进程池 回调函数 管道

---------------------------------------------------前进的道路都是由心来描绘的,所以,无论自己处于多么严酷的境遇之中,心头都不应为悲观的思想所萦绕..

# # ------------------------------------------------------------------------------------------------------------#

管道:
Pipe
Conn1,conn2 = Pipe()

数据共享:
M = Manager()
Dic = m.dict({‘name’:sbalex})
数据安全的问题
加锁

进程池   *****
Map:异步提交任务,参数是可迭代对象,自带close + join

Apply :同步提交任务,直接可以收到返回值

Apply_async()  异步提交任务:res.get()  阻塞效果
Close join  
回调函数:callback= func [return [xxx]]

# --------------[管道]--------------
 osError
    esError
from multiprocessing import Pipe,Process

def func(conn1,):
    msg = conn1.recv()
    print('>>>>',msg)

if __name__ == '__main__':
    conn1,conn2 = Pipe()

    p=Process(target=func,args=(conn1,))
    p.start()

    conn2.close()
    conn2.send('0J8K')

    print('主进程结束')

# --------------[数据共享]--------------

from multiprocessing import Manager,Process,Lock

def func(dic):
    l.acquire()
    dic['n'] -= 1
    l.release()

if __name__ == '__main__':
    m = Manager()
    l = Lock
    dic = m.dict({'n':88})

    p = Process(target=func, args=(dic,))

    p_lst = []

    for i in range(88):
        p_lst.append(i)

    [pp.join() for pp in p_lst]

    p.start()

# --------------[进程池子]--------------
from multiprocessing import Pool, Process
import time


def func(i):
    num = 0
    for j in range(5):
        num += i


if __name__ == '__main__':


    p_list = []
    start_time = time.time()
    for i in range(100):
        p = Process(target=func, args=(i,))
        p_list.append(p)
        p.start()
    [pp.join() for pp in p_list]
    end_time = time.time()
    print(end_time - start_time)


    s_time = time.time()
    pool = Pool(4)
    pool.map(func, range(100))
    e_time = time.time()
    x_time = e_time - s_time
    print(x_time)

# --------------[进程同步的方法]--------------
from multiprocessing import Process,Pool
import time

def func():
    num = 0
    for i in range(5):
        num+=i
    time.sleep(1)
    print(num)
    return num
if __name__ == '__main__':
    pool = Pool(4)

    for i in range(10):
        res = pool.apply(func,args=(i,))
                    #(apply同步串行)
        print(res)

# --------------[进程异步的方法]--------------
from multiprocessing import Process, Pool
import time


def func():
    num = 0
    for i in range(5):
        num += i
    time.sleep(1)
    print('>>>>', num)
    return num


if __name__ == '__main__':
    pool = Pool(4)

    r_lst = []
    for i in range(10):
        res = pool.apply_async(func, args=(i,))
                    # (apply_async异步)
        r_lst.append(res)
        print(res.get())

    pool.close()  # 不是关闭 是锁定
    pool.join()

    for j in r_lst:
        print(j.get())