Merge remote-tracking branch 'origin/dev' into pro

LIB/FRONTEND/DrivingRange/main.py

@@ -8,20 +8,48 @@ from sqlalchemy import create_engine
 from sqlalchemy.orm import sessionmaker
 import time, datetime
 import traceback
-from LIB.MIDDLE.DrivingRange import *
+from LIB.MIDDLE.DrivingRange import UpdtFct
+import pymysql
 
 from urllib import parse
 
 dbManager = DBManager.DBManager()
 if __name__ == "__main__":
-    SNdata_6060 = pd.read_excel('骑享资产梳理-20210621.xlsx', sheet_name='6060')
-    SNnums_6060=SNdata_6060['SN号']
-    now_time=datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
-    now_time=datetime.datetime.strptime(now_time,'%Y-%m-%d %H:%M:%S')
-    start_time=now_time-datetime.timedelta(days=31)
-    end_time=str(now_time)
-    start_time=str(start_time)
-
-    for sn in SNnums_6060.tolist():
-        res = LFPLeakCurrent.cal_LFPLeakCurrent(sn, end_time, start_time)
-        res.to_csv('BMS_LeakCurrent_'+sn+'.csv',encoding='GB18030')
+    #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_cas',
+            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)

LIB/MIDDLE/DrivingRange/UpdtFct.py

@@ -4,24 +4,24 @@ from sqlalchemy import create_engine
 import datetime
 import pdb
 
-#建立引擎
-engine = create_engine(str(r"mysql+mysqldb://%s:" + '%s' + "@%s/%s") % ('root', 'pengmin', 'localhost', 'qixiangdb'))
-#连接到qx数据库
-conn_qx = pymysql.connect(
-        host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com',
-        user='qx_cas',
-        password='Qx@123456',#Qx@123456
-        database='qx_cas',
-        charset='utf8'
-    )
-#连接到本地数据库，输出物
-conn_local = pymysql.connect(
-        host='localhost',
-        user='root',
-        password='pengmin',
-        database='qixiangdb',
-        charset='utf8'
-    )
+# #建立引擎
+# engine = create_engine(str(r"mysql+mysqldb://%s:" + '%s' + "@%s/%s") % ('root', 'pengmin', 'localhost', 'qixiangdb'))
+# #连接到qx数据库
+# conn_qx = pymysql.connect(
+#         host='rm-bp10j10qy42bzy0q77o.mysql.rds.aliyuncs.com',
+#         user='qx_cas',
+#         password='Qx@123456',#Qx@123456
+#         database='qx_cas',
+#         charset='utf8'
+#     )
+# #连接到本地数据库，输出物
+# conn_local = pymysql.connect(
+#         host='localhost',
+#         user='root',
+#         password='pengmin',
+#         database='qixiangdb',
+#         charset='utf8'
+#     )
 
 #计算下一个soc
 def getNextSoc(start_soc):
@@ -133,7 +133,7 @@ def snDayDfPreProcess(sn_day_df):
 
 
 #更新所有sn,连读多天的的factor
-def updtAllSnFct(start_date,end_date):
+def updtAllSnFct(start_date,end_date, db_engine, db_local, db_qx, sn_table_name='tb_sn_factor'):
     '''计算开始时间到结束时间的，所有sn的factor'''
     start_date_datetime=datetime.datetime.strptime(start_date,'%Y-%m-%d')#开始时间
     end_date_datetime=datetime.datetime.strptime(end_date,'%Y-%m-%d')#开始时间
@@ -141,25 +141,26 @@ def updtAllSnFct(start_date,end_date):
     i=1
     while i<=delta_day:
         end_date=(start_date_datetime+datetime.timedelta(days=i)).strftime("%Y-%m-%d")
-        updtAllSnTodayFct(start_date,end_date)#调用函数
+        updtAllSnTodayFct(start_date,end_date, db_engine, db_local, db_qx, sn_table_name)#调用函数
         # print('update all sn factor from '+start_date+" to "+end_date)
         start_date=end_date
         i+=1#自加
+
 #更新所有sn,一天的factor
-def updtAllSnTodayFct(start_date,end_date):
+def updtAllSnTodayFct(start_date,end_date, db_engine, db_local, db_qx, sn_table_name):
     ''''更新今天所有sn的factorx信息，start_date和end_date相隔一天。此处还可优化'''
-    conn_local = pymysql.connect(
-        host='localhost',
-        user='root',
-        password='pengmin',
-        database='qixiangdb',
-        charset='utf8'
-        )
+    # conn_local = pymysql.connect(
+    #     host='localhost',
+    #     user='root',
+    #     password='pengmin',
+    #     database='qixiangdb',
+    #     charset='utf8'
+    #     )
     
     start_date_str="'"+start_date+"'"
     end_date_str="'"+end_date+"'"
     sql_cmd="select * from drive_info where time between "+start_date_str+" and "+end_date_str+" and distance!=0;"
-    range_soc_df = pd.read_sql(sql_cmd, conn_qx)#使用read_sql方法查询qx数据库
+    range_soc_df = pd.read_sql(sql_cmd, db_qx)#使用read_sql方法查询qx数据库
 
     #筛选出所有当日数据之后，筛选当日有更新的sn
     today_sn_list=range_soc_df['name'].unique().tolist()#[:100]#先一次更新5个
@@ -170,15 +171,15 @@ def updtAllSnTodayFct(start_date,end_date):
         #寻找factor_df，里面是否有sn号，如果没有sn对应信息，则新增信息。
         sn_str="'"+sn+"'"
         update_today_factor_flg=True
-        sql_cmd3="select sn,date,a0,a1,a2,a3,a4 from tb_sn_factor where date="+start_date_str+" and sn="+sn_str
-        factor_today_df=pd.read_sql(sql_cmd3, conn_local)#使用read_sql方法查询local数据库
+        sql_cmd3="select sn,date,a0,a1,a2,a3,a4 from {} where date=".format(sn_table_name)+start_date_str+" and sn="+sn_str
+        factor_today_df=pd.read_sql(sql_cmd3, db_local)#使用read_sql方法查询local数据库
         if len(factor_today_df)>=1:
-            print(sn+' '+start_date_str+' factor exist in table! Factor not update.')
+            # print(sn+' '+start_date_str+' factor exist in table! Factor not update.')
             update_today_factor_flg=False
 
-        sql_cmd2="select sn,date,a0,a1,a2,a3,a4 from tb_sn_factor where date<"+start_date_str+" and sn="+sn_str
+        sql_cmd2="select sn,date,a0,a1,a2,a3,a4 from {} where date<".format(sn_table_name)+start_date_str+" and sn="+sn_str
         #此处可以限定每次查询的数量，例如不高于5行
-        factor_df=pd.read_sql(sql_cmd2, conn_local)#使用read_sql方法查询local数据库
+        factor_df=pd.read_sql(sql_cmd2, db_local)#使用read_sql方法查询local数据库
 
         #按照sn号和日期进行去重，避免运行时重复产生factor数据，保留第一次出现的行。
         factor_df=factor_df.drop_duplicates(subset=['sn','date'],keep='first')
@@ -218,10 +219,10 @@ def updtAllSnTodayFct(start_date,end_date):
     
     #将today_sn_fct_df写入到数据库中，今天所有factor更新的系数，一次写入。
     if len(today_sn_fct_df)>=1:
-        today_sn_fct_df.to_sql('tb_sn_factor',con=engine,chunksize=10000,if_exists='append',index=False)
+        today_sn_fct_df.to_sql(sn_table_name,con=db_engine,chunksize=10000,if_exists='append',index=False)
 
 #更新一个sn，连续多天的factor
-def updtOneSnFct(sn,start_date,end_date):
+def updtOneSnFct(sn,start_date,end_date,db_engine, db_local, db_qx, sn_table_name='tb_sn_factor'):
     '''计算开始时间到结束时间的，一个sn的所有factor。
     重复多次调用，updtOneSnTodayFct。
     '''
@@ -232,27 +233,27 @@ def updtOneSnFct(sn,start_date,end_date):
     while i<=delta_day:
         end_date=(start_date_datetime+datetime.timedelta(days=i)).strftime("%Y-%m-%d")
         # print('update one '+sn+'factor from '+start_date+" to "+end_date)
-        updtOneSnTodayFct(sn,start_date,end_date)#调用函数,更新当日的factor。
+        updtOneSnTodayFct(sn,start_date,end_date,db_engine, db_local, db_qx, sn_table_name)#调用函数,更新当日的factor。
         start_date=end_date
         i+=1#自加
 #更新一个sn,一天的factor
-def updtOneSnTodayFct(sn,start_date,end_date):
+def updtOneSnTodayFct(sn,start_date,end_date,db_engine, db_local, db_qx, sn_table_name):
     '''更新一个sn,一天的factor。'''
     #重新建立连接,更新数据库
-    conn_local = pymysql.connect(
-        host='localhost',
-        user='root',
-        password='pengmin',
-        database='qixiangdb',
-        charset='utf8'
-        )
+    # conn_local = pymysql.connect(
+    #     host='localhost',
+    #     user='root',
+    #     password='pengmin',
+    #     database='qixiangdb',
+    #     charset='utf8'
+    #     )
 
     start_date_str="'"+start_date+"'"
     end_date_str="'"+end_date+"'"
     sn_str="'"+sn+"'"
     sql_cmd="select * from drive_info where time between "+start_date_str+" and "+end_date_str+\
     " and distance!=0 and name="+sn_str
-    range_soc_df = pd.read_sql(sql_cmd, conn_qx)#使用read_sql方法查询qx数据库
+    range_soc_df = pd.read_sql(sql_cmd, db_qx)#使用read_sql方法查询qx数据库
 
     if len(range_soc_df)>0:
         #筛选出所有当日数据之后，筛选当日有更新的sn
@@ -265,14 +266,14 @@ def updtOneSnTodayFct(sn,start_date,end_date):
             sn_str="'"+sn+"'"
 
             update_today_factor_flg=True
-            sql_cmd3="select sn,date,a0,a1,a2,a3,a4 from tb_sn_factor where date="+start_date_str+" and sn="+sn_str
-            factor_today_df=pd.read_sql(sql_cmd3, conn_local)#使用read_sql方法查询local数据库
+            sql_cmd3="select sn,date,a0,a1,a2,a3,a4 from {} where date=".format(sn_table_name)+start_date_str+" and sn="+sn_str
+            factor_today_df=pd.read_sql(sql_cmd3, db_local)#使用read_sql方法查询local数据库
             if len(factor_today_df)>=1:
-                print(sn+' '+start_date_str+' factor exist in table! Factor not update.')
+                # print(sn+' '+start_date_str+' factor exist in table! Factor not update.')
                 update_today_factor_flg=False
 
-            sql_cmd2="select sn,date,a0,a1,a2,a3,a4 from tb_sn_factor where date<="+start_date_str+" and sn="+sn_str
-            factor_df=pd.read_sql(sql_cmd2, conn_local)#使用read_sql方法查询local数据库
+            sql_cmd2="select sn,date,a0,a1,a2,a3,a4 from {} where date<=".format(sn_table_name)+start_date_str+" and sn="+sn_str
+            factor_df=pd.read_sql(sql_cmd2, db_local)#使用read_sql方法查询local数据库
             #按照sn号和日期进行去重，避免运行时重复产生factor数据，保留第一次出现的行。
             factor_df=factor_df.drop_duplicates(subset=['sn','date'],keep='first')
             # pdb.set_trace()
@@ -313,13 +314,13 @@ def updtOneSnTodayFct(sn,start_date,end_date):
         
         # #将today_sn_fct_df写入到数据库中
         if len(today_sn_fct_df)>=1:
-            today_sn_fct_df.to_sql('tb_sn_factor',con=engine,chunksize=10000,if_exists='append',index=False)
+            today_sn_fct_df.to_sql(sn_table_name,con=db_engine,chunksize=10000,if_exists='append',index=False)
             # print(sn+' factor will be update in table tb_sn_factor!')
         return sn_factor_df_new
 
 
 #更新最新的factor，一天调用一次。
-def updtNewestFctTb():
+def updtNewestFctTb(db_local, db_engine, sn_table_name='tb_sn_factor', sn_newest_table_name='tb_sn_factor_newest'):
 
     '''更新tb_sn_factor_newest，只保留最新日期的factor。
     从tb_sn_factor中，筛选最新的日期。
@@ -329,8 +330,8 @@ def updtNewestFctTb():
     current_time_str=current_time.strftime('%Y-%m-%d %H:%M:%S')#时间格式化为字符串,年-月-日 时-分-秒
     current_time_str="'"+current_time_str+"'"
 
-    sql_cmd_4="select sn,date,a0,a1,a2,a3,a4 from tb_sn_factor where date<"+current_time_str
-    factor_all_df = pd.read_sql(sql_cmd_4, conn_local)#使用read_sql方法查询qx数据库
+    sql_cmd_4="select sn,date,a0,a1,a2,a3,a4 from {} where date<".format(sn_table_name)+current_time_str
+    factor_all_df = pd.read_sql(sql_cmd_4, db_local)#使用read_sql方法查询qx数据库
     #筛选今天之前的所有factor，只保留最近的一天。
     sn_list=factor_all_df['sn'].unique().tolist()#筛选sn序列
     newest_sn_fct_df=pd.DataFrame([],columns=['sn','date','a0','a1','a2','a3','a4'])#声明空df
@@ -344,7 +345,7 @@ def updtNewestFctTb():
 
     #按照日期排序，只保留最近的一天,输出factor_unique_df，方法为replace。
     #本函数，每天需要运行一次，用于更新factor。
-    newest_sn_fct_df.to_sql('tb_sn_factor_newest',con=engine,chunksize=10000,\
+    newest_sn_fct_df.to_sql(sn_newest_table_name,con=db_engine,chunksize=10000,\
         if_exists='replace',index=False)
 #使用factor和soc推荐剩余续驶里程
 def calDistFromFct(input_df):
@@ -372,7 +373,7 @@ def calDistFromFct(input_df):
     row_df['vehelecrng']=range#给VehElecRng列赋值
     return row_df
 #更新当前时间对应的里程，每5min调用一次
-def updtVehElecRng(input_time='2021-07-29 12:01:00'):
+def updtVehElecRng(db_qx, db_local, db_engine, range_table_name='tb_sn_factor_soc_range', sn_newest_table_name='tb_sn_factor_newest', input_time='2021-07-29 12:01:00'):
     '''更新续驶里程，到tb_sn_factor_soc_range。
     部署时设置每5min更新一次。
     '''
@@ -389,14 +390,14 @@ def updtVehElecRng(input_time='2021-07-29 12:01:00'):
 
     #从drive_info里面读取，该时间段内的name,time,soc三列
     sql_cmd="select name,time,soc from drive_info where time between "+before6min_time_str+" and "+current_time_str
-    print(sql_cmd)
-    range_soc_df = pd.read_sql(sql_cmd, conn_qx)#使用read_sql方法查询qx数据库
+    # print(sql_cmd)
+    range_soc_df = pd.read_sql(sql_cmd, db_qx)#使用read_sql方法查询qx数据库
     range_soc_df.rename(columns={'name':'sn'},inplace=True)#将name列重命名为sn列
 
     #任务2，从tb_sn_factor_newest里面读取最新的factor，获取距离今天最近的一个factor list
-    sql_cmd_1="select sn,a0,a1,a2,a3,a4 from tb_sn_factor_newest"
-    print(sql_cmd_1)
-    sn_factor_newest_df_raw = pd.read_sql(sql_cmd_1, conn_local)#使用read_sql方法查询qx数据库
+    sql_cmd_1="select sn,a0,a1,a2,a3,a4 from {}".format(sn_newest_table_name)
+    # print(sql_cmd_1)
+    sn_factor_newest_df_raw = pd.read_sql(sql_cmd_1, db_local)#使用read_sql方法查询qx数据库
 
     #任务3，将range_soc_df和sn_factor_newest_df_raw，双表合并成为一个新表格。
     sn_soc_factor_df=pd.merge(range_soc_df,sn_factor_newest_df_raw,how='left',on='sn')
@@ -412,6 +413,6 @@ def updtVehElecRng(input_time='2021-07-29 12:01:00'):
         sn_soc_factor_range_df=sn_soc_factor_range_df.append(sn_soc_factor_range_row)#拼接
 
     ##任务5，将sn_soc_factor_range_df写入到tb_sn_factor_soc_range中,使用替换关系。
-    sn_soc_factor_range_df.to_sql('tb_sn_factor_soc_range',con=engine,chunksize=10000,\
+    sn_soc_factor_range_df.to_sql(range_table_name,con=db_engine,chunksize=10000,\
         if_exists='replace',index=False)