1、线程池模块

引入

from concurrent.futures import ThreadPoolExecutor

2、使用线程池

一个简单的线程池使用案例

from concurrent.futures import ThreadPoolExecutor
import time

pool = ThreadPoolExecutor(10, 'Python')

def fun():
    time.sleep(1)
    print(1, end='')


if __name__ == '__main__':
    # 列表推导式
    [pool.submit(fun) for i in range(20) if True]

from concurrent.futures import ThreadPoolExecutor
import time

pool = ThreadPoolExecutor(10, 'Python')

def fun(arg1,arg2):
    time.sleep(1)
    print(arg1, end=' ')
    print(arg2, end=' ')


if __name__ == '__main__':
    # 列表推导式
    [pool.submit(fun,i,i) for i in range(20) if True]
    # 单个线程的执行
    task = pool.submit(fun,'Hello','world')
    # 判断任务执行状态
    print(f'task status {task.done()}')
    time.sleep(4)
    print(f'task status {task.done()}')

    # 获取结果的函数是阻塞的，所以他会等线程结束之后才会输出
    print(task.result())

 3、获取结果

阻塞等待

print(task.result())

批量获取结果

for future in as_completed(all_task):
    data = future.result()

阻塞主线程，等待执行结束再执行下一个业务

# 等待线程全部执行完毕
wait(pool.submit(fun,1,2),return_when=ALL_COMPLETED)
print('')