人生苦短之我用Python篇（线程/进程、threading模块：全局解释器锁gil/信号量/Event、）

线程: 有时被称为轻量级进程(Lightweight Process，LWP），是程序执行流的最小单元。是一串指令的集合。
线程是程序中一个单一的顺序控制流程。进程内一个相对独立的、可调度的执行单元，是系统独立调度和分派CPU的基本单位指运行中的程序的调度单位。
在单个程序中同时运行多个线程完成不同的工作，称为多线程。

进程: qq 要以一个整体的形式暴露给操作系统管理，里面包含对各种资源的调用，内存的管理，网络接口的调用等。。。
对各种资源管理的集合 就可以成为进程。

进程 要操作cpu , 必须要先创建一个线程，
all the threads in a process have the same view of the memory
所有在同一个进程里的线程是共享同一块内存空间的

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进程与线程的区别？

Threads share the address space of the process that created it; processes have their own address space.
线程共享内存空间，进程的内存是独立的
Threads have direct access to the data segment of its process; processes have their own copy of the data segment of the parent process.

Threads can directly communicate with other threads of its process; processes must use interprocess communication to communicate with sibling processes.
同一个进程的线程之间可以直接交流，两个进程想通信，必须通过一个中间代理来实现

New threads are easily created; new processes require duplication of the parent process.
创建新线程很简单， 创建新进程需要对其父进程进行一次克隆

Threads can exercise considerable control over threads of the same process; processes can only exercise control over child processes.
一个线程可以控制和操作同一进程里的其他线程，但是进程只能操作子进程

Changes to the main thread (cancellation, priority change, etc.) may affect the behavior of the other threads of the process; changes to the parent process does not affect child processes.

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threading模块

import time
import threading

def run(n):
    print('task.....',n)
    time.sleep(2)

# run("t1")
# run("t2")


#普通写法
t1 = threading.Thread(target=run,args=("t1",))
t2 = threading.Thread(target=run,args=("t2",))
t1.start()
t2.start()

import time
import threading
#类写法
class MyThread(threading.Thread):
    def __init__(self,n,sleep_time):
        super(MyThread, self).__init__()
        self.n = n
        self.sleep_time = sleep_time
    def run(self):
        print("task", self.n)
        time.sleep(self.sleep_time)
        print("task done")

t1 = MyThread("t1",2)
t2 = MyThread("t2",4)

t1.start()
t2.start()

import threading
import time

def run(n):
    print("task ",n )
    time.sleep(2)
    print("task done",n)

start_time = time.time()
t_objs = [] #存线程实例
for i in range(50):
    t = threading.Thread(target=run,args=("t-%s" %i ,))
    t.start()
    t_objs.append(t) #为了不阻塞后面线程的启动，不在这里join，先放到一个列表里

for t in t_objs: #循环线程实例列表，等待所有线程执行完毕
    t.join()

print(t_objs)
print("----------all threads has finished...")
print("cost:",time.time() - start_time)

Daemon：守护进程，即主进程一结束，守护进程也就结束

import threading
import time

def run(n):
    print("task ",n )
    time.sleep(2)
    print("task done",n,threading.current_thread())

start_time = time.time()
t_objs = [] #存线程实例
for i in range(50):
    t = threading.Thread(target=run,args=("t-%s" %i ,))
    t.setDaemon(True) #把当前线程设置为守护线程
    t.start()
    t_objs.append(t) #为了不阻塞后面线程的启动，不在这里join，先放到一个列表里

# for t in t_objs: #循环线程实例列表，等待所有线程执行完毕
#     t.join()

# time.sleep(2)
print("----------all threads has finished...",threading.current_thread(),threading.active_count())
print("cost:",time.time() - start_time)

全局锁

import threading
import time

def run(n):
    lock.acquire()#获得锁，除非释放掉锁，否则其他线程就不能再次获得，2.7中试，3.0以后不需要了
    global  num
    num +=1
    # time.sleep(1)
    lock.release()#释放锁，其他线程可以获得了


lock = threading.Lock()
num = 0
t_objs = [] #存线程实例
for i in range(50):
    t = threading.Thread(target=run,args=("t-%s" %i ,))
    t.start()
    t_objs.append(t) #为了不阻塞后面线程的启动，不在这里join，先放到一个列表里

for t in t_objs: #循环线程实例列表，等待所有线程执行完毕
    t.join()

print("----------all threads has finished...",threading.current_thread(),threading.active_count())
print("num:",num)

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 信号量：即同时可以获得多个锁

import threading
import time

def run(n):
    semaphore.acquire()#信号量获取
    time.sleep(1)
    print("run the thread :%s
" %n)
    semaphore.release()#信号量释放


if __name__ == "__main__":
    semaphore = threading.BoundedSemaphore(5)   #设置信号量，即绑定信号量可以同时拥有的锁的数量
    for i in range(22):
        t = threading.Thread(target = run,args = (i,))
        t.start()

while threading.active_count() !=1 :#当前活跃的线程数
    pass

else:
    print("______-all threads done______")

Event:

event = threading.Event()#生成event对象

event.set()#设置event标志位

event.clear()#清除event标志位

event.is_set():#判断event是否设置了标志位

 红绿灯例子：

import time
import threading

event = threading.Event()#生成event对象
def lighter():
    event.set()#设置event标志位
    count = 0
    while True:
        if count >5 and count <10:
            event.clear()#清除event标志位
            print("33[41;1m红灯亮....33[0m")
        elif count > 10:
            event.set()
            print("33[42;1m绿灯亮了....33[0m")
            count = 0
        else:
            print("33[42;1m绿灯亮着33[0m")
        time.sleep(1)
        count +=1

def car(n):
    while True:
        if event.is_set():#判断event是否设置了标志位
            print('33[34;2m[%s] running..... 33[0m'%n)
            time.sleep(0.5)
        else:
            print('[%s] stoping.....'%n)
            event.wait()
            print('路灯亮了[%s]开跑'%n)


light = threading.Thread(target=lighter,)
light.start()

car1 = threading.Thread(target=car,args=('宝马',))
car1.start()

car2 = threading.Thread(target=car,args=('大奔驰',))
car2.start()

car3 = threading.Thread(target=car,args=('玛莎拉蒂',))
car3.start()

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多进程：

和线程用法基本一致，我threading.Thread换成multiprocessing.Process

import time,threading
import multiprocessing

def thread_run():
    print(threading.get_ident())

def run(name):
    time.sleep(2)
    print("hellp",name)
    t = threading.Thread(target=thread_run,)
    t.start()

if __name__ =="__main__":
    for i in range (10):
        p = multiprocessing.Process(target=run,args=("bob %s"%i,))#与线程用法基本机制
        p.start()

 数据在不同进程间进行交换

from multiprocessing import Process,Queue

def f(qq):
    qq.put([42,None,156161])

if __name__ =="__main__":
    q =Queue()#可以在不同进程间交互使用
    p = Process(target=f,args=(q,))#把q作为参数传入
    p.start()
    print(q.get())#父进程可以得到子进程中修改过的数据
    p.join()

 进程池

Note:　　from multiprocessing import Process, Pool,freeze_support

  pool = Pool(processes=5) #允许进程池同时放入5个进程

  pool.apply_async(func=Foo, args=(i,), callback=Bar) #callback=回调，父进程操作
  #pool.apply(func=Foo, args=(i,)) #串行
  #pool.apply_async(func=Foo, args=(i,)) #并行

from  multiprocessing import Process, Pool,freeze_support
import time
import os

def Foo(i):
    time.sleep(2)
    print("in process",os.getpid())
    return i + 100

def Bar(arg):
    print('-->exec done:', arg,os.getpid())

if __name__ == '__main__':#window必须加这一句
    #freeze_support()
    pool = Pool(processes=5) #允许进程池同时放入5个进程
    print("主进程",os.getpid())
    for i in range(10):
        pool.apply_async(func=Foo, args=(i,), callback=Bar) #callback=回调
        #pool.apply(func=Foo, args=(i,)) #串行
        #pool.apply_async(func=Foo, args=(i,)) #并行
    print('end')
    pool.close()
    pool.join() #进程池中进程执行完毕后再关闭，如果注释，那么程序直接关闭。.join()

 进程锁：变串行了

from multiprocessing import Process, Lock


def f(l, i):
    #l.acquire()
    print('hello world', i)
    #l.release()


if __name__ == '__main__':
    lock = Lock()

    for num in range(100):
        Process(target=f, args=(lock, num)).start()

 Manager：进程间交换数据

from multiprocessing import Process, Manager
import os
def f(d, l):
    d[os.getpid()] =os.getpid()
    l.append(os.getpid())
    print(l)

if __name__ == '__main__':
    with Manager() as manager:
        d = manager.dict() #{} #生成一个字典，可在多个进程间共享和传递

        l = manager.list(range(5))#生成一个列表，可在多个进程间共享和传递
        p_list = []
        for i in range(10):
            p = Process(target=f, args=(d, l))
            p.start()
            p_list.append(p)
        for res in p_list: #等待结果
            res.join()

        print(d)
        print(l)

 Pipe：生成两个可以交互数据的进程

parent_conn, child_conn = Pipe()#生成两个可以交换数据的进程

from multiprocessing import Process, Pipe


def f(conn):
    conn.send([42, None, 'hello from child'])
    conn.send([42, None, 'hello from child2'])
    print("from parent:",conn.recv())
    conn.close()

if __name__ == '__main__':
    parent_conn, child_conn = Pipe()#生成两个可以交换数据的进程
    p = Process(target=f, args=(child_conn,))
    p.start()
    print(parent_conn.recv())  # prints "[42, None, 'hello']"
    print(parent_conn.recv())  # prints "[42, None, 'hello']"
    parent_conn.send("可好") # prints "[42, None, 'hello']"
    p.join()