线程 巩固

线程_apply堵塞式

'''
创建三个进程，让三个进程分别执行功能,关闭进程
Pool 创建  ，apply执行 ， close，join 关闭进程
'''
from multiprocessing import Pool
import os,time,random

def worker(msg):
    # 创建一个函数，用来使进程进行执行
    time_start = time.time()
    print("%s 号进程开始执行，进程号为 %d"%(msg,os.getpid()))
    # 使用os.getpid()获取子进程号
    # os.getppid()返回父进程号
    time.sleep(random.random()*2)
    time_end = time.time()
    print(msg,"号进程执行完毕，耗时%0.2f"%(time_end-time_start))
#     计算运行时间

if __name__ == '__main__':

    po = Pool(3)#创建三个进程
    print("进程开始")
    for i in range(3):
        # 使用for循环，运行刚刚创建的进程
        po.apply(worker,(i,))#进程池调用方式apply堵塞式
    #     第一个参数为函数名，第二个参数为元组类型的参数(函数运行会用到的形参)
    #只有当进程执行完退出后，才会新创建子进程来调用请求

    po.close()# 关闭进程池，关闭后po不再接收新的请求
    # 先使用进程的close函数关闭，后使用join函数进行等待
    po.join() # 等待po中所有子进程执行完成，必须放在close语句之后

    print("进程结束")


    '''创建->apply应用->close关闭->join等待结束'''

线程_FIFO队列实现生产者消费者

import threading # 导入线程库
import time
from queue import Queue # 队列

class Producer(threading.Thread):
    # 线程的继承类，修改 run 方法
    def run(self):
        global queue
        count = 0
        while True:
            if queue.qsize() <1000:
                for i in range(100):
                    count = count + 1
                    msg = '生成产品'+str(count)
                    queue.put(msg)#向队列中添加元素
                    print(msg)
            time.sleep(1)


class Consumer(threading.Thread):
    # 线程的继承类，修改 run 方法
    def run(self):
        global queue
        while True:
            if queue.qsize() >100 :
                for i in range(3):
                    msg = self.name + '消费了' + queue.get() #获取数据
                    # queue.get()获取到数据
                    print(msg)
            time.sleep(1)


if __name__ == '__main__':
    queue = Queue()
    # 创建一个队列

    for i in range(500):
        queue.put('初始产品'+str(i))
        # 在 queue 中放入元素 使用 put 函数

    for i in range(2):
        p = Producer()
        p.start()
    #     调用Producer类的run方法
    for i in range(5):
        c = Consumer()
        c.start()

线程_GIL最简单的例子

#解决多进程死循环
import multiprocessing

def deadLoop():
    while True:
        print("Hello")
        pass

if __name__ == '__main__':
    # 子进程死循环
    p1 = multiprocessing.Process(target=deadLoop)
    p1.start()
    # 主进程死循环
    deadLoop() 

线程_multiprocessing实现文件夹copy器 

import multiprocessing
import os
import time
import random

def copy_file(queue,file_name,source_folder_name,dest_folder_name):
    f_read = open(source_folder_name+"/"+file_name,"rb")
    f_write = open(source_folder_name+"/"+file_name,"wb")
    while True:
        time.sleep(random.random())
        content = f_read.read(1024)
        if content:
            f_write.write(content)
        else:
            break
    f_read.close()
    f_write.close()
    # 发送已经拷贝完毕的文件名字
    queue.put(file_name)

def main():
    # 获取要复制的文件夹
    source_folder_name = input("请输入要复制的文件夹名字:")
    # 整理目标文件夹
    dest_folder_name = source_folder_name + "副本"
    # 创建目标文件夹
    try:
        os.mkdir(dest_folder_name)#创建文件夹
    except:
        pass
    # 获取这个文件夹中所有的普通文件名
    file_names = os.listdir(source_folder_name)
    # 创建Queue
    queue = multiprocessing.Manager().Queue()
    # 创建线程池
    pool = multiprocessing.Pool(3)
    for file_name in file_names:
        # 向线程池中添加任务
        pool.apply_async(copy_file,args=(queue,file_name,source_folder_name,dest_folder_name))#不堵塞执行
        # 主进程显示进度
        pool.close()

        all_file_num = len(file_names)
        while True:
            file_name = queue.get()
            if file_name in file_names:
                file_names.remove(file_name)

            copy_rate = (all_file_num - len(file_names)) * 100 / all_file_num
            print("\r%.2f...(%s)" % (copy_rate, file_name) + " " * 50, end="")
            if copy_rate >= 100:
                break
        print()

if __name__ == "__main__":
            main() 

线程_multiprocessing异步 

from multiprocessing import Pool
import time
import os

def test():
    print("---进程池中的进程---pid=%d,ppid=%d--"%(os.getpid(),os.getppid()))
    for i in range(3):
        print("----%d---"%i)
        time.sleep(1)
    return "hahah"

def test2(args):
    print("---callback func--pid=%d"%os.getpid())
    print("---callback func--args=%s"%args)

if __name__ == '__main__':
    pool = Pool(3)
    pool.apply_async(func=test,callback=test2)
    # 异步执行
    time.sleep(5)

    print("----主进程-pid=%d----"%os.getpid()) 

线程_Process实例 

from multiprocessing import Process
import os
from time import sleep

def run_proc(name,age,**kwargs):

    for i in range(10):
        print("子进程运行中,名字为 = %s,年龄为 = %d,子进程 = %d..."%(name,age,os.getpid()))
        print(kwargs)
        sleep(0.5)

if __name__ == '__main__':

    print("父进程: %d"%(os.getpid()))
    pro = Process(target=run_proc,args=('test',18),kwargs={'kwargs':20})
    print("子进程将要执行")
    pro.start( )
    sleep(1)
    pro.terminate()#将进程进行终止
    pro.join()
    print("子进程已结束")

---

from multiprocessing import Process
import time
import os

#两个子进程将会调用的两个方法
def work_1(interval):

    # intercal为挂起时间
    print("work_1,父进程(%s),当前进程(%s)"%(os.getppid(),os.getpid()))
    start_time = time.time()
    time.sleep(interval)
    end_time = time.time()
    print("work_1,执行时间为%f"%(end_time-start_time))

def work_2(interval):

    print("work_2,父进程(%s),当前进程(%s)"%(os.getppid(),os.getpid()))
    start_time = time.time()
    time.sleep(2)
    end_time = time.time()
    print("work_2执行时间为:%.2f"%(end_time-start_time))

if __name__ == '__main__':

    print("进程Id:", os.getpid())
    pro1 = Process(target=work_1, args=(2,))
    pro2 = Process(target=work_2, name="pro2", args=(3,))
    pro1.start()
    pro2.start()
    print("pro2.is_alive:%s" % (pro2.is_alive()))
    print("pro1.name:", pro1.name)
    print("pro1.pid=%s" % pro1.pid)
    print("pro2.name=%s" % pro2.name)
    print("pro2.pid=%s" % pro2.pid)
    pro1.join()
    print("pro1.is_alive:", pro1.is_alive()) 

线程_Process基础语法 

"""
Process([group[,target[,name[,args[,kwargs]]]]])
group:大多数情况下用不到
target:表示这个进程实例所调用的对象 target=函数名
name:为当前进程实例的别名
args:表示调用对象的位置参数元组 args=(参数,)
kwargs:表示调用对象的关键字参数字典
"""
"""
常用方法:
is_alive( ):判断进程实例是否还在执行
join([timeout]):是否等待进程实例执行结束或等待多少秒
start():启动进程实例(创建子进程)
run():如果没有给定target函数,对这个对象调用start()方法时,
      就将执行对象中的run()方法
terminate():不管任务是否完成，立即停止
"""
"""
常用属性:
name:当前进程实例的别名,默认为Process-N,N从1开始
pid:当前进程实例的PID值
""" 

线程_ThreadLocal 

import threading
# 创建ThreadLocal对象
house = threading.local()

def process_paper():
    user = house.user
    print("%s是房子的主人,in %s"%(user,threading.current_thread().name))

def process_thread(user):
    house.user = user
    process_paper()

t1 = threading.Thread(target=process_thread,args=('Xiaoming',),name='佳木斯')
t2 = threading.Thread(target=process_thread,args=('Hany',),name='哈尔滨')
t1.start()
t1.join()
t2.start()
t2.join() 

线程_互斥锁_Lock及fork创建子进程 

"""
创建锁  mutex = threading.Lock()
锁定  mutex.acquire([blocking])
        当blocking为True时，当前线程会阻塞，直到获取到这个锁为止
        默认为True
        当blocking为False时，当前线程不会阻塞
释放  mutex.release()
"""
from threading import Thread,Lock
g_num = 0
def test1():
    global g_num
    for i in range(100000):
        mutexFlag = mutex.acquire(True)#通过全局变量进行调用函数
        # True会发生阻塞,直到结束得到锁为止
        if mutexFlag:
            g_num += 1
            mutex.release()
    print("test1--g_num = %d"%(g_num))
def test2():
    global g_num
    for i in range(100000):
        mutexFlag = mutex.acquire(True)
        if mutexFlag:
            g_num += 1
            mutex.release()
    print("----test2---g_num = %d "%(g_num))
mutex = Lock()
p1 = Thread(target=test1,)
# 开始进程
p1.start()
p2 = Thread(target=test2,)
p2.start()
print("----g_num = %d---"%(g_num))

---

fork创建子进程

import os
# fork()在windows下不可用
pid = os.fork()#返回两个值
# 操作系统创建一个新的子进程，复制父进程的信息到子进程中
# 然后父进程和子进程都会得到一个返回值，子进程为0，父进程为子进程的id号
if pid == 0:
    print("哈哈1")
else:
    print("哈哈2") 

线程_gevent实现多个视频下载及并发下载 

from gevent import monkey
import gevent
import urllib.request

#有IO操作时,使用patch_all自动切换
monkey.patch_all()

def my_downLoad(file_name, url):
    print('GET: %s' % url)
    resp = urllib.request.urlopen(url)
    # 使用库打开网页
    data = resp.read()

    with open(file_name, "wb") as f:
        f.write(data)

    print('%d bytes received from %s.' % (len(data), url))

gevent.joinall([
        gevent.spawn(my_downLoad, "1.mp4", 'http://oo52bgdsl.bkt.clouddn.com/05day-08-%E3%80%90%E7%90%86%E8%A7%A3%E3%80%91%E5%87%BD%E6%95%B0%E4%BD%BF%E7%94%A8%E6%80%BB%E7%BB%93%EF%BC%88%E4%B8%80%EF%BC%89.mp4'),
        gevent.spawn(my_downLoad, "2.mp4", 'http://oo52bgdsl.bkt.clouddn.com/05day-03-%E3%80%90%E6%8E%8C%E6%8F%A1%E3%80%91%E6%97%A0%E5%8F%82%E6%95%B0%E6%97%A0%E8%BF%94%E5%9B%9E%E5%80%BC%E5%87%BD%E6%95%B0%E7%9A%84%E5%AE%9A%E4%B9%89%E3%80%81%E8%B0%83%E7%94%A8%28%E4%B8%8B%29.mp4'),
])

---

from gevent import monkey
import gevent
import urllib.request

# 有耗时操作时需要
monkey.patch_all()

def my_downLoad(url):
    print('GET: %s' % url)
    resp = urllib.request.urlopen(url)
    data = resp.read()
    print('%d bytes received from %s.' % (len(data), url))

gevent.joinall([
        gevent.spawn(my_downLoad, 'http://www.baidu.com/'),
        gevent.spawn(my_downLoad, 'http://www.itcast.cn/'),
        gevent.spawn(my_downLoad, 'http://www.itheima.com/'),
]) 

线程_gevent自动切换CPU协程 

import gevent
def f(n):
    for i in range(n):
        print (gevent.getcurrent(), i)
        # gevent.getcurrent() 获取当前进程

g1 = gevent.spawn(f, 3)#函数名,数目
g2 = gevent.spawn(f, 4)
g3 = gevent.spawn(f, 5)
g1.join()
g2.join()
g3.join()

---

import gevent

def f(n):
    for i in range(n):
        print (gevent.getcurrent(), i)
        #用来模拟一个耗时操作，注意不是time模块中的sleep
        gevent.sleep(1)

g1 = gevent.spawn(f, 2)
g2 = gevent.spawn(f, 3)
g3 = gevent.spawn(f, 4)
g1.join()
g2.join()
g3.join()

---

import gevent
import random
import time

def coroutine_work(coroutine_name):
    for i in range(10):
        print(coroutine_name, i)
        time.sleep(random.random())

gevent.joinall([
        # 添加可以切换的协程
        gevent.spawn(coroutine_work, "work0"),
        gevent.spawn(coroutine_work, "work1"),
        gevent.spawn(coroutine_work, "work2")
])

---

from gevent import monkey
import gevent
import random
import time

# 有耗时操作时需要
monkey.patch_all()#自动切换协程
# 将程序中用到的耗时操作的代码，换为gevent中自己实现的模块

def coroutine_work(coroutine_name):
    for i in range(10):
        print(coroutine_name, i)
        time.sleep(random.random())

gevent.joinall([
        gevent.spawn(coroutine_work, "work"),
        gevent.spawn(coroutine_work, "work1"),
        gevent.spawn(coroutine_work, "work2")
]) 

线程_使用multiprocessing启动一个子进程及创建Process 的子类 

from multiprocessing import Process
import os
# 子进程执行的函数
def run_proc(name):
    print("子进程运行中,名称:%s,pid:%d..."%(name,os.getpid()))
if __name__ == "__main__":
    print("父进程为:%d..."%(os.getpid()))
    # os.getpid()获取到进程名
    pro = Process(target=run_proc,args=('test',))
    # target=函数名  args=(参数,)
    print("子进程将要执行")
    pro.start()#进程开始
    pro.join()#添加进程
    print("子进程执行结束...")

---

from multiprocessing import Process
import time
import os
# 继承Process类
class Process_Class(Process):
    def __init__(self,interval):
        Process.__init__(self)
        self.interval = interval
#     重写Process类的run方法
    def run(self):
        print("我是类中的run方法")
        print("子进程(%s),开始执行,父进程为(%s)"%(os.getpid(),os.getppid()))
        start_time = time.time()
        time.sleep(2)
        end_time = time.time()
        print("%s执行时间为:%.2f秒" % (os.getpid(),end_time-start_time))
if __name__ == '__main__':
    start_time = time.time()
    print("当前进程为:(%s)"%(os.getpid()))
    pro1 = Process_Class(2)
    # 对一个不包含target属性的Process类执行start()方法，
    # 会运行这个类中的run()方法，所以这里会执行p1.run()
    pro1.start()
    pro1.join()
    end_time = time.time()
    print("(%s)执行结束，耗时%0.2f" %(os.getpid(),end_time - start_time)) 

线程_共享全局变量(全局变量在主线程和子线程中不同) 

from threading import Thread
import time

g_num = 100

def work1():
    global g_num
    for i in range(3):
        g_num += 1
        print("----在work1函数中,g_num 是 %d "%(g_num))

def work2():
    global g_num
    print("在work2中，g_num为 %d "%(g_num))
if __name__ == '__main__':
    print("---线程创建之前 g_num 是 %d"%(g_num))
    t1 = Thread(target=work1)
    t1.start()
    t2 = Thread(target=work2)
    t2.start() 

线程_多线程_列表当做实参传递到线程中 

from threading import Thread


def work1(nums):
    nums.append('a')
    print('---在work1中---',nums)

def work2(nums):
    print("-----在work2中----,",nums)

if __name__ == '__main__':
    g_nums = [1,2,3]
    t1 = Thread(target=work1,args=(g_nums,))
    # target函数,args参数
    t1.start()

    t2 = Thread(target=work2,args=(g_nums,))
    t2.start() 

线程_threading合集 

# 主线程等待所有子线程结束才结束
import threading
from time import sleep,ctime

def sing():
    for i in range(3):
        print("正在唱歌---%d"%(i))
        sleep(2)
def dance():
    for i in range(3):
        print("正在跳舞---%d" % (i))
        sleep(2)
if __name__ == '__main__':
    print("----开始----%s"%(ctime()))
    t_sing = threading.Thread(target=sing)
    t_dance = threading.Thread(target=dance)
    t_sing.start()
    t_dance.start()
    print("----结束----%s"%(ctime()))

---

#查看线程数量
import threading
from time import sleep,ctime

def sing():
    for i in range(3):
        print("正在唱歌---%d"%i)
        sleep(1)
def dance():
    for i in range(3):
        print("正在跳舞---%d"%i)
        sleep(i)
if __name__ == '__main__':
    t_sing = threading.Thread(target=sing)
    t_dance = threading.Thread(target=dance)
    t_sing.start()
    t_dance.start()
    while True:
        length = len(threading.enumerate())
        print("当前运行的线程数为:%d"%(length))
        if length<= 1:
            break
        sleep(0.5)

---

import threading
import time

class MyThread(threading.Thread):
    # 重写 构造方法
    def __init__(self, num, sleepTime):
        threading.Thread.__init__(self)
        self.num = num
        # 类实例不同，num值不同
        self.sleepTime = sleepTime

    def run(self):
        self.num += 1
        time.sleep(self.sleepTime)
        print('线程(%s),num=%d' % (self.name, self.num))

if __name__ == '__main__':
    mutex = threading.Lock()
    t1 = MyThread(100, 3)
    t1.start()
    t2 = MyThread(200, 1)
    t2.start()

---

import threading
from time import sleep

g_num = 1

def test(sleepTime):
    num = 1 #num为局部变量
    sleep(sleepTime)
    num += 1
    global g_num #g_num为全局变量
    g_num += 1
    print('---(%s)--num=%d  --g_num=%d' % (threading.current_thread(), num,g_num))

t1 = threading.Thread(target=test, args=(3,))
t2 = threading.Thread(target=test, args=(1,))

t1.start()
t2.start()

---

import threading
import time

class MyThread1(threading.Thread):
    def run(self):
        if mutexA.acquire():
            print("A上锁了")
            mutexA.release()
            time.sleep(2)
            if mutexB.acquire():
                print("B上锁了")
                mutexB.release()
            mutexA.release()

class MyThread2(threading.Thread):
    def run(self):
        if mutexB.acquire():
            print("B上锁了")
            mutexB.release()
            time.sleep(2)
            if mutexA.acquire():
                print("A上锁了")
                mutexA.release()
            mutexB.release()
# 先看B是否上锁，然后看A是否上锁
mutexA = threading.Lock()
mutexB = threading.Lock()

if __name__ == "__main__":
    t1 = MyThread1()
    t2 = MyThread2()
    t1.start()
    t2.start()

---

多线程threading的执行顺序(不确定)

# 只能保证都执行run函数，不能保证执行顺序和开始顺序
import threading
import time

class MyThread(threading.Thread):
    def run(self):
        for i in range(3):
            time.sleep(1)
            msg = "I'm "+self.name+' @ '+str(i)
            print(msg)
def test():
    for i in range(5):
        t = MyThread()
        t.start()
if __name__ == '__main__':
    test()

---

多线程threading的注意点

import threading
import time

class MyThread(threading.Thread):
    # 重写threading.Thread类中的run方法
    def run(self):
        for i in range(3):#开始线程之后循环三次
            time.sleep(1)
            msg = "I'm "+self.name+'@'+str(i)
            # name属性是当前线程的名字
            print(msg)
if __name__ == '__main__':
    t = MyThread()#使用threading.Thread的继承类
    t.start()#继承线程之后要开始运行 start方法 

线程_进程间通信Queue合集 

# Queue的工作原理
from multiprocessing import Queue
q = Queue(3)#初始化一个Queue对象，最多可接收3条put消息
q.put("Info1")
q.put("Info2")
print("q是否满了",q.full())#查看q是否满了
q.put("Info3")
print("q是否满了",q.full())
try:
    q.put_nowait("info4")
except:
    print("消息列队已经满了,现有消息数量为:%s"%(q.qsize()))
    # 使用q.qsize()查看数量
# 先验证是否满了，再写入
if not q.full():
    q.put_nowait("info4")
# 读取信息时，先判断消息列队是否为空，再读取

if not q.empty():
    print("开始读取")
    for i in range(q.qsize()):
        print(q.get_nowait())

---

from multiprocessing import Queue
from multiprocessing import Process
import os,time,random

def  write(q):
    for value in ['a','b','c']:
        print("Put %s to q ..."%(value))
        q.put(value)
        time.sleep(random.random())

def read(q):
    while True:
        if not q.empty():
            value = q.get(True)
            print("Get %s from Queue..."%(value))
            time.sleep(random.random())
        else:
            break

if __name__ == '__main__':
    #父进程创建Queue，传给各个子进程
    q = Queue()
    pw = Process(target=write,args=(q,))
    pr = Process(target=read,args=(q,))
    pw.start()
    # 等待pw结束
    pw.join()
    pr.start()
    pr.join()
    print("数据写入读写完成")

---

from multiprocessing import Manager,Pool
import os,time,random
# 名称为reader 输出子进程和父进程 os  输出q的信息

def reader(q):
    print("reader启动,子进程:%s,父进程:%s"%(os.getpid(),os.getppid()))
    for i in range(q.qsize()):#在0 ~ qsize范围内
        print("获取到queue的信息:%s"%(q.get(True)))

def writer(q):
    print("writer启动,子进程:%s,父进程:%s"%(os.getpid(),os.getppid()))
    for i in "HanYang":#需要写入到 q 的数据
        q.put(i)

if __name__ == '__main__':
    print("%s 开始 "%(os.getpid()))
    q = Manager().Queue()#Queue使用multiprocessing.Manager()内部的
    po = Pool()#创建一个线程池
    po.apply(writer,(q,))#使用apply阻塞模式
    po.apply(reader,(q,))
    po.close()#关闭
    po.join()#等待结束
    print("(%s) 结束"%(os.getpid())) 

线程_进程池 

from multiprocessing import Pool
import os,time,random
def worker(msg):
    start_time = time.time()
    print("(%s)开始执行，进程号为(%s)"%(msg,os.getpid()))
    time.sleep(random.random()*2)
    end_time = time.time()
    print(msg,"(%s)执行完毕，执行时间为:%.2f"%(os.getpid(),end_time-start_time))
if __name__ == '__main__':
    po = Pool(3)#定义一个进程池，最大进程数为3
    for i in range(0,6):
        po.apply_async(worker,(i,))
        # 参数:函数名,(传递给目标的参数元组)
        # 每次循环使用空闲的子进程调用函数,满足每个时刻都有三个进程在执行
    print("---开始---")
    po.close()
    po.join()
    print("---结束---")
"""
multiprocessing.Pool的常用函数:
apply_async(func[,args[,kwds]]):
    使用非阻塞方式调用func,并行执行
    args为传递给func的参数列表
    kwds为传递给func的关键字参数列表
apply(func[,args[,kwds]])
    使用堵塞方式调用func  
    堵塞方式：必须等待上一个进程退出才能执行下一个进程
close()
    关闭Pool，使其不接受新的任务
terminate()
    无论任务是否完成，立即停止
join()
    主进程堵塞，等待子进程的退出
    注:必须在terminate，close函数之后使用
""" 

线程_可能发生的问题 

from threading import Thread
g_num = 0
def test1():
    global g_num
    for i in range(1000000):
        g_num += 1
    print("---test1---g_num=%d"%g_num)
def test2():
    global g_num
    for i in range(1000000):
        g_num += 1
    print("---test2---g_num=%d"%g_num)
p1 = Thread(target=test1)
p1.start()
# time.sleep(3)

p2 = Thread(target=test2)
p2.start()

print("---g_num=%d---"%g_num)

---

内存泄漏

import gc
class ClassA():
    def __init__(self):
        print('对象产生 id:%s'%str(hex(id(self))))
def f2():
    while True:
        c1 = ClassA()
        c2 = ClassA()
        c1.t = c2#引用计数变为2
        c2.t = c1
        del c1#引用计数变为1  0才进行回收
        del c2
#把python的gc关闭
gc.disable()
f2()

'''
创建三个进程，让三个进程分别执行功能,关闭进程
Pool 创建  ，apply执行 ， close，join 关闭进程
'''
from multiprocessing import Pool
import os,time,random

def worker(msg):
    # 创建一个函数，用来使进程进行执行
    time_start = time.time()
    print("%s 号进程开始执行，进程号为 %d"%(msg,os.getpid()))
    # 使用os.getpid()获取子进程号
    # os.getppid()返回父进程号
    time.sleep(random.random()*2)
    time_end = time.time()
    print(msg,"号进程执行完毕，耗时%0.2f"%(time_end-time_start))
#     计算运行时间

if __name__ == '__main__':

    po = Pool(3)#创建三个进程
    print("进程开始")
    for i in range(3):
        # 使用for循环，运行刚刚创建的进程
        po.apply(worker,(i,))#进程池调用方式apply堵塞式
    #     第一个参数为函数名，第二个参数为元组类型的参数(函数运行会用到的形参)
    #只有当进程执行完退出后，才会新创建子进程来调用请求

    po.close()# 关闭进程池，关闭后po不再接收新的请求
    # 先使用进程的close函数关闭，后使用join函数进行等待
    po.join() # 等待po中所有子进程执行完成，必须放在close语句之后

    print("进程结束")

    '''创建->apply应用->close关闭->join等待结束'''

---

2020-05-07