python 中线程、进程、协程

1.线程和线程池

 t1 =  threading.Thread(target = task, args=("a"))
 t2 =  threading.Thread(target = task, args=("b"))
 with concurrent.futures.ThreadPoolExecutor(max_workers=3) as executor:
     executor.map(task, ["A,B,C,D"])
threads = [threading.Thread(target = increment()) for _ in range(4)]
 for t in threads:
     t.start()
 for t in threads:
     t.join()
count = 0
lock = threading.Lock()
def increment():
    global count
    for i in range(100):
      with lock:
        count +=1

2.进程和进程池

def send(conn):
    conn.send("helloworld")
def receive(conn):
    print(conn.recv())
 val =  multiprocessing.Value("i",1) // 共享变量
 queue = multiprocessing.Queue()
    process = multiprocessing.Process(target = worker,args= (queue,))
    process2 = multiprocessing.Process(target = worker, args=(queue,))
    process.start()
    process2.start()
    process.join()
    process2.join()
    with concurrent.futures.ProcessPoolExecutor(5) as executor:
        executor.map(worker,["a","b","c","d"])
    processes = [multiprocessing.Process(target = printVal, args =(val,))for _ in range(4)]
    for process in processes:
        process.start()
    for process in processes:
        process.join()

asyncio  

async def cpu_bound_task(n):
    total = 0
    for i in range(10**8):
        total += i*n
    print(f"total is {total}")
    await asyncio.sleep(10)
    return total
def event_loop(n):
    asyncio.run(cpu_bound_task(n))
async def main():
    loop = asyncio.get_event_loop()
    with ProcessPoolExecutor() as pool:
        result = await loop.run_in_executor(pool,cpu_bound_task, 10)
        print(f"result is {result}")
for i in range(4):
        p = multiprocessing.Process(target= event_loop, args=(10,))
        pList.append(p)
        p.start()
    for p in pList:
        p.join()
asyncio.run(main())
print("主线程执行结束")

五、总结

如何选择？

1. CPU 密集型任务（科学计算、数据分析） → 多进程
2. I/O 密集型任务（爬虫、数据库查询） → 多线程 或 asyncio
3. 高并发任务（网络请求、日志处理） → asyncio