
)
|
||||
print(f" 两件包裹 => ${result['sell_price_usd']}")
|
||||
print(f" 运输方式: {result['shipping_type']}")
|
||||
print(f" 包裹类型: {result['package_types']}")
|
||||
print(f" 尾端费用: ${result['express_fee']}")
|
||||
print(f" 头程CNY: {result['first_cny']}, 头程USD: ${result['first_usd']}")
|
||||
print(f" 总物流: ${result['total_logistics_fee']}")
|
||||
|
|
@ -1,337 +0,0 @@
|
|||
-- 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');
|
||||
|
|
@ -1,176 +0,0 @@
|
|||
"""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"])
|
||||
|
|
@ -1,53 +0,0 @@
|
|||
"""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()
|
||||
|
|
@ -1,22 +1,13 @@
|
|||
import pymysql
|
||||
from sqlalchemy import create_engine
|
||||
from utils.config_manager import config
|
||||
|
||||
|
||||
class MySQLconnect():
|
||||
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):
|
||||
def __init__(self, dbname: str):
|
||||
if isinstance(dbname, str):
|
||||
self.dbname = dbname
|
||||
self.host = '192.168.100.33'
|
||||
else:
|
||||
raise TypeError("dbname must be a string")
|
||||
|
||||
def __enter__(self):
|
||||
|
|
@ -33,12 +24,8 @@ class MySQLconnect():
|
|||
raise
|
||||
|
||||
def engine(self):
|
||||
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
|
||||
)
|
||||
return create_engine("mysql+pymysql://zhenggantian:123456@" + self.host + f":3306/{self.dbname}",
|
||||
pool_size=10, max_overflow=5, pool_recycle=3600)
|
||||
|
||||
def connect(self):
|
||||
return pymysql.connect(host=self.host, port=3306, database=self.dbname, user="zhenggantian", password="123456",
|
||||
|
|
@ -68,4 +55,4 @@ class DBconnect():
|
|||
|
||||
def connect(self):
|
||||
return pymysql.connect(host=self.host, port=3306, database="logistics", user="logistics", password="logistics123",
|
||||
charset="utf8")
|
||||
charset="utf8")
|
||||
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自动化跟单11.ipynb
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自动化跟单11.ipynb
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跟单测试源文件.xlsx (Stored with Git LFS)
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跟单测试源文件.xlsx (Stored with Git LFS)
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Reference in New Issue