mprocessing

import multiprocessing
import time
import datetime
import collections
import os
import requests
from pprint import pprint

def timer(func):
    def function_wrapper(x):
        start = datetime.datetime.now()
        func(x)
        total = datetime.datetime.now() - start
        return total
    return function_wrapper

Scientist = collections.namedtuple('Scientist', 'name, field, born, nobel')
scientists = (
    Scientist(name='Shay', field='math', born='1987', nobel=False),
    Scientist(name='Nurit', field='math', born='1988', nobel=False),
    Scientist(name='Igor', field='physics', born='1970', nobel=True),
    Scientist(name='Abdul', field='robotics', born='1960', nobel=False),
    Scientist(name='Shay', field='math', born='1987', nobel=False),
    Scientist(name='Nurit', field='math', born='1988', nobel=False),
    Scientist(name='Igor', field='physics', born='1970', nobel=True),
    Scientist(name='Abdul', field='robotics', born='1960', nobel=False),
)

def read_google():
    r = requests.get('https://www.google.com/')
    print(r.text)
    return r.status_code

def transform(x):
    print(f"Process {os.getpid()} is currently processing record: {x.name}")
    read_google()
    result = {'name': x.name, 'age': 2017 - int(x.born)}
    print(f"finished processing record: {x.name}")
    return result

pool = multiprocessing.Pool()

@timer
def map_it(your_iterator):
    result = pool.map(transform, your_iterator)
    return result

pprint(map_it(scientists))