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ProcessPoolExecutor

我們使用 ProcessPoolExecutor 定義程序池。

任務沒有返回值

import multiprocessing
from concurrent.futures import ProcessPoolExecutor
import time


def my_task():
    for i in range(3):
        print(f'{multiprocessing.current_process().pid} - {i}')
        time.sleep(1)


if __name__ == '__main__':
    with ProcessPoolExecutor(max_workers=3) as executor:
        executor.submit(my_task)
        executor.submit(my_task)
        executor.submit(my_task)

 

任務有返回值

import multiprocessing
from concurrent.futures import ProcessPoolExecutor
import time
import random


def my_task():
    r = random.randint(1, 100)
    time.sleep(1)
    print(f'{multiprocessing.current_process().pid} - {r}')
    return r


if __name__ == '__main__':
    with ProcessPoolExecutor(max_workers=3) as executor:
        future1 = executor.submit(my_task)
        future2 = executor.submit(my_task)
        future3 = executor.submit(my_task)

        # result 會阻塞
        print(future3.result())
        print(future2.result())
        print(future3.result())
 

資料並行

import multiprocessing
from concurrent.futures import ProcessPoolExecutor
import time


def my_task(x):
    print(f'{multiprocessing.current_process().pid} - {x}')
    return pow(x, 2)


if __name__ == '__main__':
    with ProcessPoolExecutor(max_workers=3) as executor:
        executor.map(my_task, range(100))

 

Pool

import multiprocessing
import time
from multiprocessing import Pool


def my_task():
    for i in range(3):
        print(f'{multiprocessing.current_process().pid} - {i}')
        time.sleep(1)


def my_fun(x):
    print(f'{multiprocessing.current_process().pid} - {x}')
    return pow(x, 2)


if __name__ == '__main__':
    with Pool(processes=4) as pool:
        # apply 同步執行，會阻塞
        res = pool.apply(my_task)

        # apply_async 非同步執行
        res = pool.apply_async(my_task)
        print(res.get(timeout=5))

        # 資料併發
        print(pool.map(my_fun, list(range(100))))

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– 聲 明：轉載請註明出處
– Last Updated on 2018-10-14
– Written by ShangBo on 2018-10-14
– End