def deal_quan_category(city,date):
'''
处理店圈的菜品类信息，一级品类，二级品类信息
:param city:
:param date:
:return:
'''
sql = """
select DISTINCT(t1.category_id_level1),t1.category_name_level1,0 pid
from t_e_rest_category_city_1712 t1
where t1.city = '%s'
and t1.date = '%s'
union
select DISTINCT(t1.category_id_level2),t1.category_name_level2,t1.category_id_level1 pid
from t_e_rest_category_city_1712 t1
where t1.city = '%s'
and t1.date = '%s'
"""%(city,date,city,date)
result = db2.queryForList(sql, None)
print(result)
sql2 = "insert into quan_category values"
batch = BatchSql(sql2)
for item in result:
quan_category = []
quan_category.extend([0,item[1],date,item[0],item[2],time,time])
print(quan_category)
batch.addBatch(quan_category)
if batch.getSize() > 10000:
db1.update(batch)
batch.cleanBatch()
db1.update(batch)
def deal_comment_data(account,date,coupon_name,coupon_content):
coupon_type = []
"""
门店新用户立减：首
满减活动：减
折扣商品：折
下单返券：返
新用户立减活动：首
商家优惠券：卷
"""
for item in coupon_name:
if item == '限量抢购-9.9元晚餐':
coupon_type.append('抢')
if item == '限量抢购-19.9元晚餐':
coupon_type.append('抢')
if item == '新用户立减':
coupon_type.append('首')
for i in range(len(coupon_name)):
coupon_data = []
name = coupon_name[i]
type = coupon_type[i]
content = coupon_content[i]
coupon_data.extend([0, str(account), date, str(1), str(type), str(name), str(content)])
print(coupon_data)
batch = BatchSql(sql3)
batch.addBatch(coupon_data)
db.update(batch)
def deal_quan_monitor_activity_data(city,date,all_shopid_list):
'''
处理店圈店铺的活动信息
:param city: 所属城市
:param date: 数据日期
:param all_shopid_list: 店圈店铺的ID列表
:return:
'''
sql="""
select t1.rest_id,t1.description,t1.active_type
from t_e_rest_active_city_1712 t1
where t1.city = '%s'
and t1.date = '%s'
and t1.rest_id IN %s
"""%(city,date,all_shopid_list)
sql2 = "insert into quan_monitor_activity_data values"
batch = BatchSql(sql2)
result = db2.queryForList(sql, None)
print(result)
for shoplist in all_shopid_list:
all_activity = []
quan_monitor_activity_data = []
for item in result:
activity = dict(type=item[2],content=item[1])
if item[0] == shoplist:
all_activity.append(activity)
all_activity = json.dumps(all_activity)
quan_monitor_activity_data.extend([0,date,shoplist,str(all_activity),time,time])
print(quan_monitor_activity_data)
batch.addBatch(quan_monitor_activity_data)
if batch.getSize() > 10000:
db1.update(batch)
batch.cleanBatch()
db1.update(batch)
def rate_analyze(id, comment_shopid, date, comment_content):
'''
对评论数据进行分词识别出相应的类别，然后写入数据库中
:param id: 评论ID
:param date: 当前日期
:param comment_content:评论的内容
:return:
'''
time = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
key_vaule = get_config()
db2 = DBUtils(('116.62.70.68', 3306, 'bigdata', 'gisfood20171220@nj',
'big_data', 'utf8mb4'))
sql2 = "insert into comment_flag VALUES"
seg_list = jieba.cut(comment_content) #利用jieba分词，取出句子中所有的分词内容
print("评论内容：", comment_content)
flag = 0 #标志位，0：分词中没有差评信息 1：分词中存在差评信息
keywords = ' '
for item in seg_list: #对一条评论的分词结果进行匹配
for j in range(len(key_vaule)): #在词库中进行配对
if key_vaule.iloc[j, 0] == item:
print("有差评内容:", item)
keywords = item
comment_class = int(key_vaule.iloc[j, 1]) #将评论的标签置为相应的值
flag = 1
break
if flag == 0:
keywords = r' '
comment_class = 0 #没有差评的时候标签置为0
print("评论ID：" + str(id), "所属分类：" + str(comment_class))
batch = BatchSql(sql2) #写入数据库
batch.addBatch(
[0, id, comment_shopid, date, comment_class, keywords, time, None])
db2.update(batch)
def deal_quan_shop(city,date,all_shopid_list,cate_list):
'''
处理店圈店铺的基本数据
:param city: 店圈所属城市
:param date: 数据分析日期
:param all_shopid_list: 店圈数据的店铺列表的数据
:param cate_list: 店圈数据的品类列表
:return:
'''
sql = """
select t1.rest_id,t1.rest_name,t1.delivery_id,t1.longitude,t1.latitude,t1.is_new
from t_e_rest_list_city_1712 t1
where t1.city = '%s'
and t1.date = '%s'
and t1.rest_id IN %s
"""%(city,date,all_shopid_list)
sql2 = "insert into quan_shop values"
batch = BatchSql(sql2)
result = db2.queryForList(sql, None)
print(result)
for item in result:
for cate in cate_list:
if item[0] == cate[0]:
quan_shop = []
quan_shop.extend([0,item[0],1,date,item[1],item[2],item[3],item[4],item[5],cate[1],time,time])
print(quan_shop)
batch.addBatch(quan_shop)
if batch.getSize() > 1000:
db1.update(batch)
batch.cleanBatch()
db1.update(batch)
def deal_meituan_customer_prefer_activity(self):
'''
处理同行顾客喜欢的活动：id，店铺id，店铺名称，日期，
同行顾客喜欢的活动，活动类型
:return:
'''
customer_prefer_activity = self.customerPerfer['data']['pubCusAct']
for item in customer_prefer_activity:
customer_prefer_activity = []
customer_prefer_activity_name = item[0]
customer_prefer_activity_pic = item[1]
customer_prefer_activity_type = self.deal_customer_prefer_activity_type(
customer_prefer_activity_pic)
customer_prefer_activity.extend([
0, self.shopid, self.shopname,
str(self.yesterday), customer_prefer_activity_name,
customer_prefer_activity_type
])
print("顾客喜欢的活动：", customer_prefer_activity)
sql = "insert into meituan_customer_prefer_activity VALUES"
batch = BatchSql(sql)
batch.addBatch(customer_prefer_activity)
self.db2.update(batch)
def run():
# rest_id,rest_name = get_shopid()
rest_name = ['义务', '明发', '同曦', '殷象']
rest_id = [160279990, 161341608, 161378073, 161313783]
for item in rest_id:
revenue = []
print("店铺%s的12月份营收总金额为：" % item)
shop_money_off = get_shop_money_off(item)
shop_menu_order = get_shop_menu_order(item)
all_single_menu_amount = deal_single_menu(shop_menu_order)
all_activity_menu_amount = deal_activity_menu(shop_menu_order)
all_common_menu_amount = deal_common_menu(shop_money_off,
shop_menu_order)
all_amount = all_single_menu_amount + all_activity_menu_amount + all_common_menu_amount
print("营收总金额：", all_amount)
revenue.extend(
[item, rest_name[rest_id.index(item)], '2017-12-31', all_amount])
print(revenue)
print("------------------------------")
print(rest_id.index(item))
batch = BatchSql(sql)
batch.addBatch(revenue)
db.update(batch)
def deal_score_data(score):
'''
处理商家评分信息
:param score:
:return:
'''
print("处理数据", score)
batch = BatchSql(sql2)
batch.addBatch(score)
db.update(batch)
class ParseDeliveymode(object):
def __init__(self,resource_path, city, date,save_date_short,db):
'''
:param resource_path: 城市数据文件路径
:param city: 城市拼音
:param date: 保存日期
:param save_date_short:保存日期简写
:param db: 数据库配置信息
'''
self.resource_path = resource_path
self.city = city
self.date = date
self.save_date_short = save_date_short
self.db = db
self.sql = "insert into t_e_delivery_mode_city_pre_%s values" % save_date_short
self.batch = BatchSql(self.sql)
def parse_data(self, data):
try:
rest_id = str(data['param'])
if len(rest_id) <= 11:
data = data['data'].get('delivery_mode')
delever_id = getMapValue(data,"id")
delever_text = getMapValue(data, "text")
param = [self.city, self.date,rest_id,delever_text,delever_id]
self.batch.addBatch(param)
if self.batch.getSize() > 100000:
self.db.update(self.batch)
self.batch.cleanBatch()
else:
print("错误数据", data)
except Exception as e:
print(traceback.print_exc())
print('解析数据报错\n错误数据：{}'.format(data))
def run(self):
f_name = os.path.join(self.resource_path, 'rest_info.pickle')
print("解析文件：", f_name)
with open(f_name, "rb+") as f:
while True:
try:
data = pickle.load(f)
self.parse_data(data)
except EOFError as e:
print("文件读取完成", e)
break
except Exception as e2:
print("报错", e2)
break
if self.batch.getSize() > 0:
self.db.update(self.batch)
self.batch.cleanBatch()
def deal_meituan_daily_operational_data(self):
'''
运营日报数据入库：id,店铺id，店铺名称，日期，
日有效订单量，订单收入，
曝光量，进店量，下单量，进店转化率，下单转化绿
新客人数，新客占比，旧客人数，旧客占比
推广资金，(推广点击次数，单词点击费用)
:return:
'''
meituan_daily_operational_data = []
effectiveOrders = self.effectiveOrders['data']['effectiveOrders']
settleAcc = self.effectiveOrders['data']['settleAcc']
exposureNum = self.TrafficStats['data']['flowGeneralInfoVo'][
'exposureNum']
visitNum = self.TrafficStats['data']['flowGeneralInfoVo']['visitNum']
xiadanNum = self.TrafficStats['data']['flowGeneralInfoVo']['orderNum']
visitRate = self.TrafficStats['data']['flowGeneralInfoVo']['visitRate']
orderRate = self.TrafficStats['data']['flowGeneralInfoVo']['orderRate']
newOrderNum = self.customerAnalysis['data']['newOrderNum']
oldOrderNum = self.customerAnalysis['data']['oldOrderNum']
orderNum = self.customerAnalysis['data']['orderNum']
if orderNum == 0:
newOrderNum_percent = 0
oldOrderNum_percent = 0
else:
newOrderNum_percent = newOrderNum / orderNum
oldOrderNum_percent = oldOrderNum / orderNum
history_consume_list = self.history_consume['data']['flowVoList']
popularize_amount = 0
for item in history_consume_list:
history_consume_list_date = str(item['date']).split(' ')[0]
history_consume_list_reason = item['reason']
if history_consume_list_date == str(
self.yesterday) and history_consume_list_reason == '推广消费':
popularize_amount += abs(item['amount'])
# print(popularize_amount)
meituan_daily_operational_data.extend([
0, self.shopid, self.shopname,
str(self.yesterday), effectiveOrders, settleAcc, exposureNum,
visitNum, xiadanNum, visitRate, orderRate, newOrderNum,
newOrderNum_percent, oldOrderNum, oldOrderNum_percent,
popularize_amount
])
print("美团运营日报数据:", meituan_daily_operational_data)
sql = "insert into meituan_daily_operational_data VALUES"
batch = BatchSql(sql)
batch.addBatch(meituan_daily_operational_data)
self.db2.update(batch)
def deal_score_data(base_data,score):
# 用户评论信息表的内容
rating_data = []
rating_data.append(str(base_data[0])) # 店铺id
rating_data.append(base_data[1]) # 日期
rating_data.append(str('1')) # 饿了么平台标签
rating_data.append(str(score[0])) # 用户评论
print(rating_data)
# 用户评分数据入库表
batch = BatchSql(sql2)
batch.addBatch(rating_data)
db.update(batch)
def deal_coupon_data(account, date, coupon_name, coupon_content):
'''
处理店铺活动信息
:param account:
:param date:
:param coupon_name:
:param coupon_content:
:return:
'''
coupon_type = []
"""
门店新用户立减：首
满减活动：减
折扣商品：折
下单返券：返
新用户立减活动：首
商家优惠券：卷
"""
for item in coupon_name:
if item == '折扣商品':
coupon_type.append('折')
if item == '下单返券':
coupon_type.append('返')
if item == '门店新用户立减':
coupon_type.append('首')
if item == '商家优惠券':
coupon_type.append('卷')
if item == '满减活动':
coupon_type.append('减')
if item == '新用户立减活动':
coupon_type.append('首')
for i in range(len(coupon_name)):
coupon_data = []
name = coupon_name[i]
type = coupon_type[i]
content = coupon_content[i]
coupon_data.extend([
0,
str(account), date,
str(2),
str(type),
str(name),
str(content)
])
print(coupon_data)
batch = BatchSql(sql3)
batch.addBatch(coupon_data)
db.update(batch)
def deal_meituan_Operational_data_analysis(self):
'''
处理商家后台数据分析的数据：id，店铺id，店铺名称，日期，
有效订单，订单收入，
有效订单打败同行，订单收入打败同行，
下单人数，新客人数，老客人数，
曝光人数，访问人数，下单人数，访问转化率，下单转化率，
商家评分，口味评分，包装评分，配送评分，
:return:
'''
meituan_Operational_data_analysis = []
effectiveOrders = self.effectiveOrders['data']['effectiveOrders']
settleAcc = self.effectiveOrders['data']['settleAcc']
effectiveOrdersRankPercent = self.PeersCompareAnalysis['data'][
'effectiveOrdersRankPercent']
settleAccRankPercent = self.PeersCompareAnalysis['data'][
'settleAccRankPercent']
newOrderNum = self.customerAnalysis['data']['newOrderNum']
oldOrderNum = self.customerAnalysis['data']['oldOrderNum']
orderNum = self.customerAnalysis['data']['orderNum']
exposureNum = self.TrafficStats['data']['flowGeneralInfoVo'][
'exposureNum']
visitNum = self.TrafficStats['data']['flowGeneralInfoVo']['visitNum']
xiadanNum = self.TrafficStats['data']['flowGeneralInfoVo']['orderNum']
visitRate = self.TrafficStats['data']['flowGeneralInfoVo']['visitRate']
orderRate = self.TrafficStats['data']['flowGeneralInfoVo']['orderRate']
bizScore = self.commentSummary['data']['bizScore']
tasteScore = self.commentSummary['data']['tasteScore']
packScore = self.commentSummary['data']['packScore']
deliveryScore = self.commentSummary['data']['deliveryScore']
meituan_Operational_data_analysis.extend([
0, self.shopid, self.shopname,
str(self.yesterday), effectiveOrders, settleAcc,
effectiveOrdersRankPercent, settleAccRankPercent, orderNum,
newOrderNum, oldOrderNum, exposureNum, visitNum, xiadanNum,
visitRate, orderRate, bizScore, tasteScore, packScore,
deliveryScore
])
print('商家后台数据分析：', meituan_Operational_data_analysis)
sql = "insert into meituan_Operational_data_analysis VALUES"
batch = BatchSql(sql)
batch.addBatch(meituan_Operational_data_analysis)
self.db2.update(batch)
def deal_commentSummary(self):
'''
处理顾客评价的信息：店铺ID、时间、平台、评分、评分日比
:return:
'''
commentSummary_content = []
bizScore = self.commentSummary['data']['bizScore']
commentSummary_content.extend(
[self.shopid, self.date, self.platform, bizScore])
print('店铺评分信息：', commentSummary_content)
sql = "insert into rating_score VALUES "
batch = BatchSql(sql)
batch.addBatch(commentSummary_content)
self.db.update(batch)
def deal_base_data(account, date, result):
'''
处理基础的几条信息
:param account:
:param date:
:param result:
:return:
'''
base_data = []
base_data.extend([
account, date, result[4], result[6], result[8], result[10], result[11]
])
print("处理数据：", base_data)
batch = BatchSql(sql)
batch.addBatch(base_data)
db.update(batch)
def deal_quan_monitor_hot_sku_data(city,date,all_shopid_list):
'''
处理店圈sku数据，9个店铺大约110万条数据
:param city: 所属城市
:param date: 数据日期
:param all_shopid_list: 店圈店铺ID列表
:return:
'''
sql="""
select t1.rest_id,t1.food_name,t1.price,t1.food_id,t1.food_month_sales,t1.has_activity,t2.delivery_fee
from t_e_rest_menu_level2_unique_city_nj_1712 t1,
t_e_rest_list_city_1712 t2
where t1.city = '%s'
and t1.date = '%s'
and t1.rest_id IN %s
and t1.food_month_sales != 0
and t1.city = t2.city
and t1.date = t2.date
and t1.rest_id = t2.rest_id
"""%(city,date,all_shopid_list)
sql2 = 'insert into quan_monitor_hot_sku_data values'
batch = BatchSql(sql2)
result = db2.queryForList(sql, None)
print(result)
for shop_list in all_shopid_list:
for item in result:
quan_monitor_hot_sku_data = []
if shop_list == item[0]:
if item[5] == 1: #特价菜
quan_monitor_hot_sku_data.extend([0,date,shop_list,item[1],item[2],item[2],item[4],time,time])
print(quan_monitor_hot_sku_data)
batch.addBatch(quan_monitor_hot_sku_data)
elif item[5] == 0: #满减菜品
sub_price = get_sub_price(city,date,shop_list,item[2])
if sub_price == None:
sub_price = 0
true_price = item[2]-sub_price
quan_monitor_hot_sku_data.extend([0,date,shop_list,item[1],item[2],true_price,item[4],time,time])
print(quan_monitor_hot_sku_data)
batch.addBatch(quan_monitor_hot_sku_data)
if batch.getSize() > 10000:
db1.update(batch)
batch.cleanBatch()
db1.update(batch)
def deal_TrafficStats(self):
'''
处理数据流量分析的信息：店铺id、时间、曝光人数，访问人数，下单人数，访问转化率，下单转化率
:return:
'''
TrafficStats = []
exposureNum = self.TrafficStats['data']['flowGeneralInfoVo'][
'exposureNum']
visitNum = self.TrafficStats['data']['flowGeneralInfoVo']['visitNum']
orderNum = self.TrafficStats['data']['flowGeneralInfoVo']['orderNum']
visitRate = self.TrafficStats['data']['flowGeneralInfoVo']['visitRate']
orderRate = self.TrafficStats['data']['flowGeneralInfoVo']['orderRate']
TrafficStats.extend([
self.shopid, self.date, exposureNum, visitNum, orderNum, visitRate,
orderRate
])
print('流量分析信息：', TrafficStats)
sql = "insert into meituan_backstage VALUES "
batch = BatchSql(sql)
batch.addBatch(TrafficStats)
self.db.update(batch)
def deal_meituan_customer_precision_operation(self):
'''
处理精准营销的数据：id，店铺id，店铺名称，日期，
营销名称，营销活动人数
:return:
'''
customer_precision_labelList = self.getCouponLabel['data']['labelList']
for item in customer_precision_labelList:
customer_precision_operation = []
precision_operation_name = item['title']
precision_operation_numbers = item['nums']
customer_precision_operation.extend([
0, self.shopid, self.shopname,
str(self.yesterday), precision_operation_name,
precision_operation_numbers
])
print('精准营销的活动信息：', customer_precision_operation)
sql = "insert into meituan_customer_precision_operation VALUES"
batch = BatchSql(sql)
batch.addBatch(customer_precision_operation)
self.db2.update(batch)
def deal_meituan_customer_prefer_analysis(self):
'''
处理同行顾客爱好：id,店铺id，店铺名称，日期
同行顾客爱好的菜品名，该菜品的同行百分比
:return:
'''
customer_prefer_analysi = self.customerPerfer['data']['pubCusEat']
for item in customer_prefer_analysi:
meituan_customer_prefer_analysi = []
customer_prefer_name = item[0]
customer_prefer_percent = item[1]
meituan_customer_prefer_analysi.extend([
0, self.shopid, self.shopname,
str(self.yesterday), customer_prefer_name,
float(customer_prefer_percent)
])
print('同行顾客爱好：', meituan_customer_prefer_analysi)
sql = "insert into meituan_customer_prefer_analysis VALUES"
batch = BatchSql(sql)
batch.addBatch(meituan_customer_prefer_analysi)
self.db2.update(batch)
def deal_quan_monitor_shop_data(city,date,all_shopid_list):
'''
处理店圈的配送费用和配送时间的信息
:param city: 店圈所属城市
:param date: 爬取数据的日期
:param all_shopid_list: 所有店圈的店铺列表信息
:return:
'''
sql = """
select t1.rest_id,t1.order_month_sales,t2.deliver_time,t1.delivery_fee,t1.min_delivery_price,t2.overall_score
from t_e_rest_list_city_1712 t1,
t_e_rest_score_city_1712 t2
where t1.city = '%s'
and t1.date = '%s'
and t1.rest_id IN %s
and t1.rest_id = t2.rest_id
and t1.city = t2.city
and t1.date = t2.date
"""%(city,date,all_shopid_list)
sql2 = "insert into quan_monitor_shop_data values"
batch = BatchSql(sql2)
result = db2.queryForList(sql, None)
for item in result:
quan_monitor_shop_data = []
score = float('%.1f'%float(item[5]))
quan_monitor_shop_data.extend([0,date,item[0],item[1],item[2],item[3],item[4],score,time,time])
print(quan_monitor_shop_data)
batch.addBatch(quan_monitor_shop_data)
if batch.getSize() > 10000:
db1.update(batch)
batch.cleanBatch()
db1.update(batch)
def deal_CustomerReminder(self):
'''
处理店铺催单信息：id，店铺id，日期，时间，平台名称，催单次数，催单时间
:return:
'''
CustomerReminder_Info = self.customer_reminderInfo['wmOrderList']
CustomerReminder_Data = self.customer_reminder['data']
if CustomerReminder_Info != None:
for item in CustomerReminder_Info: #获取另一个催单账号信息借口获取催单的ID
CustomerReminder_ID = item['wm_order_id_view']
try:
for item in CustomerReminder_Data[str(
CustomerReminder_ID)]: #根据催单ID获取相应的催单的时间信息
times = len(CustomerReminder_Data[str(
CustomerReminder_ID)]) #催单的次数
CustomerReminder = []
reminder_time_fmt = item['reminder_time_fmt']
response_time_fmt = item['response_time_fmt']
reminder_time_fmt = str(reminder_time_fmt).split(
':')[1]
response_time_fmt = str(response_time_fmt).split(
':')[1]
reminder_time = int(response_time_fmt) - int(
reminder_time_fmt) #商家后台恢复催单信息的时长
CustomerReminder.extend([
0, self.shopid, self.date, self.time,
CustomerReminder_ID, 2, times, reminder_time
])
print('客户催单信息：', CustomerReminder)
sql = "insert into daily_customer_reminder VALUES"
batch = BatchSql(sql)
batch.addBatch(CustomerReminder)
self.db.update(batch)
except Exception:
pass
def deal_Activitylist(self):
'''
处理店铺活动的信息：id，店铺id，活动id，时间，平台名称，活动类型，活动名称，活动内容
:return:
'''
Activity_onGoingActs = self.activitylist['data']['onGoingActs']
for item in Activity_onGoingActs:
Activitylist = []
actId = item['actId']
actName = item['actName']
poiPolicy = item['poiPolicy']
type = item['type']
Activity_type = self.deal_Activity_type(type)
Activitylist.extend([
0, self.shopid, actId, self.date, 2, Activity_type, actName,
poiPolicy
])
print('店铺活动信息：', Activitylist)
sql = "insert into daily_shop_activity_data VALUES"
batch = BatchSql(sql)
batch.addBatch(Activitylist)
self.db3.update(batch)
def deal_base_data(base_data):
# 基本信息数据入库
batch = BatchSql(sql)
batch.addBatch(base_data)
db.update(batch)
class ParseHotword(object):
def __init__(self, resource_path, city, date, save_date_short,
err_rest_ids, db):
'''
:param resource_path: 城市数据文件路径
:param city: 城市拼音
:param date: 保存日期
:param save_date_short:保存日期简写
:param err_rest_ids: 错误店铺ID
:param db: 数据库配置信息
'''
self.resource_path = resource_path
self.city = city
self.date = date
self.save_date_short = save_date_short
self.err_rest_ids = err_rest_ids
self.db = db
self.sql = "insert into t_e_hot_search_word_city_%s values" % save_date_short
self.batch = BatchSql(self.sql)
def parse_data(self, data):
try:
rest_id = str(data["param"][0])
if rest_id in self.err_rest_ids:
return
if len(rest_id) <= 11:
la = data["param"][1]
lo = data["param"][2]
for item in data["data"]:
search_word = getMapValue(item, "search_word")
if search_word != '-999':
self.batch.addBatch([
self.city, self.date, rest_id, la, lo, search_word
])
if self.batch.getSize() > 100000:
self.db.update(self.batch)
self.batch.cleanBatch()
else:
print("错误数据", data)
print('错误数据\n{}'.format(data))
except Exception as e:
print("解析数据报错", e)
print('解析数据报错\n错误数据：{}'.format(data))
def run(self):
f_name = os.path.join(self.resource_path, 'hot_word.pickle')
print("解析文件：", f_name)
with open(f_name, "rb+") as f:
while True:
try:
data = pickle.load(f)
self.parse_data(data)
except EOFError as e:
print("文件读取完成", e)
break
except Exception as e2:
print("报错", e2)
break
if self.batch.getSize() > 0:
self.db.update(self.batch)
self.batch.cleanBatch()
class ParseScore(object):
def __init__(self,resource_path, city, date,save_date_short, err_rest_ids,db):
'''
:param resource_path: 城市数据文件路径
:param city: 城市拼音
:param date: 保存日期
:param save_date_short:保存日期简写
:param err_rest_ids: 错误店铺ID
:param db: 数据库配置文件
'''
self.resource_path = resource_path
self.city = city
self.date = date
self.save_date_short = save_date_short
self.err_rest_ids = err_rest_ids
self.db = db
self.sql = "insert into t_e_rest_score_city_%s values" %save_date_short
self.batch = BatchSql(self.sql)
def parse_data(self,data):
try:
rest_id = data['param']
if rest_id in self.err_rest_ids:
return
if len(rest_id) <= 11:
self.batch.addBatch([self.city, self.date, rest_id,
getMapValue(data['data'], "compare_rating"),
getMapValue(data['data'], "deliver_time"),
getMapValue(data['data'], "food_score"),
getMapValue(data['data'], "overall_score"),
getMapValue(data['data'], "service_score")])
if self.batch.getSize() > 100000:
self.db.update(self.batch)
self.batch.cleanBatch()
else:
print("错误数据", data)
print('错误数据\n{}'.format(data))
except Exception as e:
print("解析数据报错", e)
print('解析数据报错\n错误数据：{}'.format(data))
def run(self):
f_name = os.path.join(self.resource_path, 'score.pickle')
print("解析文件：", f_name)
with open(f_name, "rb+") as f:
while True:
try:
data = pickle.load(f)
self.parse_data(data)
except EOFError as e:
print("文件读取完成", e)
break
except Exception as e2:
print("报错", e2)
break
if self.batch.getSize() > 0:
self.db.update(self.batch)
self.batch.cleanBatch()
class ParseCategory(object):
def __init__(self, resource_path, city, city_cn, date, date_short, db):
'''
:param resource_path: 城市数据文件路径
:param city: 城市拼音
:param city_cn: 城市中文
:param date: 保存日期
:param date_short: 保存日期简写
:param db: 数据配置
:return:
'''
self.resource_path = resource_path
self.city = city
self.city_cn = city_cn
self.date = date
self.date_short = date_short
self.db = db
self.sql1 = "insert into t_e_rest_list_city_pre_%s values" % date_short
self.sql2 = "insert into t_e_rest_active_city_%s values" % date_short
self.sql3 = "insert into t_e_rest_category_city_%s values" % date_short
self.sql4 = "insert into t_e_rest_open_time_city_%s values" % date_short
self.sql5 = "insert into t_e_rest_money_off_city_%s values" % date_short
self.sql6 = "insert into t_e_rest_money_off_avg_city_%s values" % date_short
self.batch1 = BatchSql(self.sql1)
self.batch2 = BatchSql(self.sql2)
self.batch3 = BatchSql(self.sql3)
self.batch4 = BatchSql(self.sql4)
self.batch5 = BatchSql(self.sql5)
self.batch6 = BatchSql(self.sql6)
self.err_rest_ids = set()
self.rest_category = defaultdict(set)
self.category_level1_list = []
self.category_level2_list = []
def get_data_by_level2_id(self, category_level2_id):
category_level1_id, category_level1_name, category_level2_name = '-999', '-999', '-999'
for item in self.category_level2_list:
if category_level2_id == str(item.get('id2')):
category_level2_name = str(item.get('name2'))
category_level1_id = str(item.get('id1'))
category_level1_name = str(item.get('name'))
break
# for item in category_level1_list:
# if category_level1_id == str(item[0]):
# category_level1_name = str(item[1])
# break
return category_level1_id, category_level1_name, category_level2_id, category_level2_name
def parse_data(self, data, m):
'''
:param data: 城市数据
:param city: 城市拼音
:param date: 保存日期
:param m: 城市地图信息
:param date_short: 保存日期简写
:param db: 数据库配置信息
:return:
'''
try:
category_item = data['param'][2]
category_level2_id = str(category_item.get("id2"))
item = data["data"]
rest_id = getMapValue(item, "id")
lat = float(getMapValue(item, "latitude"))
lng = float(getMapValue(item, "longitude"))
if len(rest_id) > 11:
print('错误店铺id\nrest_id: {}'.format(rest_id))
elif not (m.is_in_city(lng, lat)):
self.err_rest_ids.add(rest_id)
print('错误地址\nrest_id: {}, lat: {}, lng: {}, name: {}\n'
'address: {}'.format(rest_id, lat, lng,
getMapValue(item, "name"),
getMapValue(item, "address")))
else:
# 店铺去重
if not self.rest_category[rest_id]:
self.batch1.addBatch([
self.city, self.date, rest_id,
getMapValue(item, "name"),
getMapValue(item, "phone", '/'),
getMapValue(item, "address"),
getMapValue(item, "average_cost"),
[1, 0][getMapValue(item, "delivery_mode") == '-999'],
getMapValue(item, "float_delivery_fee"),
getMapValue(item, "float_minimum_order_amount"),
[0, 1][getMapValue(item, "is_new") == 'True'],
[0, 1][getMapValue(item, "is_premium") == 'True'], lat,
lng,
getMapValue(item, "recent_order_num"), '-999'
])
if self.batch1.getSize() > 10000:
self.db.update(self.batch1)
self.batch1.cleanBatch()
opening_hours = getMapValue(item, "opening_hours")
arr = json.loads(opening_hours.replace("\'", "\""))
if not isinstance(arr, list):
print('错误数据：', rest_id, opening_hours)
print('错误数据\nrest_id: {}, opening_hours: {}'.format(
rest_id, opening_hours))
else:
for s in arr:
times = s.split("/")
self.batch4.addBatch(
[self.city, self.date, rest_id, *times])
if self.batch4.getSize() > 100000:
self.db.update(self.batch4)
self.batch4.cleanBatch()
# TODO 平均满减折扣有问题
discount_rate_list = []
for active in item.get('activities'):
attribute = getMapValue(active, "attribute")
active_type = getMapValue(active, "icon_name")
self.batch2.addBatch([
self.city, self.date, rest_id,
getMapValue(active, "description"), active_type
])
if self.batch2.getSize() > 100000:
self.db.update(self.batch2)
self.batch2.cleanBatch()
if active_type == '减' and attribute != '-999':
arr = json.loads(attribute)
for key, value in arr.items():
if isinstance(value, dict):
sub_price = value.get("1")
if sub_price == 0:
sub_price = value.get("0")
else:
sub_price = value
key = round(float(key), 2)
sub_price = round(float(sub_price), 2)
discount_rate = round(sub_price / key, 4)
discount_rate_list.append(discount_rate)
self.batch5.addBatch([
self.city, self.date, rest_id, key,
sub_price, discount_rate
])
if self.batch5.getSize() > 100000:
self.db.update(self.batch5)
self.batch5.cleanBatch()
# TODO 平均满减折扣有问题
if len(discount_rate_list):
avg_discount_rate = sum(discount_rate_list) / len(
discount_rate_list)
avg_discount_rate = round(avg_discount_rate, 4)
self.batch6.addBatch(
[self.city, self.date, rest_id, avg_discount_rate])
if self.batch6.getSize() > 100000:
self.db.update(self.batch6)
self.batch6.cleanBatch()
# 店铺对应品类去重
if category_level2_id not in self.rest_category[rest_id]:
self.rest_category[rest_id].add(category_level2_id)
#TODO 取消了单独的品类文件，品类信息和店铺信息保存一起，可直接获取该店铺对应品类信息
# category_level1_id, category_level1_name, category_level2_id, category_level2_name = get_data_by_level2_id(category_level2_id)
category_level1_id = category_item.get('id1')
category_level1_name = category_item.get('name')
category_level2_name = category_item.get('name2')
self.batch3.addBatch([
self.city, self.date, category_level1_id,
category_level1_name, category_level2_id,
category_level2_name, rest_id,
getMapValue(item, "name")
])
if self.batch3.getSize() > 100000:
self.db.update(self.batch3)
self.batch3.cleanBatch()
except Exception as e:
print("解析数据报错", traceback.format_exc())
print('解析数据报错\n错误数据：{}'.format(data))
def run(self):
from ShopMonitor.elm.ElmWebParse.ElmMapUtil import ElmMapUtil
m = ElmMapUtil(self.city_cn)
f_name = os.path.join(self.resource_path, 'category.pickle')
print("解析rest文件：", f_name)
with open(f_name, "rb+") as f:
while 1:
try:
data = pickle.load(f)
self.parse_data(data, m)
# parse_data(data, city, date,m,date_short,db)
except EOFError as e:
print("rest文件读取完成", e)
break
except Exception as e2:
print("报错", e2)
break
if self.batch1.getSize() > 0:
self.db.update(self.batch1)
self.batch1.cleanBatch()
if self.batch2.getSize() > 0:
self.db.update(self.batch2)
self.batch2.cleanBatch()
if self.batch3.getSize() > 0:
self.db.update(self.batch3)
self.batch3.cleanBatch()
if self.batch4.getSize() > 0:
self.db.update(self.batch4)
self.batch4.cleanBatch()
if self.batch5.getSize() > 0:
self.db.update(self.batch5)
self.batch5.cleanBatch()
if self.batch6.getSize() > 0:
self.db.update(self.batch6)
self.batch6.cleanBatch()
print('rest_list数：', len(self.rest_category.keys()))
print('rest_category数：',
sum([len(x) for x in self.rest_category.values()]))
print(self.city_cn, "错误店铺数：", len(self.err_rest_ids))
# with open("err_rest_ids_" + city_cn + ".txt", "w") as f:
# for item in err_rest_ids:
# f.write(str(item) + '\n')
return self.err_rest_ids
class ParseMenu(object):
def __init__(self, resource_path, city, date, city_short, save_date_short,
err_rest_ids, db):
'''
:param resource_path: 数据文件路径
:param city: 城市拼音
:param date: 保存日期
:param city_short: 城市简写
:param save_date_short: 保存日期简写
:param err_rest_ids: 错误城市id
:param db: 数据库配置信息
'''
self.resource_path = resource_path
self.city = city
self.date = date
self.city_short = city_short
self.save_date_short = save_date_short
self.err_rest_ids = err_rest_ids
self.db = db
self.sql1 = "insert into t_e_rest_menu_level1_city_%s values" % save_date_short
self.sql2 = "insert into t_e_rest_menu_level2_city_%s_%s values" % (
city_short, save_date_short)
self.sql3 = "insert into t_e_rest_menu_level2_unique_city_%s_%s values" % (
city_short, save_date_short)
self.sql4 = "insert into t_e_rest_menu_discount_city_%s values" % save_date_short
self.batch1 = BatchSql(self.sql1)
self.batch2 = BatchSql(self.sql2)
self.batch3 = BatchSql(self.sql3)
self.batch4 = BatchSql(self.sql4)
self.rest_food = defaultdict(set)
def parse_data(self, data):
try:
rest_id = getMapValue(data, 'param')
if rest_id in self.err_rest_ids:
return
for item in data["data"]:
# 验证是否是错误数据
try:
foods = item['foods'][::-1]
except KeyError:
print('错误数据\n{}'.format(item))
continue
menu_name = getMapValue(item, 'name')
self.batch1.addBatch(
[self.city, self.date, rest_id, menu_name])
if self.batch1.getSize() > 100000:
self.db.update(self.batch1)
self.batch1.cleanBatch()
for item2 in foods:
food_id = getMapValue(item2, 'virtual_food_id')
food_price_current = getMapValue(item2["specfoods"][0],
'price')
food_price_primary = getMapValue(item2["specfoods"][0],
'original_price')
has_activity = '0'
if food_price_primary not in ['-999', '0']:
has_activity = '1'
self.batch2.addBatch([
self.city, self.date, rest_id, food_id,
getMapValue(item2, 'name'),
getMapValue(item2, 'month_sales'),
getMapValue(item2, 'rating'),
getMapValue(item2, 'satisfy_count'),
food_price_current, has_activity, menu_name
])
if self.batch2.getSize() > 100000:
self.db.update(self.batch2)
self.batch2.cleanBatch()
if food_id not in self.rest_food[rest_id]:
self.rest_food[rest_id].add(food_id)
self.batch3.addBatch([
self.city, self.date, rest_id, food_id,
getMapValue(item2, 'name'),
getMapValue(item2, 'month_sales'),
getMapValue(item2, 'rating'),
getMapValue(item2, 'satisfy_count'),
food_price_current, has_activity, menu_name
])
if self.batch3.getSize() > 100000:
self.db.update(self.batch3)
self.batch3.cleanBatch()
if food_price_primary not in ['-999', '0']:
discount = '%.6f' % (float(food_price_current) /
float(food_price_primary))
self.batch4.addBatch([
self.city, self.date, rest_id, food_id,
food_price_primary, food_price_current,
discount
])
if self.batch4.getSize() > 100000:
self.db.update(self.batch4)
self.batch4.cleanBatch()
except Exception as e:
print("解析数据报错", e)
print('解析数据报错\n错误数据：{}'.format(data))
def run(self):
f_name = os.path.join(self.resource_path, 'menu.pickle')
print("解析文件：", f_name)
with open(f_name, "rb+") as f:
while 1:
try:
data = pickle.load(f)
self.parse_data(data)
# break
except EOFError as e:
print("文件读取完成", e)
break
except Exception as e2:
print("报错", e2)
break
if self.batch1.getSize() > 0:
self.db.update(self.batch1)
self.batch1.cleanBatch()
if self.batch2.getSize() > 0:
self.db.update(self.batch2)
self.batch2.cleanBatch()
if self.batch3.getSize() > 0:
self.db.update(self.batch3)
self.batch3.cleanBatch()
if self.batch4.getSize() > 0:
self.db.update(self.batch4)
self.batch4.cleanBatch()
def deal_quan_position():
'''
处理店圈的店铺列表信息，获取1.5,3,5公里的店圈id列表信息，并写入数据表quan_position中
:return:
'''
for i in range(len(area_shop_id)): #遍历所有店铺列表
for j in range(0,3): #获取三种店圈半径类型的数据
sql = """
SELECT t1.rest_id
FROM t_e_rest_list_city_1712 t1
where t1.longitude IN
(SELECT t1.longitude
FROM
t_e_rest_list_city_1712 t1
WHERE
t1.city = 'nanjing'
AND round(
6378.138 * 2 * asin(
sqrt(
pow(
sin(
(
t1.latitude * pi() / 180 - %s * pi() / 180
) / 2
),
2
) + cos(t1.latitude * pi() / 180) * cos(%s * pi() / 180) * pow(
sin(
(
t1.longitude * pi() / 180 - %s * pi() / 180
) / 2
),
2
)
)
) * 1000
) <= %s)
and t1.latitude IN
(SELECT t1.latitude
FROM
t_e_rest_list_city_1712 t1
WHERE
t1.city = 'nanjing'
AND round(
6378.138 * 2 * asin(
sqrt(
pow(
sin(
(
t1.latitude * pi() / 180 - %s * pi() / 180
) / 2
),
2
) + cos(t1.latitude * pi() / 180) * cos(%s * pi() / 180) * pow(
sin(
(
t1.longitude * pi() / 180 - %s * pi() / 180
) / 2
),
2
)
)
) * 1000
) <= %s)
"""%(shop_latitude[i],shop_latitude[i],shop_longitude[i],type[j],shop_latitude[i],shop_latitude[i],shop_longitude[i],type[j])
# print(sql)
area_shop_list = db2.queryForList(sql,None) #获取店圈的店铺id信息
all_area_shop_list = []
for item in area_shop_list:
all_area_shop_list.append(item[0])
all_str_shop_ids = str(all_area_shop_list) #店铺列表信息的简单处理，将[]去除
all_str_shop_ids = all_str_shop_ids.split('[')[1]
all_str_shop_ids = all_str_shop_ids.split(']')[0]
sql2 = 'insert into quan_position values'
quan_position = []
quan_position.extend([0,'2017-12-31',area_shop_id[i],area_shop_name[i],j+1,all_str_shop_ids,time,time])
print("店圈列表信息：",quan_position)
batch = BatchSql(sql2)
batch.addBatch(quan_position)
db1.update(batch)