引入

from concurrent.futures import ThreadPoolExecutor2、使用線程池

一個(gè)簡單的線程池使用案例

from concurrent.futures import ThreadPoolExecutorimport timepool = ThreadPoolExecutor(10, ’Python’)def fun(): time.sleep(1) print(1, end=’’)if __name__ == ’__main__’: # 列表推導(dǎo)式 [pool.submit(fun) for i in range(20) if True]

from concurrent.futures import ThreadPoolExecutorimport timepool = ThreadPoolExecutor(10, ’Python’)def fun(arg1,arg2): time.sleep(1) print(arg1, end=’ ’) print(arg2, end=’ ’)if __name__ == ’__main__’: # 列表推導(dǎo)式 [pool.submit(fun,i,i) for i in range(20) if True] # 單個(gè)線程的執(zhí)行 task = pool.submit(fun,’Hello’,’world’) # 判斷任務(wù)執(zhí)行狀態(tài) print(f’task status {task.done()}’) time.sleep(4) print(f’task status {task.done()}’) # 獲取結(jié)果的函數(shù)是阻塞的，所以他會(huì)等線程結(jié)束之后才會(huì)輸出 print(task.result()) 3、獲取結(jié)果

阻塞等待

print(task.result())

批量獲取結(jié)果

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

阻塞主線程，等待執(zhí)行結(jié)束再執(zhí)行下一個(gè)業(yè)務(wù)

# 等待線程全部執(zhí)行完畢wait(pool.submit(fun,1,2),return_when=ALL_COMPLETED)print(’’)

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