python高级模块concurrent 进程与线程效率对比

最近项目中用到了多进程来算模型的特征，看看python高级库的多进程与多线程的效率

from concurrent.futures import ProcessPoolExecutor, ThreadPoolExecutor
from concurrent import futures
import time


class Fast(object):

    @staticmethod
    def get_data(seq):

        time.sleep(0.02)
        return seq


if __name__ == '__main__':
    data_list_p = []
    data_list_t = []
    data_list_ = []

    # 进程
    def main_p():
        fast_p = Fast()
        with ProcessPoolExecutor(max_workers=8) as executor:
            future = [executor.submit(fast_p.get_data, i) for i in range(100)]
            for i in futures.as_completed(future):
                data_list_p.append(i.result())
        print("进程", data_list_p)
    start = time.time()
    main_p()
    end = time.time()
    print(end - start, "进程")

    # 线程
    def main_t():
        fast_t = Fast()
        with ThreadPoolExecutor(max_workers=8) as executor:
            future = [executor.submit(fast_t.get_data, i) for i in range(100)]
            futures.as_completed(future)
            for i in futures.as_completed(future):
                data_list_t.append(i.result())
        print("线程", data_list_t)
    start_t = time.time()
    main_t()
    end_t = time.time()
    print(end_t - start_t, "线程")

    # 原始
    start_ = time.time()
    fast = Fast()
    [data_list_.append(fast.get_data(i)) for i in range(100)]
    print(data_list_)

    end_ = time.time()
    print(end_ - start_)

输出如下：

小结：io频繁推荐多线程，计算频繁推荐多进程