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python之线程相关操作

2019-01-15 07:05:06来源：博客园阅读 ()

1.线程: 一个进程可以有多个线程，共享一个进程的资源；

2.进程线程的区别:

　　进程是资源分配的最小单位，线程是程序执行的最小单位

3.python中线程模块threading, 提供的类: Thread, Lock, Rlock, Semaphore, Event, 等等

4.线程的创建方式

# 第一种
# from threading import Thread
# def f1(s):
#     print('我是%s' % s)
# def f2(s):
#     print('我是%s' % s)
# 
# if __name__ == '__main__':
#     t = Thread(target=f1, args=(1,))
#     t1 = Thread(target=f1, args=(2,))
#     t.start()
#     t1.start()
#     print('我是主线程')

# 第二种
from threading import Thread

class MyThread(Thread):
    def __init__(self, name):
        super().__init__()
        self.name = name
    def run(self):
        print('%s今天还是不能皮' % self.name)
if __name__ == '__main__':
    t = MyThread('Jerry')
    t.start()
    print('主线程')

6.查看线程的进程id(同进程查看方式一样)

import os
from threading import Thread
def f1(n):
    print('1号', os.getpid())
    print('%s号线程任务' % n)
def f2(n):
    print('2号', os.getpid())
    print('%s号线程任务' % n)
if __name__ == '__main__':
    t1 = Thread(target=f1, args=(1,))
    t2 = Thread(target=f2, args=(2,))
    t1.start()
    t2.start()
    print('主线程', os.getpid())
    print('主线程')

7. 在进程之间数据是空间隔离的, 而在线程中是数据共享的

import time
from threading import Thread

#  通过对全局变量的修改来验证线程之间是数据共享的, 共享同一进程中的数据
num = 100
def f1():
    time.sleep(3)
    global  num
    num = 3
    print('子线程的num', num)

if __name__ == '__main__':
    t = Thread(target=f1)
    t.start()
    t.join() # 等待子线程运行结束才继续向下执行
    print('主线程的num', num)

8.多进程和多线程的效率对比

对于io密集型的, 多线程的时间较快

def f1():
    time.sleep(1)  #io密集型
    
if __name__ == '__main__':
    # 查看一下20个线程执行20个任务的执行时间
    t_s_time = time.time()
    t_list = []
    for i in range(5):
        t = Thread(target=f1,)
        t.start()
        t_list.append(t)
    [tt.join() for tt in t_list]
    t_e_time = time.time()
    t_dif_time = t_e_time - t_s_time
    # 查看一下20个进程执行同样的任务的执行时间
    p_s_time = time.time()
    p_list = []
    for i in range(5):
        p = Process(target=f1,)
        p.start()
        p_list.append(p)
    [pp.join() for pp in p_list]
    p_e_time = time.time()
    p_dif_time = p_e_time - p_s_time
    print('多线程的执行时间:', t_dif_time)
    print('多jincheng的执行时间:', p_dif_time)

计算型:

import time
from threading import Thread
from multiprocessing import Process

def f1():
    # 计算型:
    n = 10
    for i in range(10000000):
        n = n + i
if __name__ == '__main__':
    # 查看一下20个线程执行20个任务的执行时间
    t_s_time = time.time()
    t_list = []
    for i in range(5):
        t = Thread(target=f1,)
        t.start()
        t_list.append(t)
    [tt.join() for tt in t_list]
    t_e_time = time.time()
    t_dif_time = t_e_time - t_s_time
    # 查看一下20个进程执行同样的任务的执行时间
    p_s_time = time.time()
    p_list = []
    for i in range(5):
        p = Process(target=f1,)
        p.start()
        p_list.append(p)
    [pp.join() for pp in p_list]
    p_e_time = time.time()
    p_dif_time = p_e_time - p_s_time
    print('多线程的执行时间:', t_dif_time)
    print('多jincheng的执行时间:', p_dif_time)

9.锁,同步,互斥锁为了保护多线成中数据的完整性和线程间状态的同步.(同进程的锁一样)

在线程锁中, 会产生死锁现象. 同时抢锁

import time
from threading import Thread, Lock, RLock
def f1(locA, locB):
    # print('xxxx')
    # time.sleep(0.1)
    locA.acquire()
    print('f1>>1号抢到了A锁')

    time.sleep(1)
    locB.acquire()
    print('f1>>1号抢到了B锁')
    locB.release()

    locA.release()
def f2(locA, locB):
    print('22222')
    time.sleep(0.1)
    locB.acquire()
    print('f2>>2号抢到了B锁')
    locA.acquire()
    time.sleep(1)
    print('f2>>2号抢到了A锁')
    locA.release()
    locB.release()
if __name__ == '__main__':
    locA = Lock()
    locB = Lock()
    t1 = Thread(target=f1, args=(locA, locB))
    t2 = Thread(target=f2, args=(locA, locB))
    t1.start()
    t2.start()

递归锁解决了死锁现象

import time
from threading import Thread, Lock, RLock

def f1(locA, locB):
    print('xxxxx')
    time.sleep(0.1)
    locA.acquire()
    print('f1>>>1号抢到了A锁')
    time.sleep(1)
    locB.acquire()
    print('f1>>>2号抢到了B锁')
    locB.release()
    locA.release()
def f2(locA, locB):
    print('22222')
    time.sleep(0.1)
    locB.acquire()
    print('f2>>>1号抢到了A锁')
    time.sleep(1)
    locA.acquire()
    print('f2>>>2号抢到了B锁')
    locA.release()
    locB.release()
if __name__ == '__main__':
    locA = locB = RLock()
    t1 = Thread(target=f1, args=(locA, locB))
    t2 = Thread(target=f2, args=(locB, locA))
    t1.start()
    t2.start()

10.多线程的程序不结束和多进程的程序不结束的区别

守护进程:主进程代码执行运行结束,守护进程随之结束
守护线程:守护线程会等待所有非守护线程运行结束才结束

import time
from threading import Thread
from multiprocessing import Process


# 守护进程:主进程代码执行运行结束,守护进程随之结束
# 守护线程:守护线程会等待所有非守护线程运行结束才结束
def f1():
    time.sleep(2)
    print('一号线程')

def f2():
    time.sleep(3)
    print('二号线程')
def f3():
    time.sleep(2)
    print('一号进程')

def f4():
    time.sleep(3)
    print('二号进程')
if __name__ == '__main__':
    # t1 = Thread(target=f1,)
    # t2 = Thread(target=f2,)
    # # t1.daemon = True  #　 等非守护线程结束,守护线程才会结束 结果:  主线程结束  一号线程  二号线程
    # t2.daemon = True # 结果: 主线程结束      一号线程
    # t1.start()
    # t2.start()
    # print('主线程结束')
    p1 = Process(target=f3,)
    p2 = Process(target=f4,)
    # p1.daemon = True # 结果: 主进程   二号线程
    p2.daemon= True # 结果: 主进程   一号线程
    p1.start()
    p2.start()
    print('主进程')