from sqlalchemy import create_engine from urllib import parse import pandas as pd def update_dict(x, y): # 用字典y,来更新x # key 存在则更新,不存在则新增 x.update(y) return x def get_db_engine(db_info): db_con_str = 'mysql+pymysql://%s:%s@%s:%d/%s' % \ (db_info['username'], parse.quote_plus(db_info['password']), db_info['host'], db_info['port'], db_info['database']) engine = create_engine(db_con_str, connect_args={'charset': 'utf8'}) return engine def is_contains_region(val1, val2): """ level1 region long[] 可选 地域 传值为[]表示不限;传递上一级ID时,childrenID可以不传;不允许同时传parentID和childrenID; 仅计划的campaign_type为5时,支持设置三级地域(例:山西-大同-左云,左云是三级地域) :param val1: 推荐的城市等级组合,如 "一线城市|新一线城市|二线城市|三线城市" , "不限" :param val2: 从账户配置信息表里读取的地区信息, 如 '[]', None, '[14,15,21,22,23,31,32]' :return: """ if val1 == '不限' or val1 is None: if val2 is None or val2 == '[]': return True, {'region': None} else: return False, -1 else: if val2 is None or val2 == '[]': return False, -1 else: val = [] sql = """ select t1.city_name, t2.level, t2.region_id, t2.parent from ctop_kuaishou_city_level t1 left join ctop_kuaishou_region_list_parent t2 on t1.city_name = t2.name where t1.city_level in %s """ % (tuple(val1.split('|')),) city_df = pd.read_sql(sql, None) # level1 if set(city_df[city_df.level == 1].region_id.values).issubset(set(eval(val2))): val.extend(city_df[city_df.level == 1].region_id.values) else: return False, -1 # level2 # 元素的父级是否存在于 val2,如果存在则为包含于的关系 # 元素本身是否存在于 val2 ,如果存在则为包含于的关系 # 以上都不满足,val1 不包含于 val2 for item in city_df[city_df.level == 2].region_id.values: parent = city_df[city_df.region_id == item].parent.values[0] if parent in eval(val2): val.append(item) elif item in eval(val2): val.append(item) else: return False, -1 # level3 for item in city_df[city_df.level == 3].region_id.values: parent = city_df[city_df.region_id == item].parent.values[0] if parent in eval(val2): val.append(item) elif item in eval(val2): val.append(item) else: return False, -1 return True, {'region': val} def is_contains_gender(val1, val2): """ :param val1: ctop_ai_kuaishou_signature_recommended_target_combine 中的 gender 字段: '男'、'女'、'不限'、None :param val2: ctop_ai_kuaishou_advertiser_strategy 中的 gender 字段: 1:女性, 2:男性,0表示不限 :return: val1 是否为 val2的子集,以及传递给快手后台的值 """ is_contains = False val = None if val1 == '男' and val2 in (2, 0): is_contains = True val = 2 if val1 == '女' and val2 in (1, 0): is_contains = True val = 1 if val1 == '不限' and val2 == 0: is_contains = True val = val2 # 如果val1为空,表示该字段没有参与定向组合运算,就直接取客户投放策略里面的值 if val1 is None: is_contains = True val = val2 return is_contains, {'gender': val} def is_contains_platform_os(val1, val2): """ :param val1: ctop_ai_kuaishou_signature_recommended_target_combine 中的 client 字段: '男'、'女'、'不限'、None :param val2: :return: """ pass def is_contains_age(val1, val2_min, val2_max, val2_range): """ :param val1: 推荐的年龄等级组合,如 "31-40岁|41-49岁|50+岁" , "不限" age struct 可选 自定义年龄段 不传值表示不限,传值具体见下方表格;与ages_range不能同时传 min int 必填 年龄最小限制 年龄区间最小为18岁 max int 必填 年龄最大限制 年龄区间最大为55岁,且年龄最大限制须大于等于年龄最小限制 :param val2_min: age_min :param val2_max: age_max :param val2_range: ctop_ai_kuaishou_advertiser_strategy 中的 ages_range [] varchar 与age不能同时传;【18:表示18-23岁】;【24:表示24-30岁】;【31:表示31-40岁】;【41:表示41-49岁】;【50:表示50-100岁】 :return: """ age_dict = {'18-23岁': 18, '24-30岁': 24, '31-40岁': 31, '41-49岁': 41, '50+岁': 50, '50-100岁': 50} if val1 == '不限' or not val1: if (not val2_min) and (not val2_max) and (not val2_range or val2_range == '不限'): return True, {'ages_range': None} else: return False, -1 else: age1 = [age_dict[item] for item in val1.split('|')] if (val2_min is None and val2_max is None) and val2_range: if set(age1).issubset(set(eval(val2_range))): return True, {'ages_range': age1} else: return False, -1 if (val2_min and val2_max) and (not val2_range): if age1[0] >= val2_min and age1[-1] <= val2_max: return True, {'age_min': age1[0], 'age_max': age1[-1]} else: return False, -1 def is_contains_business_interest(val1, val2): pass