多线程

多任务指的是同时做多个任务
单核cpu里执行多任务时使用的是基于cpu的轮转方式，给各个任务分配时间片，在不同进程之间快速切换，即所谓并发，在同一时间段内执行 多个任务。像时间穿梭者快速在不同空间穿梭，在外部看起来他在哪个空间也没离开过，并把每个空间的任务都完成了。
并行是多核cpu运行任务，在同一时间点执行。
并发的实际情况是：多个进程被加载到内存里，当cpu要执行哪个进程时，他相关的数据会被调到缓冲区，切换时又被退回到内存里。
线程：一个进程里的一条代码执行流程。主线程是默认存在的线程，子线程是在主线程被创建的线程。
多线程的目的是提高cpu的利用率。
1.第一种创建子进程的方法

import threadingimport timedef sing():"""线程函数"""    for i in range(3):        print("唱歌"+str(i))        time.sleep(1)def dance():    for i in range(3):        print("跳舞"+str(i))        time.sleep(1)def main():    t1 = threading.Thread(target=sing)    t2 = threading.Thread(target=dance)#并没有这里真正创建#Thread实例对象。只是准备好，并将参数导入    #target = 线程函数名    t1.start()    t2.start()#start()方法才真正创建和启动该线程if __name__ == '__main__':    main()查看线程个数``import threadingimport timeg_num = 0def work1():    for i in range (3):        global g_num        g_num += 1    print(g_num)def work2():    print(g_num)def main():    t1 = threading.Thread(target = work1)    t2 = threading.Thread(target=work2)    t1.start()    t2.start()    while True:        if len(threading.enumerate()) <= 1:            print("子进程结束")            break        else:            print("进程个数:" + str(len(threading.enumerate())))if __name__ == '__main__':    main(）

线程的运行顺序

import  timeclass MyThread(threading.Thread):    def run(self):        for i in range(5):            print(self.getName()+"@"+str(i))            time.sleep(1)def main():    for i in range(5):        t1 = MyThread()        t1.start()if __name__ == '__main__':    main()  '''  线程的顺序是随机的，即CPU随机的切换线程  多个线程共享全局变量

import threading
import time

g_num = 0

def work1(num):
global g_num
for i in range(num):
g_num += 1
print(“—-in work1, g_num is %d—”%g_num)

def work2(num):
global g_num
for i in range(num):
g_num += 1
print(“—-in work2, g_num is %d—”%g_num)

print(“—线程创建之前g_num is %d—”%g_num)

t1 = threading.Thread(target=work1, args=(1000000,))
t1.start()

t2 = threading.Thread(target=work2, args=(1000000,))
t2.start()

while len(threading.enumerate()) != 1:
time.sleep(1)
”’上面两句代码=
t1.join()
t2.join()
在t1/t2子线程执行完之前，主线程阻塞”’

print(“2个线程对同一个全局变量操作之后的最终结果是:%s” % g_num)

如果多个线程对同一个全局变量进行操作就会出现资源竞争情况，从而导致结果不正确。解决办法：互斥锁。线程同步：协同步调，按照先后次序执行

import threading

import time

#

g_num = 0

#

def work1(num):

global g_num

for i in range(num):

g_num += 1

print(“—-in work1, g_num is %d—”%g_num)

#
#

def work2(num):

global g_num

for i in range(num):

g_num += 1

print(“—-in work2, g_num is %d—”%g_num)

#
#

print(“—线程创建之前g_num is %d—”%g_num)

#

t1 = threading.Thread(target=work1, args=(1000000,))

t1.start()

#

t2 = threading.Thread(target=work2, args=(1000000,))

t2.start()

#

while len(threading.enumerate()) != 1:

time.sleep(1)

#

print(“2个线程对同一个全局变量操作之后的最终结果是:%s” % g_num)

import threading

import time

g_num = 0
def work1(*args):
mutex,n =args
global g_num
for i in range(n):
mutex.acquire()
g_num += 1
mutex.release()

def work2(*args):
mutex, n = args
global g_num
for i in range(n):
mutex.acquire()
g_num += 1
mutex.release()

if name == ‘main‘:
n = 10000
mutex = threading.Lock()
t1 = threading.Thread(target=work1, args=(mutex,n))
t2 = threading.Thread(target=work1, args=(mutex,n))
t1.start()
t2.start()
while len(threading.enumerate()) != 1:
time.sleep(1)
print(g_num)

多线程聊天器  其实只有两个：接收消息和发送消息

import socket
import threading
def send_msg(udp_socket,ip,port):
while True:
msg = input(“>>>>”)
udp_socket.sendto(msg.encode(),(ip,port))

def recv_msg(udp_socket):
while True:
msg,adr = udp_socket.recvfrom(1024)
print(“%s<<<<<<%s”.rjust(100) % (msg.decode(),str(adr)))

def main():
udp_socket = socket.socket(socket.AF_INET,socket.SOCK_DGRAM)
udp_socket.bind((“”,7784))
ip = input(“ip:”)
port = int(input(“port:”))
t1 = threading.Thread(target = recv_msg,args=(udp_socket,))
t2 = threading.Thread(target=send_msg,args=(udp_socket,ip,port))
t1.start()
t2.start()

if name == ‘main‘:
main()
“`