import  pymysql
import  pandas as  pduser =  ''  
password =  ''  
dbName =  ''   
dbHost =  ''  
dbPort =  8888 
con =  pymysql. connect( host= dbHost, port= dbPort, user= user, password= password, database= dbName, charset= 'utf8' ) 
cursor =  con. cursor( ) 
head =  [ "Id" ,  "Url" ] 
t0,  t1,  name =  '' ,  '' ,  '' 
sql_select =  "SELECT id, Url "  \"FROM xxx "  \"WHERE createTime >= ('{}') and createTime <= ('{}') and name = ('{}')" . format ( t0,  t1,  name) 
cursor. execute( sql_select) 
cds =  cursor. fetchall( ) 
df =  pd. DataFrame( cds) 
cursor. close( ) 
con. close( ) 
import  logging
import  osif  os. path. exists( 'log_retry.log' ) : os. remove( 'log_retry.log' ) logging. basicConfig( level= logging. INFO, format = '%(asctime)s %(filename)s[line:%(lineno)d] %(levelname)s %(message)s' , datefmt= '%a, %d %b %Y %H:%M:%S' , filename= 'log_retry.log' , filemode= 'w' ) 
count =  0 
try : logging. info( '############# TOTAL number ############:{}, ' . format ( count) ) 
except : logging. error( ) 
from  kafka import  KafkaProducer
import  json
def  kfk_send ( msg) : kafka_topic =  ''  kafka_bootstrap_servers =  [ '172.25.214.75:9092' ,  '172.25.214.76:9092' ,  '172.25.214.78:9092' ] producer =  KafkaProducer( bootstrap_servers= kafka_bootstrap_servers, value_serializer= lambda  v:  json. dumps( v) . encode( 'utf-8' ) ) producer. send( kafka_topic,  value= msg) producer. flush( ) head =  [ ] 
value =  [ ] 
ndata =  dict ( zip ( head,  value) ) 
kfk_send( ndata) 
from  concurrent. futures import  ThreadPoolExecutor
from  flask import  Flask,  request
import  json
from  time import  sleepexecutor =  ThreadPoolExecutor( max_workers= 4 ) 
app =  Flask( __name__) def  task ( p1,  p2) : print ( "Hello" ) @app. route ( "/" ,  methods= [ "POST" ] ) 
def  main ( ) : request_dict =  json. loads( request. data) p1 =  request_dict[ "p1" ] p2 =  request_dict[ "p2" ] executor. submit( task,  p1,  p2)  sleep( 3 ) return  "Get your POST!!!" if  __name__ ==  '__main__' : app. run( ) 
from  multiprocessing import  Processdef  infer ( i,  filelist) : print ( i,  filelist) if  __name__ ==  '__main__' : img_list =  [ ] num_process =  5 num =  int ( len ( img_list)  /  num_process) process_list =  [ ] for  i in  range ( num_process) : filelist =  img_list[ i *  num: ( i +  1 )  *  num] if  i ==  num_process -  1 : filelist =  img_list[ i *  num: ] process_list. append( Process( target= infer,  args= ( i,  filelist) ) ) [ p. start( )  for  p in  process_list] [ p. join( )  for  p in  process_list]