diff --git a/.claude/settings.local.json b/.claude/settings.local.json new file mode 100644 index 0000000..787b5db --- /dev/null +++ b/.claude/settings.local.json @@ -0,0 +1,7 @@ +{ + "permissions": { + "allow": [ + "Bash(python -c \":*)" + ] + } +} diff --git a/config/database.json b/config/database.json new file mode 100644 index 0000000..a41e3f8 --- /dev/null +++ b/config/database.json @@ -0,0 +1,13 @@ +{ + "database": { + "host": "192.168.100.33", + "port": 3306, + "username": "zhenggantian", + "password": "123456", + "database": "logistics", + "charset": "utf8mb4", + "pool_size": 10, + "max_overflow": 5, + "pool_recycle": 3600 + } +} diff --git a/data/售价尾端价格.xlsx b/data/售价尾端价格.xlsx index 38f6ef5..7799a17 100644 --- a/data/售价尾端价格.xlsx +++ b/data/售价尾端价格.xlsx @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:113c7466854323029ab62c4a5dfb25858b37efd7a793d97724070a45f1f65628 -size 17380 +oid sha256:d8f576400e843049aa2536eff26c44580ef6fa63a01d568fd91d682e8d492bdf +size 18366 diff --git a/dataaccess/__init__.py b/dataaccess/__init__.py new file mode 100644 index 0000000..7d0521d --- /dev/null +++ b/dataaccess/__init__.py @@ -0,0 +1,4 @@ +"""数据访问层模块""" +from dataaccess.base_dao import BaseDAO + +__all__ = ["BaseDAO"] diff --git a/dataaccess/base_dao.py b/dataaccess/base_dao.py new file mode 100644 index 0000000..e780396 --- /dev/null +++ b/dataaccess/base_dao.py @@ -0,0 +1,65 @@ +"""基础数据访问类""" +import pandas as pd +from typing import Any, Dict, List, Optional +from utils.gtools import MySQLconnect + + +class BaseDAO: + """基础数据访问对象""" + + _cache: Dict[str, pd.DataFrame] = {} + _cache_enabled: bool = True + + def __init__(self, table_name: str): + self.table_name = table_name + + def _get_connection(self, dbname: str = None) -> MySQLconnect: + """获取数据库连接""" + return MySQLconnect(dbname) + + def get_all(self, dbname: str = None) -> pd.DataFrame: + """获取所有数据""" + cache_key = f"{dbname}:{self.table_name}" + + if self._cache_enabled and cache_key in self._cache: + return self._cache[cache_key] + + with self._get_connection(dbname) as conn: + df = pd.read_sql(f"SELECT * FROM {self.table_name}", conn.con) + + if self._cache_enabled: + self._cache[cache_key] = df + + return df + + def get_by_condition(self, conditions: Dict[str, Any], dbname: str = None) -> pd.DataFrame: + """根据条件查询数据""" + where_clause = " AND ".join([f"{k} = '{v}'" for k, v in conditions.items()]) + query = f"SELECT * FROM {self.table_name} WHERE {where_clause}" + + with self._get_connection(dbname) as conn: + df = pd.read_sql(query, conn.con) + + return df + + def execute_query(self, query: str, dbname: str = None) -> pd.DataFrame: + """执行自定义查询""" + with self._get_connection(dbname) as conn: + df = pd.read_sql(query, conn.con) + + return df + + @classmethod + def clear_cache(cls): + """清空缓存""" + cls._cache.clear() + + @classmethod + def disable_cache(cls): + """禁用缓存""" + cls._cache_enabled = False + + @classmethod + def enable_cache(cls): + """启用缓存""" + cls._cache_enabled = True diff --git a/dataaccess/company_dao.py b/dataaccess/company_dao.py new file mode 100644 index 0000000..15b272a --- /dev/null +++ b/dataaccess/company_dao.py @@ -0,0 +1,49 @@ +"""物流公司数据访问类""" +import pandas as pd +from typing import Dict, List, Optional +from dataaccess.base_dao import BaseDAO + + +class CompanyDAO(BaseDAO): + """物流公司数据访问""" + + def __init__(self): + super().__init__("logistics_company") + + def get_all_companies(self, country: str = None, active_only: bool = True) -> List[Dict]: + """获取所有物流公司""" + conditions = {} + if country: + conditions["country"] = country + if active_only: + conditions["active"] = 1 + + if conditions: + df = self.get_by_condition(conditions) + else: + df = self.get_all() + + if df.empty: + return [] + + return df.to_dict("records") + + def get_company_info(self, company_code: str) -> Optional[Dict]: + """获取物流公司详细信息""" + df = self.get_by_condition({"company_code": company_code}) + if df.empty: + return None + return df.iloc[0].to_dict() + + def get_companies_by_type(self, country: str, logistics_type: str) -> List[Dict]: + """根据物流类型获取公司列表""" + query = f""" + SELECT * FROM {self.table_name} + WHERE country = '{country}' + AND logistics_type = '{logistics_type}' + AND active = 1 + """ + df = self.execute_query(query) + if df.empty: + return [] + return df.to_dict("records") diff --git a/dataaccess/uk_price_dao.py b/dataaccess/uk_price_dao.py new file mode 100644 index 0000000..b880bbe --- /dev/null +++ b/dataaccess/uk_price_dao.py @@ -0,0 +1,65 @@ +"""英国物流价格数据访问类""" +import pandas as pd +from typing import Dict, List, Optional +from dataaccess.base_dao import BaseDAO + + +class UKPriceDAO(BaseDAO): + """英国物流价格数据访问""" + + def __init__(self): + super().__init__("uk_logistics_price") + + def get_all_companies(self) -> List[str]: + """获取所有英国物流公司""" + df = self.get_all() + if df.empty: + return [] + return df["company"].unique().tolist() + + def get_company_price(self, company: str) -> pd.DataFrame: + """获取指定物流公司的价格数据""" + return self.get_by_condition({"company": company}) + + def get_company_config(self, company: str) -> Dict: + """获取物流公司配置信息""" + df = self.get_by_condition({"company": company}) + if df.empty: + return {} + + config = {} + for _, row in df.iterrows(): + key = row.get("config_key") + value = row.get("config_value") + if key: + config[key] = value + + return config + + +class UKPostcodeDAO(BaseDAO): + """英国邮编分区数据访问""" + + def __init__(self): + super().__init__("uk_postcode_zone") + + def get_zone(self, postcode: str) -> Optional[str]: + """根据邮编获取分区""" + postcode_prefix = postcode.split()[0].upper() + df = self.get_by_condition({"postcode_prefix": postcode_prefix}) + + if df.empty: + return None + + return df.iloc[0].get("zone") + + def is_remote(self, postcode: str) -> bool: + """判断是否偏远""" + postcode_prefix = postcode.split()[0].upper() + remote_prefixes = ["BT", "IM", "JE", "ZE", "GY", "HS", "PO", "IV", "KA", "KW", "PH", "PA"] + + if not any(postcode_prefix.startswith(p) for p in remote_prefixes): + return False + + df = self.get_by_condition({"postcode_prefix": postcode_prefix, "is_remote": "1"}) + return not df.empty diff --git a/dataaccess/us_price_dao.py b/dataaccess/us_price_dao.py new file mode 100644 index 0000000..407ea77 --- /dev/null +++ b/dataaccess/us_price_dao.py @@ -0,0 +1,70 @@ +"""美国物流价格数据访问类""" +import pandas as pd +from typing import Dict, List, Optional +from dataaccess.base_dao import BaseDAO + + +class USPriceDAO(BaseDAO): + """美国物流价格数据访问""" + + def __init__(self): + super().__init__("us_logistics_price") + + def get_all_companies(self) -> List[str]: + """获取所有美国物流公司""" + df = self.get_all() + if df.empty: + return [] + return df["company"].unique().tolist() + + def get_company_price(self, company: str) -> pd.DataFrame: + """获取指定物流公司的价格数据""" + return self.get_by_condition({"company": company}) + + def get_company_config(self, company: str) -> Dict: + """获取物流公司配置信息""" + df = self.get_by_condition({"company": company}) + if df.empty: + return {} + + config = {} + for _, row in df.iterrows(): + key = row.get("config_key") + value = row.get("config_value") + if key: + config[key] = value + + return config + + +class USPostcodeDAO(BaseDAO): + """美国邮编分区数据访问""" + + def __init__(self): + super().__init__("us_postcode_zone") + + def get_zone(self, postcode: str, port: str = "west") -> Optional[str]: + """根据邮编获取分区""" + postcode_5 = postcode[:5] + df = self.get_by_condition({"postcode": postcode_5, "port": port}) + + if df.empty: + return None + + return df.iloc[0].get("zone") + + def get_remote_type(self, postcode: str) -> int: + """获取偏远类型: 0-非偏远, 1-偏远, 2-超偏远, 3-超超偏远""" + postcode_5 = postcode[:5] + df = self.get_by_condition({"postcode": postcode_5}) + + if df.empty: + return 0 + + return int(df.iloc[0].get("remote_type", 0)) + + def is_contiguous(self, postcode: str) -> bool: + """判断是否在本土范围内""" + postcode_5 = postcode[:5] + df = self.get_by_condition({"postcode": postcode_5}) + return not df.empty diff --git a/login_for_cookie.py b/login_for_cookie.py index 6514451..9bbe4ab 100644 --- a/login_for_cookie.py +++ b/login_for_cookie.py @@ -5,14 +5,15 @@ import re import pytesseract from PIL import Image from tempfile import NamedTemporaryFile -from selenium.webdriver.chrome.service import Service -from selenium.webdriver.common.by import By -from selenium.webdriver.remote.file_detector import UselessFileDetector #跳过文件检测 1 -from selenium import webdriver + import redis def vercode(cookie=None): - urls = 'https://cp.maso.hk:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片） + urls = 'https://cp.baycheer.com:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片） + + + + if cookie is not None: haders = { 'Cookie': cookie #使用之前的图片链接Cooike @@ -43,7 +44,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'): try : r = redis.StrictRedis(host='192.168.100.44', port=7379, db=11,password="123456") viewcookie = r.get('cpmasosessid'+user) - url="https://cp.maso.hk/index.php?main=panel"#主页 + url="https://cp.baycheer.com/index.php?main=panel"#主页 header={'Cookie':viewcookie.decode('utf8')} resp = requests.get(url=url,headers=header) exists = re.findall(r'欢迎进入本公司后台管理系统',resp.text) @@ -57,7 +58,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'): while resetcookie ==1: - urls = 'https://cp.maso.hk:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片） + urls = 'https://cp.baycheer.com:4433/index.php?main=login&act=vercode'#图片链接（每秒更新，距离当前时间最近的时间戳最近为可使用图片） res = requests.post(url=urls) ress = re.findall('Cookie (.*?) for',str(res.cookies))#获取图片链接Cooike，图片Cooike必须和登录请求的Cooike保持一致 f1 = NamedTemporaryFile(mode='wb+',suffix='.png') @@ -77,7 +78,7 @@ def Vc(user='honghuayuan',pswd= 'a12345'): bim.save(f2)#处理完成导入 f2.seek(0) text = pytesseract.image_to_string(Image.open(f2))#开始识别 - url = 'https://cp.maso.hk:4433/index.php?main=login&act=check' + url = 'https://cp.baycheer.com:4433/index.php?main=login&act=check' haders = { 'Cookie': ress[0] #使用之前的图片链接Cooike } @@ -204,9 +205,9 @@ def zenid(): options.add_argument('--disable-gpu') options.add_argument(' -port=9222') driver=webdriver.Remote(service.service_url,options=options) - mainurl='http://cp.maso.hk/index.php?main=main' - panelUrl = "http://cp.maso.hk/index.php?main=panel"#地址 - remoteurl='http://cp.maso.hk/index.php?main=sys_remote_login&act=remotelogin&id=303' + mainurl='http://cp.baycheer.com/index.php?main=main' + panelUrl = "http://cp.baycheer.com/index.php?main=panel"#地址 + remoteurl='http://cp.baycheer.com/index.php?main=sys_remote_login&act=remotelogin&id=303' driver.get(mainurl) driver.delete_all_cookies() driver.add_cookie({'name':'sessid','value':f'{t}'}) diff --git a/logisticsClass/logisticsTail_UK.py b/logisticsClass/logisticsTail_UK.py index aa46d8e..2d1eac7 100644 --- a/logisticsClass/logisticsTail_UK.py +++ b/logisticsClass/logisticsTail_UK.py @@ -5,6 +5,7 @@ import re import pandas from logisticsClass.logisticsBaseClass import LogisticsType, TailLogistics +from utils.gtools import MySQLconnect class DPDLogistics_UK(TailLogistics): @@ -218,53 +219,75 @@ class KPNVlogistics_UK(TailLogistics): country = 'United Kingdom' company = '卡派-NV' currency = 'GBP' - logistics_type = LogisticsType.COURIER + logistics_type = LogisticsType.COURIER + + # 数据库表数据(内存缓存) + _zone_cache = None # 邮编分区缓存 + _price_cache = None # 价格缓存 - parent_current_directory = Path(__file__).parent.parent - price_path = parent_current_directory.joinpath("data") - _price_files = price_path.joinpath("英国卡派.xlsx") - ltl_cost = None - ltl_zone = None def __new__(cls): - """实现单例模式，只加载一次文件""" - if cls.ltl_cost is None or cls.ltl_zone is None: - cls.ltl_cost = pandas.read_excel(cls._price_files,sheet_name="运费") - cls.ltl_zone = pandas.read_excel(cls._price_files,sheet_name="分区") + """实现单例模式，从数据库加载数据""" + if cls._zone_cache is None or cls._price_cache is None: + cls._load_from_db() return super().__new__(cls) + + @classmethod + def _load_from_db(cls): + """从数据库加载分区和价格数据""" + conn = MySQLconnect('logistics') + with conn as c: + # 加载分区表 + c.cur.execute("SELECT `邮编`, `区域` FROM uk_XLCarrier_postcode_partition") + cls._zone_cache = {} + for row in c.cur.fetchall(): + postcode = str(row[0]) if row[0] else "" + zone = str(row[1]) if row[1] else "" + cls._zone_cache[postcode] = zone + + # 加载价格表 + c.cur.execute("SELECT `分区`, `托盘`, `运费` FROM uk_XLCarrier_postcode_fee") + cls._price_cache = {} + for row in c.cur.fetchall(): + zone = str(row[0]) if row[0] else "" + tuopan = int(row[1]) if row[1] else 0 + fee = float(row[2]) if row[2] else 0 + cls._price_cache[(zone, tuopan)] = fee + def __init__(self): super().__init__() self.base_fee = 0 self.fuel_rate = 0.1 - def is_remote(self,postcode): + + def is_remote(self, postcode): """根据邮编分区，返回分区""" postcode_prefix = postcode.split()[0].upper() - postcode_prefix = str(postcode_prefix) - zone_df = self.ltl_zone[self.ltl_zone['邮编']== postcode_prefix] - if not zone_df.empty: - return zone_df['区域'].values[0] + zone = self._zone_cache.get(postcode_prefix) + if zone: + return zone return "不在配送范围内" + def calculate_fee(self, packages, postcode): detail_amount = { - "base":0.00, - "fuel":0.00, - "tail_amount":0.00 + "base": 0.00, + "fuel": 0.00, + "tail_amount": 0.00 } zone = self.is_remote(postcode) if zone == "不在配送范围内": detail_amount['tail_amount'] = 99999 return detail_amount for package in packages: - tuopan = math.ceil(package.fst_size/120) + tuopan = math.ceil(package.fst_size / 120) tuopan = min(tuopan, 7) - base_df = self.ltl_cost[(self.ltl_cost['分区']==zone)&(self.ltl_cost['托盘']==tuopan)] - if base_df.empty: + fee = self._price_cache.get((zone, tuopan)) + if fee is None: detail_amount['tail_amount'] = 99999 return detail_amount - self.base_fee = base_df['运费'].values[0] - price = self.base_fee * tuopan/len(packages) + self.base_fee = fee + price = self.base_fee * tuopan / len(packages) detail_amount['base'] += price detail_amount['fuel'] = detail_amount['base'] * self.fuel_rate - detail_amount['tail_amount'] = detail_amount['base']+detail_amount['fuel'] + detail_amount['tail_amount'] = detail_amount['base'] + detail_amount['fuel'] return detail_amount # class KPDXLogistics_UK(TailLogistics): diff --git a/logisticsClass/logisticsTail_US.py b/logisticsClass/logisticsTail_US.py index 96124d8..1dd281b 100644 --- a/logisticsClass/logisticsTail_US.py +++ b/logisticsClass/logisticsTail_US.py @@ -5,6 +5,7 @@ import pandas from logisticsClass.logisticsBaseClass import LogisticsType, TailLogistics from data.us_zone import zone_west, zone_east from pathlib import Path +from utils.gtools import MySQLconnect """ port:west(default),east @@ -84,6 +85,10 @@ class FedexLogistics(WestLogistics_US): """Fedex""" country = "United States" country_code = "US" + + # 价格缓存(子类可覆盖) + _price_cache = None + def __init__(self): super().__init__() self.volume_weight_ratio:int # lbs抛重系数 @@ -109,6 +114,16 @@ class FedexLogistics(WestLogistics_US): self.bigpackage_2:float # 大包裹费 self.bigpackage_3:float self.bigpackage_5:float + + def get_price(self, lbs: int, zone: int) -> float: + """获取价格(子类可覆盖)""" + if self._price_cache is not None: + return self._price_cache.get(lbs, {}).get(zone, 0) + # 默认从DataFrame获取(兼容旧代码) + if self.base_price is not None: + result = self.base_price[self.base_price['lbs.'] == lbs][zone] + return result.values[0] if len(result) > 0 else 0 + return 0 self.bigpackage_7:float self.bigpackage_peak:float # 大包裹旺季附加费 self.return_package:float # 超大包裹（不可发） @@ -185,8 +200,8 @@ class FedexLogistics(WestLogistics_US): detail_amount['big_package_peak'] += self.bigpackage_peak if package.girth_inch >130 or package.fst_inch >96 else 0 detail_amount['residential_delivery'] += self.residential detail_amount['residential_peak'] += self.residential_peak - - detail_amount['base'] +=self.base_price[self.base_price['lbs.']==math.ceil(cal_weight)][zone].values[0] + + detail_amount['base'] += self.get_price(math.ceil(cal_weight), zone) for key in detail_amount: if key!= 'tail_amount' and key!= 'fuel': @@ -198,18 +213,37 @@ class FedexLogistics(WestLogistics_US): class FedexPPLogistics_US(FedexLogistics): company="Fedex-彩虹小马" - parent_current_directory = Path(__file__).parent.parent - price_path = parent_current_directory.joinpath("data") - _price_files = price_path.joinpath("美国快递.xlsx") - base_price = None + # 数据库价格缓存 + _price_cache = None + def __new__(cls): - if cls.base_price is None: - cls.base_price = pandas.read_excel(cls._price_files,sheet_name='邮差小马') + if cls._price_cache is None: + cls._load_from_db() return super().__new__(cls) + + @classmethod + def _load_from_db(cls): + """从数据库加载价格数据""" + conn = MySQLconnect('logistics') + with conn as c: + c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_delivery_postpony") + cls._price_cache = {} + for row in c.cur.fetchall(): + lbs = int(row[0]) + cls._price_cache[lbs] = { + 2: float(row[1]) if row[1] else 0, + 3: float(row[2]) if row[2] else 0, + 4: float(row[3]) if row[3] else 0, + 5: float(row[4]) if row[4] else 0, + 6: float(row[5]) if row[5] else 0, + 7: float(row[6]) if row[6] else 0, + 8: float(row[7]) if row[7] else 0, + } + def __init__(self): super().__init__() self.volume_weight_ratio=250 # lbs抛重系数 - self.residential = 6.38 + self.residential = 6.38 self.residential_peak = 0 # 0.33 0.6 # 报价表没写，账单有 self.oversize_2 = 4.50 self.oversize_3 = 4.99 @@ -231,7 +265,7 @@ class FedexPPLogistics_US(FedexLogistics): self.bigpackage_3 = 36.16 self.bigpackage_5 = 38.57 self.bigpackage_7 = 41.78 - self.bigpackage_peak = 0 # 45.26 53.56# 大包裹旺季附加费 + self.bigpackage_peak = 0 # 45.26 53.56# 大包裹旺季附加费 self.fuel_rate = 0.16 # 燃油费率 self.return_package = 1419.34 # 超大包裹（不可发） @@ -239,14 +273,33 @@ class FedexKHLogistics_US(FedexLogistics): """金宏亚""" company = "Fedex-金宏亚" - parent_current_directory = Path(__file__).parent.parent - price_path = parent_current_directory.joinpath("data") - _price_files = price_path.joinpath("美国快递.xlsx") - base_price = None + # 数据库价格缓存 + _price_cache = None + def __new__(cls): - if cls.base_price is None: - cls.base_price = pandas.read_excel(cls._price_files,sheet_name='金宏亚') + if cls._price_cache is None: + cls._load_from_db() return super().__new__(cls) + + @classmethod + def _load_from_db(cls): + """从数据库加载价格数据""" + conn = MySQLconnect('logistics') + with conn as c: + c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_delivery_kinghood") + cls._price_cache = {} + for row in c.cur.fetchall(): + lbs = int(row[0]) + cls._price_cache[lbs] = { + 2: float(row[1]) if row[1] else 0, + 3: float(row[2]) if row[2] else 0, + 4: float(row[3]) if row[3] else 0, + 5: float(row[4]) if row[4] else 0, + 6: float(row[5]) if row[5] else 0, + 7: float(row[6]) if row[6] else 0, + 8: float(row[7]) if row[7] else 0, + } + def __init__(self): super().__init__() self.volume_weight_ratio = 250 # lbs抛重系数 @@ -280,14 +333,33 @@ class FedexHOMELogistics_US(FedexLogistics): """FEDEX-HOME (1-35%-30%)""" company = "Fedex-HOME" - parent_current_directory = Path(__file__).parent.parent - price_path = parent_current_directory.joinpath("data") - _price_files = price_path.joinpath("美国快递.xlsx") - base_price = None + # 数据库价格缓存 + _price_cache = None + def __new__(cls): - if cls.base_price is None: - cls.base_price = pandas.read_excel(cls._price_files,sheet_name='FEDEX') + if cls._price_cache is None: + cls._load_from_db() return super().__new__(cls) + + @classmethod + def _load_from_db(cls): + """从数据库加载价格数据""" + conn = MySQLconnect('logistics') + with conn as c: + c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_fedex_home") + cls._price_cache = {} + for row in c.cur.fetchall(): + lbs = int(row[0]) + cls._price_cache[lbs] = { + 2: float(row[1]) if row[1] else 0, + 3: float(row[2]) if row[2] else 0, + 4: float(row[3]) if row[3] else 0, + 5: float(row[4]) if row[4] else 0, + 6: float(row[5]) if row[5] else 0, + 7: float(row[6]) if row[6] else 0, + 8: float(row[7]) if row[7] else 0, + } + def __init__(self): super().__init__() self.volume_weight_ratio = 250 # lbs抛重系数 @@ -316,18 +388,38 @@ class FedexHOMELogistics_US(FedexLogistics): self.bigpackage_peak =0 # 42.25# 大包裹旺季附加费 self.return_package = 1325 # 超大包裹（不可发） self.fuel_rate = 0.18 # 燃油费率 + class FedexGROUDLogistics_US(FedexLogistics): """FEDEX-GROUD (1-35%-30%)""" company = "Fedex-GROUD" - parent_current_directory = Path(__file__).parent.parent - price_path = parent_current_directory.joinpath("data") - _price_files = price_path.joinpath("美国快递.xlsx") - base_price = None + # 数据库价格缓存(与FedexHOMELogistics_US共享us_fedex_home表) + _price_cache = None + def __new__(cls): - if cls.base_price is None: - cls.base_price = pandas.read_excel(cls._price_files,sheet_name='FEDEX') + if cls._price_cache is None: + cls._load_from_db() return super().__new__(cls) + + @classmethod + def _load_from_db(cls): + """从数据库加载价格数据""" + conn = MySQLconnect('logistics') + with conn as c: + c.cur.execute("SELECT `lbs.`, `2`, `3`, `4`, `5`, `6`, `7`, `8` FROM us_fedex_home") + cls._price_cache = {} + for row in c.cur.fetchall(): + lbs = int(row[0]) + cls._price_cache[lbs] = { + 2: float(row[1]) if row[1] else 0, + 3: float(row[2]) if row[2] else 0, + 4: float(row[3]) if row[3] else 0, + 5: float(row[4]) if row[4] else 0, + 6: float(row[5]) if row[5] else 0, + 7: float(row[6]) if row[6] else 0, + 8: float(row[7]) if row[7] else 0, + } + def __init__(self): super().__init__() self.volume_weight_ratio = 250 # lbs抛重系数 diff --git a/logistics_service.py b/logistics_service.py new file mode 100644 index 0000000..d2a97ad --- /dev/null +++ b/logistics_service.py @@ -0,0 +1,165 @@ +"""物流费用计算统一入口服务""" +import re +from typing import Dict, List, Any, Optional + +from utils.Package import Package, Package_group +from utils.countryOperator import OperateCountry +from logisticsClass.logisticsBaseClass import PortType + + +class LogisticsService: + """物流费用计算统一服务""" + + @staticmethod + def _detect_country(postcode: str) -> str: + """根据邮编格式自动识别国家""" + postcode = postcode.strip().upper() + + # 英国邮编格式：字母+数字(+字母)+空格+数字+字母 + # 支持格式: SW1A 1AA, M1 1AA, BT1 1AA, AA11 1AA 等 + if re.match(r'^[A-Z]{1,2}[0-9][A-Z0-9]?\s?[0-9][A-Z]{2}$', postcode): + return "UK" + + # 美国邮编格式：5位数字或5位-4位 + if re.match(r'^\d{5}(-\d{4})?$', postcode): + return "US" + + # 澳洲邮编格式：4位数字 + if re.match(r'^\d{4}$', postcode): + return "AU" + + # 欧洲格式（德国、法国等） + if re.match(r'^\d{5}$', postcode): + return "DE" # 默认德国 + + raise ValueError(f"无法识别的邮编格式: {postcode}") + + @staticmethod + def _parse_packages(packages_data: List[Dict]) -> Package_group: + """解析包裹数据""" + packages = [] + for i, pkg in enumerate(packages_data): + name = pkg.get("name", f"包裹{i+1}") + length = pkg.get("length", 0) + width = pkg.get("width", 0) + height = pkg.get("height", 0) + weight = pkg.get("weight", 0) + + package = Package(name, length, width, height, weight) + packages.append(package) + + return Package_group(packages) + + @staticmethod + def calculate(postcode: str, packages_data: List[Dict], + port: PortType = PortType.DEFAULT) -> Dict[str, Any]: + """ + 计算物流费用并返回最优渠道 + + Args: + postcode: 收件人邮编 + packages_data: 包裹数据列表，格式为： + [ + {"length": 63, "width": 59, "height": 48, "weight": 8000}, # 单位：cm, g + ... + ] + port: 港口类型，默认DEFAULT + + Returns: + 包含最优渠道和所有渠道费用的字典 + """ + # 1. 识别国家 + country = LogisticsService._detect_country(postcode) + + # 2. 解析包裹 + packages = LogisticsService._parse_packages(packages_data) + + # 3. 创建国家操作对象 + op_country = OperateCountry(country, port, packages, postcode) + + # 4. 获取所有渠道费用 + all_fees = op_country.get_all_tail_info() + + # 5. 找出最优渠道 + valid_fees = {k: v for k, v in all_fees.items() if v < 99999} + if not valid_fees: + return { + "country": country, + "postcode": postcode, + "optimal_channel": None, + "optimal_fee": None, + "currency": None, + "all_channels": all_fees, + "error": "所有渠道均不可用" + } + + optimal_channel = min(valid_fees, key=valid_fees.get) + optimal_fee = valid_fees[optimal_channel] + currency = op_country.get_tail_currency(optimal_channel) + + # 6. 构建结果 + result = { + "country": country, + "postcode": postcode, + "optimal_channel": optimal_channel, + "optimal_fee": optimal_fee, + "currency": currency, + "all_channels": {}, + "package_count": len(packages_data), + "total_weight": sum(p.weight for p in packages) / 1000, # kg + } + + # 7. 添加所有渠道详情 + for company, fee in all_fees.items(): + company_type = op_country.get_logistic_type(company) + company_currency = op_country.get_tail_currency(company) + result["all_channels"][company] = { + "fee": fee if fee < 99999 else None, + "currency": company_currency, + "type": company_type, + "available": fee < 99999 + } + + return result + + @staticmethod + def calculate_us(postcode: str, packages_data: List[Dict], + port: PortType = PortType.DEFAULT) -> Dict[str, Any]: + """计算美国物流费用""" + return LogisticsService.calculate(postcode, packages_data, port) + + @staticmethod + def calculate_uk(postcode: str, packages_data: List[Dict], + port: PortType = PortType.DEFAULT) -> Dict[str, Any]: + """计算英国物流费用""" + return LogisticsService.calculate(postcode, packages_data, port) + + @staticmethod + def calculate_au(postcode: str, packages_data: List[Dict], + port: PortType = PortType.DEFAULT) -> Dict[str, Any]: + """计算澳洲物流费用""" + return LogisticsService.calculate(postcode, packages_data, port) + + @staticmethod + def calculate_eur(postcode: str, packages_data: List[Dict], + port: PortType = PortType.DEFAULT) -> Dict[str, Any]: + """计算欧洲物流费用""" + return LogisticsService.calculate(postcode, packages_data, port) + + @staticmethod + def get_company_detail(postcode: str, packages_data: List[Dict], + company_name: str) -> Dict[str, Any]: + """获取指定物流公司的费用明细""" + country = LogisticsService._detect_country(postcode) + packages = LogisticsService._parse_packages(packages_data) + op_country = OperateCountry(country, PortType.DEFAULT, packages, postcode) + + detail = op_country.get_detail_amount(company_name, packages, postcode) + currency = op_country.get_tail_currency(company_name) + + return { + "company": company_name, + "currency": currency, + "detail": detail, + "total": detail.get("tail_amount", 0) + } diff --git a/scripts/import_data.py b/scripts/import_data.py new file mode 100644 index 0000000..38eea91 --- /dev/null +++ b/scripts/import_data.py @@ -0,0 +1,469 @@ +#!/usr/bin/env python +# -*- coding: utf-8 -*- +""" +数据导入脚本 +将XLSX文件中的数据导入到数据库 +""" +import pandas as pd +import numpy as np +from pathlib import Path +from utils.gtools import MySQLconnect +from utils.config_manager import config + + +class DataImporter: + """数据导入类""" + + def __init__(self): + self.data_dir = Path(__file__).parent.parent / "data" + + def get_connection(self, dbname: str = None): + """获取数据库连接""" + return MySQLconnect(dbname) + + def execute_sql(self, sql: str, dbname: str = None): + """执行SQL语句""" + with self.get_connection(dbname) as conn: + conn.cur.execute(sql) + conn.con.commit() + + def execute_many(self, sql: str, data: list, dbname: str = None): + """批量执行SQL""" + with self.get_connection(dbname) as conn: + conn.cur.executemany(sql, data) + conn.con.commit() + + def truncate_table(self, table_name: str, dbname: str = None): + """清空表""" + self.execute_sql(f"TRUNCATE TABLE {table_name}", dbname) + + # ==================== 英国数据导入 ==================== + + def import_uk_postcode_zone(self): + """导入英国邮编分区""" + print("导入英国邮编分区...") + df = pd.read_excel(self.data_dir / "英国卡派.xlsx", sheet_name="分区") + df.columns = ["postcode_prefix", "zone"] + + data = [] + for _, row in df.iterrows(): + postcode = str(row["postcode_prefix"]).strip() + zone = str(row["zone"]).strip() + is_remote = 0 + data.append((postcode, zone, is_remote)) + + sql = "INSERT IGNORE INTO uk_postcode_zone (postcode_prefix, zone, is_remote) VALUES (%s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_uk_kp_nv_price(self): + """导入英国卡派NV运费""" + print("导入英国卡派NV运费...") + df = pd.read_excel(self.data_dir / "英国卡派.xlsx", sheet_name="运费") + df.columns = ["zone", "tuopan", "fee"] + + data = [] + for _, row in df.iterrows(): + zone = str(row["zone"]).strip() + tuopan = int(row["tuopan"]) + fee = float(row["fee"]) + data.append((zone, tuopan, fee)) + + sql = "INSERT INTO uk_kp_nv_price (zone, tuopan, fee) VALUES (%s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + # ==================== 美国数据导入 ==================== + + def import_us_fedex_pp_price(self): + """导入美国Fedex邮差小马价格""" + print("导入美国Fedex邮差小马价格...") + df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name="邮差小马") + + # 转换列名 + cols = ["lbs"] + [str(c) for c in df.columns[1:]] + df.columns = cols + + data = [] + for _, row in df.iterrows(): + lbs = int(row["lbs"]) + row_data = [lbs] + for i in range(2, 9): + val = row.get(str(i), 0) + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + sql = """INSERT INTO us_fedex_pp_price + (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_us_fedex_kh_price(self): + """导入美国Fedex金宏亚价格""" + print("导入美国Fedex金宏亚价格...") + df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name="金宏亚") + + cols = ["lbs"] + [str(c) for c in df.columns[1:]] + df.columns = cols + + data = [] + for _, row in df.iterrows(): + lbs = int(row["lbs"]) + row_data = [lbs] + for i in range(2, 9): + val = row.get(str(i), 0) + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + sql = """INSERT INTO us_fedex_kh_price + (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_us_fedex_price(self): + """导入美国Fedex价格""" + print("导入美国Fedex价格...") + + for sheet_name in ["FEDEX", "FEDEX国内"]: + try: + df = pd.read_excel(self.data_dir / "美国快递.xlsx", sheet_name=sheet_name) + if "lbs." in df.columns: + cols = ["lbs"] + [str(c) for c in df.columns[1:8]] + df.columns = cols + + data = [] + for _, row in df.iterrows(): + lbs = int(row["lbs"]) + row_data = [lbs] + for i in range(2, 9): + val = row.get(str(i), 0) + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + table = "us_fedex_price" if "FEDEX" in sheet_name and "国内" not in sheet_name else "us_fedex_price" + sql = f"""INSERT INTO {table} + (lbs, zone_2, zone_3, zone_4, zone_5, zone_6, zone_7, zone_8) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 ({sheet_name})") + except Exception as e: + print(f" 跳过 {sheet_name}: {e}") + + def import_us_giga_price(self): + """导入美国GIGA价格""" + print("导入美国GIGA价格...") + df = pd.read_excel(self.data_dir / "GIGA base_fee_20240607223514.xlsx", sheet_name="Local Fee Data") + + data = [] + for _, row in df.iterrows(): + zip_code = str(int(row["Zip Code"])) if pd.notna(row["Zip Code"]) else "" + delivery_warehouse = str(row["Delivery Warehouse"]) if pd.notna(row["Delivery Warehouse"]) else "" + general_area = str(row["General Area"]) if pd.notna(row["General Area"]) else "" + fee_type = str(row["Fee Type"]) if pd.notna(row["Fee Type"]) else "" + zone = str(row["Zone"]) if pd.notna(row["Zone"]) else "" + local_pickup_fee = float(row["Local Pickup Fee"]) if pd.notna(row["Local Pickup Fee"]) else 0 + warehouse_handling_fee = float(row["Warehouse Handling Fee"]) if pd.notna(row["Warehouse Handling Fee"]) else 0 + delivery_fee_rate = float(row["Delivery Fee Rate"]) if pd.notna(row["Delivery Fee Rate"]) else 0 + additional_delivery_fee = float(row["Additional Delivery Fee"]) if pd.notna(row["Additional Delivery Fee"]) else 0 + assembly_fee = float(row["Assembly Fee"]) if pd.notna(row["Assembly Fee"]) else 0 + + data.append((zip_code, delivery_warehouse, general_area, fee_type, zone, + local_pickup_fee, warehouse_handling_fee, delivery_fee_rate, + additional_delivery_fee, assembly_fee)) + + sql = """INSERT INTO us_giga_price + (zip_code, delivery_warehouse, general_area, fee_type, zone, + local_pickup_fee, warehouse_handling_fee, delivery_fee_rate, + additional_delivery_fee, assembly_fee) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_us_ceva_price(self): + """导入美国CEVA价格""" + print("导入美国CEVA价格...") + + # CEVA base rate + df = pd.read_excel(self.data_dir / "CEVA.xlsx", sheet_name="ceva_base_rate") + df.columns = ["ceva_weight"] + list(df.columns[1:]) + + data = [] + for _, row in df.iterrows(): + ceva_weight = row["ceva_weight"] + if pd.isna(ceva_weight): + continue + row_data = [ceva_weight] + for col in df.columns[1:]: + val = row[col] + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + sql = """INSERT INTO us_ceva_price + (ceva_weight, zone_ca, zone_wa, zone_or, zone_nv, zone_az, + zone_co, zone_ut, zone_nm, remote_area_surcharge) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (ceva_base_rate)") + + # CEVA remote zone + df = pd.read_excel(self.data_dir / "CEVA.xlsx", sheet_name="remote_zone") + df.columns = ["postal_code", "state", "beyond_zone", "remote_type"] + + data = [] + for _, row in df.iterrows(): + postal_code = str(int(row["postal_code"])) if pd.notna(row["postal_code"]) else "" + state = str(row["state"]) if pd.notna(row["state"]) else "" + beyond_zone = str(row["beyond_zone"]) if pd.notna(row["beyond_zone"]) else "" + remote_type = str(row["remote_type"]) if pd.notna(row["remote_type"]) else "standard" + data.append((postal_code, state, beyond_zone, remote_type)) + + sql = "INSERT IGNORE INTO us_ceva_zone (postal_code, state, beyond_zone, remote_type) VALUES (%s, %s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (remote_zone)") + + def import_us_metro_price(self): + """导入美国Metro价格""" + print("导入美国Metro价格...") + + for sheet_name in ["cuft_25", "cuft_35", "over35_per_cuft", "over35_min"]: + try: + df = pd.read_excel(self.data_dir / "Metro.xlsx", sheet_name=sheet_name) + if "Origins" not in df.columns: + continue + + data = [] + for _, row in df.iterrows(): + origins = str(row["Origins"]) if pd.notna(row["Origins"]) else "" + row_data = [origins] + for col in df.columns[1:]: + val = row[col] + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + cols = ", ".join([f"zone_{i}l" for i in range(1, 10)]) + sql = f"INSERT INTO us_metro_price (origins, {cols}) VALUES (%s, {cols.replace('zone_', 'zone_')})" + # 简化处理 + sql = "INSERT INTO us_metro_price (origins, zone_1l, zone_2l, zone_3l, zone_4l, zone_5l, zone_6l, zone_7l, zone_8l, zone_9l) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 ({sheet_name})") + except Exception as e: + print(f" 跳过 {sheet_name}: {e}") + + # Metro zone table + try: + df = pd.read_excel(self.data_dir / "Metro.xlsx", sheet_name="zone_table") + df.columns = ["zip_code", "new_zone_name"] + + data = [] + for _, row in df.iterrows(): + zip_code = str(int(row["zip_code"])) if pd.notna(row["zip_code"]) else "" + zone = str(row["new_zone_name"]) if pd.notna(row["new_zone_name"]) else "" + data.append((zip_code, zone)) + + sql = "INSERT IGNORE INTO us_metro_zone (zip_code, new_zone_name) VALUES (%s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (zone_table)") + except Exception as e: + print(f" zone_table: {e}") + + def import_us_xmiles_zone(self): + """导入美国XMILES邮编""" + print("导入美国XMILES邮编...") + df = pd.read_excel(self.data_dir / "XMILES.xlsx", sheet_name="postcode_table") + + # 处理可能的列名问题 + cols = df.columns.tolist() + if len(cols) >= 2: + df.columns = ["postcode", "area"] + + data = [] + for _, row in df.iterrows(): + postcode = str(int(row["postcode"])) if pd.notna(row["postcode"]) else "" + area = str(row["area"]) if pd.notna(row["area"]) else "" + data.append((postcode, area)) + + sql = "INSERT IGNORE INTO us_xmiles_zone (postcode, area) VALUES (%s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_us_am_price(self): + """导入美国AM卡派价格""" + print("导入美国AM卡派价格...") + + # price表 + df = pd.read_excel(self.data_dir / "美国卡派-AM.xlsx", sheet_name="price") + df.columns = ["pu_zone", "dl_zone", "zone_combo", "minimum", "maximum", + "fee_without_sc", "shipping_cost", "internalid", "externalid", "surcharge"] + + data = [] + for _, row in df.iterrows(): + pu_zone = str(row["pu_zone"]) if pd.notna(row["pu_zone"]) else "" + dl_zone = str(row["dl_zone"]) if pd.notna(row["dl_zone"]) else "" + zone_combo = str(row["zone_combo"]) if pd.notna(row["zone_combo"]) else "" + minimum = float(row["minimum"]) if pd.notna(row["minimum"]) else 0 + maximum = float(row["maximum"]) if pd.notna(row["maximum"]) else 0 + fee_without_sc = float(row["fee_without_sc"]) if pd.notna(row["fee_without_sc"]) else 0 + shipping_cost = float(row["shipping_cost"]) if pd.notna(row["shipping_cost"]) else 0 + surcharge = float(row["surcharge"]) if pd.notna(row["surcharge"]) else 0 + + data.append((pu_zone, dl_zone, zone_combo, minimum, maximum, + fee_without_sc, shipping_cost, surcharge)) + + sql = """INSERT INTO us_am_price + (pu_zone, dl_zone, zone_combo, minimum_weight, maximum_weight, + fee_without_sc, shipping_cost, surcharge) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (price)") + + # postcode表 + df = pd.read_excel(self.data_dir / "美国卡派-AM.xlsx", sheet_name="postcode_table") + df.columns = ["zip_code", "zone"] + + data = [] + for _, row in df.iterrows(): + zip_code = str(int(row["zip_code"])) if pd.notna(row["zip_code"]) else "" + zone = str(row["zone"]) if pd.notna(row["zone"]) else "" + data.append((zip_code, zone)) + + sql = "INSERT IGNORE INTO us_am_postcode (zip_code, zone) VALUES (%s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (postcode_table)") + + # ==================== 澳洲数据导入 ==================== + + def import_au_eparcel_price(self): + """导入澳洲eparcel价格""" + print("导入澳洲eparcel价格...") + df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="eparcel") + + cols = ["post"] + [str(c) for c in df.columns[1:]] + df.columns = cols + + data = [] + for _, row in df.iterrows(): + post = str(row["post"]) if pd.notna(row["post"]) else "" + row_data = [post] + for col in cols[1:]: + val = row.get(col, 0) + row_data.append(float(val) if pd.notna(val) else 0) + data.append(tuple(row_data)) + + sql = """INSERT INTO au_eparcel_price + (post, weight_0_5, weight_1, weight_2, weight_3, weight_4, + weight_5, weight_7, weight_10, weight_15) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + + def import_au_all(self): + """导入澳洲toll和allied数据""" + print("导入澳洲toll和allied数据...") + + # toll + try: + df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="toll") + df.columns = ["post", "zone_1", "zone_2", "zone_3", "zone_4"] + + data = [] + for _, row in df.iterrows(): + post = str(row["post"]) if pd.notna(row["post"]) else "" + data.append((post, + float(row["zone_1"]) if pd.notna(row["zone_1"]) else 0, + float(row["zone_2"]) if pd.notna(row["zone_2"]) else 0, + float(row["zone_3"]) if pd.notna(row["zone_3"]) else 0, + float(row["zone_4"]) if pd.notna(row["zone_4"]) else 0)) + + sql = "INSERT INTO au_toll_price (post, zone_1, zone_2, zone_3, zone_4) VALUES (%s, %s, %s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (toll)") + except Exception as e: + print(f" toll: {e}") + + # allied + try: + df = pd.read_excel(self.data_dir / "澳洲三大渠道.xlsx", sheet_name="allied") + df.columns = ["post", "zone_1", "zone_2", "zone_3", "zone_4"] + + data = [] + for _, row in df.iterrows(): + post = str(row["post"]) if pd.notna(row["post"]) else "" + data.append((post, + float(row["zone_1"]) if pd.notna(row["zone_1"]) else 0, + float(row["zone_2"]) if pd.notna(row["zone_2"]) else 0, + float(row["zone_3"]) if pd.notna(row["zone_3"]) else 0, + float(row["zone_4"]) if pd.notna(row["zone_4"]) else 0)) + + sql = "INSERT INTO au_allied_price (post, zone_1, zone_2, zone_3, zone_4) VALUES (%s, %s, %s, %s, %s)" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录 (allied)") + except Exception as e: + print(f" allied: {e}") + + # ==================== 欧洲数据导入 ==================== + + def import_eur_dhl_price(self): + """导入欧洲DHL价格""" + print("导入欧洲DHL价格...") + + try: + df = pd.read_excel(self.data_dir / "欧洲卡派.xlsx", sheet_name="DHL卡派IP报价") + df.columns = ["type", "country", "postalcode", "country_postalcode", + "ip_1", "ip_2", "ip_3", "ip_4", "ip_5", "ip_6"] + + data = [] + for _, row in df.iterrows(): + price_type = str(row["type"]) if pd.notna(row["type"]) else "" + country = str(row["country"]) if pd.notna(row["country"]) else "" + postalcode = str(row["postalcode"]) if pd.notna(row["postalcode"]) else "" + data.append((price_type, country, postalcode, + float(row["ip_1"]) if pd.notna(row["ip_1"]) else 0, + float(row["ip_2"]) if pd.notna(row["ip_2"]) else 0, + float(row["ip_3"]) if pd.notna(row["ip_3"]) else 0, + float(row["ip_4"]) if pd.notna(row["ip_4"]) else 0, + float(row["ip_5"]) if pd.notna(row["ip_5"]) else 0, + float(row["ip_6"]) if pd.notna(row["ip_6"]) else 0)) + + sql = """INSERT INTO eur_dhl_price + (price_type, country, postalcode, ip_1, ip_2, ip_3, ip_4, ip_5, ip_6) + VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s)""" + self.execute_many(sql, data) + print(f" 已导入 {len(data)} 条记录") + except Exception as e: + print(f" 欧洲DHL: {e}") + + # ==================== 主函数 ==================== + + def import_all(self): + """导入所有数据""" + print("开始导入数据...") + + # 英国 + self.import_uk_postcode_zone() + self.import_uk_kp_nv_price() + + # 美国 + self.import_us_fedex_pp_price() + self.import_us_fedex_kh_price() + self.import_us_fedex_price() + self.import_us_giga_price() + self.import_us_ceva_price() + self.import_us_metro_price() + self.import_us_xmiles_zone() + self.import_us_am_price() + + # 澳洲 + self.import_au_eparcel_price() + self.import_au_all() + + # 欧洲 + self.import_eur_dhl_price() + + print("\n数据导入完成!") + + +if __name__ == "__main__": + importer = DataImporter() + importer.import_all() diff --git a/sell/logistic_price/uk_price.py b/sell/logistic_price/uk_price.py index 7a998b0..3c5b6ab 100644 --- a/sell/logistic_price/uk_price.py +++ b/sell/logistic_price/uk_price.py @@ -1,11 +1,37 @@ # 英国海运订单费用,返回单个sku的订单费用和订单类型 -def uk_ocean_order_price(packages,k): +import sys +sys.path.append(r'D:\workspace\dags\logistics') +import pandas as pd + +import math +from utils.Package import Package, Package_group +import re +def uk_ocean_order_price(packages_dict_str,k): """ 入参:packages的类型是Package_group,里面包含多个Package,这是一个类,这个类今天在群里发过 入参:k是物流分摊费,也就是k 出参: 订单物流费，订单类型 """ + + packages = Package_group() + def extract_number(value): + # 提取字符串中的第一个数字 + match = re.search(r"[-+]?\d*\.\d+|\d+", str(value)) + return float(match.group()) if match else 0.0 + packages_dict = eval(packages_dict_str) + if len(packages_dict) == 0: + return (0,0) + for key, package in packages_dict.items(): + package['长'] = extract_number(package['长']) + package['宽'] = extract_number(package['宽']) + package['高'] = extract_number(package['高']) + package['重量'] = extract_number(package['重量']) + + if package['长'] == 0 or package['宽'] == 0 or package['高'] == 0 or package['重量'] == 0: + return (0,0) + packages.add_package(Package(key,package['长'], package['宽'], package['高'], package['重量'])) + # 计算uk经济直达费用 order_fee = 0 express_fee = 0 @@ -20,7 +46,7 @@ def uk_ocean_order_price(packages,k): base_fee = 3.7/0.359*1.3-k-0.8*package.get_volume_weight(6000) else: base_fee = 999999 - if package.fst_size >=100 and package.sed_size >=60 and package.weight >=30000: + if package.fst_size >=100 or package.sed_size >=60 or package.weight >=30000: other_fee1 =45 order_type1 += '大包裹' @@ -44,4 +70,45 @@ def uk_ocean_order_price(packages,k): else: order_fee = ltl_fee order_type = order_type2 - return max(round(order_fee,2),2), order_type \ No newline at end of file + 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") \ No newline at end of file diff --git a/sell/logistic_price/us_price.py b/sell/logistic_price/us_price.py index 36689e1..9bb4806 100644 --- a/sell/logistic_price/us_price.py +++ b/sell/logistic_price/us_price.py @@ -1,6 +1,11 @@ +import sys +sys.path.append(r'D:\workspace\dags\logistics') import pandas as pd + import math -express_price = pd.read_excel(r'D:\test\logistics\data\售价尾端价格.xlsx', sheet_name='Sheet1') +from utils.Package import Package, Package_group +import re +express_price = pd.read_excel(r'D:\workspace\dags\logistics\data\售价尾端价格.xlsx', sheet_name='Sheet1') key_column = express_price.iloc[:, 8] # 第 I 列 value_column = express_price.iloc[:, 9] # 第 J 列 small_column = express_price.iloc[:, 10] # 第 K 列 @@ -9,7 +14,26 @@ air_small_dict = dict(zip(key_column, small_column)) air_big_dict = dict(zip(key_column, big_column)) # 转换成字典 ocean_price_dict = dict(zip(key_column, value_column)) -def ocean_order_price(packages): +def ocean_order_price(packages_dict_str): + + packages = Package_group() + def extract_number(value): + # 提取字符串中的第一个数字 + match = re.search(r"[-+]?\d*\.\d+|\d+", str(value)) + return float(match.group()) if match else 0.0 + packages_dict = eval(packages_dict_str) + if len(packages_dict) == 0: + return (0,0) + for key, package in packages_dict.items(): + package['长'] = extract_number(package['长']) + package['宽'] = extract_number(package['宽']) + package['高'] = extract_number(package['高']) + package['重量'] = extract_number(package['重量']) + + if package['长'] == 0 or package['宽'] == 0 or package['高'] == 0 or package['重量'] == 0: + return (0,0) + packages.add_package(Package(key,package['长'], package['宽'], package['高'], package['重量'])) + express_fee = 0 # 快递基础费 long_fee = 0 # 超长费 weight_fee = 0 # 超重费 @@ -19,7 +43,8 @@ def ocean_order_price(packages): express_type_length = '' for package in packages: for key, value in ocean_price_dict.items(): - if package.weight <=key: + + if max(package.get_volume_weight(8500)*1000, package.weight) <=key: express_fee+=value break if package.fst_size>=116 or package.sed_size>=71 or package.girth>=251: @@ -32,6 +57,7 @@ def ocean_order_price(packages): if package.fst_size>=238 or package.girth>=315: big_fee+=61.6 express_type_length ="大包裹" + express_fee = 9999999 if express_fee ==0 else express_fee express_fee = express_fee + long_fee + weight_fee + big_fee express_type = express_type_length + express_type_weight @@ -127,4 +153,34 @@ def air_order_price(packages): else: express_fee+=(((min(max(package.density,37),337)*0.093+27.7-1.08)/6+0.65-1.06)*package.get_volume_weight(8500))/0.45+price express_type='FEDEX' - return express_fee, express_type \ No newline at end of file + 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") \ No newline at end of file diff --git a/sql/create_tables.sql b/sql/create_tables.sql new file mode 100644 index 0000000..be1ff04 --- /dev/null +++ b/sql/create_tables.sql @@ -0,0 +1,337 @@ +-- 物流费用计算系统数据库表结构 +-- 创建数据库: logistics + +-- ============================================ +-- 物流公司配置表 +-- ============================================ +CREATE TABLE IF NOT EXISTS logistics_company ( + id INT AUTO_INCREMENT PRIMARY KEY, + company_code VARCHAR(50) NOT NULL COMMENT '公司代码', + company_name VARCHAR(100) NOT NULL COMMENT '公司名称', + country VARCHAR(10) NOT NULL COMMENT '国家代码: US, UK, AU, DE等', + logistics_type VARCHAR(20) NOT NULL COMMENT '物流类型: EXPRESS, COURIER, OCEAN, AIR', + port VARCHAR(20) DEFAULT 'DEFAULT' COMMENT '港口: DEFAULT, WEST, EAST等', + currency VARCHAR(10) DEFAULT 'USD' COMMENT '货币', + active TINYINT DEFAULT 1 COMMENT '是否启用: 0-禁用, 1-启用', + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP, + UNIQUE KEY uk_company_code (company_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='物流公司配置表'; + +-- ============================================ +-- 英国物流价格表 +-- ============================================ + +-- 英国卡派-分区表 +CREATE TABLE IF NOT EXISTS uk_postcode_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode_prefix VARCHAR(10) NOT NULL COMMENT '邮编前缀', + zone VARCHAR(10) NOT NULL COMMENT '分区', + is_remote TINYINT DEFAULT 0 COMMENT '是否偏远: 0-否, 1-是', + UNIQUE KEY uk_postcode (postcode_prefix) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='英国邮编分区表'; + +-- 英国卡派-运费表 +CREATE TABLE IF NOT EXISTS uk_kp_nv_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + zone VARCHAR(10) NOT NULL COMMENT '分区', + tuopan INT NOT NULL COMMENT '托盘数', + fee DECIMAL(10,2) NOT NULL COMMENT '运费', + INDEX idx_zone (zone) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='英国卡派NV运费表'; + +-- ============================================ +-- 美国物流价格表 +-- ============================================ + +-- 美国邮编分区表 +CREATE TABLE IF NOT EXISTS us_postcode_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(5) NOT NULL COMMENT '邮编(5位)', + port VARCHAR(20) DEFAULT 'west' COMMENT '港口: west, east', + zone VARCHAR(10) COMMENT '分区', + remote_type INT DEFAULT 0 COMMENT '偏远类型: 0-非偏远, 1-偏远, 2-超偏远, 3-超超偏远', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国邮编分区表'; + +-- 美国快递-邮差小马 价格表 +CREATE TABLE IF NOT EXISTS us_fedex_pp_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + lbs INT NOT NULL COMMENT '重量(磅)', + zone_2 DECIMAL(10,2) COMMENT '2区价格', + zone_3 DECIMAL(10,2) COMMENT '3区价格', + zone_4 DECIMAL(10,2) COMMENT '4区价格', + zone_5 DECIMAL(10,2) COMMENT '5区价格', + zone_6 DECIMAL(10,2) COMMENT '6区价格', + zone_7 DECIMAL(10,2) COMMENT '7区价格', + zone_8 DECIMAL(10,2) COMMENT '8区价格', + INDEX idx_lbs (lbs) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Fedex邮差小马价格表'; + +-- 美国快递-金宏亚 价格表 +CREATE TABLE IF NOT EXISTS us_fedex_kh_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + lbs INT NOT NULL COMMENT '重量(磅)', + zone_2 DECIMAL(10,2) COMMENT '2区价格', + zone_3 DECIMAL(10,2) COMMENT '3区价格', + zone_4 DECIMAL(10,2) COMMENT '4区价格', + zone_5 DECIMAL(10,2) COMMENT '5区价格', + zone_6 DECIMAL(10,2) COMMENT '6区价格', + zone_7 DECIMAL(10,2) COMMENT '7区价格', + zone_8 DECIMAL(10,2) COMMENT '8区价格', + INDEX idx_lbs (lbs) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Fedex金宏亚价格表'; + +-- 美国快递-FEDEX 价格表 +CREATE TABLE IF NOT EXISTS us_fedex_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + lbs INT NOT NULL COMMENT '重量(磅)', + zone_2 DECIMAL(10,2) COMMENT '2区价格', + zone_3 DECIMAL(10,2) COMMENT '3区价格', + zone_4 DECIMAL(10,2) COMMENT '4区价格', + zone_5 DECIMAL(10,2) COMMENT '5区价格', + zone_6 DECIMAL(10,2) COMMENT '6区价格', + zone_7 DECIMAL(10,2) COMMENT '7区价格', + zone_8 DECIMAL(10,2) COMMENT '8区价格', + INDEX idx_lbs (lbs) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国FEDEX价格表'; + +-- 美国卡派-GIGA 价格表 +CREATE TABLE IF NOT EXISTS us_giga_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + zip_code VARCHAR(5) NOT NULL COMMENT '邮编', + delivery_warehouse VARCHAR(50) COMMENT '仓库', + general_area VARCHAR(50) COMMENT '地区', + fee_type VARCHAR(20) COMMENT '费用类型', + zone VARCHAR(10) COMMENT '分区', + local_pickup_fee DECIMAL(10,2) COMMENT '本地取货费', + warehouse_handling_fee DECIMAL(10,2) COMMENT '仓库操作费', + delivery_fee_rate DECIMAL(10,2) COMMENT '配送费率', + additional_delivery_fee DECIMAL(10,2) COMMENT '额外配送费', + assembly_fee DECIMAL(10,2) COMMENT '装配费', + INDEX idx_zip (zip_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国GIGA价格表'; + +-- 美国卡派-CEVA 价格表 +CREATE TABLE IF NOT EXISTS us_ceva_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + ceva_weight INT NOT NULL COMMENT 'CEVA重量', + zone_ca DECIMAL(10,2) COMMENT 'CA区价格', + zone_wa DECIMAL(10,2) COMMENT 'WA区价格', + zone_or DECIMAL(10,2) COMMENT 'OR区价格', + zone_nv DECIMAL(10,2) COMMENT 'NV区价格', + zone_az DECIMAL(10,2) COMMENT 'AZ区价格', + zone_co DECIMAL(10,2) COMMENT 'CO区价格', + zone_ut DECIMAL(10,2) COMMENT 'UT区价格', + zone_nm DECIMAL(10,2) COMMENT 'NM区价格', + remote_area_surcharge DECIMAL(10,2) COMMENT '偏远地区附加费', + INDEX idx_weight (ceva_weight) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA价格表'; + +-- 美国卡派-CEVA 邮编分区表 +CREATE TABLE IF NOT EXISTS us_ceva_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postal_code VARCHAR(5) NOT NULL COMMENT '邮编', + state VARCHAR(20) COMMENT '州', + beyond_zone VARCHAR(10) COMMENT '超出分区', + remote_type VARCHAR(20) DEFAULT 'standard' COMMENT '偏远类型: standard, remote', + INDEX idx_postal (postal_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA邮编分区表'; + +-- 美国卡派-CEVA 分区表 +CREATE TABLE IF NOT EXISTS us_ceva_zone_grade ( + id INT AUTO_INCREMENT PRIMARY KEY, + to_state VARCHAR(20) NOT NULL COMMENT '目的地州', + ca DECIMAL(10,2) COMMENT 'CA分区', + wa DECIMAL(10,2) COMMENT 'WA分区', + INDEX idx_state (to_state) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国CEVA分区等级表'; + +-- 美国卡派-Metro 价格表 +CREATE TABLE IF NOT EXISTS us_metro_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + origins VARCHAR(20) NOT NULL COMMENT '出发地', + zone_1l DECIMAL(10,2) COMMENT 'Zone 1L价格', + zone_2l DECIMAL(10,2) COMMENT 'Zone 2L价格', + zone_3l DECIMAL(10,2) COMMENT 'Zone 3L价格', + zone_4l DECIMAL(10,2) COMMENT 'Zone 4L价格', + zone_5l DECIMAL(10,2) COMMENT 'Zone 5L价格', + zone_6l DECIMAL(10,2) COMMENT 'Zone 6L价格', + zone_7l DECIMAL(10,2) COMMENT 'Zone 7L价格', + zone_8l DECIMAL(10,2) COMMENT 'Zone 8L价格', + zone_9l DECIMAL(10,2) COMMENT 'Zone 9L价格', + INDEX idx_origins (origins) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro价格表'; + +-- 美国卡派-Metro 邮编分区表 +CREATE TABLE IF NOT EXISTS us_metro_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + zip_code VARCHAR(5) NOT NULL COMMENT '邮编', + new_zone_name VARCHAR(20) COMMENT '新分区名', + INDEX idx_zip (zip_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro邮编分区表'; + +-- 美国卡派-Metro 偏远表 +CREATE TABLE IF NOT EXISTS us_metro_remote ( + id INT AUTO_INCREMENT PRIMARY KEY, + zip_code VARCHAR(5) NOT NULL COMMENT '邮编', + area_type VARCHAR(50) COMMENT '区域类型', + INDEX idx_zip (zip_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国Metro偏远表'; + +-- 美国卡派-XMILES 邮编表 +CREATE TABLE IF NOT EXISTS us_xmiles_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(5) NOT NULL COMMENT '邮编', + area VARCHAR(20) COMMENT '地区', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国XMILES邮编分区表'; + +-- 美国卡派-AM 价格表 +CREATE TABLE IF NOT EXISTS us_am_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + pu_zone VARCHAR(5) NOT NULL COMMENT 'PU区', + dl_zone VARCHAR(5) NOT NULL COMMENT 'DL区', + zone_combo VARCHAR(10) NOT NULL COMMENT '分区组合', + minimum_weight DECIMAL(10,2) NOT NULL COMMENT '最小重量', + maximum_weight DECIMAL(10,2) NOT NULL COMMENT '最大重量', + fee_without_sc DECIMAL(10,2) COMMENT '无附加费价格', + shipping_cost DECIMAL(10,2) COMMENT '运费', + surcharge DECIMAL(10,2) DEFAULT 0 COMMENT '附加费', + INDEX idx_zone_combo (zone_combo) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国AM卡派价格表'; + +-- 美国卡派-AM 邮编表 +CREATE TABLE IF NOT EXISTS us_am_postcode ( + id INT AUTO_INCREMENT PRIMARY KEY, + zip_code VARCHAR(5) NOT NULL COMMENT '邮编', + zone VARCHAR(5) NOT NULL COMMENT '分区', + INDEX idx_zip (zip_code) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='美国AM卡派邮编表'; + +-- ============================================ +-- 澳洲物流价格表 +-- ============================================ + +-- 澳洲eparcel价格表 +CREATE TABLE IF NOT EXISTS au_eparcel_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + post VARCHAR(20) NOT NULL COMMENT '邮寄方式', + weight_0_5 DECIMAL(10,2) COMMENT '0.5kg价格', + weight_1 DECIMAL(10,2) COMMENT '1kg价格', + weight_2 DECIMAL(10,2) COMMENT '2kg价格', + weight_3 DECIMAL(10,2) COMMENT '3kg价格', + weight_4 DECIMAL(10,2) COMMENT '4kg价格', + weight_5 DECIMAL(10,2) COMMENT '5kg价格', + weight_7 DECIMAL(10,2) COMMENT '7kg价格', + weight_10 DECIMAL(10,2) COMMENT '10kg价格', + weight_15 DECIMAL(10,2) COMMENT '15kg价格', + INDEX idx_post (post) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲eparcel价格表'; + +-- 澳洲eparcel邮编表 +CREATE TABLE IF NOT EXISTS au_eparcel_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(10) NOT NULL COMMENT '邮编', + zone VARCHAR(10) COMMENT '分区', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲eparcel邮编表'; + +-- 澳洲toll价格表 +CREATE TABLE IF NOT EXISTS au_toll_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + post VARCHAR(20) NOT NULL COMMENT '邮寄方式', + zone_1 DECIMAL(10,2) COMMENT '1区价格', + zone_2 DECIMAL(10,2) COMMENT '2区价格', + zone_3 DECIMAL(10,2) COMMENT '3区价格', + zone_4 DECIMAL(10,2) COMMENT '4区价格', + INDEX idx_post (post) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll价格表'; + +-- 澳洲toll邮编表 +CREATE TABLE IF NOT EXISTS au_toll_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(10) NOT NULL COMMENT '邮编', + zone VARCHAR(10) COMMENT '分区', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll邮编表'; + +-- 澳洲toll偏远表 +CREATE TABLE IF NOT EXISTS au_toll_remote ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(10) NOT NULL COMMENT '邮编', + remote_type VARCHAR(20) COMMENT '偏远类型', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲toll偏远表'; + +-- 澳洲allied价格表 +CREATE TABLE IF NOT EXISTS au_allied_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + post VARCHAR(20) NOT NULL COMMENT '邮寄方式', + zone_1 DECIMAL(10,2) COMMENT '1区价格', + zone_2 DECIMAL(10,2) COMMENT '2区价格', + zone_3 DECIMAL(10,2) COMMENT '3区价格', + zone_4 DECIMAL(10,2) COMMENT '4区价格', + INDEX idx_post (post) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied价格表'; + +-- 澳洲allied邮编表 +CREATE TABLE IF NOT EXISTS au_allied_zone ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(10) NOT NULL COMMENT '邮编', + zone VARCHAR(10) COMMENT '分区', + remote_zone VARCHAR(10) COMMENT '偏远分区', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied邮编表'; + +-- 澳洲allied偏远表 +CREATE TABLE IF NOT EXISTS au_allied_remote ( + id INT AUTO_INCREMENT PRIMARY KEY, + postcode VARCHAR(10) NOT NULL COMMENT '邮编', + remote_type VARCHAR(20) COMMENT '偏远类型', + INDEX idx_postcode (postcode) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='澳洲allied偏远表'; + +-- ============================================ +-- 欧洲物流价格表 +-- ============================================ + +-- 欧洲卡派-DHL价格表 +CREATE TABLE IF NOT EXISTS eur_dhl_price ( + id INT AUTO_INCREMENT PRIMARY KEY, + price_type VARCHAR(20) NOT NULL COMMENT '价格类型', + country VARCHAR(50) NOT NULL COMMENT '国家', + postalcode VARCHAR(10) COMMENT '邮编', + ip_1 DECIMAL(10,2) COMMENT '1IP价格', + ip_2 DECIMAL(10,2) COMMENT '2IP价格', + ip_3 DECIMAL(10,2) COMMENT '3IP价格', + ip_4 DECIMAL(10,2) COMMENT '4IP价格', + ip_5 DECIMAL(10,2) COMMENT '5IP价格', + ip_6 DECIMAL(10,2) COMMENT '6IP价格', + INDEX idx_country (country) +) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='欧洲DHL卡派价格表'; + +-- ============================================ +-- 物流公司配置数据 +-- ============================================ +INSERT INTO logistics_company (company_code, company_name, country, logistics_type, port, currency) VALUES +-- 英国 +('UK_DPD', '智谷-DPD', 'UK', 'EXPRESS', 'DEFAULT', 'GBP'), +('UK_BIG', '智谷-大件', 'UK', 'COURIER', 'DEFAULT', 'GBP'), +('UK_KPZG', '海GB-卡派', 'UK', 'COURIER', 'DEFAULT', 'GBP'), +('UK_KPNV', '卡派-NV', 'UK', 'COURIER', 'DEFAULT', 'GBP'), +-- 美国 +('US_FEDEX_PP', 'Fedex-邮差小马', 'US', 'EXPRESS', 'WEST', 'USD'), +('US_FEDEX_KH', 'Fedex-金宏亚', 'US', 'EXPRESS', 'WEST', 'USD'), +('US_FEDEX_HOME', 'Fedex-HOME', 'US', 'EXPRESS', 'WEST', 'USD'), +('US_FEDEX_GROUND', 'Fedex-GROUND', 'US', 'EXPRESS', 'WEST', 'USD'), +('US_GIGA', '大健-GIGA', 'US', 'COURIER', 'DEFAULT', 'USD'), +('US_CEVA', '大健-CEVA', 'US', 'COURIER', 'DEFAULT', 'USD'), +('US_METRO', 'Metro-SAIR', 'US', 'COURIER', 'DEFAULT', 'USD'), +('US_XMILES', 'XMILES-SAIR', 'US', 'COURIER', 'DEFAULT', 'USD'), +('US_AM_WEST', 'AM-美西', 'US', 'COURIER', 'WEST', 'USD'), +('US_AM_EAST', 'AM-美东', 'US', 'COURIER', 'EAST', 'USD'), +-- 澳洲 +('AU_EPARCEL', 'AU-eparcel', 'AU', 'EXPRESS', 'DEFAULT', 'AUD'), +('AU_TOLL', 'AU-Toll', 'AU', 'COURIER', 'DEFAULT', 'AUD'), +('AU_ALLIED', 'AU-Allied', 'AU', 'COURIER', 'DEFAULT', 'AUD'); diff --git a/tests/test_logistics_service.py b/tests/test_logistics_service.py new file mode 100644 index 0000000..b360a82 --- /dev/null +++ b/tests/test_logistics_service.py @@ -0,0 +1,176 @@ +"""物流费用计算服务测试文件""" +import pytest +from logistics_service import LogisticsService +from logisticsClass.logisticsBaseClass import PortType + + +class TestLogisticsService: + """物流服务测试类""" + + def test_detect_country_uk(self): + """测试英国邮编识别""" + assert LogisticsService._detect_country("PA2 9BF") == "UK" + assert LogisticsService._detect_country("SW1A 1AA") == "UK" + assert LogisticsService._detect_country("BT1 1AA") == "UK" + + def test_detect_country_us(self): + """测试美国邮编识别""" + assert LogisticsService._detect_country("10001") == "US" + assert LogisticsService._detect_country("10001-1234") == "US" + assert LogisticsService._detect_country("90210") == "US" + + def test_detect_country_au(self): + """测试澳洲邮编识别""" + assert LogisticsService._detect_country("2000") == "AU" + assert LogisticsService._detect_country("3000") == "AU" + + def test_parse_packages(self): + """测试包裹解析""" + packages_data = [ + {"name": "包裹1", "length": 63, "width": 59, "height": 48, "weight": 8000}, + {"name": "包裹2", "length": 50, "width": 40, "height": 30, "weight": 5000}, + ] + packages = LogisticsService._parse_packages(packages_data) + + assert len(packages.packages) == 2 + assert packages.packages[0].fst_size == 63 + assert packages.packages[1].fst_size == 50 + + def test_parse_packages_default_name(self): + """测试包裹解析-默认名称""" + packages_data = [ + {"length": 63, "width": 59, "height": 48, "weight": 8000}, + ] + packages = LogisticsService._parse_packages(packages_data) + + assert len(packages.packages) == 1 + + def test_calculate_uk(self): + """测试英国物流费用计算""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + result = LogisticsService.calculate_uk("PA2 9BF", packages) + + assert result["country"] == "UK" + assert result["postcode"] == "PA2 9BF" + assert result["optimal_channel"] is not None + assert result["optimal_fee"] is not None + assert result["currency"] == "GBP" + assert len(result["all_channels"]) > 0 + + def test_calculate_uk_london(self): + """测试英国伦敦邮编""" + packages = [{"length": 30, "width": 20, "height": 10, "weight": 2000}] + result = LogisticsService.calculate_uk("SW1A 1AA", packages) + + assert result["country"] == "UK" + assert result["optimal_channel"] is not None + + def test_calculate_us(self): + """测试美国物流费用计算""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + result = LogisticsService.calculate_us("10001", packages) + + assert result["country"] == "US" + assert result["postcode"] == "10001" + assert result["optimal_channel"] is not None + assert result["optimal_fee"] is not None + assert result["currency"] == "USD" + + def test_calculate_us_west(self): + """测试美国美西邮编""" + packages = [{"length": 50, "width": 40, "height": 30, "weight": 5000}] + result = LogisticsService.calculate_us("90001", packages) + + assert result["country"] == "US" + assert result["optimal_channel"] is not None + + def test_calculate_auto_detect(self): + """测试自动识别国家""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + + # 英国 + result_uk = LogisticsService.calculate("PA2 9BF", packages) + assert result_uk["country"] == "UK" + + # 美国 + result_us = LogisticsService.calculate("10001", packages) + assert result_us["country"] == "US" + + def test_calculate_multiple_packages(self): + """测试多包裹计算""" + packages = [ + {"length": 63, "width": 59, "height": 48, "weight": 8000}, + {"length": 50, "width": 40, "height": 30, "weight": 5000}, + {"length": 40, "width": 30, "height": 20, "weight": 3000}, + ] + result = LogisticsService.calculate_uk("PA2 9BF", packages) + + assert result["package_count"] == 3 + assert result["total_weight"] == 16.0 # kg + + def test_get_company_detail(self): + """测试获取指定物流公司详情""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + detail = LogisticsService.get_company_detail("PA2 9BF", packages, "智谷-DPD") + + assert detail["company"] == "智谷-DPD" + assert detail["currency"] == "GBP" + assert "detail" in detail + assert "total" in detail + + def test_invalid_postcode(self): + """测试无效邮编""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + + with pytest.raises(ValueError): + LogisticsService.calculate("invalid", packages) + + def test_result_structure(self): + """测试返回结果结构""" + packages = [{"length": 63, "width": 59, "height": 48, "weight": 8000}] + result = LogisticsService.calculate_uk("PA2 9BF", packages) + + # 验证必需字段 + required_fields = [ + "country", "postcode", "optimal_channel", "optimal_fee", + "currency", "all_channels", "package_count", "total_weight" + ] + for field in required_fields: + assert field in result, f"缺少字段: {field}" + + # 验证渠道详情结构 + for company, info in result["all_channels"].items(): + assert "fee" in info + assert "currency" in info + assert "type" in info + assert "available" in info + + +class TestPackageCalculation: + """包裹计算测试类""" + + def test_small_package(self): + """测试小包裹""" + packages = [{"length": 20, "width": 15, "height": 10, "weight": 500}] + result = LogisticsService.calculate_uk("SW1A 1AA", packages) + + assert result["optimal_fee"] is not None + + def test_large_package(self): + """测试大包裹""" + packages = [{"length": 200, "width": 100, "height": 80, "weight": 50000}] + result = LogisticsService.calculate_uk("PA2 9BF", packages) + + # 大包裹可能被某些渠道拒绝 + assert result is not None + + def test_heavy_package(self): + """测试重包裹""" + packages = [{"length": 50, "width": 40, "height": 30, "weight": 80000}] + result = LogisticsService.calculate_us("10001", packages) + + assert result is not None + + +if __name__ == "__main__": + pytest.main([__file__, "-v"]) diff --git a/utils/config_manager.py b/utils/config_manager.py new file mode 100644 index 0000000..94a97cd --- /dev/null +++ b/utils/config_manager.py @@ -0,0 +1,53 @@ +"""配置管理模块""" +import json +import os +from pathlib import Path +from typing import Any, Dict + + +class ConfigManager: + """配置管理器""" + + _instance = None + _config: Dict[str, Any] = {} + + def __new__(cls): + if cls._instance is None: + cls._instance = super().__new__(cls) + return cls._instance + + def __init__(self): + if not self._config: + self._load_config() + + def _load_config(self): + """加载配置文件""" + config_dir = Path(__file__).parent.parent / "config" + config_file = config_dir / "database.json" + + if not config_file.exists(): + raise FileNotFoundError(f"配置文件不存在: {config_file}") + + with open(config_file, "r", encoding="utf-8") as f: + self._config = json.load(f) + + def get(self, key: str, default: Any = None) -> Any: + """获取配置项""" + keys = key.split(".") + value = self._config + for k in keys: + if isinstance(value, dict): + value = value.get(k) + if value is None: + return default + else: + return default + return value + + def get_database_config(self) -> Dict[str, Any]: + """获取数据库配置""" + return self._config.get("database", {}) + + +# 全局配置实例 +config = ConfigManager() diff --git a/utils/gtools.py b/utils/gtools.py index c55a174..bcf81cd 100644 --- a/utils/gtools.py +++ b/utils/gtools.py @@ -1,13 +1,22 @@ import pymysql from sqlalchemy import create_engine +from utils.config_manager import config class MySQLconnect(): - def __init__(self, dbname: str): - if isinstance(dbname, str): - self.dbname = dbname - self.host = '192.168.100.33' - else: + def __init__(self, dbname: str = None): + db_config = config.get_database_config() + self.host = db_config.get("host", "192.168.100.33") + self.port = db_config.get("port", 3306) + self.user = db_config.get("username", "zhenggantian") + self.password = db_config.get("password", "123456") + self.dbname = dbname or db_config.get("database", "logistics") + self.charset = db_config.get("charset", "utf8") + self.pool_size = db_config.get("pool_size", 10) + self.max_overflow = db_config.get("max_overflow", 5) + self.pool_recycle = db_config.get("pool_recycle", 3600) + + if not isinstance(self.dbname, str): raise TypeError("dbname must be a string") def __enter__(self): @@ -24,9 +33,19 @@ class MySQLconnect(): raise def engine(self): - return create_engine("mysql+pymysql://zhenggantian:123456@" + self.host + f":3306/{self.dbname}", - pool_size=10, max_overflow=5, pool_recycle=3600) + return create_engine( + f"mysql+pymysql://{self.user}:{self.password}@{self.host}:{self.port}/{self.dbname}", + pool_size=self.pool_size, + max_overflow=self.max_overflow, + pool_recycle=self.pool_recycle + ) def connect(self): - return pymysql.connect(host=self.host, port=3306, database=self.dbname, user="zhenggantian", password="123456", - charset="utf8") + return pymysql.connect( + host=self.host, + port=self.port, + database=self.dbname, + user=self.user, + password=self.password, + charset=self.charset + ) diff --git a/~$单包裹SKU售价分析1.xlsx b/~$单包裹SKU售价分析1.xlsx deleted file mode 100644 index 234494c..0000000 --- a/~$单包裹SKU售价分析1.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/~$表头更新方案.xlsx b/~$表头更新方案.xlsx deleted file mode 100644 index 234494c..0000000 --- a/~$表头更新方案.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$1-3月利润分段.xlsx b/拦截数据/~$1-3月利润分段.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$1-3月利润分段.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$batch_release.xlsx b/拦截数据/~$batch_release.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$batch_release.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$product_property_data.xlsx b/拦截数据/~$product_property_data.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$product_property_data.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$工作日报-文雪茜.xlsx b/拦截数据/~$工作日报-文雪茜.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$工作日报-文雪茜.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$拦截总表.xlsx b/拦截数据/~$拦截总表.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$拦截总表.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$拦截订单登记明细.xlsx b/拦截数据/~$拦截订单登记明细.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$拦截订单登记明细.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/拦截数据/~$订单数据.xlsx b/拦截数据/~$订单数据.xlsx deleted file mode 100644 index 234494c..0000000 --- a/拦截数据/~$订单数据.xlsx +++ /dev/null @@ -1,3 +0,0 @@ -version https://git-lfs.github.com/spec/v1 -oid sha256:e4ba04959837c27019a2349015543802439e152ddc4baf4e8c7b9d2b483362a8 -size 165 diff --git a/自动化跟单11.ipynb b/自动化跟单11.ipynb index 7bb3526..fcbc7b7 100644 --- a/自动化跟单11.ipynb +++ b/自动化跟单11.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T14:28:31.802210Z", @@ -16,17 +16,17 @@ "from login_for_cookie import Vc\n", "import pendulum\n", "import json\n", - "from utils/gtools import MySQLconnect \n", - "from lxml import etree\n", + "\n", + "from utils.gtools import MySQLconnect \n", "from pathlib import Path\n", "from datetime import datetime\n", - "cookie = Vc(user='robot1',pswd= 'xi%26SiH4LbJ')\n", + "cookie = Vc(user='robot1',pswd= 'a123456')\n", "headers = {\"Cookie\":cookie}" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T10:32:48.135119Z", @@ -36,83 +36,4169 @@ "outputs": [], "source": [ "def get_fs(row):\n", - " data = row[\"采购单号\"]\n", - " buy_url = \"http://cp.maso.hk/index.php?main=store_in_receive\"\n", + " try:\n", + " print(row[\"采购单号\"])\n", + " data = row[\"采购单号\"]\n", + " buy_url = \"http://cp.baycheer.com/index.php?main=store_in_receive\"\n", "\n", - " payload = {\n", - " \"s_pid\": 2867159,\n", - " \"s_suborderid\": \"\",\n", - " \"pdt_standard_id\": \"\",\n", - " \"s_store\": -1,\n", - " \"s_status[0]\": 0,\n", - " \"s_sort\": \"desc\",\n", - " \"Submit\": \"查询\",\n", - " \"synergy_sign\": -1,\n", - " \"start_dep\": \"\",\n", - " \"start_user\": \"\",\n", - " \"to_dep\": \"\",\n", - " \"to_user\": \"\",\n", - " \"swebid\": 0,\n", - " \"local_pdt_id\": 0,\n", - " \"sadd_time\": \"\",\n", - " \"sadd_time_end\": \"\",\n", - " \"sreal_express_no\": \"\",\n", - " \"sweb_id\": \"\",\n", - " \"sof\": 0,\n", - " \"soe\": 0,\n", - " \"sod\": \"\",\n", - " \"tsid\": -1,\n", - " \"tsdid\": -1,\n", - " \"tsst\": -1,\n", - " \"order_cate\": -1,\n", - " \"error_status\": -1,\n", - " \"web_uid\": -1,\n", - " \"team_id\": -1,\n", - " \"handle\": -1,\n", - " \"handle_uid\": 0,\n", - " \"handle_time_start\": \"\",\n", - " \"handle_time_end\": \"\",\n", - " \"shiping_time_start\": \"\",\n", - " \"shiping_time_end\": \"\",\n", - " \"trade_time_start\": \"\",\n", - " \"trade_time_end\": \"\",\n", - " \"order_express_fee\": -1,\n", - " \"web_type\": -1,\n", - " \"shipping_type\": -1,\n", - " \"maintain_add_time_s\": \"\",\n", - " \"maintain_add_time_e\": \"\",\n", - " \"maintain_comfirm_time_s\": \"\",\n", - " \"maintain_comfirm_time_e\": \"\",\n", - " \"dispense_user_id\": \"\",\n", - " \"export_page\": 1\n", - " }\n", - " payload[\"s_pid\"] = data\n", - " resp = requests.post(url = buy_url ,headers=headers , data=payload)\n", - " buy_df_list = pd.read_html(resp.text,match=\"所属网站ID\")\n", - " buy_df = buy_df_list[1]\n", - " buy_df.columns = buy_df.loc[0,:]\n", - " trade_id = buy_df[\"交易ID\"][1]\n", - " #交易明细里头\n", - " trade_url = f\"http://cp.maso.hk/index.php?main=store_tradelist_info&trade_id={trade_id}\"\n", - " resp2 = requests.get(url = trade_url ,headers=headers )\n", - " df_list2 = pd.read_html(resp2.text,match=\"下单发货时间\")\n", - " df2 = df_list2[0]\n", - " df2.columns = df2.loc[0,:]\n", - " 下单发货时间 = int(df2.iloc[2,1][0].replace(\"--\",\"0\"))\n", - " 维护发货时间 = int(df2.iloc[2,3].replace(\"--\",\"0\"))\n", - " 支付时间 = pendulum.parse(df2.iloc[3,3])\n", - " 最大发货时间 = 支付时间.add(days=max(下单发货时间,维护发货时间))\n", - " #交易列表\n", - " trade_list_url = f\"http://cp.maso.hk/index.php?main=store_in_receive&navlist=trade_list&s_trade_id={trade_id}\"\n", - " resp3 = requests.get(url = trade_list_url ,headers=headers )\n", - " df_list3 = pd.read_html(resp3.text,match=\"涨幅\")\n", - " df3 = df_list3[0]\n", - " df3.columns = df3.loc[0,:]\n", - " 交易平台 = df3[\"交易平台\"][1]\n", - " 交易号 = df3[\"交易号\"][1]\n", - " 交易平台订单号 = df3[\"交易平台订单号\"][1]\n", + " payload = {\n", + " \"s_pid\": 2867159,\n", + " \"s_suborderid\": \"\",\n", + " \"pdt_standard_id\": \"\",\n", + " \"s_store\": -1,\n", + " \"s_status[0]\": 0,\n", + " \"s_sort\": \"desc\",\n", + " \"Submit\": \"查询\",\n", + " \"synergy_sign\": -1,\n", + " \"start_dep\": \"\",\n", + " \"start_user\": \"\",\n", + " \"to_dep\": \"\",\n", + " \"to_user\": \"\",\n", + " \"swebid\": 0,\n", + " \"local_pdt_id\": 0,\n", + " \"sadd_time\": \"\",\n", + " \"sadd_time_end\": \"\",\n", + " \"sreal_express_no\": \"\",\n", + " \"sweb_id\": \"\",\n", + " \"sof\": 0,\n", + " \"soe\": 0,\n", + " \"sod\": \"\",\n", + " \"tsid\": -1,\n", + " \"tsdid\": -1,\n", + " \"tsst\": -1,\n", + " \"order_cate\": -1,\n", + " \"error_status\": -1,\n", + " \"web_uid\": -1,\n", + " \"team_id\": -1,\n", + " \"handle\": -1,\n", + " \"handle_uid\": 0,\n", + " \"handle_time_start\": \"\",\n", + " \"handle_time_end\": \"\",\n", + " \"shiping_time_start\": \"\",\n", + " \"shiping_time_end\": \"\",\n", + " \"trade_time_start\": \"\",\n", + " \"trade_time_end\": \"\",\n", + " \"order_express_fee\": -1,\n", + " \"web_type\": -1,\n", + " \"shipping_type\": -1,\n", + " \"maintain_add_time_s\": \"\",\n", + " \"maintain_add_time_e\": \"\",\n", + " \"maintain_comfirm_time_s\": \"\",\n", + " \"maintain_comfirm_time_e\": \"\",\n", + " \"dispense_user_id\": \"\",\n", + " \"export_page\": 1\n", + " }\n", + " payload[\"s_pid\"] = data\n", + " resp = requests.post(url = buy_url ,headers=headers , data=payload)\n", + " buy_df_list = pd.read_html(resp.text,match=\"所属网站ID\")\n", + " buy_df = buy_df_list[1]\n", + " buy_df.columns = buy_df.loc[0,:]\n", + " trade_id = buy_df[\"交易ID\"][1]\n", + " #交易明细里头\n", + " if trade_id ==\"无记录\":\n", + " return pd.Series([None,None,None,None,None,None,None,None])\n", + " trade_url = f\"http://cp.baycheer.com/index.php?main=store_tradelist_info&trade_id={trade_id}\"\n", + " resp2 = requests.get(url = trade_url ,headers=headers )\n", + " df_list2 = pd.read_html(resp2.text,match=\"下单发货时间\")\n", + " df2 = df_list2[0]\n", + " df2.columns = df2.loc[0,:]\n", + " 下单发货时间 = int(df2.iloc[2,1][0].replace(\"--\",\"0\"))\n", + " 维护发货时间 = int(df2.iloc[2,3].replace(\"--\",\"0\"))\n", + " 支付时间 = pendulum.parse(df2.iloc[3,3])\n", + " 最大发货时间 = 支付时间.add(days=max(下单发货时间,维护发货时间))\n", + " #交易列表\n", + " trade_list_url = f\"http://cp.baycheer.com/index.php?main=store_in_receive&navlist=trade_list&s_trade_id={trade_id}\"\n", + " resp3 = requests.get(url = trade_list_url ,headers=headers )\n", + " df_list3 = pd.read_html(resp3.text,match=\"涨幅\")\n", + " df3 = df_list3[0]\n", + " df3.columns = df3.loc[0,:]\n", + " 交易平台 = df3[\"交易平台\"][1]\n", + " 交易号 = df3[\"交易号\"][1]\n", + " 交易平台订单号 = df3[\"交易平台订单号\"][1]\n", " \n", - " return pd.Series([trade_id,下单发货时间, 维护发货时间,支付时间,最大发货时间,交易平台,交易号,交易平台订单号])" + " return pd.Series([trade_id,下单发货时间, 维护发货时间,支付时间,最大发货时间,交易平台,交易号,交易平台订单号])\n", + " except:\n", + " return pd.Series([None,None,None,None,None,None,None,None])" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "resultdf_ori = pd.read_excel(r\"跟单测试源文件.xlsx\")\n", + "#resultdf_ori = pd.read_excel(r\"跟单测试源文件.xlsx\")[[\"跟单任务ID\", \"采购单号\"]]\n", + "# 扩展 get_fs" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "跟单任务ID", + "rawType": "int64", + "type": "integer" + }, + { + "name": "任务组", + "rawType": "object", + "type": "string" + }, + { + "name": "指派人员", + "rawType": "object", + "type": "string" + }, + { + "name": "跟单人员", + "rawType": "float64", + "type": "float" + }, + { + "name": "创建时间", + "rawType": "datetime64[ns]", + "type": "datetime" + }, + { + "name": "跟单时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "状态", + "rawType": "object", + "type": "string" + }, + { + "name": "审核时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "审核人", + "rawType": "float64", + "type": "float" + }, + { + "name": "包裹数量", + "rawType": "int64", + "type": "integer" + }, + { + "name": "约定时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "约定发货地址", + "rawType": "float64", + "type": "float" + }, + { + "name": "是否需要退货", + "rawType": "object", + "type": "string" + }, + { + "name": "是否需要退款", + "rawType": "object", + "type": "string" + }, + { + "name": "是否需要找货", + "rawType": "object", + "type": "string" + }, + { + "name": "备注", + "rawType": "float64", + "type": "float" + }, + { + "name": "任务类型", + "rawType": "object", + "type": "string" + }, + { + "name": "采购单号", + "rawType": "int64", + "type": "integer" + }, + { + "name": "该类型的跟单次数", + "rawType": "int64", + "type": "integer" + } + ], + "ref": "3e728e3c-40c0-4182-9485-e423ac97a4cf", + "rows": [ + [ + "0", + "359974", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:08", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902619", + "1" + ], + [ + "1", + "359970", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:08", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902615", + "1" + ], + [ + "2", + "359964", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:08", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902607", + "1" + ], + [ + "3", + "359957", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:07", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902596", + "1" + ], + [ + "4", + "359952", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:07", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902588", + "1" + ], + [ + "5", + "359948", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:06", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902584", + "1" + ], + [ + "6", + "359945", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:06", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902579", + "1" + ], + [ + "7", + "359942", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:06", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902574", + "1" + ], + [ + "8", + "359939", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:05", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902570", + "1" + ], + [ + "9", + "359935", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:05", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902565", + "1" + ], + [ + "10", + "359932", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:05", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902561", + "1" + ], + [ + "11", + "359926", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:04", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902553", + "1" + ], + [ + "12", + "359923", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:04", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902550", + "1" + ], + [ + "13", + "359920", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:04", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902547", + "1" + ], + [ + "14", + "359916", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:03", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902543", + "1" + ], + [ + "15", + "359906", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:03", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902531", + "1" + ], + [ + "16", + "359902", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:02", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902527", + "1" + ], + [ + "17", + "359899", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:02", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902524", + "1" + ], + [ + "18", + "359893", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:01", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902517", + "1" + ], + [ + "19", + "359885", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:01", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902504", + "1" + ], + [ + "20", + "359879", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:00", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902496", + "1" + ], + [ + "21", + "359876", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:00", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902491", + "1" + ], + [ + "22", + "359871", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:13:00", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902484", + "1" + ], + [ + "23", + "359865", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:59", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902476", + "1" + ], + [ + "24", + "359862", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:59", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902473", + "1" + ], + [ + "25", + "359858", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:58", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902469", + "1" + ], + [ + "26", + "359854", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:58", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902465", + "1" + ], + [ + "27", + "359851", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:58", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902462", + "1" + ], + [ + "28", + "359847", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:58", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902458", + "1" + ], + [ + "29", + "359841", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:57", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902452", + "1" + ], + [ + "30", + "359838", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:57", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902449", + "1" + ], + [ + "31", + "359829", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:56", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902438", + "1" + ], + [ + "32", + "359825", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:56", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902432", + "1" + ], + [ + "33", + "359822", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:56", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902429", + "1" + ], + [ + "34", + "359818", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:55", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902424", + "1" + ], + [ + "35", + "359814", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:55", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902420", + "1" + ], + [ + "36", + "359810", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:55", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902416", + "1" + ], + [ + "37", + "359807", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:55", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902413", + "1" + ], + [ + "38", + "359804", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:54", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902410", + "1" + ], + [ + "39", + "359801", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:54", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902407", + "1" + ], + [ + "40", + "359797", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:54", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902401", + "1" + ], + [ + "41", + "359793", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:53", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902396", + "1" + ], + [ + "42", + "359788", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:53", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902390", + "1" + ], + [ + "43", + "359784", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:53", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902386", + "1" + ], + [ + "44", + "359781", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:52", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902382", + "1" + ], + [ + "45", + "359767", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:52", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902368", + "1" + ], + [ + "46", + "359763", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:51", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902364", + "1" + ], + [ + "47", + "359758", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:51", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902357", + "1" + ], + [ + "48", + "359752", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:51", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902351", + "1" + ], + [ + "49", + "359748", + "未发货-跟单组", + "机器人1", + null, + "2025-05-30 09:12:50", + null, + "待处理", + null, + null, + "0", + null, + null, + "否", + "否", + "否", + null, + "已付款，待发货-未约定发货时间", + "2902344", + "1" + ] + ], + "shape": { + "columns": 19, + "rows": 98 + } + }, + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
跟单任务ID任务组指派人员跟单人员创建时间跟单时间状态审核时间审核人包裹数量约定时间约定发货地址是否需要退货是否需要退款是否需要找货备注任务类型采购单号该类型的跟单次数
0359974未发货-跟单组机器人1NaN2025-05-30 09:13:08NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29026191
1359970未发货-跟单组机器人1NaN2025-05-30 09:13:08NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29026151
2359964未发货-跟单组机器人1NaN2025-05-30 09:13:08NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29026071
3359957未发货-跟单组机器人1NaN2025-05-30 09:13:07NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29025961
4359952未发货-跟单组机器人1NaN2025-05-30 09:13:07NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29025881
............................................................
93359509未发货-跟单组机器人1NaN2025-05-30 09:12:35NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29020951
94359506未发货-跟单组机器人1NaN2025-05-30 09:12:35NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29020921
95359501未发货-跟单组机器人1NaN2025-05-30 09:12:35NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29020871
96359488未发货-跟单组机器人1NaN2025-05-30 09:12:34NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29019991
97359486未发货-跟单组机器人1NaN2025-05-30 09:12:34NaN待处理NaNNaN0NaNNaN否否否NaN已付款，待发货-未约定发货时间29019971
\n", + "

98 rows × 19 columns

\n", + "
" + ], + "text/plain": [ + " 跟单任务ID 任务组 指派人员 跟单人员 创建时间 跟单时间 状态 审核时间 审核人 \\\n", + "0 359974 未发货-跟单组 机器人1 NaN 2025-05-30 09:13:08 NaN 待处理 NaN NaN \n", + "1 359970 未发货-跟单组 机器人1 NaN 2025-05-30 09:13:08 NaN 待处理 NaN NaN \n", + "2 359964 未发货-跟单组 机器人1 NaN 2025-05-30 09:13:08 NaN 待处理 NaN NaN \n", + "3 359957 未发货-跟单组 机器人1 NaN 2025-05-30 09:13:07 NaN 待处理 NaN NaN \n", + "4 359952 未发货-跟单组 机器人1 NaN 2025-05-30 09:13:07 NaN 待处理 NaN NaN \n", + ".. ... ... ... ... ... ... ... ... ... \n", + "93 359509 未发货-跟单组 机器人1 NaN 2025-05-30 09:12:35 NaN 待处理 NaN NaN \n", + "94 359506 未发货-跟单组 机器人1 NaN 2025-05-30 09:12:35 NaN 待处理 NaN NaN \n", + "95 359501 未发货-跟单组 机器人1 NaN 2025-05-30 09:12:35 NaN 待处理 NaN NaN \n", + "96 359488 未发货-跟单组 机器人1 NaN 2025-05-30 09:12:34 NaN 待处理 NaN NaN \n", + "97 359486 未发货-跟单组 机器人1 NaN 2025-05-30 09:12:34 NaN 待处理 NaN NaN \n", + "\n", + " 包裹数量 约定时间 约定发货地址 是否需要退货 是否需要退款 是否需要找货 备注 任务类型 采购单号 \\\n", + "0 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902619 \n", + "1 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902615 \n", + "2 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902607 \n", + "3 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902596 \n", + "4 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902588 \n", + ".. ... ... ... ... ... ... .. ... ... \n", + "93 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902095 \n", + "94 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902092 \n", + "95 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2902087 \n", + "96 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2901999 \n", + "97 0 NaN NaN 否 否 否 NaN 已付款，待发货-未约定发货时间 2901997 \n", + "\n", + " 该类型的跟单次数 \n", + "0 1 \n", + "1 1 \n", + "2 1 \n", + "3 1 \n", + "4 1 \n", + ".. ... \n", + "93 1 \n", + "94 1 \n", + "95 1 \n", + "96 1 \n", + "97 1 \n", + "\n", + "[98 rows x 19 columns]" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "resultdf_ori" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "跟单任务ID", + "rawType": "int64", + "type": "integer" + }, + { + "name": "采购单号", + "rawType": "int64", + "type": "integer" + } + ], + "ref": "42fe9f0e-dc5f-47b3-a032-0f7f436a8166", + "rows": [ + [ + "0", + "359974", + "2902619" + ], + [ + "1", + "359970", + "2902615" + ], + [ + "2", + "359964", + "2902607" + ], + [ + "3", + "359957", + "2902596" + ], + [ + "4", + "359952", + "2902588" + ], + [ + "5", + "359948", + "2902584" + ], + [ + "6", + "359945", + "2902579" + ], + [ + "7", + "359942", + "2902574" + ], + [ + "8", + "359939", + "2902570" + ], + [ + "9", + "359935", + "2902565" + ], + [ + "10", + "359932", + "2902561" + ], + [ + "11", + "359926", + "2902553" + ], + [ + "12", + "359923", + "2902550" + ], + [ + "13", + "359920", + "2902547" + ], + [ + "14", + "359916", + "2902543" + ], + [ + "15", + "359906", + "2902531" + ], + [ + "16", + "359902", + "2902527" + ], + [ + "17", + "359899", + "2902524" + ], + [ + "18", + "359893", + "2902517" + ], + [ + "19", + "359885", + "2902504" + ], + [ + "20", + "359879", + "2902496" + ], + [ + "21", + "359876", + "2902491" + ], + [ + "22", + "359871", + "2902484" + ], + [ + "23", + "359865", + "2902476" + ], + [ + "24", + "359862", + "2902473" + ], + [ + "25", + "359858", + "2902469" + ], + [ + "26", + "359854", + "2902465" + ], + [ + "27", + "359851", + "2902462" + ], + [ + "28", + "359847", + "2902458" + ], + [ + "29", + "359841", + "2902452" + ], + [ + "30", + "359838", + "2902449" + ], + [ + "31", + "359829", + "2902438" + ], + [ + "32", + "359825", + "2902432" + ], + [ + "33", + "359822", + "2902429" + ], + [ + "34", + "359818", + "2902424" + ], + [ + "35", + "359814", + "2902420" + ], + [ + "36", + "359810", + "2902416" + ], + [ + "37", + "359807", + "2902413" + ], + [ + "38", + "359804", + "2902410" + ], + [ + "39", + "359801", + "2902407" + ], + [ + "40", + "359797", + "2902401" + ], + [ + "41", + "359793", + "2902396" + ], + [ + "42", + "359788", + "2902390" + ], + [ + "43", + "359784", + "2902386" + ], + [ + "44", + "359781", + "2902382" + ], + [ + "45", + "359767", + "2902368" + ], + [ + "46", + "359763", + "2902364" + ], + [ + "47", + "359758", + "2902357" + ], + [ + "48", + "359752", + "2902351" + ], + [ + "49", + "359748", + "2902344" + ] + ], + "shape": { + "columns": 2, + "rows": 98 + } + }, + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
跟单任务ID采购单号
03599742902619
13599702902615
23599642902607
33599572902596
43599522902588
.........
933595092902095
943595062902092
953595012902087
963594882901999
973594862901997
\n", + "

98 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " 跟单任务ID 采购单号\n", + "0 359974 2902619\n", + "1 359970 2902615\n", + "2 359964 2902607\n", + "3 359957 2902596\n", + "4 359952 2902588\n", + ".. ... ...\n", + "93 359509 2902095\n", + "94 359506 2902092\n", + "95 359501 2902087\n", + "96 359488 2901999\n", + "97 359486 2901997\n", + "\n", + "[98 rows x 2 columns]" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "resultdf" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "交易ID", + "rawType": "object", + "type": "unknown" + }, + { + "name": "下单发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "维护发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "支付时间", + "rawType": "datetime64[ns, UTC]", + "type": "unknown" + }, + { + "name": "最大发货时间", + "rawType": "datetime64[ns, UTC]", + "type": "unknown" + }, + { + "name": "交易平台", + "rawType": "object", + "type": "unknown" + }, + { + "name": "交易号", + "rawType": "object", + "type": "unknown" + }, + { + "name": "交易平台订单号", + "rawType": "object", + "type": "unknown" + } + ], + "ref": "6bbcfc6d-5ce7-4209-95a5-92505322ae4b", + "rows": [ + [ + "0", + "1871514", + "5.0", + "0.0", + "2025-05-29 17:49:40+00:00", + "2025-06-03 17:49:40+00:00", + "淘天", + "2586394887255538788", + "501566-187151429026196065" + ], + [ + "1", + "1871511", + "5.0", + "3.0", + "2025-05-29 17:45:57+00:00", + "2025-06-03 17:45:57+00:00", + "1688", + "2586866558699340655", + "2586866558699340655" + ], + [ + "2", + "1871510", + "4.0", + "5.0", + "2025-05-29 17:38:32+00:00", + "2025-06-03 17:38:32+00:00", + "淘天", + "2586724428509538788", + "501566-187151029026079158" + ], + [ + "3", + "1871507", + "4.0", + "2.0", + "2025-05-29 17:31:48+00:00", + "2025-06-02 17:31:48+00:00", + "1688", + "2586369831696340655", + "2586369831696340655" + ], + [ + "4", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "5", + "1871487", + "5.0", + "0.0", + "2025-05-29 17:28:01+00:00", + "2025-06-03 17:28:01+00:00", + "1688", + "2586712116394340655", + "2586712116394340655" + ], + [ + "6", + "1871489", + "5.0", + "0.0", + "2025-05-29 17:27:31+00:00", + "2025-06-03 17:27:31+00:00", + "1688", + "2586843158361340655", + "2586843158361340655" + ], + [ + "7", + "1871504", + "5.0", + "0.0", + "2025-05-29 18:00:00+00:00", + "2025-06-03 18:00:00+00:00", + "淘天", + "2586391611043219261", + "1748511690120" + ], + [ + "8", + "1871464", + "4.0", + "0.0", + "2025-05-29 16:21:00+00:00", + "2025-06-02 16:21:00+00:00", + "淘天", + "2586603684278538788", + "501566-187146429025706383" + ], + [ + "9", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "10", + "1871446", + "4.0", + "0.0", + "2025-05-29 16:07:18+00:00", + "2025-06-02 16:07:18+00:00", + "1688", + "2586713774989340655", + "2586713774989340655" + ], + [ + "11", + "1871492", + "5.0", + "0.0", + "2025-05-29 17:58:47+00:00", + "2025-06-03 17:58:47+00:00", + "淘天", + "2587422217794219261", + "1748511214446" + ], + [ + "12", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "13", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "14", + "1871438", + "5.0", + "0.0", + "2025-05-29 17:16:28+00:00", + "2025-06-03 17:16:28+00:00", + "淘天", + "2586693324476219261", + "1748510063327" + ], + [ + "15", + "1871398", + "5.0", + "0.0", + "2025-05-29 15:24:42+00:00", + "2025-06-03 15:24:42+00:00", + "淘天", + "2587229653074538788", + "501566-187139829025312437" + ], + [ + "16", + "1871388", + "4.0", + "0.0", + "2025-05-29 14:52:40+00:00", + "2025-06-02 14:52:40+00:00", + "1688", + "2586139179096340655", + "2586139179096340655" + ], + [ + "17", + "1871418", + "5.0", + "0.0", + "2025-05-29 16:52:00+00:00", + "2025-06-03 16:52:00+00:00", + "淘天", + "2587321165625219261", + "1748507467551" + ], + [ + "18", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "19", + "1871417", + "5.0", + "0.0", + "2025-05-29 16:59:34+00:00", + "2025-06-03 16:59:34+00:00", + "淘天", + "2586615528437219261", + "1748507336231" + ], + [ + "20", + "1871353", + "5.0", + "0.0", + "2025-05-29 13:50:02+00:00", + "2025-06-03 13:50:02+00:00", + "淘天", + "2587088497261538788", + "501566-187135329024968677" + ], + [ + "21", + "1871348", + "5.0", + "0.0", + "2025-05-29 13:38:38+00:00", + "2025-06-03 13:38:38+00:00", + "淘天", + "2587071793982538788", + "501566-187134829024913484" + ], + [ + "22", + "1871345", + "5.0", + "0.0", + "2025-05-29 13:37:24+00:00", + "2025-06-03 13:37:24+00:00", + "1688", + "2586508466020340655", + "2586508466020340655" + ], + [ + "23", + "1871336", + "4.0", + "0.0", + "2025-05-29 13:16:17+00:00", + "2025-06-02 13:16:17+00:00", + "淘天", + "2586347292443538788", + "501566-187133629024764267" + ], + [ + "24", + "1871333", + "5.0", + "0.0", + "2025-05-29 13:13:58+00:00", + "2025-06-03 13:13:58+00:00", + "1688", + "2586340380550340655", + "2586340380550340655" + ], + [ + "25", + "1871376", + "4.0", + "2.0", + "2025-05-29 14:39:00+00:00", + "2025-06-02 14:39:00+00:00", + "1688", + "2586448056601340655", + "2586448056601340655" + ], + [ + "26", + "1871328", + "5.0", + "0.0", + "2025-05-29 13:08:21+00:00", + "2025-06-03 13:08:21+00:00", + "淘天", + "2585944419692538788", + "501566-187132829024652036" + ], + [ + "27", + "1871325", + "5.0", + "0.0", + "2025-05-29 13:13:12+00:00", + "2025-06-03 13:13:12+00:00", + "1688", + "2586259956829340655", + "2586259956829340655" + ], + [ + "28", + "1871321", + "5.0", + "0.0", + "2025-05-29 13:09:21+00:00", + "2025-06-03 13:09:21+00:00", + "淘天", + "2586950761285538788", + "501566-187132129024582904" + ], + [ + "29", + "1871427", + "5.0", + "0.0", + "2025-05-29 17:53:42+00:00", + "2025-06-03 17:53:42+00:00", + "1688", + "2587394317530340655", + "2587394317530340655" + ], + [ + "30", + "1871311", + "3.0", + "0.0", + "2025-05-29 15:24:37+00:00", + "2025-06-01 15:24:37+00:00", + "淘天", + "2587197865978219261", + "1748502201757" + ], + [ + "31", + "1871279", + "5.0", + "0.0", + "2025-05-29 13:22:05+00:00", + "2025-06-03 13:22:05+00:00", + "1688", + "2586172152427340655", + "2586172152427340655" + ], + [ + "32", + "1871275", + "5.0", + "0.0", + "2025-05-29 11:32:47+00:00", + "2025-06-03 11:32:47+00:00", + "淘天", + "2586173376131538788", + "501566-187127529024321722" + ], + [ + "33", + "1871488", + "4.0", + "3.0", + "2025-05-29 17:24:19+00:00", + "2025-06-02 17:24:19+00:00", + "淘天", + "2586701748701538788", + "501566-187148829024292162" + ], + [ + "34", + "1871271", + "5.0", + "0.0", + "2025-05-29 15:12:41+00:00", + "2025-06-03 15:12:41+00:00", + "淘天", + "2586574490907219261", + "1748500080517" + ], + [ + "35", + "1871264", + "5.0", + "0.0", + "2025-05-29 13:46:25+00:00", + "2025-06-03 13:46:25+00:00", + "1688", + "2587078993310340655", + "2587078993310340655" + ], + [ + "36", + "1871237", + "5.0", + "0.0", + "2025-05-29 11:39:23+00:00", + "2025-06-03 11:39:23+00:00", + "1688", + "2586290990951340655", + "2586290990951340655" + ], + [ + "37", + "1871285", + "5.0", + "0.0", + "2025-05-29 17:01:31+00:00", + "2025-06-03 17:01:31+00:00", + "1688", + "2586572256272340655", + "2586572256272340655" + ], + [ + "38", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "39", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "40", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "41", + "1871229", + "5.0", + "0.0", + "2025-05-29 11:12:41+00:00", + "2025-06-03 11:12:41+00:00", + "1688", + "2586266222731340655", + "2586266222731340655" + ], + [ + "42", + "1871224", + "5.0", + "0.0", + "2025-05-29 11:04:09+00:00", + "2025-06-03 11:04:09+00:00", + "1688", + "2586250310081340655", + "2586250310081340655" + ], + [ + "43", + "1871494", + "5.0", + "3.0", + "2025-05-29 17:55:54+00:00", + "2025-06-03 17:55:54+00:00", + "1688", + "2587438345355340655", + "2587438345355340655" + ], + [ + "44", + "1871211", + "5.0", + "0.0", + "2025-05-29 10:53:54+00:00", + "2025-06-03 10:53:54+00:00", + "1688", + "2586085464690340655", + "2586085464690340655" + ], + [ + "45", + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "46", + "1871217", + "5.0", + "0.0", + "2025-05-29 13:11:46+00:00", + "2025-06-03 13:11:46+00:00", + "淘天", + "4361308743534622839", + "1748495352189" + ], + [ + "47", + "1871423", + "5.0", + "5.0", + "2025-05-29 17:27:11+00:00", + "2025-06-03 17:27:11+00:00", + "1688", + "2587381285816340655", + "2587381285816340655" + ], + [ + "48", + "1871181", + "5.0", + "0.0", + "2025-05-29 10:30:13+00:00", + "2025-06-03 10:30:13+00:00", + "1688", + "2585723127206340655", + "2585723127206340655" + ], + [ + "49", + "1871175", + "5.0", + "0.0", + "2025-05-29 10:42:17+00:00", + "2025-06-03 10:42:17+00:00", + "淘天", + "2586047844742538788", + "501566-187117529023447247" + ] + ], + "shape": { + "columns": 8, + "rows": 118 + } + }, + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
交易ID下单发货时间维护发货时间支付时间最大发货时间交易平台交易号交易平台订单号
018715145.00.02025-05-29 17:49:40+00:002025-06-03 17:49:40+00:00淘天2586394887255538788501566-187151429026196065
118715115.03.02025-05-29 17:45:57+00:002025-06-03 17:45:57+00:00168825868665586993406552586866558699340655
218715104.05.02025-05-29 17:38:32+00:002025-06-03 17:38:32+00:00淘天2586724428509538788501566-187151029026079158
318715074.02.02025-05-29 17:31:48+00:002025-06-02 17:31:48+00:00168825863698316963406552586369831696340655
4NoneNaNNaNNaTNaTNoneNoneNone
...........................
113NoneNaNNaNNaTNaTNoneNoneNone
114NoneNaNNaNNaTNaTNoneNoneNone
115NoneNaNNaNNaTNaTNoneNoneNone
116NoneNaNNaNNaTNaTNoneNoneNone
117NoneNaNNaNNaTNaTNoneNoneNone
\n", + "

118 rows × 8 columns

\n", + "
" + ], + "text/plain": [ + " 交易ID 下单发货时间 维护发货时间 支付时间 \\\n", + "0 1871514 5.0 0.0 2025-05-29 17:49:40+00:00 \n", + "1 1871511 5.0 3.0 2025-05-29 17:45:57+00:00 \n", + "2 1871510 4.0 5.0 2025-05-29 17:38:32+00:00 \n", + "3 1871507 4.0 2.0 2025-05-29 17:31:48+00:00 \n", + "4 None NaN NaN NaT \n", + ".. ... ... ... ... \n", + "113 None NaN NaN NaT \n", + "114 None NaN NaN NaT \n", + "115 None NaN NaN NaT \n", + "116 None NaN NaN NaT \n", + "117 None NaN NaN NaT \n", + "\n", + " 最大发货时间 交易平台 交易号 \\\n", + "0 2025-06-03 17:49:40+00:00 淘天 2586394887255538788 \n", + "1 2025-06-03 17:45:57+00:00 1688 2586866558699340655 \n", + "2 2025-06-03 17:38:32+00:00 淘天 2586724428509538788 \n", + "3 2025-06-02 17:31:48+00:00 1688 2586369831696340655 \n", + "4 NaT None None \n", + ".. ... ... ... \n", + "113 NaT None None \n", + "114 NaT None None \n", + "115 NaT None None \n", + "116 NaT None None \n", + "117 NaT None None \n", + "\n", + " 交易平台订单号 \n", + "0 501566-187151429026196065 \n", + "1 2586866558699340655 \n", + "2 501566-187151029026079158 \n", + "3 2586369831696340655 \n", + "4 None \n", + ".. ... \n", + "113 None \n", + "114 None \n", + "115 None \n", + "116 None \n", + "117 None \n", + "\n", + "[118 rows x 8 columns]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fs_cols" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "fs_cols = resultdf.apply(lambda x: get_fs(x), axis=1, result_type=\"expand\")" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "fs_cols.columns = [\"交易ID\",'下单发货时间', '维护发货时间','支付时间','最大发货时间','交易平台','交易号','交易平台订单号']\n", + "resultdf = pd.concat([resultdf, fs_cols], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "跟单任务ID", + "rawType": "int64", + "type": "integer" + }, + { + "name": "采购单号", + "rawType": "int64", + "type": "integer" + }, + { + "name": "交易ID", + "rawType": "object", + "type": "string" + }, + { + "name": "下单发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "维护发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "支付时间", + "rawType": "datetime64[ns, UTC]", + "type": "unknown" + }, + { + "name": "最大发货时间", + "rawType": "datetime64[ns, UTC]", + "type": "unknown" + }, + { + "name": "交易平台", + "rawType": "object", + "type": "string" + }, + { + "name": "交易号", + "rawType": "object", + "type": "string" + }, + { + "name": "交易平台订单号", + "rawType": "object", + "type": "string" + } + ], + "ref": "cb539345-eef0-47c0-b4c1-578a3eb97ce2", + "rows": [ + [ + "0", + "359974", + "2902619", + "1871514", + "5.0", + "0.0", + "2025-05-29 17:49:40+00:00", + "2025-06-03 17:49:40+00:00", + "淘天", + "2586394887255538788", + "501566-187151429026196065" + ], + [ + "1", + "359970", + "2902615", + "1871511", + "5.0", + "3.0", + "2025-05-29 17:45:57+00:00", + "2025-06-03 17:45:57+00:00", + "1688", + "2586866558699340655", + "2586866558699340655" + ] + ], + "shape": { + "columns": 10, + "rows": 2 + } + }, + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
跟单任务ID采购单号交易ID下单发货时间维护发货时间支付时间最大发货时间交易平台交易号交易平台订单号
0359974290261918715145.00.02025-05-29 17:49:40+00:002025-06-03 17:49:40+00:00淘天2586394887255538788501566-187151429026196065
1359970290261518715115.03.02025-05-29 17:45:57+00:002025-06-03 17:45:57+00:00168825868665586993406552586866558699340655
\n", + "
" + ], + "text/plain": [ + " 跟单任务ID 采购单号 交易ID 下单发货时间 维护发货时间 支付时间 \\\n", + "0 359974 2902619 1871514 5.0 0.0 2025-05-29 17:49:40+00:00 \n", + "1 359970 2902615 1871511 5.0 3.0 2025-05-29 17:45:57+00:00 \n", + "\n", + " 最大发货时间 交易平台 交易号 \\\n", + "0 2025-06-03 17:49:40+00:00 淘天 2586394887255538788 \n", + "1 2025-06-03 17:45:57+00:00 1688 2586866558699340655 \n", + "\n", + " 交易平台订单号 \n", + "0 501566-187151429026196065 \n", + "1 2586866558699340655 " + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "resultdf[:2]" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "状态码: 201\n", + "响应内容: {'message': '录入成功'}\n" + ] + } + ], + "source": [ + "data = resultdf[:2].to_dict(orient='records')\n", + "headers = {\"Content-Type\": \"application/json; charset=utf-8\"}\n", + "url = \"http://192.168.100.44/rpaapi/followup\" \n", + "response = requests.post(url, headers=headers, data=json.dumps(data))\n", + "print(\"状态码:\", response.status_code)\n", + "print(\"响应内容:\", response.json())" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.microsoft.datawrangler.viewer.v0+json": { + "columns": [ + { + "name": "index", + "rawType": "int64", + "type": "integer" + }, + { + "name": "跟单任务ID", + "rawType": "int64", + "type": "integer" + }, + { + "name": "采购单号", + "rawType": "int64", + "type": "integer" + }, + { + "name": "交易ID", + "rawType": "object", + "type": "unknown" + }, + { + "name": "下单发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "维护发货时间", + "rawType": "float64", + "type": "float" + }, + { + "name": "支付时间", + "rawType": "object", + "type": "unknown" + }, + { + "name": "最大发货时间", + "rawType": "object", + "type": "unknown" + }, + { + "name": "交易平台", + "rawType": "object", + "type": "unknown" + }, + { + "name": "交易号", + "rawType": "object", + "type": "unknown" + }, + { + "name": "交易平台订单号", + "rawType": "object", + "type": "unknown" + }, + { + "name": "pay_date", + "rawType": "object", + "type": "unknown" + } + ], + "ref": "149160c6-811d-4ecb-b083-f13e17485053", + "rows": [ + [ + "0", + "359974", + "2902619", + "1871514", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586394887255538788", + "501566-187151429026196065", + "2025-05-29" + ], + [ + "1", + "359970", + "2902615", + "1871511", + "5.0", + "3.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586866558699340655", + "2586866558699340655", + "2025-05-29" + ], + [ + "2", + "359964", + "2902607", + "1871510", + "4.0", + "5.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586724428509538788", + "501566-187151029026079158", + "2025-05-29" + ], + [ + "3", + "359957", + "2902596", + "1871507", + "4.0", + "2.0", + "2025-05-29", + "2025-06-02", + "1688", + "2586369831696340655", + "2586369831696340655", + "2025-05-29" + ], + [ + "4", + "359952", + "2902588", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "5", + "359948", + "2902584", + "1871487", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586712116394340655", + "2586712116394340655", + "2025-05-29" + ], + [ + "6", + "359945", + "2902579", + "1871489", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586843158361340655", + "2586843158361340655", + "2025-05-29" + ], + [ + "7", + "359942", + "2902574", + "1871504", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586391611043219261", + "1748511690120", + "2025-05-29" + ], + [ + "8", + "359939", + "2902570", + "1871464", + "4.0", + "0.0", + "2025-05-29", + "2025-06-02", + "淘天", + "2586603684278538788", + "501566-187146429025706383", + "2025-05-29" + ], + [ + "9", + "359935", + "2902565", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "10", + "359932", + "2902561", + "1871446", + "4.0", + "0.0", + "2025-05-29", + "2025-06-02", + "1688", + "2586713774989340655", + "2586713774989340655", + "2025-05-29" + ], + [ + "11", + "359926", + "2902553", + "1871492", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2587422217794219261", + "1748511214446", + "2025-05-29" + ], + [ + "12", + "359923", + "2902550", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "13", + "359920", + "2902547", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "14", + "359916", + "2902543", + "1871438", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586693324476219261", + "1748510063327", + "2025-05-29" + ], + [ + "15", + "359906", + "2902531", + "1871398", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2587229653074538788", + "501566-187139829025312437", + "2025-05-29" + ], + [ + "16", + "359902", + "2902527", + "1871388", + "4.0", + "0.0", + "2025-05-29", + "2025-06-02", + "1688", + "2586139179096340655", + "2586139179096340655", + "2025-05-29" + ], + [ + "17", + "359899", + "2902524", + "1871418", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2587321165625219261", + "1748507467551", + "2025-05-29" + ], + [ + "18", + "359893", + "2902517", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "19", + "359885", + "2902504", + "1871417", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586615528437219261", + "1748507336231", + "2025-05-29" + ], + [ + "20", + "359879", + "2902496", + "1871353", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2587088497261538788", + "501566-187135329024968677", + "2025-05-29" + ], + [ + "21", + "359876", + "2902491", + "1871348", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2587071793982538788", + "501566-187134829024913484", + "2025-05-29" + ], + [ + "22", + "359871", + "2902484", + "1871345", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586508466020340655", + "2586508466020340655", + "2025-05-29" + ], + [ + "23", + "359865", + "2902476", + "1871336", + "4.0", + "0.0", + "2025-05-29", + "2025-06-02", + "淘天", + "2586347292443538788", + "501566-187133629024764267", + "2025-05-29" + ], + [ + "24", + "359862", + "2902473", + "1871333", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586340380550340655", + "2586340380550340655", + "2025-05-29" + ], + [ + "25", + "359858", + "2902469", + "1871376", + "4.0", + "2.0", + "2025-05-29", + "2025-06-02", + "1688", + "2586448056601340655", + "2586448056601340655", + "2025-05-29" + ], + [ + "26", + "359854", + "2902465", + "1871328", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2585944419692538788", + "501566-187132829024652036", + "2025-05-29" + ], + [ + "27", + "359851", + "2902462", + "1871325", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586259956829340655", + "2586259956829340655", + "2025-05-29" + ], + [ + "28", + "359847", + "2902458", + "1871321", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586950761285538788", + "501566-187132129024582904", + "2025-05-29" + ], + [ + "29", + "359841", + "2902452", + "1871427", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2587394317530340655", + "2587394317530340655", + "2025-05-29" + ], + [ + "30", + "359838", + "2902449", + "1871311", + "3.0", + "0.0", + "2025-05-29", + "2025-06-01", + "淘天", + "2587197865978219261", + "1748502201757", + "2025-05-29" + ], + [ + "31", + "359829", + "2902438", + "1871279", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586172152427340655", + "2586172152427340655", + "2025-05-29" + ], + [ + "32", + "359825", + "2902432", + "1871275", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586173376131538788", + "501566-187127529024321722", + "2025-05-29" + ], + [ + "33", + "359822", + "2902429", + "1871488", + "4.0", + "3.0", + "2025-05-29", + "2025-06-02", + "淘天", + "2586701748701538788", + "501566-187148829024292162", + "2025-05-29" + ], + [ + "34", + "359818", + "2902424", + "1871271", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586574490907219261", + "1748500080517", + "2025-05-29" + ], + [ + "35", + "359814", + "2902420", + "1871264", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2587078993310340655", + "2587078993310340655", + "2025-05-29" + ], + [ + "36", + "359810", + "2902416", + "1871237", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586290990951340655", + "2586290990951340655", + "2025-05-29" + ], + [ + "37", + "359807", + "2902413", + "1871285", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586572256272340655", + "2586572256272340655", + "2025-05-29" + ], + [ + "38", + "359804", + "2902410", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "39", + "359801", + "2902407", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "40", + "359797", + "2902401", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "41", + "359793", + "2902396", + "1871229", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586266222731340655", + "2586266222731340655", + "2025-05-29" + ], + [ + "42", + "359788", + "2902390", + "1871224", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586250310081340655", + "2586250310081340655", + "2025-05-29" + ], + [ + "43", + "359784", + "2902386", + "1871494", + "5.0", + "3.0", + "2025-05-29", + "2025-06-03", + "1688", + "2587438345355340655", + "2587438345355340655", + "2025-05-29" + ], + [ + "44", + "359781", + "2902382", + "1871211", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2586085464690340655", + "2586085464690340655", + "2025-05-29" + ], + [ + "45", + "359767", + "2902368", + null, + null, + null, + null, + null, + null, + null, + null, + null + ], + [ + "46", + "359763", + "2902364", + "1871217", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "4361308743534622839", + "1748495352189", + "2025-05-29" + ], + [ + "47", + "359758", + "2902357", + "1871423", + "5.0", + "5.0", + "2025-05-29", + "2025-06-03", + "1688", + "2587381285816340655", + "2587381285816340655", + "2025-05-29" + ], + [ + "48", + "359752", + "2902351", + "1871181", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "1688", + "2585723127206340655", + "2585723127206340655", + "2025-05-29" + ], + [ + "49", + "359748", + "2902344", + "1871175", + "5.0", + "0.0", + "2025-05-29", + "2025-06-03", + "淘天", + "2586047844742538788", + "501566-187117529023447247", + "2025-05-29" + ] + ], + "shape": { + "columns": 11, + "rows": 98 + } + }, + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
跟单任务ID采购单号交易ID下单发货时间维护发货时间支付时间最大发货时间交易平台交易号交易平台订单号pay_date
0359974290261918715145.00.02025-05-292025-06-03淘天2586394887255538788501566-1871514290261960652025-05-29
1359970290261518715115.03.02025-05-292025-06-031688258686655869934065525868665586993406552025-05-29
2359964290260718715104.05.02025-05-292025-06-03淘天2586724428509538788501566-1871510290260791582025-05-29
3359957290259618715074.02.02025-05-292025-06-021688258636983169634065525863698316963406552025-05-29
43599522902588NoneNaNNaNNaNNaNNoneNoneNoneNaN
....................................
93359509290209518710805.00.02025-05-292025-06-03淘天436100835946462283917484855885962025-05-29
94359506290209218708744.00.02025-05-292025-06-02淘天2585831448930538788501566-1870874290209243402025-05-29
95359501290208718714294.05.02025-05-292025-06-03淘天2586690554346538788501566-1871429290208715762025-05-29
96359488290199918714195.05.02025-05-292025-06-031688258737541737934065525873754173793406552025-05-29
97359486290199718714195.05.02025-05-292025-06-031688258737541737934065525873754173793406552025-05-29
\n", + "

98 rows × 11 columns

\n", + "
" + ], + "text/plain": [ + " 跟单任务ID 采购单号 交易ID 下单发货时间 维护发货时间 支付时间 最大发货时间 交易平台 \\\n", + "0 359974 2902619 1871514 5.0 0.0 2025-05-29 2025-06-03 淘天 \n", + "1 359970 2902615 1871511 5.0 3.0 2025-05-29 2025-06-03 1688 \n", + "2 359964 2902607 1871510 4.0 5.0 2025-05-29 2025-06-03 淘天 \n", + "3 359957 2902596 1871507 4.0 2.0 2025-05-29 2025-06-02 1688 \n", + "4 359952 2902588 None NaN NaN NaN NaN None \n", + ".. ... ... ... ... ... ... ... ... \n", + "93 359509 2902095 1871080 5.0 0.0 2025-05-29 2025-06-03 淘天 \n", + "94 359506 2902092 1870874 4.0 0.0 2025-05-29 2025-06-02 淘天 \n", + "95 359501 2902087 1871429 4.0 5.0 2025-05-29 2025-06-03 淘天 \n", + "96 359488 2901999 1871419 5.0 5.0 2025-05-29 2025-06-03 1688 \n", + "97 359486 2901997 1871419 5.0 5.0 2025-05-29 2025-06-03 1688 \n", + "\n", + " 交易号 交易平台订单号 pay_date \n", + "0 2586394887255538788 501566-187151429026196065 2025-05-29 \n", + "1 2586866558699340655 2586866558699340655 2025-05-29 \n", + "2 2586724428509538788 501566-187151029026079158 2025-05-29 \n", + "3 2586369831696340655 2586369831696340655 2025-05-29 \n", + "4 None None NaN \n", + ".. ... ... ... \n", + "93 4361008359464622839 1748485588596 2025-05-29 \n", + "94 2585831448930538788 501566-187087429020924340 2025-05-29 \n", + "95 2586690554346538788 501566-187142929020871576 2025-05-29 \n", + "96 2587375417379340655 2587375417379340655 2025-05-29 \n", + "97 2587375417379340655 2587375417379340655 2025-05-29 \n", + "\n", + "[98 rows x 11 columns]" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "resultdf" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'跟单任务ID': 359974,\n", + " '采购单号': 2902619,\n", + " '交易ID': '1871514',\n", + " '下单发货时间': 5.0,\n", + " '维护发货时间': 0.0,\n", + " '支付时间': '2025-05-29',\n", + " '最大发货时间': '2025-06-03',\n", + " '交易平台': '淘天',\n", + " '交易号': '2586394887255538788',\n", + " '交易平台订单号': '501566-187151429026196065',\n", + " 'pay_date': '2025-05-29'},\n", + " {'跟单任务ID': 359970,\n", + " '采购单号': 2902615,\n", + " '交易ID': '1871511',\n", + " '下单发货时间': 5.0,\n", + " '维护发货时间': 3.0,\n", + " '支付时间': '2025-05-29',\n", + " '最大发货时间': '2025-06-03',\n", + " '交易平台': '1688',\n", + " '交易号': '2586866558699340655',\n", + " '交易平台订单号': '2586866558699340655',\n", + " 'pay_date': '2025-05-29'}]" + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "resultdf = pd.concat([resultdf, fs_cols], axis=1)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "for col in ['支付时间', '最大发货时间']:\n", + " resultdf[col] = pd.to_datetime(resultdf[col], errors='coerce')\n", + " resultdf[col] = resultdf[col].dt.strftime('%Y-%m-%d')\n", + "resultdf['pay_date'] = resultdf['支付时间']" ] }, { @@ -319,6 +4405,36 @@ "rows_as_dict_list" ] }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "url = \"http://192.168.100.44/rpaapi/followup\" \n", + "response = requests.get(url).json()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'key': None, 'task_id': None}" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "response" + ] + }, { "cell_type": "code", "execution_count": null, @@ -375,7 +4491,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T15:38:46.563968Z", @@ -398,7 +4514,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -412,7 +4528,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -431,7 +4547,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T15:38:58.960899Z", @@ -446,7 +4562,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T15:39:01.808655Z", @@ -454,772 +4570,7 @@ }, "collapsed": false }, - "outputs": [ - { - "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
cpmaso_task_idbuy_idtrade_idtrade_platform_order_numpay_datemaintain_datelast_task_idfollow_typemax_logis_dateagreed_delivery_timetrans_idpayment_datetimeplatformtask_statusneed_refundhas_imageclearly_specify_the_delivery_timeone_more_timecreate_dateupload_cpmaso
03436362896029289602928960292025-05-200012025-05-21None18636241淘天000002025-05-210
13436502896044289604428960442025-05-200012025-05-27None18636457淘天000002025-05-210
23454412896633289663328966332025-05-210012025-05-22None18643491淘天000002025-05-220
334546028966538966538966532025-05-210012025-05-22None18643731淘天000002025-05-220
43455102896706289670628967062025-05-210012025-05-23None18644402淘天000002025-05-220
53473352897332289733228973322025-05-220012025-05-25None18652973淘天000002025-05-230
63473392897336289733628973362025-05-220012025-05-27None18653015淘天000002025-05-230
73473452897342289734228973422025-05-220012025-05-25None18653073淘天000002025-05-230
83473482897345289734528973452025-05-220012025-05-24None18653082淘天000002025-05-230
93474152897416289741628974162025-05-220012025-05-27None18654065淘天000002025-05-230
103491552898014257849936530153878817479912802362025-05-23753212025-05-30None18665187淘天000002025-05-240
1134919128980602577712694448538788501566-1866395289806034642025-05-23353312025-05-28None18663955淘天000002025-05-240
123492192898090289809028980902025-05-230012025-05-30None18662727淘天000002025-05-240
133493502898239289823928982392025-05-230012025-05-28None18665005淘天000002025-05-240
1435234028991782579933964195538788501566-1867502289917834252025-05-25053712025-05-30None18675025淘天000002025-05-260
153523632899201435471858054768814817481398278232025-05-25554012025-05-30None18677733淘天000002025-05-260
1635239228992312580629125407538788501566-1867547289923149102025-05-25054212025-05-30None18675475淘天000002025-05-260
1735249428993342579651619722538788501566-1867697289933410372025-05-25055312025-05-30None18676975淘天000002025-05-260
1835250428993452580008664490538788501566-1867714289934597182025-05-25055512025-05-30None18677145淘天000002025-05-260
1935252628993682579710119285538788501566-1867753289936893312025-05-25055812025-05-30None18677535淘天000002025-05-260
2035263128994812579924751782538788501566-1867892289948174322025-05-25058012025-05-30None18678925淘天000002025-05-260
213526492899501289950128995012025-05-250012025-05-28None18679133淘天000002025-05-260
223526982899552435508977914746394817481524774972025-05-25559412025-05-30None18679835淘天000002025-05-260
2335273528995902580755954053538788501566-1868040289959000682025-05-25060112025-05-30None18680405淘天000002025-05-260
2435274128995962580765530729538788501566-1868048289959682412025-05-25560312025-05-30None18680485淘天000002025-05-260
\n", - "
" - ], - "text/plain": [ - " cpmaso_task_id buy_id trade_id trade_platform_order_num \\\n", - "0 343636 2896029 2896029 2896029 \n", - "1 343650 2896044 2896044 2896044 \n", - "2 345441 2896633 2896633 2896633 \n", - "3 345460 2896653 896653 896653 \n", - "4 345510 2896706 2896706 2896706 \n", - "5 347335 2897332 2897332 2897332 \n", - "6 347339 2897336 2897336 2897336 \n", - "7 347345 2897342 2897342 2897342 \n", - "8 347348 2897345 2897345 2897345 \n", - "9 347415 2897416 2897416 2897416 \n", - "10 349155 2898014 2578499365301538788 1747991280236 \n", - "11 349191 2898060 2577712694448538788 501566-186639528980603464 \n", - "12 349219 2898090 2898090 2898090 \n", - "13 349350 2898239 2898239 2898239 \n", - "14 352340 2899178 2579933964195538788 501566-186750228991783425 \n", - "15 352363 2899201 4354718580547688148 1748139827823 \n", - "16 352392 2899231 2580629125407538788 501566-186754728992314910 \n", - "17 352494 2899334 2579651619722538788 501566-186769728993341037 \n", - "18 352504 2899345 2580008664490538788 501566-186771428993459718 \n", - "19 352526 2899368 2579710119285538788 501566-186775328993689331 \n", - "20 352631 2899481 2579924751782538788 501566-186789228994817432 \n", - "21 352649 2899501 2899501 2899501 \n", - "22 352698 2899552 4355089779147463948 1748152477497 \n", - "23 352735 2899590 2580755954053538788 501566-186804028995900068 \n", - "24 352741 2899596 2580765530729538788 501566-186804828995968241 \n", - "\n", - " pay_date maintain_date last_task_id follow_type max_logis_date \\\n", - "0 2025-05-20 0 0 1 2025-05-21 \n", - "1 2025-05-20 0 0 1 2025-05-27 \n", - "2 2025-05-21 0 0 1 2025-05-22 \n", - "3 2025-05-21 0 0 1 2025-05-22 \n", - "4 2025-05-21 0 0 1 2025-05-23 \n", - "5 2025-05-22 0 0 1 2025-05-25 \n", - "6 2025-05-22 0 0 1 2025-05-27 \n", - "7 2025-05-22 0 0 1 2025-05-25 \n", - "8 2025-05-22 0 0 1 2025-05-24 \n", - "9 2025-05-22 0 0 1 2025-05-27 \n", - "10 2025-05-23 7 532 1 2025-05-30 \n", - "11 2025-05-23 3 533 1 2025-05-28 \n", - "12 2025-05-23 0 0 1 2025-05-30 \n", - "13 2025-05-23 0 0 1 2025-05-28 \n", - "14 2025-05-25 0 537 1 2025-05-30 \n", - "15 2025-05-25 5 540 1 2025-05-30 \n", - "16 2025-05-25 0 542 1 2025-05-30 \n", - "17 2025-05-25 0 553 1 2025-05-30 \n", - "18 2025-05-25 0 555 1 2025-05-30 \n", - "19 2025-05-25 0 558 1 2025-05-30 \n", - "20 2025-05-25 0 580 1 2025-05-30 \n", - "21 2025-05-25 0 0 1 2025-05-28 \n", - "22 2025-05-25 5 594 1 2025-05-30 \n", - "23 2025-05-25 0 601 1 2025-05-30 \n", - "24 2025-05-25 5 603 1 2025-05-30 \n", - "\n", - " agreed_delivery_time trans_id payment_datetime platform task_status \\\n", - "0 None 1863624 1 淘天 0 \n", - "1 None 1863645 7 淘天 0 \n", - "2 None 1864349 1 淘天 0 \n", - "3 None 1864373 1 淘天 0 \n", - "4 None 1864440 2 淘天 0 \n", - "5 None 1865297 3 淘天 0 \n", - "6 None 1865301 5 淘天 0 \n", - "7 None 1865307 3 淘天 0 \n", - "8 None 1865308 2 淘天 0 \n", - "9 None 1865406 5 淘天 0 \n", - "10 None 1866518 7 淘天 0 \n", - "11 None 1866395 5 淘天 0 \n", - "12 None 1866272 7 淘天 0 \n", - "13 None 1866500 5 淘天 0 \n", - "14 None 1867502 5 淘天 0 \n", - "15 None 1867773 3 淘天 0 \n", - "16 None 1867547 5 淘天 0 \n", - "17 None 1867697 5 淘天 0 \n", - "18 None 1867714 5 淘天 0 \n", - "19 None 1867753 5 淘天 0 \n", - "20 None 1867892 5 淘天 0 \n", - "21 None 1867913 3 淘天 0 \n", - "22 None 1867983 5 淘天 0 \n", - "23 None 1868040 5 淘天 0 \n", - "24 None 1868048 5 淘天 0 \n", - "\n", - " need_refund has_image clearly_specify_the_delivery_time one_more_time \\\n", - "0 0 0 0 0 \n", - "1 0 0 0 0 \n", - "2 0 0 0 0 \n", - "3 0 0 0 0 \n", - "4 0 0 0 0 \n", - "5 0 0 0 0 \n", - "6 0 0 0 0 \n", - "7 0 0 0 0 \n", - "8 0 0 0 0 \n", - "9 0 0 0 0 \n", - "10 0 0 0 0 \n", - "11 0 0 0 0 \n", - "12 0 0 0 0 \n", - "13 0 0 0 0 \n", - "14 0 0 0 0 \n", - "15 0 0 0 0 \n", - "16 0 0 0 0 \n", - "17 0 0 0 0 \n", - "18 0 0 0 0 \n", - "19 0 0 0 0 \n", - "20 0 0 0 0 \n", - "21 0 0 0 0 \n", - "22 0 0 0 0 \n", - "23 0 0 0 0 \n", - "24 0 0 0 0 \n", - "\n", - " create_date upload_cpmaso \n", - "0 2025-05-21 0 \n", - "1 2025-05-21 0 \n", - "2 2025-05-22 0 \n", - "3 2025-05-22 0 \n", - "4 2025-05-22 0 \n", - "5 2025-05-23 0 \n", - "6 2025-05-23 0 \n", - "7 2025-05-23 0 \n", - "8 2025-05-23 0 \n", - "9 2025-05-23 0 \n", - "10 2025-05-24 0 \n", - "11 2025-05-24 0 \n", - "12 2025-05-24 0 \n", - "13 2025-05-24 0 \n", - "14 2025-05-26 0 \n", - "15 2025-05-26 0 \n", - "16 2025-05-26 0 \n", - "17 2025-05-26 0 \n", - "18 2025-05-26 0 \n", - "19 2025-05-26 0 \n", - "20 2025-05-26 0 \n", - "21 2025-05-26 0 \n", - "22 2025-05-26 0 \n", - "23 2025-05-26 0 \n", - "24 2025-05-26 0 " - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "df = pd.read_sql(sql,mdm.engine())\n", "df" @@ -1227,7 +4578,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2025-05-15T15:26:13.035452Z", @@ -1251,7 +4602,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": { "ExecuteTime": { "end_time": "2025-05-16T15:45:35.889562Z", @@ -1501,17 +4852,750 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 60, "metadata": { "collapsed": false }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'success': True,\n", + " 'msg': '成功获取会话任务详情',\n", + " 'url': 'https://distributor.taobao.global/apps/open/imchat?loginToken=7OXaq3%2B20t8Fslz9ewVQmJvp%2F6nWulgUe1UVHUURSfP5dyPsFgpb%2Babr2%2BnnUUN9RmP0iZ9aq6fVttswuHtXvJxK%2FCP8OpkHIR%2BytvG9q%2F0%3D&sellerId=NTg3OTUxMDY5',\n", + " 'text': '平台交易号:3275492124464538788,您好，之前联系过您多次，仍未收到回复。03月12日前可以发货吗？如果近期无法发货，我们只能申请退款处理。',\n", + " 'shopname': '首选家具专盈店'}" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + " \n", + "def get_session_task_detail(task_id):\n", + " \"\"\"获取会话任务详情\"\"\"\n", + " url = f\"http://192.168.100.44/rpaapi/get_session_task_detail/{task_id}\"\n", + " try:\n", + " response = requests.get(url, timeout=10)\n", + " res = response.json()\n", + " if res.get('message') == \"success\":\n", + " return {\n", + " \"success\": True,\n", + " \"msg\": \"成功获取会话任务详情\",\n", + " \"url\": res['url'],\n", + " \"text\": res['text'],\n", + " \"shopname\": res['shopname']\n", + " }\n", + " else:\n", + " return {\n", + " \"success\": False,\n", + " \"msg\": f\"获取会话任务详情失败: {res['message']}\",\n", + " \"url\": None,\n", + " \"text\": None,\n", + " \"shopname\": None\n", + " }\n", + " except Exception as e:\n", + " print(e)\n", + " return {\n", + " \"success\": False,\n", + " \"msg\": f\"获取会话任务详情失败: {e}\",\n", + " \"url\": None,\n", + " \"text\": None,\n", + " \"shopname\": None\n", + " }\n", + "\n", + "get_session_task_detail(43439)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:23: SyntaxWarning: invalid escape sequence '\\/'\n", + "<>:23: SyntaxWarning: invalid escape sequence '\\/'\n", + "C:\\Users\\joker\\AppData\\Local\\Temp\\ipykernel_96992\\365462581.py:23: SyntaxWarning: invalid escape sequence '\\/'\n", + " !function(t){function e(a){if(n[a])return n[a].exports;var o=n[a]={exports:{},id:a,loaded:!1};return t[a].call(o.exports,o,o.exports,e),o.loaded=!0,o.exports}var n={};return e.m=t,e.c=n,e.p=\"\",e(0)}([function(t,e,n){t.exports=n(1)},function(t,e,n){\"use strict\";n(2).initGlobal(window),function(){var t=n(4);n(156)(t)}()},function(t,e,n){\"use strict\";var a,o=n(3),r=o.APLUS,i=o.APLUS_QUEUE,s=o.GOLDLOG,u=o.GOLDLOG_QUEUE,c=!1;try{\"undefined\"!=typeof window&&(a=window,c=!0)}catch(t){a={},c=!1}e.getContext=function(){return a},e.isWeb=function(){return\"undefined\"!=typeof window&&window},e.initGlobal=function(t){a=t?t:{v:1,aplus:{},aplus_queue:[]};var e,n;if(c)try{e=a.aplus||a.goldlog||(a.aplus={});var o=a.goldlog_queue||(a.goldlog_queue=[]);n=a.aplus_queue||(a.aplus_queue=[]),n=o.concat(n)}catch(t){}else e=a.aplus,n=a.aplus_queue;return a.aplus=a.goldlog=e,a.aplus_queue=a.goldlog_queue=n,a};var l=function(t){if(t===r||t===s){var e=a[r]||a[s];return e||(e=a[r]=a[s]={}),e}var n=u,o=i;if(t===o||t===n){var c=a[o]||a[n];return c||(c=a[o]=a[n]=[]),c}};e.getGlobalValue=l,e.setGlobalValue=function(t,e){a[t]=e};var p=function(t){var e;try{var n=l(r);e=n[t]}catch(t){e=\"\"}finally{return e}};e.getGoldlogVal=p;var f=function(t,e){var n=!1;try{var a=l(r);t&&(a[t]=e,n=!0)}catch(t){n=!1}finally{return n}};e.setGoldlogVal=f,e.getClientInfo=function(){return p(\"_aplus_client\")||{}}},function(t,e){var n=\"aplus\",a=\"goldlog\",o=n+\"_queue\",r=a+\"_queue\",i=\"mw_change\",s=\"MetaInfo\",u=\"append\"+s,c=\"set\"+s,l=\"http\",p=\"_pubsub\",f=\"other\",g=\"2101\",d=\"2201\",m=\"2202\",_=\"19999\",h=\"1023\",v=\"1010\",b=3e4,y=18e5,S=\"ekvs\",A=1e4,E=1,T=1,I=3e3,P=\"$$_page_start\",w=\"$$_page_end\",C=\"$$_app_start\",M=\"$$_app_end\",x=\"aplus_user_profile\",O=\"imprint\",L=n+\"-idtype\",U=n+\"-jsbridge-only\",k=n+\"-page-config\",R=n+\"-skip-apv-rules\",N=n+\"-rhost-v\",G=n+\"-rhost-g\",D=n+\"-forward-domain\",V=n+\"-forward-event-filter\",j=\"autoGetOpenid\",F=n+\"-forward-appkey\";t.exports={PAGE_ENTER:\"PAGE_ENTER\",ETAG_EVENT_NAME:\"etag\",CURRENT_PAGE_CONFIG:\"CURRENT_PAGE_CONFIG\",_ANONY_ID:\"_anony_id\",_DEV_ID:\"_dev_id\",_USER_ID:\"_user_id\",_CNA:\"cna\",DEFAULT_CODE:f,OTHER:_,EVENT_MAP:{2101:\"click\",2201:\"exposure\",2202:\"exposure\",19999:f,1023:\"app_show\",1010:\"app_hide_or_unload\"},EVENT_ID_MAP:{EXP:d,IMPEXP:m,CLK:g,OTHER:_,SHOW:h,H_OR_U:v},APLUS:n,APLUS_CONFIG:\"APLUS_CONFIG\",GOLDLOG:a,UNSUBSCRIBE:n+\".\"+n+p+\".unsubscribe\",SUBSCRIBE:n+\".\"+n+p+\".subscribe\",PUBLISH:n+\".\"+n+p+\".publish\",CACHE_PUBS:n+\".\"+n+p+\".cachePubs\",APLUS_UNIVERSAL:n+\"_universal\",APLUS_QUEUE:o,GOLDLOG_QUEUE:r,COMPLETE:\"complete\",PV_CODE:\"2001\",EXP_CODE:d,CLK_CODE:g,OTHER_CODE:_,CLK:\"CLK\",EXP:\"EXP\",SPM_CNT:\"spm-cnt\",SPM_URL:\"spm-url\",SPM_PRE:\"spm-pre\",MW_CHANGE_PV:i+\"_pv\",MW_CHANGE_HJLJ:i+\"_hjlj\",HTTP:l+\":\",HTTPS:\"https:\",APPEND_META_INFO:u,SET_META_INFO:c,APLUS_APPEND_META_INFO:n+\".\"+u,APLUS_SET_META_INFO:n+\".\"+c,PVID:\"pvid\",openAPIs:[\"send\",\"enter\",\"sendPV\",\"record\",\"combineRecord\",\"recordUdata\",\"requestVTConfig\",\"requestRemoteConfig\",\"setPageSPM\",\"setMetaInfo\",\"appendMetaInfo\",\"updatePageProperties\",\"updateNextPageProperties\",\"updatePageUtparam\",\"updateNextPageUtparam\",\"pageAppear\",\"pageDisappear\",\"pageDisAppear\",\"skipPage\",\"updatePageName\",\"updatePageUrl\",\"requestPageAllProperties\",\"updateSessionProperties\",\"getPageSpmUrl\",\"getPageSpmPre\",\"updateNextPageUtparamCnt\",\"setPageName\",\"getElementSPM\",\"getAutoElementSPM\",\"setUserProfile\",\"getUserProfile\",\"getCna\"],SESSION_INTERVAL:b,SESSION_PAUSE_TIME:\"session_pause_time\",IMPRINT:\"imprint\",CURRENT_SESSION:\"current_session\",MAX_EVENTID_LENGTH:128,MAX_PROPERTY_KEY_LENGTH:256,MAX_PROPERTY_KEYS_COUNT:100,FAILED_REQUESTS:\"failed_requests\",REQUESTS:\"requests\",SHARES:\"shares\",APLUS_SSRC:\"_aplus_ssrc\",ARMS_TRACE:\"_arms_trace\",EKVS:S,EVENT_MAX_COUNT:A,MEMORY_MAX_COUNT:E,MAX_QUEUE_COUNT:T,EVENT_SEND_DEFAULT_INTERVAL:I,PAGE_START:P,PAGE_END:w,APP_START:C,APP_END:M,USER_PROFILE_KEY:x,SHARE_CACHE_INTERVAL:y,IMPRINT:O,ID_TYPE:L,GLOBAL_PROPERTY:\"globalproperty\",JSBRIDGE_ONLY:U,PAGE_CONFIG:k,APLUS_SKIP_APV_RULES:R,APLUS_PV_DOMAIN:N,APLUS_EKV_DOMAIN:G,APLUS_FORWARD_DOMAIN:D,APLUS_IMPRINT_VERSION:\"APLUS_IMPRINT_VERSION\",APLUS_REMOTE_CONFIG:\"APLUS_REMOTE_CONFIG\",RANK:\"ekv_rank\",WEB_EVENT_SUFFIX:\"/web_logs\",WEB_PC_PV_SUFFIX:\"v.gif\",WEB_WAP_PV_SUFFIX:\"m.gif\",PAGE_LEAVE:\"$$_page_leave\",APLUS_DOM_CHANGE:\"APLUS_DOM_CHANGE\",APLUS_PAGE_CHANGE:\"APLUS_PAGE_CHANGE\",PERFORMANCE_WARING:\"$$_perf_warning\",START_ID:\"START_ID\",AUTO_GET_OPENID:j,APLUS_LATEAST_UTM:\"APLUS_LATEAST_UTM\",APLUS_FORWARD_EVENT_FILTER:V,APLUS_FORWARD_APPKEY:F,APLUS_RHOST_V:n+\"-rhost-v\",APLUS_CPVDATA:n+\"-cpvdata\",APLUS_EXDATA:n+\"-exdata\",APLUS_EXINFO:n+\"-exinfo\",APLUS_LOG_PIPE:n+\"-log-pipe\",APLUS_TRACK_COMBINE:n+\"-track-combine\",APLUS_COOKIES:n+\"-cookies\",APLUS_CODELESS_TRACK_CONFIG:\"_\"+n+\"_codeless_track_config\",APLUS_AUTO_CLK:n+\"-auto-clk\",APLUS_AUTO_EXP:n+\"-auto-exp\",APLUS_AUTO_PV:n+\"-auto-pv\",APLUS_BRIDGE_NAME:n+\"-bridge-name\",APLUS_MINI_REQUEST_TIMEOUT:n+\"-request-timeout\",APLUS_VT_CONFIG_URL:n+\"-vt-cfg-url\",APLUS_EXPOSURE_EVENT_CAN_REPEAT:n+\"-exposure-event-can-repeat\",APLUS_IGNORE_LIFECYCLES:n+\"-ignore-lifecycles\",APLUS_TRACK_DEBUG_ID:n+\"-track-debug-id\",APLUS_SINGLE_RECORD_LOGKEYS:n+\"-single-record-logkeys\",APLUS_GOKEY_ISOLATE:n+\"-gokey-isolate\",APLUS_AUTOTRACK_ENABLED:n+\"-autotrack-enabled\",APLUS_AUTOTRACK_ENABLED_REMOTE:n+\"-autotrack-enabled-remote\",APLUS_AUTOTRACK_CONFIG:n+\"-autotrack-config\",APLUS_AUTO_TRACK_CONFIG_IMPORT:n+\"-auto-track-config-import\",APLUS_AUTOTRACK_CONFIG_REMOTE:n+\"-autotrack-config-remote\",APLUS_EVENT_LIMITRATES:n+\"-event-limitrates\",APLUS_DISABLE_AUTOEVENT:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOEVENT_REMOTE:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOPV:n+\"-disable-apv\",APLUS_DISABLE_AUTOPV_REMOTE:n+\"-disable-apv-remote\",APLUS_DEVICE_ENABLE:n+\"-device-enable\",APLUS_USER_PROFILE:n+\"-user-profile\",APLUS_CNA_ENABLE:n+\"-cna-enable\",APLUS_CNA_MODE:n+\"-cna-mode\",APLUS_ETAG_TIMEOUT:n+\"-etag-timeout\",APLUS_SPA_TYPE:n+\"-spa-type\",APLUS_MONITOR_ENABLE:n+\"-monitor-enable\",APLUS_OBSERVATIONS:\"_\"+n+\"_observations\",APLUS_REPORT_RATE:n+\"-report-rate\",APLUS_CNA_MONITOR:n+\"-cna-monitor\",APLUS_MMSTAT_TIMEOUT:n+\"-mmstat-timeout\",APLUS_REMOTE_CONTROL:n+\"-remote-control\",APLUS_CNA_STABILITY:n+\"-cna-stability\",APLUS_AUTO_PID:n+\"-auto-pid\"}},function(t,e,n){t.exports={metaInfo:{\"aplus-ifr-pv\":\"0\",\"aplus-rhost-v\":\"log.mmstat.com\",\"aplus-rhost-g\":\"gm.mmstat.com\",\"aplus-channel\":\"WS\",appId:\"60506758\",sdkId:\"customSdkId\",\"aplus-cpvdata\":{},\"aplus-exdata\":{},\"aplus-globaldata\":{},\"aplus-mmstat-timeout\":\"10000\",\"aplus-toUT\":\"auto\",\"aplus-track-combine\":\"on\",\"aplus-vt-auto-userfn-enable\":\"on\",\"aplus-cna-enable\":\"on\",\"aplus-cna-mode\":\"CK\",\"aplus-auto-track-config-import\":\"off\",\"aplus-form-track\":\"off\",\"aplus-gokey-isolate\":\"on\",\"aplus-only-update-page-properties\":\"off\",\"aplus-spm-from-url\":\"on\",\"aplus-user-profile\":{},\"aplus-report-rate\":{},\"aplus-single-record-logkeys\":[],\"aplus-cross-day-auto-pv\":\"off\",\"aplus-cna-monitor\":\"off\",\"aplus-cna-stability\":\"off\",\"aplus-auto-pid\":\"on\",\"aplus-monitor-enable\":\"off\",\"aplus-remote-control\":\"on\"},globalConfig:{isAli:!0,APLUS_QUEUE:\"aplus_queue\",ETAG_STORAGE_KEY:\"__ETAG__CNA__ID__\",script_name:\"aplus.js\",NAME_STORAGE_KEYS:{REFERRER:\"wm_referrer\",REFERRER_PV_ID:\"refer_pv_id\",LOST_PV_PAGE_DURATION:\"lost_pv_page_duration\",LOST_PV_PAGE_SPMAB:\"lost_pv_page_spmab\",LOST_PV_PAGE:\"lost_pv_page\",LOST_PV_PAGE_MSG:\"lost_pv_page_msg\"},lver:\"1.13.27\"},plugins:[{name:\"aplus_body_ready\",path:n(5)},{name:\"pubsub\",path:n(6)},{name:\"aplus_client\",path:n(11)},{name:\"aplus_meta_inject\",path:n(15)},{name:\"aplus_remote_control\",path:n(49)},{name:\"aplus_observer\",path:n(51)},{name:\"aplus_ac\",path:n(53)},{name:\"aplus_ae\",path:n(72)},{name:\"name_storage\",path:n(80)},{name:\"record_lost_pv\",path:n(83),config:{lostPvRecordRatio:.01}},{name:\"aplus_monitor\",path:n(85),config:{obsoleteInterRecordRatio:\"0.01\",jsErrorRecordRatio:\"0.01\",browserSupportRatio:\"0.01\"}},{name:\"aplus_web_http_ali\",path:n(92)},{name:\"aplus_log_inject\",path:n(95),deps:[\"aplus_meta_inject\"],config:{plugins:{pv:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"when_to_sendpv\",path:n(101),config:{aplusWaiting:\"\"}},{name:\"where_to_send\",path:n(102),config:{method:\"GET\",url:\"//log.mmstat.com/v.gif\"}},{name:\"what_to_send\",path:n(103),config:{pvdataToUt:{}}},{name:\"cookie_data\",path:n(104)},{name:\"what_to_sendpv_userdata\",path:n(105),deps:[\"what_to_send\"]},{name:\"what_to_sendpv_userdata_web\",path:n(106),deps:[\"what_to_send\",\"what_to_sendpv_userdata\"]},{name:\"what_to_sendpv_ut2\",path:n(108),deps:[\"what_to_send\"]},{name:\"can_to_sendpv\",path:n(109),config:{flag:\"NO\"}},{name:\"after_pv\",path:n(114)}],hjlj:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"where_to_send\",path:n(102),deps:[],config:{method:\"GET\",url:\"//gm.mmstat.com/\",ac_atpanel:\"//ac.mmstat.com/\",tblogUrl:\"//log.mmstat.com/\"}},{name:\"what_to_send\",path:n(103),deps:[]},{name:\"cookie_data\",path:n(104)},{name:\"what_to_hjlj_userdata\",path:n(115),deps:[\"what_to_send\"]},{name:\"what_to_hjlj_userdata_web\",path:n(116),deps:[\"what_to_send\",\"what_to_hjlj_userdata\"]},{name:\"what_to_hjlj_ut2\",path:n(117),deps:[\"what_to_send\"]}]}}},{name:\"aplus_spm_inject\",path:n(118)},{name:\"aplus_api\",path:n(132)},{name:\"meta_queue\",path:n(141)},{name:\"etag\",path:n(96)},{name:\"etag_web_sync\",path:n(143)},{name:\"aplus_queue\",path:n(144)},{name:\"hot_loader\",path:n(145),config:{urlRules:[{id:\"aplus_webvt_messager\",rule:\"aplus_webvt_messager\",cacheType:\"sessionStorage\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_webvt_messager.js\",\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_track_debug_id\",cacheType:\"sessionStorage\",rule:\"aplus_track_debug_id\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_auto_register\",rule:\"aplus_auto_register=true\",cacheType:\"sessionStorage\",allowIframeLoad:!0,cdnPath:[\"https://d.alicdn.com/alilog/aplus/1.13.9/plugin/aplus_auto_register.js\"]},{id:\"aplus_heat\",rule:\"aplus_heat=true\",cacheType:\"cookie\",allowIframeLoad:!0,cdnPath:[\"https://o.alicdn.com/alilog/aplus-visual-client/heat.js\"]}]}},{name:\"hot_sufei_pc\",path:n(146)},{name:\"aplus_apv\",path:n(147),deps:[\"aplus_log_inject\",\"aplus_api\"]},{name:\"aplus_form_track\",path:n(150)}]}},function(t,e){\"use strict\";t.exports=function(){return{run:function(t,e){var n=setInterval(function(){document.getElementsByTagName(\"body\").length&&(clearInterval(n),n=null,e())},50);return setTimeout(function(){n&&clearInterval(n)},1e3),1e3}}}},function(t,e,n){var a=n(7),o=n(2);t.exports=function(){return{run:function(){var t=o.getGlobalValue(\"aplus\");t.aplus_pubsub||(t.aplus_pubsub=a.create())}}}},function(t,e,n){var a=n(8);t.exports=a.extend({subscribeOnce:function(t,e){this.callable(e);var n,a=this;return this.subscribe.call(this,t,n=function(){a.unsubscribe.call(a,t,n);var o=Array.prototype.slice.call(arguments);e.apply(a,o)}),this}})},function(t,e,n){\"use strict\";var a=n(9),o=n(10),r=function(t){for(var e=t.length,n=new Array(e-1),a=1;a0){for(var a=0;a0)for(var i=0;i\",A=u&&u.createElement(\"div\"),E=[],T={isAliapp:!1,webkit:void 0,edge:void 0,trident:void 0,gecko:void 0,presto:void 0,chrome:void 0,safari:void 0,firefox:void 0,ie:void 0,ieMode:void 0,opera:void 0,mobile:void 0,core:void 0,shell:void 0,phantomjs:void 0,os:void 0,ipad:void 0,iphone:void 0,ipod:void 0,ios:void 0,android:void 0,nodejs:void 0,extraName:void 0,extraVersion:void 0};if(A&&A.getElementsByTagName&&(A.innerHTML=S.replace(y,\"\"),E=A.getElementsByTagName(\"s\")),E.length>0){for(d(t,T),i=b[0],s=b[1];i<=s;i++)if(A.innerHTML=S.replace(y,i),E.length>0){T[v=\"ie\"]=i;break}!T.ie&&(r=m(t))&&(T[v=\"ie\"]=r)}else((o=t.match(/AppleWebKit\\/*\\s*([\\d.]*)/i))||(o=t.match(/Safari\\/([\\d.]*)/)))&&o[1]?(T[h=\"webkit\"]=g(o[1]),(o=t.match(/OPR\\/(\\d+\\.\\d+)/))&&o[1]?T[v=\"opera\"]=g(o[1]):(o=t.match(/Chrome\\/([\\d.]*)/))&&o[1]?T[v=\"chrome\"]=g(o[1]):(o=t.match(/\\/([\\d.]*) Safari/))&&o[1]?T[v=\"safari\"]=g(o[1]):T.safari=T.webkit,(o=t.match(/Edge\\/([\\d.]*)/))&&o[1]&&(h=v=\"edge\",T[h]=g(o[1])),/ Mobile\\//.test(t)&&t.match(/iPad|iPod|iPhone/)?(T.mobile=\"apple\",o=t.match(/OS ([^\\s]*)/),o&&o[1]&&(T.ios=g(o[1].replace(\"_\",\".\"))),a=\"ios\",o=t.match(/iPad|iPod|iPhone/),o&&o[0]&&(T[o[0].toLowerCase()]=T.ios)):/ Android/i.test(t)?(/Mobile/.test(t)&&(a=T.mobile=\"android\"),o=t.match(/Android ([^\\s]*);/),o&&o[1]&&(T.android=g(o[1]))):(o=t.match(/NokiaN[^\\/]*|Android \\d\\.\\d|webOS\\/\\d\\.\\d/))&&(T.mobile=o[0].toLowerCase()),(o=t.match(/PhantomJS\\/([^\\s]*)/))&&o[1]&&(T.phantomjs=g(o[1]))):(o=t.match(/Presto\\/([\\d.]*)/))&&o[1]?(T[h=\"presto\"]=g(o[1]),(o=t.match(/Opera\\/([\\d.]*)/))&&o[1]&&(T[v=\"opera\"]=g(o[1]),(o=t.match(/Opera\\/.* Version\\/([\\d.]*)/))&&o[1]&&(T[v]=g(o[1])),(o=t.match(/Opera Mini[^;]*/))&&o?T.mobile=o[0].toLowerCase():(o=t.match(/Opera Mobi[^;]*/))&&o&&(T.mobile=o[0]))):(r=m(t))?(T[v=\"ie\"]=r,d(t,T)):(o=t.match(/Gecko/))&&(T[h=\"gecko\"]=.1,(o=t.match(/rv:([\\d.]*)/))&&o[1]&&(T[h]=g(o[1]),/Mobile|Tablet/.test(t)&&(T.mobile=\"firefox\")),(o=t.match(/Firefox\\/([\\d.]*)/))&&o[1]&&(T[v=\"firefox\"]=g(o[1])));if(!T[v]){var I=t.match(/Ali\\w+\\(\\w+\\/(\\d+\\.)+\\d+\\)/);if(I){T.isAliapp=!0;var P=I[0],w=\"\",C=\"\",M=P.match(/(\\d+\\.)+\\d+/);M&&(w=M[0],C=P.replace(\"/\"+w,\"\").replace(/\\(|\\)/g,\"\")),T[v=C]=w}}a||(a=e());var x,O,L;if(!n(\"type\",\"application/vnd.chromium.remoting-viewer\")){x=\"scoped\"in u.createElement(\"style\"),L=\"v8Locale\"in c;try{O=c.external||void 0}catch(t){}if(o=t.match(/360SE/))l=\"360\";else if((o=t.match(/SE\\s([\\d.]*)/))||O&&\"SEVersion\"in O)l=\"sougou\",f=g(o[1])||.1;else if((o=t.match(/Maxthon(?:\\/)+([\\d.]*)/))&&O){l=\"maxthon\";try{f=g(O.max_version||o[1])}catch(t){f=.1}}else x&&L?l=\"360se\":x||L||!/Gecko\\)\\s+Chrome/.test(p)||T.opera||T.edge||(l=\"360ee\")}(o=t.match(/TencentTraveler\\s([\\d.]*)|QQBrowser\\/([\\d.]*)/))?(l=\"tt\",f=g(o[2])||.1):(o=t.match(/LBBROWSER/))||O&&\"LiebaoGetVersion\"in O?l=\"liebao\":(o=t.match(/TheWorld/))?(l=\"theworld\",f=3):(o=t.match(/TaoBrowser\\/([\\d.]*)/))?(l=\"taobao\",f=g(o[1])||.1):(o=t.match(/UCBrowser\\/([\\d.]*)/))&&(l=\"uc\",f=g(o[1])||.1),T.os=a,T.core=T.core||h,T.shell=v,T.ieMode=T.ie&&u.documentMode||T.ie,T.extraName=l,T.extraVersion=f;var U=c.screen.width,k=c.screen.height;return T.resolution=U+\"x\"+k,T}function o(t){function e(t){return Object.prototype.toString.call(t)}function n(t,n,a){if(\"[object Function]\"==e(n)&&(n=n(a)),!n)return null;var o={name:t,version:\"\"},r=e(n);if(n===!0)return o;if(\"[object String]\"===r){if(a.indexOf(n)!==-1)return o}else if(n.exec){var i=n.exec(a);if(i)return i.length>=2&&i[1]?o.version=i[1].replace(/_/g,\".\"):o.version=\"\",o}}var a={name:\"other\",version:\"\"};t=(t||\"\").toLowerCase();for(var o=[[\"nokia\",function(t){return t.indexOf(\"nokia \")!==-1?/\\bnokia ([0-9]+)?/:/\\bnokia([a-z0-9]+)?/}],[\"samsung\",function(t){return t.indexOf(\"samsung\")!==-1?/\\bsamsung(?:[ \\-](?:sgh|gt|sm))?-([a-z0-9]+)/:/\\b(?:sgh|sch|gt|sm)-([a-z0-9]+)/}],[\"wp\",function(t){return t.indexOf(\"windows phone \")!==-1||t.indexOf(\"xblwp\")!==-1||t.indexOf(\"zunewp\")!==-1||t.indexOf(\"windows ce\")!==-1}],[\"pc\",\"windows\"],[\"ipad\",\"ipad\"],[\"ipod\",\"ipod\"],[\"iphone\",/\\biphone\\b|\\biph(\\d)/],[\"mac\",\"macintosh\"],[\"mi\",/\\bmi[ \\-]?([a-z0-9 ]+(?= build|\\)))/],[\"hongmi\",/\\bhm[ \\-]?([a-z0-9]+)/],[\"aliyun\",/\\baliyunos\\b(?:[\\-](\\d+))?/],[\"meizu\",function(t){return t.indexOf(\"meizu\")>=0?/\\bmeizu[\\/ ]([a-z0-9]+)\\b/:/\\bm([0-9x]{1,3})\\b/}],[\"nexus\",/\\bnexus ([0-9s.]+)/],[\"huawei\",function(t){var e=/\\bmediapad (.+?)(?= build\\/huaweimediapad\\b)/;return t.indexOf(\"huawei-huawei\")!==-1?/\\bhuawei\\-huawei\\-([a-z0-9\\-]+)/:e.test(t)?e:/\\bhuawei[ _\\-]?([a-z0-9]+)/}],[\"lenovo\",function(t){return t.indexOf(\"lenovo-lenovo\")!==-1?/\\blenovo\\-lenovo[ \\-]([a-z0-9]+)/:/\\blenovo[ \\-]?([a-z0-9]+)/}],[\"zte\",function(t){return/\\bzte\\-[tu]/.test(t)?/\\bzte-[tu][ _\\-]?([a-su-z0-9\\+]+)/:/\\bzte[ _\\-]?([a-su-z0-9\\+]+)/}],[\"vivo\",/\\bvivo(?: ([a-z0-9]+))?/],[\"htc\",function(t){return/\\bhtc[a-z0-9 _\\-]+(?= build\\b)/.test(t)?/\\bhtc[ _\\-]?([a-z0-9 ]+(?= build))/:/\\bhtc[ _\\-]?([a-z0-9 ]+)/}],[\"oppo\",/\\boppo[_]([a-z0-9]+)/],[\"konka\",/\\bkonka[_\\-]([a-z0-9]+)/],[\"sonyericsson\",/\\bmt([a-z0-9]+)/],[\"coolpad\",/\\bcoolpad[_ ]?([a-z0-9]+)/],[\"lg\",/\\blg[\\-]([a-z0-9]+)/],[\"android\",/\\bandroid\\b|\\badr\\b/],[\"blackberry\",function(t){return t.indexOf(\"blackberry\")>=0?/\\bblackberry\\s?(\\d+)/:\"bb10\"}]],r=0;rc.length?u:c,a=decodeURIComponent(a)}else n=e.match(o),a=n&&2===n.length?n[1]:\"\"}catch(t){}finally{return a}}function o(t,e){var n,a,o,r,i,s=e||location.href,c=\"&\",l=[];return u(t,function(t,e){new RegExp(t+\"=\").test(s)||l.push(t+\"=\"+e)}),0===l.length?s:(s.indexOf(\"#\")!==-1&&(o=s.split(\"#\"),s=o.shift(),a=o.join(\"#\")),r=s.split(\"?\"),i=r.length-1,o=r[0].split(\"//\"),o=o[o.length-1].split(\"/\"),i>0&&(n=r.pop(),s=r.join(\"?\")),n&&i>1&&n.indexOf(\"&\")==-1&&n.indexOf(\"%\")!==-1&&(c=\"%26\"),s=s+\"?\"+l.join(\"&\")+(n?c+n:\"\")+(a?\"#\"+a:\"\"))}function r(t){var e=s(location.hash)+\"\";c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"hashchange\",function(){e!==s(location.hash)&&(e=s(location.hash)+\"\",t&&\"function\"==typeof t&&t(e,p))}])}function i(t){function e(e){var a=\"\";if(e){a=e&&e.arguments&&e.arguments.length>2&&e.arguments[2];var o=/^http|https/.test(a)?a:location.protocol+\"//\"+location.host+a;location.href!==o&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0)}else a=location.pathname+location.search,a!==n&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0);n=a}var n=location.pathname+location.search;if(history.pushState&&window.addEventListener){c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"pushState\",function(t){e(t)}]),c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"popstate\",function(){e()}]);var a=l.getMetaCnt(\"aplus-track-replacestate\")||aplus.getMetaInfo&&aplus.getMetaInfo(\"aplus-track-replacestate\");a&&c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"replaceState\",function(t){e(t)}])}}function s(t){var e=\"\";return t&&(e=t.indexOf(\"?\")!=-1?t.split(\"?\")[0]:t),e}var u=n(18);e.addParamsIntoUrl=o,e.getParamFromUrl=a,e.getSPMFromUrl=function(t){return a(\"spm\",t)},e.getQueryFromUrl=function(){function t(t){for(var e=decodeURIComponent(t),n=e.indexOf(\"?\")+1,a=e.substring(n),o=Object.create(null),r=a.split(\"&\"),i=0;i-1)try{S[e]=JSON.parse(n)}catch(t){g.logger({msg:\"the content of meta<\"+e+\"> is invalid json string\"})}if(e===A)try{u=S[e]=JSON.parse(h.getMetaCnt(e))}catch(t){}}}),d(E,function(t){S[t]=h.getMetaCnt(t)}),S.spm_protocol=o(t),u&&(S=p.assign(S,u));var e,n,i=[\"aplus-rate-ahot\"],s=i.length;for(e=0;e\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " TaoWorld跨境供货平台\n", + " \n", + " \n", + " \n", + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + "\n", + " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + "
  • 联系人
  • 商品
  • 聊天记录
\"暂无数据\"
请输入搜索词
卓梵实木家居
2025/12/20
喜欢的亲亲抓紧购买吧，今日下单还有好礼相送哦！ https://item.taobao.com/item.htm?id=752045743811 \u0006
最近联系过
功成地毯工厂
2025/12/19
/:)-(
最近联系过
领风灯具旗舰店
2025/12/14
双十二活动倒计时最后一天活动截止到今晚23:59分结束 宝宝有选好可以咨询客服下单哟
最近联系过
Ephdarren海外旗舰店
2025/12/14
/:087亲，再打扰您一下，双十二活动还剩最后一天了哦/:066\n", + "心动不如行动，看上的别犹豫，活动过了价格会全面上涨的呢~/:^x^\n", + "遇到喜欢的东西，就把它买下来吧，钱并不是真的花掉了/:087\n", + "我们支持365天延迟发货的哦/:066
最近联系过
揽月摘星品牌家具
2025/12/12
[图片]
最近联系过
Tide leader家居
2025/12/12
双十二活动接近尾声了，家具还有哪些顾虑呢，消费券可以叠加立减，提前订购没装修好，也支持延迟发货哟/:081
最近联系过
玲芬美家LF HOME
2025/12/12
🔥亲亲，今晚双12秒杀狂欢夜了哦，您之前看中的家具可以入手啦！\n", + "✅全店商品立减12% + 店铺优惠券 + 大额消费券，最高500元！\n", + "⏰晚上20:00-23:59 还有超低折扣秒杀价，售卖4小时\n", + "🛒现在提前加入购物车锁定优惠特权，定好闹钟准时付款\n", + "🎁本店所有商品均支持【等通知发货】\n", + " \u0006
最近联系过
皇利莱旗舰店
2025/12/12
/:066天猫双12狂欢节最后一天倒计时！\n", + "\n", + "今晚8点！为庆祝活动最终冲刺，我们将开启最后一波限时95折抢购福利！！ 8-12点 ，只限4个小时！全场灯具， 价格直降+店铺券+限时95折+官方立减12%（上不封顶）+满额赠送安装服务，买灯即送LED三色光源一套，365天保价，让你购物无忧，而且，以上优惠可以叠加使用，力度空前巨大！\n", + "\n", + "只有4个小时，只有4个小时哦！快来抢购吧！\n", + "别再错过了，不然再等一年哦！/:066\n", + " \u0006
最近联系过
云栖木作
2025/12/10
亲主要在考虑什么呢?货物早拍下早发货的哦~而且咱们这边售后都是专业一对一的，不用担心货物收到没有保险哦~
最近联系过
勤朗旗舰店
2025/12/10
亲，您是在挑选款式呢，还是挑好款式准备下单呢 ? \n", + "/:^x^现在双十二活动， 喜欢就下手了哦/:-F
最近联系过
意百万家具品牌店
2025/12/08
双十二活动开始了亲。没有下单可以早点下单发货
最近联系过
锦盛实木家居
2025/12/07
/:$双十二福利来袭，亲爱的不要错过活动福利哦！！\n", + "\n", + "12月8日 0点——12月14日 24 点：\n", + "①.全店商品无需凑单，下单享官方立减12%！\n", + "②.更有店铺券满 200 减25，可与官方立减叠加使用，上不封顶哈！\n", + "③.下单即送限量精美台灯/抱枕哦！\n", + "④.活动期间购买，可优先安排发货，还能享受 30 天保价服务呢~ https://item.taobao.com/item.htm?id=838023940983 \u0006
最近联系过
玖传世家具
2025/12/07
✈️88VIP领券链接：https://pages-fast.m.taobao.com/wow/z/blackvip/v/home?x-ssr=true&disableNav \u0006
最近联系过
福祥工艺家具
2025/12/07
/:066/:066/:066/:clock今晚0:00-1:00，限时1小时95折秒杀！！！\n", + "/:$全店商品均享超低折扣价，更有店铺专属大额优惠劵，叠加官方立减13%！！！/:081/:081/:081\n", + "赶快将心仪好物加入购物车，火速下单吧！！！/:809/:809/:809 \u0006
最近联系过
依诺家居生活馆yn
下拉或点此加载更多
t-2217567810350-0
2025-11-28 10:01:58 
您好！关于【平台交易号:4896044463230622839】，请问货物的发车日期是几号呢？方便提供下吗？★重要信息麻烦打字告知哦★
依诺家居生活馆yn
2025-11-28 10:02:41 
4896044463230622839
依诺家居生活馆yn
2025-11-28 10:04:04 
30号左右到
t-2217567810350-0
2025-11-28 10:05:23 
平台交易号:4908583513312069844,您好，请问订单的发货时间能否确定？12月02日前可以发货吗? 如果近期无法确定我们只能申请退款处理了哦。（不要图片版哈）
依诺家居生活馆yn
2025-11-28 10:05:39 
可以
t-2217567810350-0
2025-11-28 10:18:59 
平台交易号:4908196119382069844,您好，请问订单的发货时间能否确定？12月02日前可以发货吗? 如果近期无法确定我们只能申请退款处理了哦。（不要图片版哈）
依诺家居生活馆yn
2025-11-28 10:19:17 
可以
t-2217567810350-0
2025-11-28 10:51:45 
平台交易号:3089818957047538788,你好，请问最快什么时候发货，12月03日前可以发货吗？（麻烦不要发图片）
t-2217567810350-0
2025-11-28 11:00:24 
平台交易号:3089812045891538788,你好，请问最快什么时候发货，12月03日前可以发货吗？（麻烦不要发图片）
依诺家居生活馆yn
2025-11-28 11:00:40 
可以
t-2217567810350-0
2025-11-28 13:25:31 
平台交易号:4910096557371069844,你好，请问最快什么时候发货，12月03日前可以发货吗？（麻烦不要发图片）
依诺家居生活馆yn
2025-11-28 13:25:37 
可以
t-2217567810350-0
2025-11-28 14:53:09 
亲！关于【平台交易号:4908196119382069844】，能麻烦您查下实际发车日期吗？谢谢配合！（麻烦不要发图片）
依诺家居生活馆yn
2025-11-28 14:53:41 
前天发货的
依诺家居生活馆yn
2025-11-28 14:53:45 
30号到
依诺家居生活馆yn
2025-11-28 14:53:55 
现在查不到信息
依诺家居生活馆yn
2025-11-28 14:53:59 
中途不卸车
t-2217567810350-0
2025-11-28 16:26:58 
平台交易号:3090519877328538788,你好，请问最快什么时候发货，12月03日前可以发货吗？（麻烦不要发图片）
依诺家居生活馆yn
2025-11-28 16:27:20 
可以
依诺家居生活馆yn
2025-11-28 16:38:59 
请问是机器人吗
表情
发送图片
发送视频
78 / 500
平台交易号:3277680960636538788,您好，之前联系过您多次，仍未收到回复。03月11日前可以发货吗？如果近期无法发货，我们只能申请退款处理。
产品服务能力由钉钉提供
依诺家居生活馆yn
近三个月订单
没有数据
\n", + "
TaoWorld跨境供货平台，链接天猫淘宝海量货源，为跨境卖家、代采代购商提供全链路的解决方案。
\n", + " \n", + " \n", + "\n", + "
AliPrice
AliPrice
仅本次浏览关闭插件浮标
永久关闭此网站插件浮标
使用快捷键Ctrl+Shift+4快速唤起
或在设置中重新启用(永久关闭则不支持此网站快捷键唤起使用)
全网图搜
店雷达1688选品工具，快速查找热销、飙升、上新商品；新品早发现,好商品早知道！
去看看
' \"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:23: SyntaxWarning: invalid escape sequence '\\/'\n", + "<>:23: SyntaxWarning: invalid escape sequence '\\/'\n", + "C:\\Users\\joker\\AppData\\Local\\Temp\\ipykernel_96992\\4169073732.py:23: SyntaxWarning: invalid escape sequence '\\/'\n", + " !function(t){function e(a){if(n[a])return n[a].exports;var o=n[a]={exports:{},id:a,loaded:!1};return t[a].call(o.exports,o,o.exports,e),o.loaded=!0,o.exports}var n={};return e.m=t,e.c=n,e.p=\"\",e(0)}([function(t,e,n){t.exports=n(1)},function(t,e,n){\"use strict\";n(2).initGlobal(window),function(){var t=n(4);n(156)(t)}()},function(t,e,n){\"use strict\";var a,o=n(3),r=o.APLUS,i=o.APLUS_QUEUE,s=o.GOLDLOG,u=o.GOLDLOG_QUEUE,c=!1;try{\"undefined\"!=typeof window&&(a=window,c=!0)}catch(t){a={},c=!1}e.getContext=function(){return a},e.isWeb=function(){return\"undefined\"!=typeof window&&window},e.initGlobal=function(t){a=t?t:{v:1,aplus:{},aplus_queue:[]};var e,n;if(c)try{e=a.aplus||a.goldlog||(a.aplus={});var o=a.goldlog_queue||(a.goldlog_queue=[]);n=a.aplus_queue||(a.aplus_queue=[]),n=o.concat(n)}catch(t){}else e=a.aplus,n=a.aplus_queue;return a.aplus=a.goldlog=e,a.aplus_queue=a.goldlog_queue=n,a};var l=function(t){if(t===r||t===s){var e=a[r]||a[s];return e||(e=a[r]=a[s]={}),e}var n=u,o=i;if(t===o||t===n){var c=a[o]||a[n];return c||(c=a[o]=a[n]=[]),c}};e.getGlobalValue=l,e.setGlobalValue=function(t,e){a[t]=e};var p=function(t){var e;try{var n=l(r);e=n[t]}catch(t){e=\"\"}finally{return e}};e.getGoldlogVal=p;var f=function(t,e){var n=!1;try{var a=l(r);t&&(a[t]=e,n=!0)}catch(t){n=!1}finally{return n}};e.setGoldlogVal=f,e.getClientInfo=function(){return p(\"_aplus_client\")||{}}},function(t,e){var n=\"aplus\",a=\"goldlog\",o=n+\"_queue\",r=a+\"_queue\",i=\"mw_change\",s=\"MetaInfo\",u=\"append\"+s,c=\"set\"+s,l=\"http\",p=\"_pubsub\",f=\"other\",g=\"2101\",d=\"2201\",m=\"2202\",_=\"19999\",h=\"1023\",v=\"1010\",b=3e4,y=18e5,S=\"ekvs\",A=1e4,E=1,T=1,I=3e3,P=\"$$_page_start\",w=\"$$_page_end\",C=\"$$_app_start\",M=\"$$_app_end\",x=\"aplus_user_profile\",O=\"imprint\",L=n+\"-idtype\",U=n+\"-jsbridge-only\",k=n+\"-page-config\",R=n+\"-skip-apv-rules\",N=n+\"-rhost-v\",G=n+\"-rhost-g\",D=n+\"-forward-domain\",V=n+\"-forward-event-filter\",j=\"autoGetOpenid\",F=n+\"-forward-appkey\";t.exports={PAGE_ENTER:\"PAGE_ENTER\",ETAG_EVENT_NAME:\"etag\",CURRENT_PAGE_CONFIG:\"CURRENT_PAGE_CONFIG\",_ANONY_ID:\"_anony_id\",_DEV_ID:\"_dev_id\",_USER_ID:\"_user_id\",_CNA:\"cna\",DEFAULT_CODE:f,OTHER:_,EVENT_MAP:{2101:\"click\",2201:\"exposure\",2202:\"exposure\",19999:f,1023:\"app_show\",1010:\"app_hide_or_unload\"},EVENT_ID_MAP:{EXP:d,IMPEXP:m,CLK:g,OTHER:_,SHOW:h,H_OR_U:v},APLUS:n,APLUS_CONFIG:\"APLUS_CONFIG\",GOLDLOG:a,UNSUBSCRIBE:n+\".\"+n+p+\".unsubscribe\",SUBSCRIBE:n+\".\"+n+p+\".subscribe\",PUBLISH:n+\".\"+n+p+\".publish\",CACHE_PUBS:n+\".\"+n+p+\".cachePubs\",APLUS_UNIVERSAL:n+\"_universal\",APLUS_QUEUE:o,GOLDLOG_QUEUE:r,COMPLETE:\"complete\",PV_CODE:\"2001\",EXP_CODE:d,CLK_CODE:g,OTHER_CODE:_,CLK:\"CLK\",EXP:\"EXP\",SPM_CNT:\"spm-cnt\",SPM_URL:\"spm-url\",SPM_PRE:\"spm-pre\",MW_CHANGE_PV:i+\"_pv\",MW_CHANGE_HJLJ:i+\"_hjlj\",HTTP:l+\":\",HTTPS:\"https:\",APPEND_META_INFO:u,SET_META_INFO:c,APLUS_APPEND_META_INFO:n+\".\"+u,APLUS_SET_META_INFO:n+\".\"+c,PVID:\"pvid\",openAPIs:[\"send\",\"enter\",\"sendPV\",\"record\",\"combineRecord\",\"recordUdata\",\"requestVTConfig\",\"requestRemoteConfig\",\"setPageSPM\",\"setMetaInfo\",\"appendMetaInfo\",\"updatePageProperties\",\"updateNextPageProperties\",\"updatePageUtparam\",\"updateNextPageUtparam\",\"pageAppear\",\"pageDisappear\",\"pageDisAppear\",\"skipPage\",\"updatePageName\",\"updatePageUrl\",\"requestPageAllProperties\",\"updateSessionProperties\",\"getPageSpmUrl\",\"getPageSpmPre\",\"updateNextPageUtparamCnt\",\"setPageName\",\"getElementSPM\",\"getAutoElementSPM\",\"setUserProfile\",\"getUserProfile\",\"getCna\"],SESSION_INTERVAL:b,SESSION_PAUSE_TIME:\"session_pause_time\",IMPRINT:\"imprint\",CURRENT_SESSION:\"current_session\",MAX_EVENTID_LENGTH:128,MAX_PROPERTY_KEY_LENGTH:256,MAX_PROPERTY_KEYS_COUNT:100,FAILED_REQUESTS:\"failed_requests\",REQUESTS:\"requests\",SHARES:\"shares\",APLUS_SSRC:\"_aplus_ssrc\",ARMS_TRACE:\"_arms_trace\",EKVS:S,EVENT_MAX_COUNT:A,MEMORY_MAX_COUNT:E,MAX_QUEUE_COUNT:T,EVENT_SEND_DEFAULT_INTERVAL:I,PAGE_START:P,PAGE_END:w,APP_START:C,APP_END:M,USER_PROFILE_KEY:x,SHARE_CACHE_INTERVAL:y,IMPRINT:O,ID_TYPE:L,GLOBAL_PROPERTY:\"globalproperty\",JSBRIDGE_ONLY:U,PAGE_CONFIG:k,APLUS_SKIP_APV_RULES:R,APLUS_PV_DOMAIN:N,APLUS_EKV_DOMAIN:G,APLUS_FORWARD_DOMAIN:D,APLUS_IMPRINT_VERSION:\"APLUS_IMPRINT_VERSION\",APLUS_REMOTE_CONFIG:\"APLUS_REMOTE_CONFIG\",RANK:\"ekv_rank\",WEB_EVENT_SUFFIX:\"/web_logs\",WEB_PC_PV_SUFFIX:\"v.gif\",WEB_WAP_PV_SUFFIX:\"m.gif\",PAGE_LEAVE:\"$$_page_leave\",APLUS_DOM_CHANGE:\"APLUS_DOM_CHANGE\",APLUS_PAGE_CHANGE:\"APLUS_PAGE_CHANGE\",PERFORMANCE_WARING:\"$$_perf_warning\",START_ID:\"START_ID\",AUTO_GET_OPENID:j,APLUS_LATEAST_UTM:\"APLUS_LATEAST_UTM\",APLUS_FORWARD_EVENT_FILTER:V,APLUS_FORWARD_APPKEY:F,APLUS_RHOST_V:n+\"-rhost-v\",APLUS_CPVDATA:n+\"-cpvdata\",APLUS_EXDATA:n+\"-exdata\",APLUS_EXINFO:n+\"-exinfo\",APLUS_LOG_PIPE:n+\"-log-pipe\",APLUS_TRACK_COMBINE:n+\"-track-combine\",APLUS_COOKIES:n+\"-cookies\",APLUS_CODELESS_TRACK_CONFIG:\"_\"+n+\"_codeless_track_config\",APLUS_AUTO_CLK:n+\"-auto-clk\",APLUS_AUTO_EXP:n+\"-auto-exp\",APLUS_AUTO_PV:n+\"-auto-pv\",APLUS_BRIDGE_NAME:n+\"-bridge-name\",APLUS_MINI_REQUEST_TIMEOUT:n+\"-request-timeout\",APLUS_VT_CONFIG_URL:n+\"-vt-cfg-url\",APLUS_EXPOSURE_EVENT_CAN_REPEAT:n+\"-exposure-event-can-repeat\",APLUS_IGNORE_LIFECYCLES:n+\"-ignore-lifecycles\",APLUS_TRACK_DEBUG_ID:n+\"-track-debug-id\",APLUS_SINGLE_RECORD_LOGKEYS:n+\"-single-record-logkeys\",APLUS_GOKEY_ISOLATE:n+\"-gokey-isolate\",APLUS_AUTOTRACK_ENABLED:n+\"-autotrack-enabled\",APLUS_AUTOTRACK_ENABLED_REMOTE:n+\"-autotrack-enabled-remote\",APLUS_AUTOTRACK_CONFIG:n+\"-autotrack-config\",APLUS_AUTO_TRACK_CONFIG_IMPORT:n+\"-auto-track-config-import\",APLUS_AUTOTRACK_CONFIG_REMOTE:n+\"-autotrack-config-remote\",APLUS_EVENT_LIMITRATES:n+\"-event-limitrates\",APLUS_DISABLE_AUTOEVENT:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOEVENT_REMOTE:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOPV:n+\"-disable-apv\",APLUS_DISABLE_AUTOPV_REMOTE:n+\"-disable-apv-remote\",APLUS_DEVICE_ENABLE:n+\"-device-enable\",APLUS_USER_PROFILE:n+\"-user-profile\",APLUS_CNA_ENABLE:n+\"-cna-enable\",APLUS_CNA_MODE:n+\"-cna-mode\",APLUS_ETAG_TIMEOUT:n+\"-etag-timeout\",APLUS_SPA_TYPE:n+\"-spa-type\",APLUS_MONITOR_ENABLE:n+\"-monitor-enable\",APLUS_OBSERVATIONS:\"_\"+n+\"_observations\",APLUS_REPORT_RATE:n+\"-report-rate\",APLUS_CNA_MONITOR:n+\"-cna-monitor\",APLUS_MMSTAT_TIMEOUT:n+\"-mmstat-timeout\",APLUS_REMOTE_CONTROL:n+\"-remote-control\",APLUS_CNA_STABILITY:n+\"-cna-stability\",APLUS_AUTO_PID:n+\"-auto-pid\"}},function(t,e,n){t.exports={metaInfo:{\"aplus-ifr-pv\":\"0\",\"aplus-rhost-v\":\"log.mmstat.com\",\"aplus-rhost-g\":\"gm.mmstat.com\",\"aplus-channel\":\"WS\",appId:\"60506758\",sdkId:\"customSdkId\",\"aplus-cpvdata\":{},\"aplus-exdata\":{},\"aplus-globaldata\":{},\"aplus-mmstat-timeout\":\"10000\",\"aplus-toUT\":\"auto\",\"aplus-track-combine\":\"on\",\"aplus-vt-auto-userfn-enable\":\"on\",\"aplus-cna-enable\":\"on\",\"aplus-cna-mode\":\"CK\",\"aplus-auto-track-config-import\":\"off\",\"aplus-form-track\":\"off\",\"aplus-gokey-isolate\":\"on\",\"aplus-only-update-page-properties\":\"off\",\"aplus-spm-from-url\":\"on\",\"aplus-user-profile\":{},\"aplus-report-rate\":{},\"aplus-single-record-logkeys\":[],\"aplus-cross-day-auto-pv\":\"off\",\"aplus-cna-monitor\":\"off\",\"aplus-cna-stability\":\"off\",\"aplus-auto-pid\":\"on\",\"aplus-monitor-enable\":\"off\",\"aplus-remote-control\":\"on\"},globalConfig:{isAli:!0,APLUS_QUEUE:\"aplus_queue\",ETAG_STORAGE_KEY:\"__ETAG__CNA__ID__\",script_name:\"aplus.js\",NAME_STORAGE_KEYS:{REFERRER:\"wm_referrer\",REFERRER_PV_ID:\"refer_pv_id\",LOST_PV_PAGE_DURATION:\"lost_pv_page_duration\",LOST_PV_PAGE_SPMAB:\"lost_pv_page_spmab\",LOST_PV_PAGE:\"lost_pv_page\",LOST_PV_PAGE_MSG:\"lost_pv_page_msg\"},lver:\"1.13.27\"},plugins:[{name:\"aplus_body_ready\",path:n(5)},{name:\"pubsub\",path:n(6)},{name:\"aplus_client\",path:n(11)},{name:\"aplus_meta_inject\",path:n(15)},{name:\"aplus_remote_control\",path:n(49)},{name:\"aplus_observer\",path:n(51)},{name:\"aplus_ac\",path:n(53)},{name:\"aplus_ae\",path:n(72)},{name:\"name_storage\",path:n(80)},{name:\"record_lost_pv\",path:n(83),config:{lostPvRecordRatio:.01}},{name:\"aplus_monitor\",path:n(85),config:{obsoleteInterRecordRatio:\"0.01\",jsErrorRecordRatio:\"0.01\",browserSupportRatio:\"0.01\"}},{name:\"aplus_web_http_ali\",path:n(92)},{name:\"aplus_log_inject\",path:n(95),deps:[\"aplus_meta_inject\"],config:{plugins:{pv:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"when_to_sendpv\",path:n(101),config:{aplusWaiting:\"\"}},{name:\"where_to_send\",path:n(102),config:{method:\"GET\",url:\"//log.mmstat.com/v.gif\"}},{name:\"what_to_send\",path:n(103),config:{pvdataToUt:{}}},{name:\"cookie_data\",path:n(104)},{name:\"what_to_sendpv_userdata\",path:n(105),deps:[\"what_to_send\"]},{name:\"what_to_sendpv_userdata_web\",path:n(106),deps:[\"what_to_send\",\"what_to_sendpv_userdata\"]},{name:\"what_to_sendpv_ut2\",path:n(108),deps:[\"what_to_send\"]},{name:\"can_to_sendpv\",path:n(109),config:{flag:\"NO\"}},{name:\"after_pv\",path:n(114)}],hjlj:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"where_to_send\",path:n(102),deps:[],config:{method:\"GET\",url:\"//gm.mmstat.com/\",ac_atpanel:\"//ac.mmstat.com/\",tblogUrl:\"//log.mmstat.com/\"}},{name:\"what_to_send\",path:n(103),deps:[]},{name:\"cookie_data\",path:n(104)},{name:\"what_to_hjlj_userdata\",path:n(115),deps:[\"what_to_send\"]},{name:\"what_to_hjlj_userdata_web\",path:n(116),deps:[\"what_to_send\",\"what_to_hjlj_userdata\"]},{name:\"what_to_hjlj_ut2\",path:n(117),deps:[\"what_to_send\"]}]}}},{name:\"aplus_spm_inject\",path:n(118)},{name:\"aplus_api\",path:n(132)},{name:\"meta_queue\",path:n(141)},{name:\"etag\",path:n(96)},{name:\"etag_web_sync\",path:n(143)},{name:\"aplus_queue\",path:n(144)},{name:\"hot_loader\",path:n(145),config:{urlRules:[{id:\"aplus_webvt_messager\",rule:\"aplus_webvt_messager\",cacheType:\"sessionStorage\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_webvt_messager.js\",\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_track_debug_id\",cacheType:\"sessionStorage\",rule:\"aplus_track_debug_id\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_auto_register\",rule:\"aplus_auto_register=true\",cacheType:\"sessionStorage\",allowIframeLoad:!0,cdnPath:[\"https://d.alicdn.com/alilog/aplus/1.13.9/plugin/aplus_auto_register.js\"]},{id:\"aplus_heat\",rule:\"aplus_heat=true\",cacheType:\"cookie\",allowIframeLoad:!0,cdnPath:[\"https://o.alicdn.com/alilog/aplus-visual-client/heat.js\"]}]}},{name:\"hot_sufei_pc\",path:n(146)},{name:\"aplus_apv\",path:n(147),deps:[\"aplus_log_inject\",\"aplus_api\"]},{name:\"aplus_form_track\",path:n(150)}]}},function(t,e){\"use strict\";t.exports=function(){return{run:function(t,e){var n=setInterval(function(){document.getElementsByTagName(\"body\").length&&(clearInterval(n),n=null,e())},50);return setTimeout(function(){n&&clearInterval(n)},1e3),1e3}}}},function(t,e,n){var a=n(7),o=n(2);t.exports=function(){return{run:function(){var t=o.getGlobalValue(\"aplus\");t.aplus_pubsub||(t.aplus_pubsub=a.create())}}}},function(t,e,n){var a=n(8);t.exports=a.extend({subscribeOnce:function(t,e){this.callable(e);var n,a=this;return this.subscribe.call(this,t,n=function(){a.unsubscribe.call(a,t,n);var o=Array.prototype.slice.call(arguments);e.apply(a,o)}),this}})},function(t,e,n){\"use strict\";var a=n(9),o=n(10),r=function(t){for(var e=t.length,n=new Array(e-1),a=1;a0){for(var a=0;a0)for(var i=0;i\",A=u&&u.createElement(\"div\"),E=[],T={isAliapp:!1,webkit:void 0,edge:void 0,trident:void 0,gecko:void 0,presto:void 0,chrome:void 0,safari:void 0,firefox:void 0,ie:void 0,ieMode:void 0,opera:void 0,mobile:void 0,core:void 0,shell:void 0,phantomjs:void 0,os:void 0,ipad:void 0,iphone:void 0,ipod:void 0,ios:void 0,android:void 0,nodejs:void 0,extraName:void 0,extraVersion:void 0};if(A&&A.getElementsByTagName&&(A.innerHTML=S.replace(y,\"\"),E=A.getElementsByTagName(\"s\")),E.length>0){for(d(t,T),i=b[0],s=b[1];i<=s;i++)if(A.innerHTML=S.replace(y,i),E.length>0){T[v=\"ie\"]=i;break}!T.ie&&(r=m(t))&&(T[v=\"ie\"]=r)}else((o=t.match(/AppleWebKit\\/*\\s*([\\d.]*)/i))||(o=t.match(/Safari\\/([\\d.]*)/)))&&o[1]?(T[h=\"webkit\"]=g(o[1]),(o=t.match(/OPR\\/(\\d+\\.\\d+)/))&&o[1]?T[v=\"opera\"]=g(o[1]):(o=t.match(/Chrome\\/([\\d.]*)/))&&o[1]?T[v=\"chrome\"]=g(o[1]):(o=t.match(/\\/([\\d.]*) Safari/))&&o[1]?T[v=\"safari\"]=g(o[1]):T.safari=T.webkit,(o=t.match(/Edge\\/([\\d.]*)/))&&o[1]&&(h=v=\"edge\",T[h]=g(o[1])),/ Mobile\\//.test(t)&&t.match(/iPad|iPod|iPhone/)?(T.mobile=\"apple\",o=t.match(/OS ([^\\s]*)/),o&&o[1]&&(T.ios=g(o[1].replace(\"_\",\".\"))),a=\"ios\",o=t.match(/iPad|iPod|iPhone/),o&&o[0]&&(T[o[0].toLowerCase()]=T.ios)):/ Android/i.test(t)?(/Mobile/.test(t)&&(a=T.mobile=\"android\"),o=t.match(/Android ([^\\s]*);/),o&&o[1]&&(T.android=g(o[1]))):(o=t.match(/NokiaN[^\\/]*|Android \\d\\.\\d|webOS\\/\\d\\.\\d/))&&(T.mobile=o[0].toLowerCase()),(o=t.match(/PhantomJS\\/([^\\s]*)/))&&o[1]&&(T.phantomjs=g(o[1]))):(o=t.match(/Presto\\/([\\d.]*)/))&&o[1]?(T[h=\"presto\"]=g(o[1]),(o=t.match(/Opera\\/([\\d.]*)/))&&o[1]&&(T[v=\"opera\"]=g(o[1]),(o=t.match(/Opera\\/.* Version\\/([\\d.]*)/))&&o[1]&&(T[v]=g(o[1])),(o=t.match(/Opera Mini[^;]*/))&&o?T.mobile=o[0].toLowerCase():(o=t.match(/Opera Mobi[^;]*/))&&o&&(T.mobile=o[0]))):(r=m(t))?(T[v=\"ie\"]=r,d(t,T)):(o=t.match(/Gecko/))&&(T[h=\"gecko\"]=.1,(o=t.match(/rv:([\\d.]*)/))&&o[1]&&(T[h]=g(o[1]),/Mobile|Tablet/.test(t)&&(T.mobile=\"firefox\")),(o=t.match(/Firefox\\/([\\d.]*)/))&&o[1]&&(T[v=\"firefox\"]=g(o[1])));if(!T[v]){var I=t.match(/Ali\\w+\\(\\w+\\/(\\d+\\.)+\\d+\\)/);if(I){T.isAliapp=!0;var P=I[0],w=\"\",C=\"\",M=P.match(/(\\d+\\.)+\\d+/);M&&(w=M[0],C=P.replace(\"/\"+w,\"\").replace(/\\(|\\)/g,\"\")),T[v=C]=w}}a||(a=e());var x,O,L;if(!n(\"type\",\"application/vnd.chromium.remoting-viewer\")){x=\"scoped\"in u.createElement(\"style\"),L=\"v8Locale\"in c;try{O=c.external||void 0}catch(t){}if(o=t.match(/360SE/))l=\"360\";else if((o=t.match(/SE\\s([\\d.]*)/))||O&&\"SEVersion\"in O)l=\"sougou\",f=g(o[1])||.1;else if((o=t.match(/Maxthon(?:\\/)+([\\d.]*)/))&&O){l=\"maxthon\";try{f=g(O.max_version||o[1])}catch(t){f=.1}}else x&&L?l=\"360se\":x||L||!/Gecko\\)\\s+Chrome/.test(p)||T.opera||T.edge||(l=\"360ee\")}(o=t.match(/TencentTraveler\\s([\\d.]*)|QQBrowser\\/([\\d.]*)/))?(l=\"tt\",f=g(o[2])||.1):(o=t.match(/LBBROWSER/))||O&&\"LiebaoGetVersion\"in O?l=\"liebao\":(o=t.match(/TheWorld/))?(l=\"theworld\",f=3):(o=t.match(/TaoBrowser\\/([\\d.]*)/))?(l=\"taobao\",f=g(o[1])||.1):(o=t.match(/UCBrowser\\/([\\d.]*)/))&&(l=\"uc\",f=g(o[1])||.1),T.os=a,T.core=T.core||h,T.shell=v,T.ieMode=T.ie&&u.documentMode||T.ie,T.extraName=l,T.extraVersion=f;var U=c.screen.width,k=c.screen.height;return T.resolution=U+\"x\"+k,T}function o(t){function e(t){return Object.prototype.toString.call(t)}function n(t,n,a){if(\"[object Function]\"==e(n)&&(n=n(a)),!n)return null;var o={name:t,version:\"\"},r=e(n);if(n===!0)return o;if(\"[object String]\"===r){if(a.indexOf(n)!==-1)return o}else if(n.exec){var i=n.exec(a);if(i)return i.length>=2&&i[1]?o.version=i[1].replace(/_/g,\".\"):o.version=\"\",o}}var a={name:\"other\",version:\"\"};t=(t||\"\").toLowerCase();for(var o=[[\"nokia\",function(t){return t.indexOf(\"nokia \")!==-1?/\\bnokia ([0-9]+)?/:/\\bnokia([a-z0-9]+)?/}],[\"samsung\",function(t){return t.indexOf(\"samsung\")!==-1?/\\bsamsung(?:[ \\-](?:sgh|gt|sm))?-([a-z0-9]+)/:/\\b(?:sgh|sch|gt|sm)-([a-z0-9]+)/}],[\"wp\",function(t){return t.indexOf(\"windows phone \")!==-1||t.indexOf(\"xblwp\")!==-1||t.indexOf(\"zunewp\")!==-1||t.indexOf(\"windows ce\")!==-1}],[\"pc\",\"windows\"],[\"ipad\",\"ipad\"],[\"ipod\",\"ipod\"],[\"iphone\",/\\biphone\\b|\\biph(\\d)/],[\"mac\",\"macintosh\"],[\"mi\",/\\bmi[ \\-]?([a-z0-9 ]+(?= build|\\)))/],[\"hongmi\",/\\bhm[ \\-]?([a-z0-9]+)/],[\"aliyun\",/\\baliyunos\\b(?:[\\-](\\d+))?/],[\"meizu\",function(t){return t.indexOf(\"meizu\")>=0?/\\bmeizu[\\/ ]([a-z0-9]+)\\b/:/\\bm([0-9x]{1,3})\\b/}],[\"nexus\",/\\bnexus ([0-9s.]+)/],[\"huawei\",function(t){var e=/\\bmediapad (.+?)(?= build\\/huaweimediapad\\b)/;return t.indexOf(\"huawei-huawei\")!==-1?/\\bhuawei\\-huawei\\-([a-z0-9\\-]+)/:e.test(t)?e:/\\bhuawei[ _\\-]?([a-z0-9]+)/}],[\"lenovo\",function(t){return t.indexOf(\"lenovo-lenovo\")!==-1?/\\blenovo\\-lenovo[ \\-]([a-z0-9]+)/:/\\blenovo[ \\-]?([a-z0-9]+)/}],[\"zte\",function(t){return/\\bzte\\-[tu]/.test(t)?/\\bzte-[tu][ _\\-]?([a-su-z0-9\\+]+)/:/\\bzte[ _\\-]?([a-su-z0-9\\+]+)/}],[\"vivo\",/\\bvivo(?: ([a-z0-9]+))?/],[\"htc\",function(t){return/\\bhtc[a-z0-9 _\\-]+(?= build\\b)/.test(t)?/\\bhtc[ _\\-]?([a-z0-9 ]+(?= build))/:/\\bhtc[ _\\-]?([a-z0-9 ]+)/}],[\"oppo\",/\\boppo[_]([a-z0-9]+)/],[\"konka\",/\\bkonka[_\\-]([a-z0-9]+)/],[\"sonyericsson\",/\\bmt([a-z0-9]+)/],[\"coolpad\",/\\bcoolpad[_ ]?([a-z0-9]+)/],[\"lg\",/\\blg[\\-]([a-z0-9]+)/],[\"android\",/\\bandroid\\b|\\badr\\b/],[\"blackberry\",function(t){return t.indexOf(\"blackberry\")>=0?/\\bblackberry\\s?(\\d+)/:\"bb10\"}]],r=0;rc.length?u:c,a=decodeURIComponent(a)}else n=e.match(o),a=n&&2===n.length?n[1]:\"\"}catch(t){}finally{return a}}function o(t,e){var n,a,o,r,i,s=e||location.href,c=\"&\",l=[];return u(t,function(t,e){new RegExp(t+\"=\").test(s)||l.push(t+\"=\"+e)}),0===l.length?s:(s.indexOf(\"#\")!==-1&&(o=s.split(\"#\"),s=o.shift(),a=o.join(\"#\")),r=s.split(\"?\"),i=r.length-1,o=r[0].split(\"//\"),o=o[o.length-1].split(\"/\"),i>0&&(n=r.pop(),s=r.join(\"?\")),n&&i>1&&n.indexOf(\"&\")==-1&&n.indexOf(\"%\")!==-1&&(c=\"%26\"),s=s+\"?\"+l.join(\"&\")+(n?c+n:\"\")+(a?\"#\"+a:\"\"))}function r(t){var e=s(location.hash)+\"\";c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"hashchange\",function(){e!==s(location.hash)&&(e=s(location.hash)+\"\",t&&\"function\"==typeof t&&t(e,p))}])}function i(t){function e(e){var a=\"\";if(e){a=e&&e.arguments&&e.arguments.length>2&&e.arguments[2];var o=/^http|https/.test(a)?a:location.protocol+\"//\"+location.host+a;location.href!==o&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0)}else a=location.pathname+location.search,a!==n&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0);n=a}var n=location.pathname+location.search;if(history.pushState&&window.addEventListener){c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"pushState\",function(t){e(t)}]),c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"popstate\",function(){e()}]);var a=l.getMetaCnt(\"aplus-track-replacestate\")||aplus.getMetaInfo&&aplus.getMetaInfo(\"aplus-track-replacestate\");a&&c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"replaceState\",function(t){e(t)}])}}function s(t){var e=\"\";return t&&(e=t.indexOf(\"?\")!=-1?t.split(\"?\")[0]:t),e}var u=n(18);e.addParamsIntoUrl=o,e.getParamFromUrl=a,e.getSPMFromUrl=function(t){return a(\"spm\",t)},e.getQueryFromUrl=function(){function t(t){for(var e=decodeURIComponent(t),n=e.indexOf(\"?\")+1,a=e.substring(n),o=Object.create(null),r=a.split(\"&\"),i=0;i-1)try{S[e]=JSON.parse(n)}catch(t){g.logger({msg:\"the content of meta<\"+e+\"> is invalid json string\"})}if(e===A)try{u=S[e]=JSON.parse(h.getMetaCnt(e))}catch(t){}}}),d(E,function(t){S[t]=h.getMetaCnt(t)}),S.spm_protocol=o(t),u&&(S=p.assign(S,u));var e,n,i=[\"aplus-rate-ahot\"],s=i.length;for(e=0;e\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " TaoWorld跨境供货平台\n", + " \n", + " \n", + " \n", + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + "\n", + " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + "
  • 联系人
  • 商品
  • 聊天记录
\"暂无数据\"
请输入搜索词
Gentle Township
12:23
可以呢 这两天会安排发出哦
最近联系过
卓梵实木家居
2025/12/20
喜欢的亲亲抓紧购买吧，今日下单还有好礼相送哦！ https://item.taobao.com/item.htm?id=752045743811 \u0006
最近联系过
功成地毯工厂
2025/12/19
/:)-(
最近联系过
领风灯具旗舰店
2025/12/14
双十二活动倒计时最后一天活动截止到今晚23:59分结束 宝宝有选好可以咨询客服下单哟
最近联系过
Ephdarren海外旗舰店
2025/12/14
/:087亲，再打扰您一下，双十二活动还剩最后一天了哦/:066\n", + "心动不如行动，看上的别犹豫，活动过了价格会全面上涨的呢~/:^x^\n", + "遇到喜欢的东西，就把它买下来吧，钱并不是真的花掉了/:087\n", + "我们支持365天延迟发货的哦/:066
最近联系过
揽月摘星品牌家具
2025/12/12
[图片]
最近联系过
Tide leader家居
2025/12/12
双十二活动接近尾声了，家具还有哪些顾虑呢，消费券可以叠加立减，提前订购没装修好，也支持延迟发货哟/:081
最近联系过
玲芬美家LF HOME
2025/12/12
🔥亲亲，今晚双12秒杀狂欢夜了哦，您之前看中的家具可以入手啦！\n", + "✅全店商品立减12% + 店铺优惠券 + 大额消费券，最高500元！\n", + "⏰晚上20:00-23:59 还有超低折扣秒杀价，售卖4小时\n", + "🛒现在提前加入购物车锁定优惠特权，定好闹钟准时付款\n", + "🎁本店所有商品均支持【等通知发货】\n", + " \u0006
最近联系过
皇利莱旗舰店
2025/12/12
/:066天猫双12狂欢节最后一天倒计时！\n", + "\n", + "今晚8点！为庆祝活动最终冲刺，我们将开启最后一波限时95折抢购福利！！ 8-12点 ，只限4个小时！全场灯具， 价格直降+店铺券+限时95折+官方立减12%（上不封顶）+满额赠送安装服务，买灯即送LED三色光源一套，365天保价，让你购物无忧，而且，以上优惠可以叠加使用，力度空前巨大！\n", + "\n", + "只有4个小时，只有4个小时哦！快来抢购吧！\n", + "别再错过了，不然再等一年哦！/:066\n", + " \u0006
最近联系过
云栖木作
2025/12/10
亲主要在考虑什么呢?货物早拍下早发货的哦~而且咱们这边售后都是专业一对一的，不用担心货物收到没有保险哦~
最近联系过
勤朗旗舰店
2025/12/10
亲，您是在挑选款式呢，还是挑好款式准备下单呢 ? \n", + "/:^x^现在双十二活动， 喜欢就下手了哦/:-F
最近联系过
意百万家具品牌店
2025/12/08
双十二活动开始了亲。没有下单可以早点下单发货
最近联系过
锦盛实木家居
2025/12/07
/:$双十二福利来袭，亲爱的不要错过活动福利哦！！\n", + "\n", + "12月8日 0点——12月14日 24 点：\n", + "①.全店商品无需凑单，下单享官方立减12%！\n", + "②.更有店铺券满 200 减25，可与官方立减叠加使用，上不封顶哈！\n", + "③.下单即送限量精美台灯/抱枕哦！\n", + "④.活动期间购买，可优先安排发货，还能享受 30 天保价服务呢~ https://item.taobao.com/item.htm?id=838023940983 \u0006
最近联系过
玖传世家具
2025/12/07
✈️88VIP领券链接：https://pages-fast.m.taobao.com/wow/z/blackvip/v/home?x-ssr=true&disableNav \u0006
最近联系过
Gentle Township
t-2217567810350-0
2026-03-10 12:21:57 
平台交易号:3278844338603995979,您好，之前联系过您多次，仍未收到回复。03月12日前可以发货吗？如果近期无法发货，我们只能申请退款处理。
tb006113750:七愿
2026-03-10 12:22:23 
您好
tb006113750:七愿
2026-03-10 12:23:09 
可以呢 这两天会安排发出哦
表情
发送图片
发送视频
38 / 500
平台交易号:3278844338603995979,您好，之前联系过您多次，
产品服务能力由钉钉提供
Gentle Township
近三个月订单
没有数据
\n", + "
TaoWorld跨境供货平台，链接天猫淘宝海量货源，为跨境卖家、代采代购商提供全链路的解决方案。
\n", + " \n", + " \n", + "\n", + "
AliPrice
AliPrice
仅本次浏览关闭插件浮标
永久关闭此网站插件浮标
使用快捷键Ctrl+Shift+4快速唤起
或在设置中重新启用(永久关闭则不支持此网站快捷键唤起使用)
全网图搜
店雷达1688选品工具，快速查找热销、飙升、上新商品；新品早发现,好商品早知道！
去看看
'\"\"\"" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'平台交易号:3277680960636538788,您好，之前联系过您多次，仍未收到回复。03月11日前可以发货吗？如果近期无法发货，我们只能申请退款处理。'" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from lxml import etree\n", + "\n", + "def get_input_content(html):\n", + " tree = etree.HTML(html)\n", + " content = tree.xpath(\n", + " \"//div[contains(@class, 'ww_input--')]//pre[contains(@class, 'edit')]/text()\"\n", + " )\n", + " return \"\".join(content).strip() if content else \"\"\n", + "\n", + "get_input_content(web_page_attr)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "ename": "IndexError", + "evalue": "list index out of range", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mIndexError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[66]\u001b[39m\u001b[32m, line 58\u001b[39m\n\u001b[32m 52\u001b[39m results.append(result)\n\u001b[32m 53\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m {\n\u001b[32m 54\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mshopname\u001b[39m\u001b[33m\"\u001b[39m: shopname,\n\u001b[32m 55\u001b[39m \u001b[33m\"\u001b[39m\u001b[33mmessages\u001b[39m\u001b[33m\"\u001b[39m: results\n\u001b[32m 56\u001b[39m }\n\u001b[32m---> \u001b[39m\u001b[32m58\u001b[39m \u001b[43mget_latest_chats_records\u001b[49m\u001b[43m(\u001b[49m\u001b[43mweb_attr\u001b[49m\u001b[43m)\u001b[49m\n", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[66]\u001b[39m\u001b[32m, line 4\u001b[39m, in \u001b[36mget_latest_chats_records\u001b[39m\u001b[34m(html)\u001b[39m\n\u001b[32m 2\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"提取最新平台交易号及其后续聊天记录\"\"\"\u001b[39;00m\n\u001b[32m 3\u001b[39m tree = etree.HTML(html)\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m container = \u001b[43mtree\u001b[49m\u001b[43m.\u001b[49m\u001b[43mxpath\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43m//*[contains(@class, \u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mIMChat--ww_container--rcKMqZZ\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[33;43m)]\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[32m 5\u001b[39m shopname = container.xpath(\u001b[33m\"\u001b[39m\u001b[33m//*[contains(@class, \u001b[39m\u001b[33m'\u001b[39m\u001b[33mIMChat--ww_header--qyQJ4Lp\u001b[39m\u001b[33m'\u001b[39m\u001b[33m)]/text()\u001b[39m\u001b[33m\"\u001b[39m)[\u001b[32m0\u001b[39m].strip()\n\u001b[32m 6\u001b[39m message_item_lines = container.xpath(\u001b[33m\"\u001b[39m\u001b[33m//*[contains(@class, \u001b[39m\u001b[33m'\u001b[39m\u001b[33mmessage-item-lin\u001b[39m\u001b[33m'\u001b[39m\u001b[33m)]\u001b[39m\u001b[33m\"\u001b[39m)\n", + "\u001b[31mIndexError\u001b[39m: list index out of range" + ] + } + ], + "source": [ + "def get_latest_chats_records(html):\n", + " \"\"\"提取最新平台交易号及其后续聊天记录\"\"\"\n", + " tree = etree.HTML(html)\n", + " container = tree.xpath(\"//*[contains(@class, 'IMChat--ww_container--rcKMqZZ')]\")[0]\n", + " shopname = container.xpath(\"//*[contains(@class, 'IMChat--ww_header--qyQJ4Lp')]/text()\")[0].strip()\n", + " message_item_lines = container.xpath(\"//*[contains(@class, 'message-item-lin')]\")\n", + "\n", + " # 找到最新的平台交易号\n", + " latest_order_index = -1\n", + " latest_order_number = None\n", + "\n", + " for i, msg in enumerate(message_item_lines):\n", + " content_x = msg.xpath(\".//pre[contains(@class, 'edit')]/text()\")\n", + " content = ','.join(content_x).strip() if content_x else ''\n", + " if '平台交易号' in content:\n", + " latest_order_index = i\n", + " if latest_order_index == -1:\n", + " return {\n", + " \"shopname\": shopname,\n", + " \"messages\": []\n", + " }\n", + " \n", + " results = []\n", + " for i in range(latest_order_index, len(message_item_lines)):\n", + " msg = message_item_lines[i]\n", + " message_id = msg.get('id', '')\n", + " \n", + " # 昵称\n", + " nick_x = msg.xpath(\".//div[contains(@class, 'nick')]/text()\")\n", + " nick = nick_x[0].strip() if nick_x else ''\n", + " \n", + " # 时间\n", + " time_x = msg.xpath(\".//div[contains(@class, 'time')]/text()\")\n", + " time_str = time_x[0].strip() if time_x else ''\n", + " try:\n", + " time = datetime.strptime(time_str, \"%Y-%m-%d %H:%M:%S\") if time_str else None\n", + " except ValueError:\n", + " time = None\n", + "\n", + " # 内容或图片\n", + " content_x = msg.xpath(\".//pre[contains(@class, 'edit')]/text()\")\n", + " content = ','.join(content_x).strip() if content_x else ''\n", + " img_x = msg.xpath(\".//img[contains(@class, 'imui-msg-img')]/@src\")\n", + " if img_x:\n", + " content = img_x[0]\n", + " result = {\n", + " 'id': message_id,\n", + " 'nick': nick,\n", + " 'time': time.strftime(\"%Y-%m-%d %H:%M:%S\") if time else None,\n", + " 'content': content\n", + " }\n", + " results.append(result)\n", + " return {\n", + " \"shopname\": shopname,\n", + " \"messages\": results\n", + " }\n", + "\n", + "get_latest_chats_records(web_attr)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, "outputs": [], - "source": [] + "source": [ + "from lxml import etree\n", + "from datetime import datetime\n", + "import re\n", + "\n", + "\n", + "def get_latest_chats_records(html):\n", + " \"\"\"提取最近一次出现“平台交易号”的消息及其后续聊天记录（通用版）\"\"\"\n", + " tree = etree.HTML(html)\n", + " if tree is None:\n", + " return {\"shopname\": \"\", \"messages\": []}\n", + "\n", + " def first_or_default(lst, default=\"\"):\n", + " return lst[0].strip() if lst and isinstance(lst[0], str) else (lst[0] if lst else default)\n", + "\n", + " # 1) 找聊天主容器：优先找包含 header/body/input 的 ww_container--\n", + " containers = tree.xpath(\n", + " \"//div[contains(@class, 'ww_container--') \"\n", + " \"and .//div[contains(@class, 'ww_header--')] \"\n", + " \"and .//div[contains(@class, 'ww_body--')]]\"\n", + " )\n", + "\n", + " if containers:\n", + " container = containers[0]\n", + " else:\n", + " # 兜底：直接在全局查\n", + " container = tree\n", + "\n", + " # 2) 店铺名\n", + " shopname_x = container.xpath(\".//div[contains(@class, 'ww_header--')]/text()\")\n", + " shopname = first_or_default(shopname_x, \"\")\n", + "\n", + " # 3) 消息行\n", + " message_item_lines = container.xpath(\".//div[contains(@class, 'message-item-line')]\")\n", + "\n", + " if not message_item_lines:\n", + " return {\n", + " \"shopname\": shopname,\n", + " \"messages\": []\n", + " }\n", + "\n", + " # 4) 找最后一个包含“平台交易号”的消息\n", + " latest_order_index = -1\n", + " latest_order_number = None\n", + "\n", + " for i, msg in enumerate(message_item_lines):\n", + " text_nodes = msg.xpath(\".//pre[contains(@class, 'edit')]//text()\")\n", + " content = \"\".join(text_nodes).strip()\n", + "\n", + " if \"平台交易号\" in content:\n", + " latest_order_index = i\n", + "\n", + " # 顺手提取交易号\n", + " m = re.search(r\"平台交易号[:：]\\s*([0-9]+)\", content)\n", + " if m:\n", + " latest_order_number = m.group(1)\n", + "\n", + " if latest_order_index == -1:\n", + " return {\n", + " \"shopname\": shopname,\n", + " \"latest_order_number\": None,\n", + " \"messages\": []\n", + " }\n", + "\n", + " # 5) 收集从最新平台交易号开始的所有消息\n", + " results = []\n", + "\n", + " for msg in message_item_lines[latest_order_index:]:\n", + " message_id = msg.get(\"id\", \"\")\n", + "\n", + " # 昵称\n", + " nick_x = msg.xpath(\".//div[contains(@class, 'nick')]/text()\")\n", + " nick = first_or_default(nick_x, \"\")\n", + "\n", + " # 时间\n", + " time_x = msg.xpath(\".//div[contains(@class, 'time')]/text()\")\n", + " time_str = first_or_default(time_x, \"\")\n", + " formatted_time = None\n", + "\n", + " if time_str:\n", + " try:\n", + " dt = datetime.strptime(time_str, \"%Y-%m-%d %H:%M:%S\")\n", + " formatted_time = dt.strftime(\"%Y-%m-%d %H:%M:%S\")\n", + " except ValueError:\n", + " formatted_time = time_str\n", + "\n", + " # 文本内容\n", + " text_nodes = msg.xpath(\".//pre[contains(@class, 'edit')]//text()\")\n", + " content = \"\".join(text_nodes).strip()\n", + "\n", + " # 图片兜底：优先取消息区域图片\n", + " if not content:\n", + " img_x = msg.xpath(\".//img/@src\")\n", + " if img_x:\n", + " content = img_x[0]\n", + "\n", + " results.append({\n", + " \"id\": message_id,\n", + " \"nick\": nick,\n", + " \"time\": formatted_time,\n", + " \"content\": content\n", + " })\n", + "\n", + " return {\n", + " \"shopname\": shopname,\n", + " \"latest_order_number\": latest_order_number,\n", + " \"messages\": results\n", + " }\n", + "get_latest_chats_records(web_attr)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "<>:29: SyntaxWarning: invalid escape sequence '\\/'\n", + "<>:29: SyntaxWarning: invalid escape sequence '\\/'\n", + "C:\\Users\\joker\\AppData\\Local\\Temp\\ipykernel_96992\\2613722200.py:29: SyntaxWarning: invalid escape sequence '\\/'\n", + " !function(t){function e(a){if(n[a])return n[a].exports;var o=n[a]={exports:{},id:a,loaded:!1};return t[a].call(o.exports,o,o.exports,e),o.loaded=!0,o.exports}var n={};return e.m=t,e.c=n,e.p=\"\",e(0)}([function(t,e,n){t.exports=n(1)},function(t,e,n){\"use strict\";n(2).initGlobal(window),function(){var t=n(4);n(156)(t)}()},function(t,e,n){\"use strict\";var a,o=n(3),r=o.APLUS,i=o.APLUS_QUEUE,s=o.GOLDLOG,u=o.GOLDLOG_QUEUE,c=!1;try{\"undefined\"!=typeof window&&(a=window,c=!0)}catch(t){a={},c=!1}e.getContext=function(){return a},e.isWeb=function(){return\"undefined\"!=typeof window&&window},e.initGlobal=function(t){a=t?t:{v:1,aplus:{},aplus_queue:[]};var e,n;if(c)try{e=a.aplus||a.goldlog||(a.aplus={});var o=a.goldlog_queue||(a.goldlog_queue=[]);n=a.aplus_queue||(a.aplus_queue=[]),n=o.concat(n)}catch(t){}else e=a.aplus,n=a.aplus_queue;return a.aplus=a.goldlog=e,a.aplus_queue=a.goldlog_queue=n,a};var l=function(t){if(t===r||t===s){var e=a[r]||a[s];return e||(e=a[r]=a[s]={}),e}var n=u,o=i;if(t===o||t===n){var c=a[o]||a[n];return c||(c=a[o]=a[n]=[]),c}};e.getGlobalValue=l,e.setGlobalValue=function(t,e){a[t]=e};var p=function(t){var e;try{var n=l(r);e=n[t]}catch(t){e=\"\"}finally{return e}};e.getGoldlogVal=p;var f=function(t,e){var n=!1;try{var a=l(r);t&&(a[t]=e,n=!0)}catch(t){n=!1}finally{return n}};e.setGoldlogVal=f,e.getClientInfo=function(){return p(\"_aplus_client\")||{}}},function(t,e){var n=\"aplus\",a=\"goldlog\",o=n+\"_queue\",r=a+\"_queue\",i=\"mw_change\",s=\"MetaInfo\",u=\"append\"+s,c=\"set\"+s,l=\"http\",p=\"_pubsub\",f=\"other\",g=\"2101\",d=\"2201\",m=\"2202\",_=\"19999\",h=\"1023\",v=\"1010\",b=3e4,y=18e5,S=\"ekvs\",A=1e4,E=1,T=1,I=3e3,P=\"$$_page_start\",w=\"$$_page_end\",C=\"$$_app_start\",M=\"$$_app_end\",x=\"aplus_user_profile\",O=\"imprint\",L=n+\"-idtype\",U=n+\"-jsbridge-only\",k=n+\"-page-config\",R=n+\"-skip-apv-rules\",N=n+\"-rhost-v\",G=n+\"-rhost-g\",D=n+\"-forward-domain\",V=n+\"-forward-event-filter\",j=\"autoGetOpenid\",F=n+\"-forward-appkey\";t.exports={PAGE_ENTER:\"PAGE_ENTER\",ETAG_EVENT_NAME:\"etag\",CURRENT_PAGE_CONFIG:\"CURRENT_PAGE_CONFIG\",_ANONY_ID:\"_anony_id\",_DEV_ID:\"_dev_id\",_USER_ID:\"_user_id\",_CNA:\"cna\",DEFAULT_CODE:f,OTHER:_,EVENT_MAP:{2101:\"click\",2201:\"exposure\",2202:\"exposure\",19999:f,1023:\"app_show\",1010:\"app_hide_or_unload\"},EVENT_ID_MAP:{EXP:d,IMPEXP:m,CLK:g,OTHER:_,SHOW:h,H_OR_U:v},APLUS:n,APLUS_CONFIG:\"APLUS_CONFIG\",GOLDLOG:a,UNSUBSCRIBE:n+\".\"+n+p+\".unsubscribe\",SUBSCRIBE:n+\".\"+n+p+\".subscribe\",PUBLISH:n+\".\"+n+p+\".publish\",CACHE_PUBS:n+\".\"+n+p+\".cachePubs\",APLUS_UNIVERSAL:n+\"_universal\",APLUS_QUEUE:o,GOLDLOG_QUEUE:r,COMPLETE:\"complete\",PV_CODE:\"2001\",EXP_CODE:d,CLK_CODE:g,OTHER_CODE:_,CLK:\"CLK\",EXP:\"EXP\",SPM_CNT:\"spm-cnt\",SPM_URL:\"spm-url\",SPM_PRE:\"spm-pre\",MW_CHANGE_PV:i+\"_pv\",MW_CHANGE_HJLJ:i+\"_hjlj\",HTTP:l+\":\",HTTPS:\"https:\",APPEND_META_INFO:u,SET_META_INFO:c,APLUS_APPEND_META_INFO:n+\".\"+u,APLUS_SET_META_INFO:n+\".\"+c,PVID:\"pvid\",openAPIs:[\"send\",\"enter\",\"sendPV\",\"record\",\"combineRecord\",\"recordUdata\",\"requestVTConfig\",\"requestRemoteConfig\",\"setPageSPM\",\"setMetaInfo\",\"appendMetaInfo\",\"updatePageProperties\",\"updateNextPageProperties\",\"updatePageUtparam\",\"updateNextPageUtparam\",\"pageAppear\",\"pageDisappear\",\"pageDisAppear\",\"skipPage\",\"updatePageName\",\"updatePageUrl\",\"requestPageAllProperties\",\"updateSessionProperties\",\"getPageSpmUrl\",\"getPageSpmPre\",\"updateNextPageUtparamCnt\",\"setPageName\",\"getElementSPM\",\"getAutoElementSPM\",\"setUserProfile\",\"getUserProfile\",\"getCna\"],SESSION_INTERVAL:b,SESSION_PAUSE_TIME:\"session_pause_time\",IMPRINT:\"imprint\",CURRENT_SESSION:\"current_session\",MAX_EVENTID_LENGTH:128,MAX_PROPERTY_KEY_LENGTH:256,MAX_PROPERTY_KEYS_COUNT:100,FAILED_REQUESTS:\"failed_requests\",REQUESTS:\"requests\",SHARES:\"shares\",APLUS_SSRC:\"_aplus_ssrc\",ARMS_TRACE:\"_arms_trace\",EKVS:S,EVENT_MAX_COUNT:A,MEMORY_MAX_COUNT:E,MAX_QUEUE_COUNT:T,EVENT_SEND_DEFAULT_INTERVAL:I,PAGE_START:P,PAGE_END:w,APP_START:C,APP_END:M,USER_PROFILE_KEY:x,SHARE_CACHE_INTERVAL:y,IMPRINT:O,ID_TYPE:L,GLOBAL_PROPERTY:\"globalproperty\",JSBRIDGE_ONLY:U,PAGE_CONFIG:k,APLUS_SKIP_APV_RULES:R,APLUS_PV_DOMAIN:N,APLUS_EKV_DOMAIN:G,APLUS_FORWARD_DOMAIN:D,APLUS_IMPRINT_VERSION:\"APLUS_IMPRINT_VERSION\",APLUS_REMOTE_CONFIG:\"APLUS_REMOTE_CONFIG\",RANK:\"ekv_rank\",WEB_EVENT_SUFFIX:\"/web_logs\",WEB_PC_PV_SUFFIX:\"v.gif\",WEB_WAP_PV_SUFFIX:\"m.gif\",PAGE_LEAVE:\"$$_page_leave\",APLUS_DOM_CHANGE:\"APLUS_DOM_CHANGE\",APLUS_PAGE_CHANGE:\"APLUS_PAGE_CHANGE\",PERFORMANCE_WARING:\"$$_perf_warning\",START_ID:\"START_ID\",AUTO_GET_OPENID:j,APLUS_LATEAST_UTM:\"APLUS_LATEAST_UTM\",APLUS_FORWARD_EVENT_FILTER:V,APLUS_FORWARD_APPKEY:F,APLUS_RHOST_V:n+\"-rhost-v\",APLUS_CPVDATA:n+\"-cpvdata\",APLUS_EXDATA:n+\"-exdata\",APLUS_EXINFO:n+\"-exinfo\",APLUS_LOG_PIPE:n+\"-log-pipe\",APLUS_TRACK_COMBINE:n+\"-track-combine\",APLUS_COOKIES:n+\"-cookies\",APLUS_CODELESS_TRACK_CONFIG:\"_\"+n+\"_codeless_track_config\",APLUS_AUTO_CLK:n+\"-auto-clk\",APLUS_AUTO_EXP:n+\"-auto-exp\",APLUS_AUTO_PV:n+\"-auto-pv\",APLUS_BRIDGE_NAME:n+\"-bridge-name\",APLUS_MINI_REQUEST_TIMEOUT:n+\"-request-timeout\",APLUS_VT_CONFIG_URL:n+\"-vt-cfg-url\",APLUS_EXPOSURE_EVENT_CAN_REPEAT:n+\"-exposure-event-can-repeat\",APLUS_IGNORE_LIFECYCLES:n+\"-ignore-lifecycles\",APLUS_TRACK_DEBUG_ID:n+\"-track-debug-id\",APLUS_SINGLE_RECORD_LOGKEYS:n+\"-single-record-logkeys\",APLUS_GOKEY_ISOLATE:n+\"-gokey-isolate\",APLUS_AUTOTRACK_ENABLED:n+\"-autotrack-enabled\",APLUS_AUTOTRACK_ENABLED_REMOTE:n+\"-autotrack-enabled-remote\",APLUS_AUTOTRACK_CONFIG:n+\"-autotrack-config\",APLUS_AUTO_TRACK_CONFIG_IMPORT:n+\"-auto-track-config-import\",APLUS_AUTOTRACK_CONFIG_REMOTE:n+\"-autotrack-config-remote\",APLUS_EVENT_LIMITRATES:n+\"-event-limitrates\",APLUS_DISABLE_AUTOEVENT:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOEVENT_REMOTE:n+\"-disable-autoevent\",APLUS_DISABLE_AUTOPV:n+\"-disable-apv\",APLUS_DISABLE_AUTOPV_REMOTE:n+\"-disable-apv-remote\",APLUS_DEVICE_ENABLE:n+\"-device-enable\",APLUS_USER_PROFILE:n+\"-user-profile\",APLUS_CNA_ENABLE:n+\"-cna-enable\",APLUS_CNA_MODE:n+\"-cna-mode\",APLUS_ETAG_TIMEOUT:n+\"-etag-timeout\",APLUS_SPA_TYPE:n+\"-spa-type\",APLUS_MONITOR_ENABLE:n+\"-monitor-enable\",APLUS_OBSERVATIONS:\"_\"+n+\"_observations\",APLUS_REPORT_RATE:n+\"-report-rate\",APLUS_CNA_MONITOR:n+\"-cna-monitor\",APLUS_MMSTAT_TIMEOUT:n+\"-mmstat-timeout\",APLUS_REMOTE_CONTROL:n+\"-remote-control\",APLUS_CNA_STABILITY:n+\"-cna-stability\",APLUS_AUTO_PID:n+\"-auto-pid\"}},function(t,e,n){t.exports={metaInfo:{\"aplus-ifr-pv\":\"0\",\"aplus-rhost-v\":\"log.mmstat.com\",\"aplus-rhost-g\":\"gm.mmstat.com\",\"aplus-channel\":\"WS\",appId:\"60506758\",sdkId:\"customSdkId\",\"aplus-cpvdata\":{},\"aplus-exdata\":{},\"aplus-globaldata\":{},\"aplus-mmstat-timeout\":\"10000\",\"aplus-toUT\":\"auto\",\"aplus-track-combine\":\"on\",\"aplus-vt-auto-userfn-enable\":\"on\",\"aplus-cna-enable\":\"on\",\"aplus-cna-mode\":\"CK\",\"aplus-auto-track-config-import\":\"off\",\"aplus-form-track\":\"off\",\"aplus-gokey-isolate\":\"on\",\"aplus-only-update-page-properties\":\"off\",\"aplus-spm-from-url\":\"on\",\"aplus-user-profile\":{},\"aplus-report-rate\":{},\"aplus-single-record-logkeys\":[],\"aplus-cross-day-auto-pv\":\"off\",\"aplus-cna-monitor\":\"off\",\"aplus-cna-stability\":\"off\",\"aplus-auto-pid\":\"on\",\"aplus-monitor-enable\":\"off\",\"aplus-remote-control\":\"on\"},globalConfig:{isAli:!0,APLUS_QUEUE:\"aplus_queue\",ETAG_STORAGE_KEY:\"__ETAG__CNA__ID__\",script_name:\"aplus.js\",NAME_STORAGE_KEYS:{REFERRER:\"wm_referrer\",REFERRER_PV_ID:\"refer_pv_id\",LOST_PV_PAGE_DURATION:\"lost_pv_page_duration\",LOST_PV_PAGE_SPMAB:\"lost_pv_page_spmab\",LOST_PV_PAGE:\"lost_pv_page\",LOST_PV_PAGE_MSG:\"lost_pv_page_msg\"},lver:\"1.13.27\"},plugins:[{name:\"aplus_body_ready\",path:n(5)},{name:\"pubsub\",path:n(6)},{name:\"aplus_client\",path:n(11)},{name:\"aplus_meta_inject\",path:n(15)},{name:\"aplus_remote_control\",path:n(49)},{name:\"aplus_observer\",path:n(51)},{name:\"aplus_ac\",path:n(53)},{name:\"aplus_ae\",path:n(72)},{name:\"name_storage\",path:n(80)},{name:\"record_lost_pv\",path:n(83),config:{lostPvRecordRatio:.01}},{name:\"aplus_monitor\",path:n(85),config:{obsoleteInterRecordRatio:\"0.01\",jsErrorRecordRatio:\"0.01\",browserSupportRatio:\"0.01\"}},{name:\"aplus_web_http_ali\",path:n(92)},{name:\"aplus_log_inject\",path:n(95),deps:[\"aplus_meta_inject\"],config:{plugins:{pv:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"when_to_sendpv\",path:n(101),config:{aplusWaiting:\"\"}},{name:\"where_to_send\",path:n(102),config:{method:\"GET\",url:\"//log.mmstat.com/v.gif\"}},{name:\"what_to_send\",path:n(103),config:{pvdataToUt:{}}},{name:\"cookie_data\",path:n(104)},{name:\"what_to_sendpv_userdata\",path:n(105),deps:[\"what_to_send\"]},{name:\"what_to_sendpv_userdata_web\",path:n(106),deps:[\"what_to_send\",\"what_to_sendpv_userdata\"]},{name:\"what_to_sendpv_ut2\",path:n(108),deps:[\"what_to_send\"]},{name:\"can_to_sendpv\",path:n(109),config:{flag:\"NO\"}},{name:\"after_pv\",path:n(114)}],hjlj:[{name:\"etag\",path:n(96)},{name:\"pha_trackinfo\",path:n(100)},{name:\"where_to_send\",path:n(102),deps:[],config:{method:\"GET\",url:\"//gm.mmstat.com/\",ac_atpanel:\"//ac.mmstat.com/\",tblogUrl:\"//log.mmstat.com/\"}},{name:\"what_to_send\",path:n(103),deps:[]},{name:\"cookie_data\",path:n(104)},{name:\"what_to_hjlj_userdata\",path:n(115),deps:[\"what_to_send\"]},{name:\"what_to_hjlj_userdata_web\",path:n(116),deps:[\"what_to_send\",\"what_to_hjlj_userdata\"]},{name:\"what_to_hjlj_ut2\",path:n(117),deps:[\"what_to_send\"]}]}}},{name:\"aplus_spm_inject\",path:n(118)},{name:\"aplus_api\",path:n(132)},{name:\"meta_queue\",path:n(141)},{name:\"etag\",path:n(96)},{name:\"etag_web_sync\",path:n(143)},{name:\"aplus_queue\",path:n(144)},{name:\"hot_loader\",path:n(145),config:{urlRules:[{id:\"aplus_webvt_messager\",rule:\"aplus_webvt_messager\",cacheType:\"sessionStorage\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_webvt_messager.js\",\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_track_debug_id\",cacheType:\"sessionStorage\",rule:\"aplus_track_debug_id\",cdnPath:[\"https://d.alicdn.com/alilog/mlog/aplus_track_debug.js\"]},{id:\"aplus_auto_register\",rule:\"aplus_auto_register=true\",cacheType:\"sessionStorage\",allowIframeLoad:!0,cdnPath:[\"https://d.alicdn.com/alilog/aplus/1.13.9/plugin/aplus_auto_register.js\"]},{id:\"aplus_heat\",rule:\"aplus_heat=true\",cacheType:\"cookie\",allowIframeLoad:!0,cdnPath:[\"https://o.alicdn.com/alilog/aplus-visual-client/heat.js\"]}]}},{name:\"hot_sufei_pc\",path:n(146)},{name:\"aplus_apv\",path:n(147),deps:[\"aplus_log_inject\",\"aplus_api\"]},{name:\"aplus_form_track\",path:n(150)}]}},function(t,e){\"use strict\";t.exports=function(){return{run:function(t,e){var n=setInterval(function(){document.getElementsByTagName(\"body\").length&&(clearInterval(n),n=null,e())},50);return setTimeout(function(){n&&clearInterval(n)},1e3),1e3}}}},function(t,e,n){var a=n(7),o=n(2);t.exports=function(){return{run:function(){var t=o.getGlobalValue(\"aplus\");t.aplus_pubsub||(t.aplus_pubsub=a.create())}}}},function(t,e,n){var a=n(8);t.exports=a.extend({subscribeOnce:function(t,e){this.callable(e);var n,a=this;return this.subscribe.call(this,t,n=function(){a.unsubscribe.call(a,t,n);var o=Array.prototype.slice.call(arguments);e.apply(a,o)}),this}})},function(t,e,n){\"use strict\";var a=n(9),o=n(10),r=function(t){for(var e=t.length,n=new Array(e-1),a=1;a0){for(var a=0;a0)for(var i=0;i\",A=u&&u.createElement(\"div\"),E=[],T={isAliapp:!1,webkit:void 0,edge:void 0,trident:void 0,gecko:void 0,presto:void 0,chrome:void 0,safari:void 0,firefox:void 0,ie:void 0,ieMode:void 0,opera:void 0,mobile:void 0,core:void 0,shell:void 0,phantomjs:void 0,os:void 0,ipad:void 0,iphone:void 0,ipod:void 0,ios:void 0,android:void 0,nodejs:void 0,extraName:void 0,extraVersion:void 0};if(A&&A.getElementsByTagName&&(A.innerHTML=S.replace(y,\"\"),E=A.getElementsByTagName(\"s\")),E.length>0){for(d(t,T),i=b[0],s=b[1];i<=s;i++)if(A.innerHTML=S.replace(y,i),E.length>0){T[v=\"ie\"]=i;break}!T.ie&&(r=m(t))&&(T[v=\"ie\"]=r)}else((o=t.match(/AppleWebKit\\/*\\s*([\\d.]*)/i))||(o=t.match(/Safari\\/([\\d.]*)/)))&&o[1]?(T[h=\"webkit\"]=g(o[1]),(o=t.match(/OPR\\/(\\d+\\.\\d+)/))&&o[1]?T[v=\"opera\"]=g(o[1]):(o=t.match(/Chrome\\/([\\d.]*)/))&&o[1]?T[v=\"chrome\"]=g(o[1]):(o=t.match(/\\/([\\d.]*) Safari/))&&o[1]?T[v=\"safari\"]=g(o[1]):T.safari=T.webkit,(o=t.match(/Edge\\/([\\d.]*)/))&&o[1]&&(h=v=\"edge\",T[h]=g(o[1])),/ Mobile\\//.test(t)&&t.match(/iPad|iPod|iPhone/)?(T.mobile=\"apple\",o=t.match(/OS ([^\\s]*)/),o&&o[1]&&(T.ios=g(o[1].replace(\"_\",\".\"))),a=\"ios\",o=t.match(/iPad|iPod|iPhone/),o&&o[0]&&(T[o[0].toLowerCase()]=T.ios)):/ Android/i.test(t)?(/Mobile/.test(t)&&(a=T.mobile=\"android\"),o=t.match(/Android ([^\\s]*);/),o&&o[1]&&(T.android=g(o[1]))):(o=t.match(/NokiaN[^\\/]*|Android \\d\\.\\d|webOS\\/\\d\\.\\d/))&&(T.mobile=o[0].toLowerCase()),(o=t.match(/PhantomJS\\/([^\\s]*)/))&&o[1]&&(T.phantomjs=g(o[1]))):(o=t.match(/Presto\\/([\\d.]*)/))&&o[1]?(T[h=\"presto\"]=g(o[1]),(o=t.match(/Opera\\/([\\d.]*)/))&&o[1]&&(T[v=\"opera\"]=g(o[1]),(o=t.match(/Opera\\/.* Version\\/([\\d.]*)/))&&o[1]&&(T[v]=g(o[1])),(o=t.match(/Opera Mini[^;]*/))&&o?T.mobile=o[0].toLowerCase():(o=t.match(/Opera Mobi[^;]*/))&&o&&(T.mobile=o[0]))):(r=m(t))?(T[v=\"ie\"]=r,d(t,T)):(o=t.match(/Gecko/))&&(T[h=\"gecko\"]=.1,(o=t.match(/rv:([\\d.]*)/))&&o[1]&&(T[h]=g(o[1]),/Mobile|Tablet/.test(t)&&(T.mobile=\"firefox\")),(o=t.match(/Firefox\\/([\\d.]*)/))&&o[1]&&(T[v=\"firefox\"]=g(o[1])));if(!T[v]){var I=t.match(/Ali\\w+\\(\\w+\\/(\\d+\\.)+\\d+\\)/);if(I){T.isAliapp=!0;var P=I[0],w=\"\",C=\"\",M=P.match(/(\\d+\\.)+\\d+/);M&&(w=M[0],C=P.replace(\"/\"+w,\"\").replace(/\\(|\\)/g,\"\")),T[v=C]=w}}a||(a=e());var x,O,L;if(!n(\"type\",\"application/vnd.chromium.remoting-viewer\")){x=\"scoped\"in u.createElement(\"style\"),L=\"v8Locale\"in c;try{O=c.external||void 0}catch(t){}if(o=t.match(/360SE/))l=\"360\";else if((o=t.match(/SE\\s([\\d.]*)/))||O&&\"SEVersion\"in O)l=\"sougou\",f=g(o[1])||.1;else if((o=t.match(/Maxthon(?:\\/)+([\\d.]*)/))&&O){l=\"maxthon\";try{f=g(O.max_version||o[1])}catch(t){f=.1}}else x&&L?l=\"360se\":x||L||!/Gecko\\)\\s+Chrome/.test(p)||T.opera||T.edge||(l=\"360ee\")}(o=t.match(/TencentTraveler\\s([\\d.]*)|QQBrowser\\/([\\d.]*)/))?(l=\"tt\",f=g(o[2])||.1):(o=t.match(/LBBROWSER/))||O&&\"LiebaoGetVersion\"in O?l=\"liebao\":(o=t.match(/TheWorld/))?(l=\"theworld\",f=3):(o=t.match(/TaoBrowser\\/([\\d.]*)/))?(l=\"taobao\",f=g(o[1])||.1):(o=t.match(/UCBrowser\\/([\\d.]*)/))&&(l=\"uc\",f=g(o[1])||.1),T.os=a,T.core=T.core||h,T.shell=v,T.ieMode=T.ie&&u.documentMode||T.ie,T.extraName=l,T.extraVersion=f;var U=c.screen.width,k=c.screen.height;return T.resolution=U+\"x\"+k,T}function o(t){function e(t){return Object.prototype.toString.call(t)}function n(t,n,a){if(\"[object Function]\"==e(n)&&(n=n(a)),!n)return null;var o={name:t,version:\"\"},r=e(n);if(n===!0)return o;if(\"[object String]\"===r){if(a.indexOf(n)!==-1)return o}else if(n.exec){var i=n.exec(a);if(i)return i.length>=2&&i[1]?o.version=i[1].replace(/_/g,\".\"):o.version=\"\",o}}var a={name:\"other\",version:\"\"};t=(t||\"\").toLowerCase();for(var o=[[\"nokia\",function(t){return t.indexOf(\"nokia \")!==-1?/\\bnokia ([0-9]+)?/:/\\bnokia([a-z0-9]+)?/}],[\"samsung\",function(t){return t.indexOf(\"samsung\")!==-1?/\\bsamsung(?:[ \\-](?:sgh|gt|sm))?-([a-z0-9]+)/:/\\b(?:sgh|sch|gt|sm)-([a-z0-9]+)/}],[\"wp\",function(t){return t.indexOf(\"windows phone \")!==-1||t.indexOf(\"xblwp\")!==-1||t.indexOf(\"zunewp\")!==-1||t.indexOf(\"windows ce\")!==-1}],[\"pc\",\"windows\"],[\"ipad\",\"ipad\"],[\"ipod\",\"ipod\"],[\"iphone\",/\\biphone\\b|\\biph(\\d)/],[\"mac\",\"macintosh\"],[\"mi\",/\\bmi[ \\-]?([a-z0-9 ]+(?= build|\\)))/],[\"hongmi\",/\\bhm[ \\-]?([a-z0-9]+)/],[\"aliyun\",/\\baliyunos\\b(?:[\\-](\\d+))?/],[\"meizu\",function(t){return t.indexOf(\"meizu\")>=0?/\\bmeizu[\\/ ]([a-z0-9]+)\\b/:/\\bm([0-9x]{1,3})\\b/}],[\"nexus\",/\\bnexus ([0-9s.]+)/],[\"huawei\",function(t){var e=/\\bmediapad (.+?)(?= build\\/huaweimediapad\\b)/;return t.indexOf(\"huawei-huawei\")!==-1?/\\bhuawei\\-huawei\\-([a-z0-9\\-]+)/:e.test(t)?e:/\\bhuawei[ _\\-]?([a-z0-9]+)/}],[\"lenovo\",function(t){return t.indexOf(\"lenovo-lenovo\")!==-1?/\\blenovo\\-lenovo[ \\-]([a-z0-9]+)/:/\\blenovo[ \\-]?([a-z0-9]+)/}],[\"zte\",function(t){return/\\bzte\\-[tu]/.test(t)?/\\bzte-[tu][ _\\-]?([a-su-z0-9\\+]+)/:/\\bzte[ _\\-]?([a-su-z0-9\\+]+)/}],[\"vivo\",/\\bvivo(?: ([a-z0-9]+))?/],[\"htc\",function(t){return/\\bhtc[a-z0-9 _\\-]+(?= build\\b)/.test(t)?/\\bhtc[ _\\-]?([a-z0-9 ]+(?= build))/:/\\bhtc[ _\\-]?([a-z0-9 ]+)/}],[\"oppo\",/\\boppo[_]([a-z0-9]+)/],[\"konka\",/\\bkonka[_\\-]([a-z0-9]+)/],[\"sonyericsson\",/\\bmt([a-z0-9]+)/],[\"coolpad\",/\\bcoolpad[_ ]?([a-z0-9]+)/],[\"lg\",/\\blg[\\-]([a-z0-9]+)/],[\"android\",/\\bandroid\\b|\\badr\\b/],[\"blackberry\",function(t){return t.indexOf(\"blackberry\")>=0?/\\bblackberry\\s?(\\d+)/:\"bb10\"}]],r=0;rc.length?u:c,a=decodeURIComponent(a)}else n=e.match(o),a=n&&2===n.length?n[1]:\"\"}catch(t){}finally{return a}}function o(t,e){var n,a,o,r,i,s=e||location.href,c=\"&\",l=[];return u(t,function(t,e){new RegExp(t+\"=\").test(s)||l.push(t+\"=\"+e)}),0===l.length?s:(s.indexOf(\"#\")!==-1&&(o=s.split(\"#\"),s=o.shift(),a=o.join(\"#\")),r=s.split(\"?\"),i=r.length-1,o=r[0].split(\"//\"),o=o[o.length-1].split(\"/\"),i>0&&(n=r.pop(),s=r.join(\"?\")),n&&i>1&&n.indexOf(\"&\")==-1&&n.indexOf(\"%\")!==-1&&(c=\"%26\"),s=s+\"?\"+l.join(\"&\")+(n?c+n:\"\")+(a?\"#\"+a:\"\"))}function r(t){var e=s(location.hash)+\"\";c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"hashchange\",function(){e!==s(location.hash)&&(e=s(location.hash)+\"\",t&&\"function\"==typeof t&&t(e,p))}])}function i(t){function e(e){var a=\"\";if(e){a=e&&e.arguments&&e.arguments.length>2&&e.arguments[2];var o=/^http|https/.test(a)?a:location.protocol+\"//\"+location.host+a;location.href!==o&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0)}else a=location.pathname+location.search,a!==n&&setTimeout(function(){t&&\"function\"==typeof t&&t(a,f)},0);n=a}var n=location.pathname+location.search;if(history.pushState&&window.addEventListener){c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"pushState\",function(t){e(t)}]),c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"popstate\",function(){e()}]);var a=l.getMetaCnt(\"aplus-track-replacestate\")||aplus.getMetaInfo&&aplus.getMetaInfo(\"aplus-track-replacestate\");a&&c.pushIntoGoldlogQueue(\"aplus.on\",[window,\"replaceState\",function(t){e(t)}])}}function s(t){var e=\"\";return t&&(e=t.indexOf(\"?\")!=-1?t.split(\"?\")[0]:t),e}var u=n(18);e.addParamsIntoUrl=o,e.getParamFromUrl=a,e.getSPMFromUrl=function(t){return a(\"spm\",t)},e.getQueryFromUrl=function(){function t(t){for(var e=decodeURIComponent(t),n=e.indexOf(\"?\")+1,a=e.substring(n),o=Object.create(null),r=a.split(\"&\"),i=0;i-1)try{S[e]=JSON.parse(n)}catch(t){g.logger({msg:\"the content of meta<\"+e+\"> is invalid json string\"})}if(e===A)try{u=S[e]=JSON.parse(h.getMetaCnt(e))}catch(t){}}}),d(E,function(t){S[t]=h.getMetaCnt(t)}),S.spm_protocol=o(t),u&&(S=p.assign(S,u));var e,n,i=[\"aplus-rate-ahot\"],s=i.length;for(e=0;e\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " TaoWorld跨境供货平台\n", + " \n", + " \n", + " \n", + "\n", + "\n", + "\n", + " \n", + " \n", + " \n", + "\n", + " \n", + " \n", + " \n", + "\n", + "\n", + " \n", + "
  • 联系人
  • 商品
  • 聊天记录
\"暂无数据\"
请输入搜索词
012345678901234567890123456789012345678901234567890123456789
角落小屋家具
13:17
9821706252365 补发三合一固定层板1个，444奶咖颗粒，428*405*16
3
最近联系过
九选家具
13:17
明天才能发
4
最近联系过
鹊禧生活家居馆
13:16
安排发货了
2
最近联系过
是是但但
下拉或点此加载更多
t-2217567810350-0
2025-09-12 18:51:10 
111
t-2217567810350-0
2025-09-12 18:51:22 
78778
t-2217567810350-0
2025-09-12 18:51:34 
87878
t-2217567810350-0
2025-09-13 10:51:24 
jkl
t-2217567810350-0
2025-09-15 09:15:41 
123
t-2217567810350-0
2025-09-15 09:21:30 
444
t-2217567810350-0
2025-09-15 13:08:21 
123
t-2217567810350-0
2025-09-15 13:51:53 
666
t-2217567810350-0
2025-09-15 13:52:55 
9999
t-2217567810350-0
2025-09-16 14:24:44 
666
t-2217567810350-0
2025-09-17 16:16:03 
得到的
t-2217567810350-0
2025-09-18 10:06:38 
早上好
t-2217567810350-0
2025-09-18 13:59:21 
zsh
sowhat_cyx:冼
2025-09-18 14:38:12 
151551
t-2217567810350-0
2025-09-19 09:11:44 
456
t-2217567810350-0
2025-09-19 13:34:18 
八嘎八嘎
t-2217567810350-0
2025-09-23 09:52:50 
早上好
t-2217567810350-0
2025-09-26 10:39:37 
134
t-2217567810350-0
2025-09-29 10:58:59
t-2217567810350-0
2025-09-29 10:59:08
表情
发送图片
发送视频
0 / 500
请输入消息，按Enter键 或 点击发送按钮发送
产品服务能力由钉钉提供
是是但但
近三个月订单
没有数据
\n",
+    "  
TaoWorld跨境供货平台，链接天猫淘宝海量货源，为跨境卖家、代采代购商提供全链路的解决方案。
\n",
+    "  \n",
+    "  \n",
+    "\n",
+    "
AliPrice
AliPrice
仅本次浏览关闭插件浮标
永久关闭此网站插件浮标
使用快捷键Ctrl+Shift+4快速唤起
或在设置中重新启用(永久关闭则不支持此网站快捷键唤起使用)
全网图搜
 店雷达1688选品工具，快速查找热销、飙升、上新商品；新品早发现,好商品早知道！ 
去看看
'\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 103,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "msg_list = {'shopname': '简梵家居90', 'latest_order_number': '3278852331057995979', 'messages': [{'id': '3998708106340.PNM', 'nick': 't-2217567810350-0', 'time': '2026-03-10 14:55:42', 'content': '平台交易号:3278852331057995979,您好，之前联系过您多次，仍未收到回复。03月12日前可以发货吗？如果近期无法发货，我们只能申请退款处理。'}, {'id': '4008743628843.PNM', 'nick': 'tb809265783186', 'time': '2026-03-10 15:28:22', 'content': '可以'}]}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 104,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'上传成功'"
+      ]
+     },
+     "execution_count": 104,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def upload_msg_to_cpmaso(msg_list):\n",
+    "    url = \"http://192.168.100.44/rpaapi/upload_system_chat_msg\"\n",
+    "    payload = {\n",
+    "        \"messages\": msg_list[\"messages\"]\n",
+    "    }\n",
+    "\n",
+    "    headers = {\n",
+    "        \"Content-Type\": \"application/json\"\n",
+    "    }\n",
+    "\n",
+    "    try:\n",
+    "        resp = requests.post(url, headers=headers, data=json.dumps(payload))\n",
+    "        if resp.status_code == 200:\n",
+    "            return \"上传成功\"\n",
+    "        else:\n",
+    "            return(f\"上传失败: {resp.status_code} - {resp.text}\")\n",
+    "    except Exception as e:\n",
+    "        print(f\"请求异常: {e}\")\n",
+    "upload_msg_to_cpmaso(msg_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 105,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'success': False, 'msg': '影刀调用get_next_session_task_id失败', 'task_id': None}"
+      ]
+     },
+     "execution_count": 105,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def get_next_session_task_id(platform, task_type):\n",
+    "    \"\"\"获得redis内对应平台和上游任务的对话任务id\n",
+    "    Example response:\n",
+    "        {\"key\": queue_name, \"task_id\": item}, 200\n",
+    "        {\"message\": \"没有可用的会话任务\"}, 404\n",
+    "        {\"message\": \"获取下一个会话任务ID失败\"}, 500\n",
+    "\n",
+    "    \"\"\"\n",
+    "    url = f\"http://192.168.100.44/rpaapi/get_next_session_task_id/{platform}/{task_type}\"\n",
+    "    try:\n",
+    "        response = requests.get(url, timeout=10)\n",
+    "        res = response.json()\n",
+    "        if response.status_code == 200:\n",
+    "            return {\"success\": True, \"msg\": f\"成功获得会话任务id{res['task_id']}\", \"task_id\": res['task_id']}\n",
+    "        elif response.status_code == 404:\n",
+    "            return {\"success\": False, \"msg\": res['message'], \"task_id\": None}\n",
+    "        elif response.status_code == 500:\n",
+    "            return {\"success\": False, \"msg\": \"服务器获取下一个会话任务ID失败\", \"task_id\": None}\n",
+    "    except Exception as e:\n",
+    "        return {\"success\": False, \"msg\": \"影刀调用get_next_session_task_id失败\", \"task_id\": None}\n",
+    "    \n",
+    "get_next_session_task_id(\"taotian\", \"follow_up\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'sessid=bd8e2a3ea362030b9c55ac71e4e7ac6f'"
+      ]
+     },
+     "execution_count": 74,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from login_for_cookie import Vc\n",
+    "Vc(\"robot1\",\"a123456\")"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "funny",
    "language": "python",
    "name": "python3"
   },
@@ -1525,7 +5609,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.12.12"
   },
   "orig_nbformat": 4
  },
diff --git a/订单拦截总数据.py b/订单拦截总数据.py
index a7ffec5..839ffea 100644
--- a/订单拦截总数据.py
+++ b/订单拦截总数据.py
@@ -28,7 +28,15 @@ def get_package_real_vol_by_api(packages_id):
         #     package_width = resp[0][1]
         #     package_hight = resp[0][2]
         # 拦截
-        url = f'https://cp.maso.hk/index.php?main=biphp&act=package_fund&key=W6BOYJ7BH27YCGRFCA0LWBVKMU1KRU5Q&package={package_id}'
+        url = f'https://cp.baycheer.com/index.php?main=biphp&act=package_fund&key=W6BOYJ7BH27YCGRFCA0LWBVKMU1KRU5Q&package={package_id}'
+
+
+
+
+
+
+
+        
         resp = requests.get(url).json()
         if resp['code'] == "0":
             weight = int(float(resp['data'][0]['weight'])*1000)
diff --git a/跟单测试源文件.xlsx b/跟单测试源文件.xlsx
new file mode 100644
index 0000000..c085e1c
--- /dev/null
+++ b/跟单测试源文件.xlsx
@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5eef0d0bfe5f15b0fb9bbfe21c3367614c2cd988382cc237f3964f2a54b1bc14
+size 2818213