浅谈一下python线程池简单应用

threadPool = ThreadPoolExecutor(max_workers=self.max_workers, thread_name_prefix="test_")

from concurrent.futures import ThreadPoolExecutor # 导入ThreadPoolExecutor模块
import time
 
max_workers = 5
t = []
t1 = time.time()
 
# 作为线程任务的函数
def task(x, y):
    return x + y
 
threadPool = ThreadPoolExecutor(max_workers)    # 创建最大线程数为max_workers的线程池
 
for i in range(20):     # 循环向线程池中提交task任务
    future = threadPool.submit(task, i, i+1)
    t.append(future)
 
# 若不需要获取返回值，则可不需要下面两行代码
for i in t:
    print(i.result())   # 获取每个任务的返回值，result()会阻塞主线程
 
threadPool.shutdown()   # 阻塞主线程，所有任务执行完后关闭线程池
print(time.time() - t1)

from concurrent.futures import ThreadPoolExecutor	# 导入ThreadPoolExecutor模块
 
max_workers = 5
t = []
t1 = time.time()
 
# 作为线程任务的函数
def task(x):
    return x + (x + 1)
 
args = (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
 
with ThreadPoolExecutor(max_workers) as threadPool:   # 创建最大线程数为max_workers的线程池
    results = threadPool.map(task, args)    # 启动线程,并收集每个线任务的返回结果
 
    # 若无返回值，则可不需要下面两行代码
    for i in results:
        print(i)   

from concurrent.futures import ThreadPoolExecutor, as_completed
import time
 
max_workers = 5
t = []
t1 = time.time()
 
# 作为线程任务的函数
def task(x, y):
    return x + y
 
def handle_result(future):
    print(future.result())
 
with ThreadPoolExecutor(max_workers) as threadPool:    # 创建最大线程数为max_workers的线程池
 
    for i in range(20):     # 循环向线程池中提交task任务
        future = threadPool.submit(task, i, i+1)
        t.append(future)
 
    # 若不需要获取返回值，则可不需要下面两行代码
    for future in as_completed(t):  # as_completed,哪个先完成就先处理哪个，会阻塞主线程，直到完成所有，除非设置timeout
        future.add_done_callback(handle_result)