from functools import reduce
import multiprocessing
import collections
import os
from pprint import pprint
import itertools

Scientist = collections.namedtuple('Scientist', [
    'name',
    'field',
    'born',
    'nobel',
])

scientists = (
    Scientist(name='Ada Lovelace', field='math', born=1815, nobel=False),
    Scientist(name='Emmy Noether', field='math', born=1882, nobel=False),
    Scientist(name='Marie Curie', field='physics', born=1867, nobel=True),
    Scientist(name='Tu Youyou', field='chemistry', born=1930, nobel=True),
    Scientist(name='Ada Yonath', field='chemistry', born=1939, nobel=True),
    Scientist(name='Vera Rubin', field='astronomy', born=1928, nobel=False),
    Scientist(name='Sally Ride', field='physics', born=1951, nobel=True),
)

#pprint(scientists)
#print()

import time

def transform(x):
    print(f'Processing {os.getpid()} work record {x.name}')
    time.sleep(1)
    result = {'name': x.name, 'age': 2021 - x.born}
    print(f'Done processing {os.getpid()} record {x.name}')
    return result
    
    
start = time.time()

pool = multiprocessing.Pool()
result = pool.map(transform, scientists)

#result = tuple(map(
#    transform,
#    scientists
#))

end = time.time()

print(f'Time to complete: {end-start} \n')
pprint(result)