Use Multi Processing in Loop using Python

Question

I have three functions that I want to use async in Python in a loop

how can I use all 3 functions in a loop?

using multi-processing I have also mentioned the desired result

def sum(a, b):
    sum= a+b
    return sum

def multi(a, b):
    mutli= a*b
    return multi

def divide(a, b):
    divide= a/b
    return divide

final_data = [{'a':1, 'b':3},{'a':7, 'b':5},{'a':6, 'b':4}]
for data in final :
    sum_value = sum(data['a'], data['b']
    multi_value = multi(data['a'], data['b']
    divide_value = divide(data['a'], data['b']

#desired final output 

final_data = [{'a':1, 'b':3, 'sum_value':4, 'multi_value':3, 'divide_value':0.34},{'a':7, 'b':5,'sum_value':12, 'multi_value':35, 'divide_value':1.4},{'a':6, 'b':4,'sum_value':10, 'multi_value':24, 'divide_value':1.5}]

Answer 1

Interpreting the question as being how to use asynchronous threads then one possibility could be:

from multiprocessing.pool import ThreadPool
from functools import partial
import json  # used only for output presentation


def run(a, b, func):
    s, v = func(a, b)
    return s, round(v, 2)


def add(a, b):
    return "sum_value", a + b


def multiply(a, b):
    return "multi_value", a * b


def divide(a, b):
    return "divide_value", a / b


def main():
    data = [{"a": 1, "b": 3}, {"a": 7, "b": 5}, {"a": 6, "b": 4}]
    with ThreadPool() as pool:
        for d in data:
            p = partial(run, *d.values())
            for s, v in pool.map_async(p, (add, multiply, divide)).get():
                d[s] = v

    print(json.dumps(data, indent=2))


if __name__ == "__main__":
    main()

Output:

[
  {
    "a": 1,
    "b": 3,
    "sum_value": 4,
    "multi_value": 3,
    "divide_value": 0.33
  },
  {
    "a": 7,
    "b": 5,
    "sum_value": 12,
    "multi_value": 35,
    "divide_value": 1.4
  },
  {
    "a": 6,
    "b": 4,
    "sum_value": 10,
    "multi_value": 24,
    "divide_value": 1.5
  }
]