线程池

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Python 线程池的两种实现

创建和销毁线程对象都会消耗系统资源和时间， 线程池的原理就是复用已创建的线程对象执行操作，以此来提高程序效率。 具体实现：开启 n 个线程无限循环地从工作队列中获取任务执行。

利用 并发未来包

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import time
from concurrent.futures import ThreadPoolExecutor, as_completed


def task(n):
    """任务定义"""
    time.sleep(2)
    return n + 10


with ThreadPoolExecutor(max_workers=4) as executor:
    # 1.map 方式
    iter_args = range(9)
    res_list = executor.map(task, iter_args)
    for i in res_list:
        print("map: ", i)

    # 2.submit + as_completed 组合
    future_list = [executor.submit(task, j) for j in range(9)]
    for future in as_completed(future_list):
        data = future.result()
        print("submit + as_completed: ", data)

参考 官方文档

自定义

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import time
from queue import Queue
from threading import Thread, current_thread


class Work(Thread):
    def __init__(self, work_queue: Queue):
        Thread.__init__(self)
        self.work_queue = work_queue
        self.start()

    def run(self) -> None:
        while True:
            try:
                do, args = self.work_queue.get(block=False)
                do(args)
                self.work_queue.task_done()
            except Exception as e:
                print(e)
                break


class WorkManager:
    def __init__(self, max_workers=3):
        self.max_workers = max_workers
        self.work_queue = Queue()
        self.threads = []

    def submit(self, task, args):
        """提交任务"""
        self.work_queue.put((task, args))

    def wait_all_completed(self):
        self.threads = [Work(self.work_queue) for _ in range(self.max_workers)]
        for i in self.threads:
            if i.is_alive():
                i.join()


def my_task(n):
    """任务定义"""
    time.sleep(2)
    print(n + 10, current_thread())
    return n + 10


if __name__ == '__main__':
    work_manager = WorkManager(max_workers=3)
    [work_manager.submit(my_task, i) for i in range(9)]
    work_manager.wait_all_completed()