How to use MYSQL select query with threading without duplicating the select query results?

Question

Short context: I am using mysql table to select a value, by using an API+value i fetch a result and the result is saved into the same table.

Problem : How to process multiple rows simultaneously? whenever i use a thread to start the function , it selects the same value for each thread (i.e cursor returns same value for each thread). i need different value for each thread to process. so that i will reduce some time.

My program is

import requests
import os
import json
import pymysql
import threading

conn = pymysql.connect(host='localhost', user=USER, passwd=PASSWORD, db='sampledb',charset='utf8mb4',autocommit=True)

url = "http://www.someapi.com/somelink/"

cur = conn.cursor()

def main():
    cur.execute("select asset_id from getprocessid where status =%s LIMIT 1",("uploaded",))
    idofassets = cur.fetchone()[0]
    req = requests.Session()
    resp = req.get(url+str(idofassets))
    resp_json = json.loads(resp.text)
    actual = resp_json['getResponse']
    cur.execute("update getprocessid set class = %s ,status =%s where asset_id = %s",(str(actual),"completed",str(idofasset),))

while True:

    # For threading purpose i added

    thread1 = threading.Thread(target=main)
    thread2 = threading.Thread(target=main)
    thread3 = threading.Thread(target=main)

    thread1.start()
    thread2.start()
    thread3.start()

    thread1.join()
    thread2.join()
    thread3.join()

Answer 1

Your problem seems to be divided into two main different tasks:

1 - Fetching the results from the getprocessid MySQL table

2 - Processing the result and updating the same table (but different fields)

So one way to optimize your code is to have a thread (it could be the main thread) do step 1 and then divide the problem in step 2 among your 3 threads:

import requests
import os
import json
import pymysql
import threading
#you can create these dynamically if you 
#want more (or less) threads
batches = [[], [], []]

conn = pymysql.connect(host='localhost', user=USER, 
  passwd=PASSWORD, 
db='sampledb',charset='utf8mb4',autocommit=True)

url = "http://www.someapi.com/somelink/"

cur = conn.cursor()

def fetch_and_split():
    cur.execute("select asset_id from getprocessid 
      where status =%s LIMIT 1",("uploaded",))
    results = cur.fetchall()
    count = 0
    #this populates the lists to be processed with the ids
    while count < size(results):
        cur_batch = batches[size(batches) % count ]
        cur_batch.append(results[count][0])
        count++

def process_and_update(batch):
    #each thread receives its own list
    for idofassets in batch:
        req = requests.Session()
        resp = req.get(url+str(idofassets))
        resp_json = json.loads(resp.text)
        actual = resp_json['getResponse']
        cur.execute("update getprocessid set class = %s 
          ,status =%s where asset_id = %s", 
          (str(actual),"completed",str(idofasset),))


while True:

    # For threading purpose i added
    # The main thread splits the results
    fetch_and_split()    
    # The other threads process the 
    # results and update the values
    thread1 = threading.Thread(target=process_and_update, args=(batches[0],))
    thread2 = threading.Thread(target=process_and_update, args=(batches[1],))
    thread3 = threading.Thread(target=process_and_update, args=(batches[2],))

    thread1.start()
    thread2.start()
    thread3.start()

    thread1.join()
    thread2.join()
    thread3.join()