2 May 18 网路IO(阻塞IO模型、非阻塞IO模型、IO多路复用模型、异步IO模型) 网络编程+并发编程重点知识归纳

2 May 18
socketserver = 多进程 + 多线程 +  IO模型
一、上节课复习及作业讲解
a、spawn用法复习
from gevent import monkey,spawn;monkey.patch_all()
import time
 
def f1():
    print('from f1 1')
    time.sleep(3)  # 直接调用gevent模块实现遇到IO切换+保持状态
    print('from f1 2')
 
def f2():
    print('from f2 1')
    time.sleep(2)
    print('from f2 2')
 
def f3():
    print('from f3 1')
    time.sleep(5)
    print('from f3 2')
 
g1=spawn(f1)
g2=spawn(f2)
g3=spawn(f3)
# time.sleep(10) # spawn 默认为异步调用,如果不加time.sleep或 g.join(),spawn提交后不在原地等待执行, 程序直接结束
g1.join()
g2.join()
g3.join()
 
b、作业讲解  
服务端:
from gevent import monkey,spawn;monkey.patch_all()
from threading import Thread
from socket import *
 
def talk(conn):
    while True:
        try:
            data=conn.recv(1024)
            if not data:break
            conn.send(data.upper())
        except ConnectionResetError:
            break
    conn.close()
 
def server(ip,port,backlog=5):
    s = socket()
    s.bind((ip,port))
    s.listen(backlog)
 
    while True:
        conn, addr = s.accept()
        print(addr)
        # 通信
        g=spawn(talk,conn)
 
    s.close()
 
if __name__ == '__main__':
    spawn(server,'127.0.0.1',8080).join() # spawn 默认为异步调用,如果不加time.sleep或 g.join(),spawn提交后不在原地等待执行, 程序直接结束
    # server('127.0.0.1',8080)  # 效果等用于spawn(server,'127.0.0.1',8080).join()
 
客户端:
from threading import Thread,current_thread
from socket import *
 
import os
 
def client():
    client = socket()
    client.connect(('127.0.0.1', 8080))
 
    while True:
        data = '%s hello' % current_thread().name
        client.send(data.encode('utf-8'))
        res = client.recv(1024)
        print(res.decode('utf-8'))
 
if __name__ == '__main__':
    for i in range(1000):  #开启1000个线程,以提高效率
        t=Thread(target=client)
        t.start()
 
二、网络IO操作之wait data和copy data
网路IO的两个阶段(copy data阶段 + wait data阶段),换言之,所有IO都围绕这两个阶段
 
服务端:
from socket import *
 
s = socket()  # 等同于s=socket(AF_INET, SOCK_STREAM) 默认AF_INET 及 SOCK_STREAM
s.bind(('127.0.0.1',8080))
s.listen(5)
 
while True:
    conn, addr = s.accept()  # wait data (wait的时间取决于客户端和网络两方面因素)+ copy data(app <=> kernel);accept可感觉到明显的阻塞
    print(addr)
    while True:
        try:
            data = conn.recv(1024)  # wait data + copy data(app <=> kernel) ;recv可感觉到明显的阻塞
            if not data: break      # for linux, do not pop ConnectionResetError
            print('from client msg: ',data)
        except ConnectionResetError:  # for windows 
            break
    conn.close()
 
客户端:
from socket import *
 
client = socket()  # s=socket(AF_INET, SOCK_STREAM) 默认AF_INET 及 SOCK_STREAM
client.connect(('127.0.0.1', 8080))
 
while True:
 
    data = input('>>: ').strip()
    if not data:continue   # if just enter, ask to re-input
client.send(data.encode('utf-8')) # copy data(app <=> kernel) only
#send(只有copy data阶段)是IO操作,但有时可能感觉不到明显的阻塞,一是因为传输的数据量少,二是因为是本地copy操作不经历网络过程;但如果send的数据量特别大,是有可能感受到阻塞的。
print('has send')
 
讲IO模型的目的:自己实现gevent模块,解决单线程下的IO问题(网络IO,不含time.sleep),从而得到高性能。(之前讲的多进程和多线程并没有解决IO)
 
三、阻塞IO模型

wait data和copy data阶段一个都不能少,完完整整的等下来即为阻塞IO模型
之前所接触的多进程、多线程、进程池、线程池(除了gevent模块以外)都是阻塞IO模型。

四、非阻塞IO模型(更好的利用wait data阶段)

非阻塞IO只能监测网络IO,不监测time.sleep()这种IO
非阻塞IO有可能大规模占用CPU做无用操作,所以不推荐使用非阻塞IO
 
a、 非阻塞IO模型(基础bug版)
服务端:
from socket import *
import time
 
s = socket()
s.bind(('127.0.0.1',8080))
s.listen(5)
s.setblocking(False)  # 不设置默认是True;将其设置成False,即将所有阻塞编程非阻塞(遇到等不到数据的情况,不阻塞,会抛出信息:BlockingIOError)
#gevent模块中 monkey.patch_all() 即 s.setblocking(False)
r_list=[]
while True:
    try:
        conn, addr = s.accept()
        r_list.append(conn)
 
    except BlockingIOError:
        # time.sleep(3)  # 非阻塞IO即完全没有阻塞,不应该人为加入time.sleep()
        print('可以去干其他的活了')
        print('rlist: ',len(r_list))
        for conn in r_list:
            try:
                data=conn.recv(1024)
                conn.send(data.upper())
            except BlockingIOError:  #如果等不到数据,报出的错误为BlockingIOError
                continue
 
客户端:
from socket import *
import os
 
client = socket()
client.connect(('127.0.0.1', 8080))
 
while True:
    data='%s say hello' %os.getpid()
    client.send(data.encode('utf-8'))
    res=client.recv(1024)
    print(res.decode('utf-8'))
 
b、 非阻塞IO模型(修正)
服务端: 
from socket import *
import time
 
s = socket()
s.bind(('127.0.0.1',8080))
s.listen(5)
s.setblocking(False)
 
r_list=[]
w_list=[]
while True:
    try:
        conn, addr = s.accept()
        r_list.append(conn)
 
    except BlockingIOError:
        # time.sleep(0.05)  #非阻塞模型不应该加time.sleep(); 加上time.sleep(0.05) 即把非阻塞IO模型变成IO多路复用模型
        print('可以去干其他的活了')
        print('rlist: ',len(r_list))
 
        # 收消息
        del_rlist=[]
        for conn in r_list:
            try:
                data=conn.recv(1024)
                if not data:   # for linux,不抛出ConnectionResetError,监测是否收到数据
                    conn.close()
                    del_rlist.append(conn)
                    continue
                # conn.send(data.upper())  # 错误做法: send亦有可能阻塞,所以不推荐放在这个位置,宜分到下面发消息模块独立完成
                w_list.append((conn,data.upper())) # 正确做法: 收集待send数据信息; 以小元组的形式写入列表
            except BlockingIOError:
                continue
            except ConnectionResetError:
                conn.close()
                # r_list.remove(conn)   # 错误做法: 在循环期间不推荐改变所循环对象(list,dict等)的结构
                del_rlist.append(conn)  # 正确做法: 在循环期间不推荐改变所循环对象(list,dict等)的结构
 
        # 发消息
        del_wlist=[]
        for item in w_list:
            try:
                conn=item[0] # 将小元组中数据依次取出
                res=item[1]  # 将小元组中数据依次取出
                conn.send(res)
                del_wlist.append(item)
            except BlockingIOError:
                continue
            except ConnectionResetError:
                conn.close()
                del_wlist.append(item)
 
        # 回收无用连接
        for conn in del_rlist:
            r_list.remove(conn) # 正确做法: 在循环期间不推荐改变所循环对象(list,dict等)的结构
 
        for item in del_wlist:
            w_list.remove(item)
 
客户端: 
from socket import *
import os
 
client = socket()
client.connect(('127.0.0.1', 8080))
 
while True:
    data='%s say hello' %os.getpid()
    client.send(data.encode('utf-8'))
    res=client.recv(1024)
    print(res.decode('utf-8'))
 
五、IO多路复用

IO多路复用可同时监测多个套接字,循环询问操作系统是否已准备好数据。在之前修正版的非阻塞IO模型中加入time.sleep() 即将非阻塞IO模型转化成IO多路复用模型
当只监测一个套接字时,多路复用比阻塞IO的效率还要低。
一般会使用select模块帮忙完成IO多路复用模型。(注意: select不能监测到ConnectionResetError,只能监测到BlockingIOError)
 
服务端: 
from socket import *
import select
 
s = socket()
s.bind(('127.0.0.1',8080))
s.listen(5)
s.setblocking(False)
# print(s)
 
r_list=[s,]
w_list=[]
w_data={}
while True:
    print('被检测r_list: ',len(r_list))
    print('被检测w_list: ',len(w_list))
    rl,wl,xl=select.select(r_list,w_list,[],) #r_list=[server,conn] rl等存放等到数据的对象
 
    # print('rl: ',len(rl)) #rl=[conn,]
    # print('wl: ',len(wl))
 
    # 收消息
    for r in rl: #r=conn
        if r == s:   #r l为已经有等到信息的对象,可能为s,亦可为conn;当为s时,执行accept,当为conn时,执行recv
            conn,addr=r.accept()
            r_list.append(conn) # 建立好连接后,将连接丢入r_list中监测
        else:
            try:
                data=r.recv(1024)
                if not data:  # select模块不帮忙捕捉ConnectionResetError,此操作针对linux系统
                    r.close()
                    r_list.remove(r)
                    continue
                # r.send(data.upper())
                w_list.append(r)
                w_data[r]=data.upper()
            except ConnectionResetError: #select模块不帮忙捕捉ConnectionResetError,此操作针对windows系统
                r.close()
                r_list.remove(r)
                continue
 
    # 发消息
    for w in wl:
        w.send(w_data[w])
        w_list.remove(w)
        w_data.pop(w)
 
客户端: 
from socket import *
import os
 
client = socket()
client.connect(('127.0.0.1', 8080))
 
while True:
    data='%s say hello' %os.getpid()
    client.send(data.encode('utf-8'))
    res=client.recv(1024)
    print(res.decode('utf-8'))
 
六、异步IO模型

异步IO模型的效率最高
之前设计到的异步调用+回调即用到了异步IO模型。具体的实现操作会在爬虫中详细介绍 
from concurrent.futures import ThreadPoolExecutor
from threading import current_thread
import time
import os
 
def task(n):
    print('%s is running' %current_thread().name)
    time.sleep(2)
    return n**2
 
def parse(obj):
    res=obj.result()
    print(res)
 
if __name__ == '__main__':
    t=ThreadPoolExecutor(4)
 
    future1=t.submit(task,1)
    future1.add_done_callback(parse) #parse函数会在future1对应的任务执行完毕后自动执行,会把future1自动传给parse
 
    future2=t.submit(task,2)
    future2.add_done_callback(parse)
 
    future3=t.submit(task,3)
    future3.add_done_callback(parse)
 
    future4=t.submit(task,4)
future4.add_done_callback(parse) 
 
七、重点知识归纳(网络编程+ 并发编程)
一 网络编程
                       目标:编写一个C/S或B/S架构的基于网络通信的软件
                                                                     
                       1、C/S,B/S(*****)
                                              server<===============>client
                                              服务端特点:
                                                                     1、不间断地提供服务
                                                                     2、服务端要支持并发+高性能
 
                       2、互联网
                                              互联网=物理连接介质+互联网协议(OSI七层***)
                                              
                                              tcp三次握手,四次挥手 (*****)
                                              tcp可靠,但不如udp效率高 (*****)
                                              udp不可靠,但效率高 (*****)
                       
                       3、socket(*****)
                                              socket抽象层位于传输层与应用层之间
                       
                       4、基于tcp协议的套接字通信(*****)
                                              加上连接循环
                                              加上通信循环
                       
                       5、粘包问题:(*****)
                                              tcp流式协议独有的粘包问题
                                                                     解决方法:自定义报头
                       
                                              udp数据报协议没有粘包问题
                                                                     
                       6、远程执行命令的小程序/上传下载文件的程序(*****)
                       
                       7、基于udp协议的套接字通信(***)
                       
                       
二 并发编程
                       目标:让服务端能够支持高并发+高性能
 
                       1、               操作系统发展史
                                              多道技术(*****)
                                                                     产生背景
                                                                     多道技术的核心:
                                                                                            1、空间上的复用
                                                                                            2、时间上的复用
                                                                                            
                                              *****
                                              并发:看起来同时运行
                                              并行:真正意义上的同时运行,一个cpu同一时刻只能做一件事
                                                                     只有多核才能同时做多件事,即并行的效果
                                                                     
                                              
                       2、进程
                                              1、进程理论(*****)
                                              2、开启进程的两种方式(*****)
                                              3、守护进程(**)
                                              4、互斥锁与信号量(**)
                                              5、IPC机制:队列,管道(*)
                                              6、进程queue=管道+锁 (***)
                                              7、生产者消费者模型(*****)
                                              
                       3、线程
                                              1、线程理论(*****)
                                              2、开启线程的两种方式(*****)
                                              3、守护线程(**)
                                              4、互斥锁与信号量(**)
                                              5、GIL vs 互斥锁(*****)
                                              6、Cpython的解释器下(*****)
                                                                     多个任务是IO密集型:多线程
                                                                     多个任务是计算密集型:多进程
                                              7、死锁现象与递归锁(**)
                                              8、线程queue(***)
                                              9、Event事件(**)
                       
                       4、池(*****)
                                              为何要用池:
                                                                     操作系统无法无限开启进程或线程
                                                                     池作用是将进程或线程控制操作系统可承受的范围内
                                              什么时候用池:
                                                                     当并发的任务数要远超过操作系统所能承受的进程数或
                                                                     线程数的情况应该使用池对进程数或线程数加以限制
                                              
                                              如何用池?
                                                                     池内装的东西有两种:
                                                                                            装进程:进程池
                                                                                            装线程:线程池
                                                                                            
                                                                     进程线程池的使用
                       
                                              
                                              提交的两种方式:
                                                                     同步调用
                                                                     异步调用+回调机制
                                                                     
                                              任务执行的三种状态:
                                                                     阻塞
                                                                                            阻塞
                                                                     非阻塞:
                                                                                            就绪
                                                                                            运行
                                                                     
                                              
                       
                       5、单线程下实现并发(****)
                                              协程:在应用程序级别实现多个任务之间切换+保存状态
                                              
                                              高性能:
                                                                     单纯地切换,或者说么有遇到io操作也切换,反而会降低效率
                                                                     检测单线程下的IO行为,实现遇到IO立即切换到其他任务执行
                                                                     
                                              gevent
                                                                     
                       6、IO模型(主要掌握理论****)
                                              阻塞IO
                                              非阻塞IO
                                              IO多路复用
                                              异步IO

                            

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转载自www.cnblogs.com/zhangyaqian/p/py20180502.html