異步【ThreadPoolExecutor】和【ProcessPoolExecutor】運算比較

from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor, as_completed
import time
number_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]


def evaluate_item(x):
    # 計算總和，這裏只是爲了消耗時間
    result_item = count(x)
    # 打印輸入和輸出結果
    print(result_item, end=", ")


def count(number):
    for i in range(0, 10000000):
        i = i + 1
    return i * number


if __name__ == "__main__":
    # 順序執行------------------------------------------
    start_01 = time.time()
    for item in number_list:
        evaluate_item(item)
    end_01 = time.time() - start_01
    print(f"\n順序執行：{end_01}秒")

    # 線程池執行----------------------------------------
    start_02 = time.time()
    with ThreadPoolExecutor(max_workers=5) as executor:
        futures = [executor.submit(evaluate_item, item)
                   for item in number_list]
        for future in as_completed(futures):
            future.result()
    end_02 = time.time() - start_02
    print(f"\n線程池執行：{end_02}秒")

    # 進程池--------------------------------------------
    start_03 = time.time()
    with ProcessPoolExecutor(max_workers=5) as executor:
        futures = [executor.submit(evaluate_item, item)
                   for item in number_list]
        for future in as_completed(futures):
            future.result()
    end_03 = time.time() - start_03
    print(f"進程池執行：{end_03}秒")

輸出：

10000000, 20000000, 30000000, 40000000, 50000000, 60000000, 70000000, 80000000, 90000000, 100000000, 
順序執行：6.06318211555481秒
40000000, 30000000, 10000000, 20000000, 50000000, 70000000, 80000000, 100000000, 60000000, 90000000, 
線程池執行：5.89125394821167秒
40000000, 60000000, 50000000, 80000000, 10000000, 100000000, 20000000, 70000000, 30000000, 90000000, 
進程池執行：3.3284432888031006秒