Python多进程编程及多进程间的通信,数据传输
Python多进程编程及多进程间的通信
多进程编程及进程间的通信多进程的优缺点进程(process)三态五态(三态的基础上增加了新建态和终止态)进程优先级进程特征孤儿进程僵尸进程要求理解多进程编程进程相关的函数多进程模块Process()创建自定义继承Process类进程池技术Pool函数进程间的通讯(IPC)管道通讯多进程管道传输数据示例消息队列单进程示例多进程消息队列传递数据共享内存信号通信
多进程编程及进程间的通信
- 意义:充分利用计算机的资源提高程序的运算速率
- 定义:通过应用程序利用计算机多个核心达到同时执行多个任务的目的,以此提高计算机的运行速率
- 实施方案:多进程 多线程
- 并行: 计算机同时处理多个任务
- 并发:同时处理多个任务,内核在不断的任务间小虎切换,达到好像还都在处理运行的效果,但是实际是一个时间点内核只能处理其中一个任务
多进程的优缺点
-
优点
- 可以使用计算机多核,进行任务的并发执行,提高执行效率
- 空间独立,数据安全
- 运行不受其他进程影响,创建方便
-
缺点
- 进程的删除和创建消耗的系统资源多
进程(process)
查看进程:ps -aux
查看进程树:pstree
查看父进程:ps -ajx
标志 | 名称 | 说明 |
---|---|---|
S | 等待态 | 可中断等待 |
D | 等待态 | 不可中断等待 |
T | 等待态 | 暂停状态 |
R | 运行态 | 包含就绪状态 |
Z | 僵尸进程 | |
< | 高优先级 | |
N | 优先级较低 | |
l | 有子进程的 | |
s | 会话组组长 | |
+ | 前台进程 |
三态
- 就绪态:进程具备执行条件,等待系统分配资源
- 运行态:进程占有CPU,处于运行状态
- 等待态:进程暂时不具备执行条件,阻塞等待,满足条件后再执行
五态(三态的基础上增加了新建态和终止态)
- 新建态:创建一个新的进程,获取资源的过程
- 终止态:进程执行结束,资源释放回收的过程
进程优先级
-
作用:决定了一个进程的执行权限
-
动态查看系统中的进程信息:
top
,用< , >
翻页- 取值范围:-20 — 19 -20优先级最高
-
使用指定的优先级运行程序
-
nice
: 指定运行的优先级e.g. :
nice -9 ./while.py
—>>以优先级-9运行
-
进程特征
- 进程之间运行互不影响,各自独立运行
- 进程是操作系统资源分配的最小单位
- 每个进程空间独立,各自占有一定的虚拟内存
孤儿进程
- 父进程先于子进程退出,此时子进程就称为孤儿进程
- 孤儿进程会被操作系统指定的进程收养,系统进程就成为了孤儿进程的父进程
僵尸进程
- 子进程先于父进程退出,但是父进程没有处理子进程的退出状态,此时子进程就会成为僵尸进程
- 僵尸进程会存留少量的PCB信息在内存中,大量的僵尸进程会消耗系统资源,应该避免僵尸进程的产生
-
如何避免僵尸进程的产生
-
处理子进程的退出状态
pid, status = os.wait()
功能:在父进程中堵塞等待子进程退出
返回值:
-
要求理解
- 什么是进程?
- 了解进程特征
- 清楚进程每种状态,
多进程编程
1 2 3 # 功能 : 创建新的进程 4 # 参数 : 无 5 # 返回值 : 失败--->返回一个负数 6 # 成功--->在新的进程中返回 ‘0’ 7 # 在原有的进程中返回新的进程的PID号 8 import os 9 pid = os.fork() 10 pid = os.fork() 11 print(pid) 12 13 \'\'\'打印 14 9352 15 0 16 9353 17 \'\'\'
- 子进程会复制父进程的全部代码,包括fork之前产生的内存空间
- 子进程从fork的下一句开始执行,与父进程互不干扰
- 父子进程的执行顺序不一定,父子进程公用一个终端显示
- 父子进程通常会根据fork返回值的差异选择执行不同的代码。所以if结构几乎是fork的标配
- 父子进程空间独立,操作都是本空间的内容,互不影响
- 子进程也有自己的特性,比如PID号,PCB,命令集等。
进程相关的函数
函数方法 | 参数 | 说明 |
---|---|---|
os.getpid() | 返回当前进程的PID号 | |
os.getppid() | 返回当前进程的父进程的PID号 | |
os._exit( status ) | 程序的退出状态 | 进程退出 |
sys.exit( [ status ] ) | 数字:表示退出状态,不写默认为 | 进程退出 |
import os pid = os.fork() if pid < 0: print("创建进程失败") elif pid == 0: print("子进程我的真实PID为:",os.getpid(),"我的父进程PID为:",os.getppid()) else: print("我是父进程执行的代码,当前的变量pid为:",pid,"我的真实PID为:",os.getpid()) \'\'\'打印内容\'\'\'\'\'\' 我是父进程执行的代码,当前的变量pid为: 10992 我的真实PID为: 10991 子进程我的真实PID为: 10992 我的父进程PID为: 10991 \'\'\'\'\'\'打印内容\'\'\' # 如果pid 10992和子进程真实PID不同,那么这个子进程就变成了孤儿进程
多进程模块
import multiprocessing
from multiprocessing import Process
Process()
-
功能:创建一个进程对象
-
参数
- name:进程名称
- target:绑定函数
- args:元组,给target函数按照位置传参
- kwargs:字典,给target函数按照键值对传参
- name: 字符串,新的进程的名字
- 例如:p = Process(target = fun,args=(a,b))
函数方法 | 说明 |
---|---|
p.start() | 启动进程,target函数自动执行,此时进程被真正创建 |
p.join([timeout]) | 阻塞等待回收子进程,timeout为超时时间 |
p.is_alive() | 判断进程生命周期状态,处于生命周期,返回布尔值 |
p.name() | 获取进程名称 |
p.pid() | 获取进程 的pid |
p.daemon() | 默认状态False,主进程退出不影响子进程。True :子进程随着主进程结束 |
-
使用multiprocessing创建子进程,同样子进程复制父进程的全部代码,父子进程各自执行互不影响,父子进程有各自的运行空间
-
如果不使用join挥手子进程则子进程退出后会成为僵尸进程
from multiprocessing import Process from time import sleep #带参数的进程函数 def worker(sec,name): for i in range(3): sleep(sec) print("I\'m %s"%name) print("I\'m working...") p = Process(target = worker,args = (2,),\ kwargs = {\'name\':\'Daivl\'},name = "Worker") p.start() print("Process name:",p.name) #进程名称 print("Process PID:",p.pid) #获取进程PID #进程alive情况 print("Process is alive:",p.is_alive()) p.join(3) print("==================")
创建自定义继承Process类
-
继承Process
-
编写自己的
__init__
,同时加载父类的__init__
方法 -
重写
run
方法,可以通过生成的对象调用start自动运行
from import Process import time class ClockProcess(Process): def __init__(self,value): self.value = value super(ClockProcess,self).__init__() def run(self): for i in range(5): print("现在的时间是",time.ctime()) time.sleep(self.value) # 创建自定义进的类的对象 p =ClockProcess(2) # 自动调用run p.start() p.join()
进程池技术
-
产生原因
- 如果有大量任务需要多进程完成。则需要频繁的创建删除进程,给计算机带来较多的资源消耗
-
原理
- 创建适当的进程放入进程池,用来池里待处理的时间,处理完当前任务后进程不销毁,仍然哎进程池等待处理其他时间,进程的复用降低了系统资源的消耗
-
使用方法
- 创建进程池,在池内放入适当的进程
- 将事件加入到事件等待队列
- 不断取进程执行时间,直到所有进程执行完毕
- 关闭进程池,回收进程
Pool函数
-
Pool(Processes)
- 功能:创建进程池对象
- 表示进程池中有多少进程
-
pool.apply_async(func, args, kwds)
-
功能:将时间放入进程池队列
-
参数
- func:事件函数
- args:以元组形式给func传参
- kwds : 以字典形式给func传参
-
返回值一个对象
-
-
pool.apply(func, args, kwds)
-
功能:将时间放入进程池队列
-
参数
- func:事件函数
- args:以元组形式给func传参
- kwds : 以字典形式给func传参
-
-
pool.close()
- 功能:关闭进程池
-
pool.join()
- 功能:回收进程池
-
pool.map(func,iter)
-
功能:将要做的事件放入进程池
-
参数
- func : 要执行的函数
- iter : 迭代对象
-
返回值:多次return的结果列
-
from multiprocessing import Process import time class ClockProcess(Process): def __init__(self,value): self.value = value super(ClockProcess,self).__init__() def run(self): for i in range(5): print("现在的时间是",time.ctime()) time.sleep(self.value) # 创建自定义进的类的对象 p =ClockProcess(2) # 自动调用run p.start() p.join()
进程间的通讯(IPC)
进程间通讯的方法有:管道,消息队列,共享内存,信号,信号量,套接字
管道 | 消息队列 | 共享内存 | |
---|---|---|---|
开辟空间 | 内存 | 内存 | 内存 |
读写方式 | 两端读写[双向/单向] | 先进先出 | 覆盖之前的内容 |
效率 | 一般 | 一般 | 较高 |
应用 | 多用于父子进程 | 广泛灵活 | 需要注意互斥 |
管道通讯
通信原理:在内存中开辟管道空间,生成管道操作对象,多个进程使用“同一个”管道对象进行操作,即可实现通信
multiprocessing –> Pipe
-
fd1,fd2 = Pipe(duplex = True)
-
功能:创建管道
-
参数
- 默认表示为双向管道
- 设置False则为单向管道
-
返回值
- 如果是双向管道则都可以读写
- 如果是单向管道,则fd1只读,fd2只写
-
-
fd.recv()
- 功能:从管道读取信息
- 返回值:读取到的内容
- 如果管道为空则堵塞
-
fd.send(data)
- 功能:向管道中写入内容
- 参数:要写入的内容
- 可以发送任意Python数据类型
多进程管道传输数据示例
from multiprocessing import Process,Pipe import time,os # 创建管道对象 fd1, fd2 = Pipe() def fun(name): time.sleep(1) fd2.send(os.getppid()) jobs = [] # 创建5个子进程 for i in range(5): p = Process(target = fun,args = (i,)) jobs.append(p) p.start() for i in range(5): data = fd1.recv() print(data) for i in jobs: i.join()
消息队列
队列:先进先出,按照顺序来
通信原理:在内存中建立队列数据结构模型。多个进程都可以通过队列存入内容,取出内容的顺序和存入的顺序保持一致
-
创建队列
q = Queue(maxsize = 0)
- 功能:创建队列消息
- 参数:表示最多存储多少消息。默认表示根据内存分配存储
- 返回值:队列对象
-
q.put(data, [block, timeout])
-
功能:像队列存储消息
-
参数
- data:要存的内容
- block:默认队列满时候会堵塞,设置False则非堵塞
- timeout:超时时间
-
-
data = q.get([block, timeout])
-
功能:获取队列消息
-
参数
- block:默认设置队列空时会堵塞,设置为False则非堵塞
- timeout:超时时间
-
返回值:返回取出的内容
-
-
q.full()
:判断队列是否为满 -
q.empty()
:判断队列是否为空 -
q.size()
:判断队列中的消息数量 -
q.close
:关闭队列
单进程示例
#!《 单进程 》 from multiprocessing import Queue from time import sleep # 创建队列,可以放3条消息 q = Queue(3) # 存一条消息 q.put(1) sleep(0.5) # 判断队列是否为空 print(q.empty()) q.put(2) # 判断队列是否满 print(q.full()) q.put(3) # 输出队列消息数量 print(q.qsize()) # 输出 print(q.get()) q.close()
多进程消息队列传递数据
from multiprocessing import Queue,Process from time import sleep # 创建队列,可以放3条消息 q = Queue(3) def fun1(): sleep(1) q.put({"a":1,"b":2}) def fun2(): sleep(2) print("收到消息",q.get()) p1 = Process(target = fun1) p2 = Process(target = fun2) p1.start() p2.start() p1.join() p2.join()
共享内存
通信原理:在内存中开辟一段空间,对多个进程可见,进程可以写入可以读,但是每次写入的内容会覆盖上一次的内容。
只能进行单个数据的发送
-
obj = Value(ctype, obj)
-
功能:开辟共享内存空间
-
参数
- ctype:要存储的数据类型
- obj:共享内存的初始数据
-
返回值:共享内存对象
-
obj.value
即共享内存值,对其修改即可修改内存 -
from multiprocessing import Value from time import sleep import os # 创建共享内存对象 money = Value(\'i\',2000) # 操作共享内存 def deposite(): while True: i = int(input("请输入:")) money.value = i sleep(0.05) def withdraw(): data = money.value while True: if data != money.value : data = money.value print(data) pid = os.fork() if pid == 0 : deposite() withdraw()
-
-
obj = Array(ctype, obj)
-
功能:开辟共享内存空间
-
参数:
- ctype:要存入的数据格式
- obj:初始化存入的内容,比如列表、字符串。如果是数字则代表开辟内存空间的个数
-
返回值:返回共享内存对象,可以遍历
-
from multiprocessing import Array,Process from time import sleep import os # 开辟100字符内存空间,\'c\'代表字符,\'i\'代表整形 shm = Array(\'c\',100) # 必须使用字节流 shm.value = "哈哈哈".encode() def fun1(): print(os.getpid(),"子进程1:",shm.value.decode()) shm.value = "夜夜夜".encode() def fun2(): sleep(1) print(os.getpid(), "子进程2:",shm.value.decode()) p1 = Process(target = fun1) p2 = Process(target = fun2) p1.start() p2.start() p1.join() p2.join()
-
信号通信
一个进程向另一个进程发送一个信号来传递某种信息,接受者根据传递的信息来做相应的事
$ kill -l
查看系统信号说明
$ kill -9 pid号
对进程发送信号
信号名称 | 说明 | ||
---|---|---|---|
1) SIGHUP | 连接断开 | ||
2) SIGINT | ctrl+c | ||
3) SIGQUIT | ctrl+\ | ||
20) SIGTSTP | ctrl+z | ||
9) SIGKILL | 终止进程 | ||
19) SIGSTOP | 暂停进程 | ||
26) SIGVTALRM | 时钟信号 | ||
17) SIGCHLD | 子进程退出时给父进程发的信号 | ||
在Python中import signal
可以获取信号
-
os.kill(pid, sig)
-
功能:发送信号
-
参数
- pid:要发送信号的PID号
- sig :信号名称
-
import os import signal os.kill(12345,signal.SIGKILL) #杀死进程
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