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@@ -0,0 +1,373 @@
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+#-*- coding: utf-8 -*-
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+#__author__ = "dukun"
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+
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+import json
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+import time
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+import pymysql
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+import logging
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+import numpy as np
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+import pandas as pd
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+import configparser
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+from celery_tasks import cel
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+#from DBUtils.PooledDB import PooledDB
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+from dbutils.pooled_db import PooledDB
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+from datetime import datetime,timedelta,date
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+
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+
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+#配置输出日志格式
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+LOG_FORMAT = "%(asctime)s %(filename)s[line:%(lineno)d] %(name)s %(levelname)s %(pathname)s %(message)s "
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+
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+#配置输出时间的格式，注意月份和天数不要搞乱了
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+DATE_FORMAT = '%Y-%m-%d %H:%M:%S %a '
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+logging.basicConfig(level=logging.INFO,
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+ format=LOG_FORMAT,
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+ datefmt = DATE_FORMAT ,
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+ filename=r"./logs/manage.log" #有了filename参数就不会直接输出显示到控制台，而是直接写入文件
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+ )
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+
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+cf = configparser.RawConfigParser()
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+cf.read(r"./config.ini")
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+
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+CHANNEL_HOST = cf.get("database1","host")
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+CHANNEL_PORT = int(cf.get("database1","port"))
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+CHANNEL_USER = cf.get("database1","user")
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+CHANNEL_PASSWORD = cf.get("database1","password")
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+CHANNEL_DB = cf.get("database1","db")
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+
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+STAT_HOST = cf.get("database2","host")
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+STAT_PORT = int(cf.get("database2","port"))
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+STAT_USER = cf.get("database2","user")
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+STAT_PASSWORD = cf.get("database2","password")
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+STAT_DB = cf.get("database2","db")
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+
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+
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+
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+
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+#通道数据库
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+channel_db_config = {
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+ 'host' : CHANNEL_HOST,
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+ 'port' : CHANNEL_PORT,
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+ 'user' : CHANNEL_USER,
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+ 'password' : CHANNEL_PASSWORD,
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+ 'db' : CHANNEL_DB,
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+ 'charset' : 'utf8',
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+ 'autocommit' : 1
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+}
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+
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+#监控数据库
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+stat_db_config = {
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+ 'host' : STAT_HOST,
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+ 'port' : STAT_PORT,
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+ 'user' : STAT_USER,
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+ 'password' : STAT_PASSWORD,
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+ 'db' : STAT_DB,
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+ 'charset' : 'utf8',
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+ 'autocommit' : 1
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+}
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+
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+#创建数据库连接池
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+def createPool(db_config):
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+ spool = PooledDB(pymysql, 5, **db_config)
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+ return spool
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+
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+@cel.task
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+def save_yesterday_data():
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+ today = datetime.today()
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+ yesterday = today - timedelta(days=1)
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+ yesterday = yesterday.strftime("%Y-%m-%d")
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+
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+ ins_manage_sql = "INSERT INTO manage_data VALUES(0,'{}',%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)".format(yesterday)
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+ ins_use_time_sql = "INSERT INTO yesterday_use_time VALUES(0,'{}',%s,%s)".format(yesterday)
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+ #print(ins_manage_sql)
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+
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+ conn = createPool(channel_db_config).connection()
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+ stat_conn = createPool(stat_db_config).connection()
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+
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+ month_df = get_month_data(conn)
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+ yesterday_df = get_yesterday_data(conn)
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+ use_time_df = get_yesterday_use_time(conn)
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+
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+ df = pd.merge(month_df,yesterday_df,how = 'outer',on=['enterprise_id','customer_name'])
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+ #df = df.fillna(0)
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+ #df['yes_rate'] = 0
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+ df['yes_rate'] = df['profit'] / df['income']
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+ df['month_rate'] = df['month_profit'] / df['income']
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+ df = df.fillna(0)
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+ df['today_income'] = -1
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+ df['today_profit'] = -1
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+ df = df.reindex(columns=['enterprise_id','customer_name','income','profit','yes_rate','month_income','month_profit',
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+ 'month_rate','today_income','today_profit'])
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+
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+ yes_profit_sum = float(df['profit'].sum())
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+ yes_income_sum = float(df['income'].sum())
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+ month_profit_sum = float(df['month_profit'].sum())
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+ month_income_sum = float(df['month_income'].sum())
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+ yes_profit_rate = yes_profit_sum /yes_income_sum
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+ month_profit_rate = month_profit_sum /month_income_sum
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+
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+ ins_manage_list = df.values.tolist()
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+ ins_manage_list.append(['0001','',yes_income_sum,yes_profit_sum,yes_profit_rate,month_income_sum,
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+ month_profit_sum,month_profit_rate,-1,-1] )
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+ #print(ins_manage_list)
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+
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+ ins_use_time_list = []
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+ ins_use_time_list.append(('小于10分钟',int(use_time_df['A'].iloc[0])))
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+ ins_use_time_list.append(('10-20分钟',int(use_time_df['B'].iloc[0])))
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+ ins_use_time_list.append(('20-30分钟',int(use_time_df['C'].iloc[0])))
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+ ins_use_time_list.append(('30-40分钟',int(use_time_df['D'].iloc[0])))
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+ ins_use_time_list.append(('40-50分钟',int(use_time_df['E'].iloc[0])))
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+ ins_use_time_list.append(('50-60分钟',int(use_time_df['F'].iloc[0])))
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+ ins_use_time_list.append(('大于60分钟',int(use_time_df['G'].iloc[0])))
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+ ins_use_time_list.append(('平均时长',float(use_time_df['avg_time'].iloc[0]/60)))
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+ #print(use_time_df)
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+ #print(ins_use_time_list)
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+
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+ cursor = stat_conn.cursor()
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+ try:
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+ cursor.executemany(ins_manage_sql,ins_manage_list)
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+ cursor.executemany(ins_use_time_sql,ins_use_time_list)
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+
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+ except Exception as ex :
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+ stat_conn.rollback()
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+ print(ex)
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+
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+
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+ #print(month_df)
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+ #print(yesterday_df)
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+ #print(df)
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+ #print(use_time_df)
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+
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+ conn.close()
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+ stat_conn.close()
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+ print(44444444444)
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+
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+@cel.task
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+def save_now_data():
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+ conn = createPool(channel_db_config).connection()
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+ stat_conn = createPool(stat_db_config).connection()
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+
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+ income,profit = get_now_data(conn)
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+ #print(income,profit)
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+
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+ #now = today.strftime("%Y-%m-%d %H:%M:%S")
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+ now_time = time.strftime("%Y-%m-%d %H:%M:%S",time.localtime())
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+ #print(now_time)
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+
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+ que_sql = " SELECT * FROM manage_data WHERE customer_id = '0000' "
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+ ins_sql = """ INSERT INTO manage_data (time,customer_id,today_income,today_profit) VALUES('{}','0000',
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+ {},{}) """.format(now_time,income,profit)
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+ upd_sql = """ UPDATE manage_data SET time = '{}',today_income= {},today_profit={}
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+ WHERE customer_id = '0000' """.format(now_time,income,profit)
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+ #print(upd_sql)
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+
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+ df = pd.read_sql(que_sql,stat_conn)
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+
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+ cursor = stat_conn.cursor()
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+ try:
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+ if df.empty is True:
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+ cursor.execute(ins_sql)
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+ else:
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+ cursor.execute(upd_sql)
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+ except Exception as ex:
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+ print(ex)
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+ stat_conn.rollback()
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+
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+ cursor.close()
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+ conn.close()
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+ stat_conn.close()
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+
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+ print(555555555555)
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+
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+def get_now_data(conn):
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+ today = datetime.today()
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+
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+ time_start = today.strftime("%Y-%m-%d") + ' 00:00:00'
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+ sql = """SELECT SUM(price) income,SUM(price - operator_balance_price - partner_balance_price) profit
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+ FROM
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+ flow_order_info
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+ WHERE
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+ check_time BETWEEN '{}' AND now() AND status = 6
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+ AND enterprise_id NOT IN (57,61,63,64,72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112) """.format(time_start)
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+ #print(sql)
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+ df = pd.read_sql(sql,conn)
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+
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+ return df['income'].iloc[0],df['profit'].iloc[0]
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+
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+
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+#获取本月总利润
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+def get_month_data(conn):
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+
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+ DATE = None
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+ STEP = None
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+
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+ today = datetime.today()
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+ year = today.year
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+ month = today.month
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+
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+ yesterday = today - timedelta(days=1)
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+ yesterday = yesterday.strftime("%Y-%m-%d")
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+ yesterdayStart = yesterday + ' 00:00:00'
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+ yesterdayEnd = yesterday + ' 23:59:59'
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+
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+ date2 = datetime(year, month, today.day)
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+ if date2.day == 1:
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+ if month == 1:
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+ month = 12
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+ year = year -1
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+ else:
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+ month = month - 1
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+
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+ date1 = datetime(year, month, 1)
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+ date1_week = date1.isocalendar()[1]
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+ date2_week = date2.isocalendar()[1]
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+
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+ if DATE is None:
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+ DATE = date1
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+ if STEP is None:
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+ STEP = (date2 - date1).days
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+
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+ DATE_STR = DATE.strftime("%Y-%m")
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+
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+
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+ time_start = DATE.strftime("%Y-%m-%d %H:%M:%S")
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+
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+ #print(time_start)
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+ time_end = (DATE + timedelta(days=STEP)).strftime("%Y-%m-%d %H:%M:%S")
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+ #print(time_start)
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+ #print(time_end)
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+
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+
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+
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+ profit_temp_sql = """SELECT enterprise_id,customer_name,income,profit
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+ FROM
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+ (SELECT enterprise_id,SUM(price) income,SUM(price - operator_balance_price - partner_balance_price) profit
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+ FROM
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+ flow_order_info_{}
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+ WHERE
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+ check_time BETWEEN '{}' AND '{}' AND status = 6
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+ AND enterprise_id NOT IN (57,61,63,64,72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)
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+ GROUP BY enterprise_id) t1 LEFT JOIN customer_info
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+ ON customer_info.customer_id = t1.enterprise_id"""
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+
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+ profit_sql_temp_1 = """SELECT SUM(price - operator_balance_price - partner_balance_price -
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+ price * cast(0.06 / 1.06 AS decimal(12,4))) profits
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+ FROM
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+ flow_order_info_{}
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+ WHERE
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+ apply_date BETWEEN '{}' AND '{}' AND status = 6 AND enterprise_id IN (72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)"""
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+
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+
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+
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+ profit_end_sql = """ SELECT enterprise_id,customer_name,income,profit
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+ FROM
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+ (SELECT enterprise_id,SUM(price) income,SUM(price - operator_balance_price - partner_balance_price) profit
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+ FROM
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+ flow_order_info
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+ WHERE
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+ check_time BETWEEN '{}' AND '{}' AND status = 6
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+ AND enterprise_id NOT IN (57,61,63,64,72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)
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+ GROUP BY enterprise_id) t1 LEFT JOIN customer_info
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+ ON customer_info.customer_id = t1.enterprise_id"""
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+
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+ profit_end_sql_1 = """SELECT SUM(price - operator_balance_price - partner_balance_price
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+ - price * cast(0.06 / 1.06 AS decimal(12,4))) profit
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+ FROM
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+ flow_order_info
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+ WHERE
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+ apply_date BETWEEN '{}' AND '{}' AND status = 6 AND enterprise_id IN (72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)"""
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+
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+
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+ sql = ''
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+ for i in range(date1_week,date2_week+1):
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+ str_table_suffix = "{0}{1:02d}".format(year,i)
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+ if i == date2_week:
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+ if (today - date2) < timedelta(days=7):
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+ sql += profit_end_sql.format(time_start,yesterdayEnd)
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+ else:
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+ sql += prifit_temp_sql.format(str_table_suffix,time_start,yesterdayEnd)
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+ else :
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+ sql += profit_temp_sql.format(str_table_suffix,time_start,yesterdayEnd) + ' UNION '
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+
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+ last_sql = ''' SELECT enterprise_id,customer_name,SUM(income) month_income,SUM(profit) month_profit
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+ FROM ({})t6 GROUP BY enterprise_id
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+
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+ '''.format(sql)
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+
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+ #print(last_sql)
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+ df = pd.read_sql(last_sql,conn)
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+
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+ return df
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+
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+
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+def get_yesterday_data(conn):
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+ today = datetime.today()
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+ yesterday = today - timedelta(days=1)
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+ yesterday = yesterday.strftime("%Y-%m-%d")
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+ yesterdayStart = yesterday + ' 00:00:00'
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+ yesterdayEnd = yesterday + ' 23:59:59'
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+
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+
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+ yes_profit_sql = """SELECT enterprise_id,customer_name,income,profit
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+ FROM
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+ (SELECT enterprise_id,SUM(price) income,SUM(price - operator_balance_price - partner_balance_price) profit
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+ FROM
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+ flow_order_info
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+ WHERE
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+ check_time BETWEEN '{}' AND '{}' AND status = 6
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+ AND enterprise_id NOT IN (57,61,63,64,72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)
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+ GROUP BY enterprise_id) t1 LEFT JOIN customer_info
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+ ON customer_info.customer_id = t1.enterprise_id""".format(yesterdayStart,yesterdayEnd)
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+
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+ yes_profit_sql_1 = """SELECT SUM(price) sum_income,
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+ SUM(operator_balance_price + partner_balance_price
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+ + price * cast(0.06 / 1.06 AS decimal(12,4))) sum_cost
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+ FROM
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+ flow_order_info
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+ WHERE
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+ apply_date BETWEEN '{}' AND '{}' AND status = 6 AND enterprise_id IN (72)
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+ AND channel_id NOT IN ( 101,102,103,110,111,112)""".format(yesterdayStart,yesterdayEnd)
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+ #print(yes_profit_sql)
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+
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+ df = pd.read_sql(yes_profit_sql,conn)
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+
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+ return df
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+
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+def get_yesterday_use_time(conn):
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+ today = datetime.today()
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+ yesterday = today - timedelta(days=1)
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+ yesterday = yesterday.strftime("%Y-%m-%d")
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+ yesterdayStart = yesterday + ' 00:00:00'
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+ yesterdayEnd = yesterday + ' 23:59:59'
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+
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+
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+ sql = """ SELECT
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+ SUM(CASE WHEN diff_time BETWEEN 0 AND 600 THEN 1 ELSE 0 END) AS 'A',
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+ SUM(CASE WHEN diff_time BETWEEN 601 AND 1200 THEN 1 ELSE 0 END) AS 'B',
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+ SUM(CASE WHEN diff_time BETWEEN 1201 AND 1800 THEN 1 ELSE 0 END) AS 'C',
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+ SUM(CASE WHEN diff_time BETWEEN 1801 AND 2400 THEN 1 ELSE 0 END) AS 'D',
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+ SUM(CASE WHEN diff_time BETWEEN 2401 AND 3000 THEN 1 ELSE 0 END) AS 'E',
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+ SUM(CASE WHEN diff_time BETWEEN 3001 AND 3600 THEN 1 ELSE 0 END) AS 'F',
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+ SUM(CASE WHEN diff_time > 3600 THEN 1 ELSE 0 END) AS 'G',
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+ (SUM(diff_time) /COUNT(*)) AS 'avg_time'
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+ FROM
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+ ( SELECT
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+ (UNIX_TIMESTAMP(check_time) - UNIX_TIMESTAMP(apply_date)) AS diff_time
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+ FROM
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+ flow_order_info
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+ WHERE
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+ apply_date BETWEEN '{}' AND '{}' AND
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+ status = 6 AND
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+ channel_id NOT IN ( 101,102,103,110,111,112 ) ) AS t1 """.format(yesterdayStart,yesterdayEnd)
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+
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+ df = pd.read_sql(sql,conn)
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+
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+ return df
|
|
|
+
|
|
|
+save_yesterday_data()
|
|
|
+#save_now_data()
|
