52 lines
1.2 KiB
Python
52 lines
1.2 KiB
Python
from functools import reduce
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import multiprocessing
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import collections
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import os
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from pprint import pprint
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import itertools
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Scientist = collections.namedtuple('Scientist', [
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'name',
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'field',
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'born',
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'nobel',
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])
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scientists = (
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Scientist(name='Ada Lovelace', field='math', born=1815, nobel=False),
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Scientist(name='Emmy Noether', field='math', born=1882, nobel=False),
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Scientist(name='Marie Curie', field='physics', born=1867, nobel=True),
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Scientist(name='Tu Youyou', field='chemistry', born=1930, nobel=True),
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Scientist(name='Ada Yonath', field='chemistry', born=1939, nobel=True),
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Scientist(name='Vera Rubin', field='astronomy', born=1928, nobel=False),
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Scientist(name='Sally Ride', field='physics', born=1951, nobel=True),
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)
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#pprint(scientists)
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#print()
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import time
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def transform(x):
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print(f'Processing {os.getpid()} work record {x.name}')
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time.sleep(1)
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result = {'name': x.name, 'age': 2021 - x.born}
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print(f'Done processing {os.getpid()} record {x.name}')
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return result
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start = time.time()
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pool = multiprocessing.Pool()
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result = pool.map(transform, scientists)
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#result = tuple(map(
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# transform,
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# scientists
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#))
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end = time.time()
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print(f'Time to complete: {end-start} \n')
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pprint(result)
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