data_analyze_platform/LIB/FRONTEND/DrivingRange/main.py

#coding=utf-8
import os
import datetime
import pandas as pd
from LIB.BACKEND import DBManager, Log
from LIB.MIDDLE import SignalMonitor
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
import time, datetime
import traceback
from LIB.MIDDLE.DrivingRange import UpdtFct
import pymysql

from urllib import parse

dbManager = DBManager.DBManager()
if __name__ == "__main__":
    #建立引擎
    db_engine = create_engine(str(r"mysql+pymysql://%s:" + '%s' + "@%s/%s") % ('root', 'pengmin', 'localhost', 'qixiangdb'))
    #连接到qx数据库
    db_qx = pymysql.connect(
            host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com',
            user='qx_read',
            password='Qx@123456',#Qx@123456
            database='qx_cas',
            charset='utf8'
        )
    #连接到本地数据库，输出物
    db_local = pymysql.connect(
            host='localhost',
            user='root',
            password='pengmin',
            database='qixiangdb',
            charset='utf8'
        )

    #调度周期：每天运行一次。

    #更新所有sn，连读多日的factor，如果start_date和end_date相隔一天，代表更新start_date的factor。
    start_date="2021-07-23"
    end_date="2021-07-28"
    UpdtFct.updtAllSnFct(start_date,end_date, db_engine, db_local, db_qx)
    UpdtFct.updtNewestFctTb(db_local, db_engine)


    #调度周期：程序每5分钟运行一次

    #更新剩余里程，每5min一次，几秒钟运行结束。
    test_time=datetime.datetime.now()#当前系统时间
    input_time=datetime.datetime.strftime(test_time,'%Y-%m-%d %H:%M:%S')

    # input_time='2021-07-29 11:59:00'#手动设定一个时间

    #函数每5min调度一次，input_time为当前时间，更新tb_sn_factor_soc_range表格
    UpdtFct.updtVehElecRng(db_qx, db_local, db_engine, input_time)