多线程 VS 多进程(二)
【摘要】 共享变量 共享变量:当多个线程同时访问同一个变量的时候,会产生共享变量的问题案例11import threading
sum = 0
loopSum = 1000000
def myAdd(): global sum, loopSum for i in range(1, loopSum): sum += 1
def myMinu(): global sum, lo...
- 共享变量
- 共享变量:当多个线程同时访问同一个变量的时候,会产生共享变量的问题
- 案例11
import threading sum = 0 loopSum = 1000000 def myAdd(): global sum, loopSum for i in range(1, loopSum): sum += 1 def myMinu(): global sum, loopSum for i in range(1, loopSum): sum -= 1 if __name__ == '__main__': print("Starting ....{0}".format(sum)) # 开始多线程的实现,看执行结果是否一样 t1 = threading.Thread(target=myAdd, args=()) t2 = threading.Thread(target=myMinu, args=()) t1.start() t2.start() t1.join() t2.join() print("Done ....{0}".format(sum))
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Starting ....0 Done ....157577
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- 解决变量:锁,信号灯
- 锁(Lock):
- 是一个标志,表示一个线程在占用一些资源
- 使用方法
- 上锁
- 使用共享变量,放心的用
- 取消锁,释放锁
- 案例12
import threading sum = 0 loopSum = 1000000 lock = threading.Lock() def myAdd(): global sum, loopSum for i in range(1, loopSum): # 上锁,申请锁 lock.acquire() sum += 1 # 释放锁 lock.release() def myMinu(): global sum, loopSum for i in range(1, loopSum): lock.acquire() sum -= 1 lock.release() if __name__ == '__main__': print("Starting ....{0}".format(sum)) # 开始多线程的实现,看执行结果是否一样 t1 = threading.Thread(target=myAdd, args=()) t2 = threading.Thread(target=myMinu, args=()) t1.start() t2.start() t1.join() t2.join() print("Done ....{0}".format(sum))
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Starting ....0 Done ....0
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- 锁谁:哪个资源需要多个线程共享,锁哪个
- 理解锁:锁其实不是锁住谁,而是一个令牌
- 线程安全问题:
- 如果一个资源/变量,他对于多线程来讲,不用加锁也不会引起任何问题,则称为线程安全
- 线程不安全变量类型:list,set,dict
- 线程安全变量类型:queue(队列)
- 生产者消费者问题
- 一个模型,可以用来搭建消息队列
- queue是一个用来存放变量的数据结构,特点是先进先出,内部元素排队,可以理解成一个特殊的list
- 案例13
#encoding=utf-8 import threading import time # Python2 # from Queue import Queue # Python3 import queue class Producer(threading.Thread): def run(self): global queue count = 0 while True: # qsize返回queue内容长度 if queue.qsize() < 1000: for i in range(100): count = count +1 msg = '生成产品'+str(count) # put是往queue中放入一个值 queue.put(msg) print(msg) time.sleep(0.5) class Consumer(threading.Thread): def run(self): global queue while True: if queue.qsize() > 100: for i in range(3): # get是从queue中取出一个值 msg = self.name + '消费了 '+queue.get() print(msg) time.sleep(1) if __name__ == '__main__': queue = queue.Queue() for i in range(500): queue.put('初始产品'+str(i)) for i in range(2): p = Producer() p.start() for i in range(5): c = Consumer() c.start()
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生成产品1 生成产品2 生成产品3 生成产品4 生成产品5 生成产品6 生成产品7 生成产品8 生成产品9 生成产品10 生成产品11 生成产品12 生成产品13 生成产品14 生成产品15 生成产品16 生成产品17 生成产品18生成产品1 生成产品2 生成产品3 生成产品4 生成产品5 生成产品6 生成产品7 生成产品8 生成产品9 生成产品10 生成产品11 生成产品19 生成产品12 生成产品13 生成产品14 生成产品20 生成产品21 生成产品22 生成产品23 生成产品24 生成产品25 生成产品26 生成产品15 生成产品16 生成产品17 生成产品18 生成产品19 生成产品20Thread-3消费了 初始产品0 Thread-3消费了 初始产品1 Thread-3消费了 初始产品2 生成产品27 Thread-4消费了 初始产品3 Thread-4消费了 初始产品4 Thread-4消费了 初始产品5 生成产品21生成产品28 生成产品29 生成产品30 生成产品31 生成产品32 生成产品33 生成产品34 生成产品22 生成产品23 生成产品24 生成产品25 生成产品26 生成产品27Thread-5消费了 初始产品6 Thread-5消费了 初始产品7 Thread-5消费了 初始产品8 ...
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- 死锁问题,案例14
import threading import time lock_1 = threading.Lock() lock_2 = threading.Lock() def func_1(): print("func_1 starting.........") lock_1.acquire() print("func_1 申请了 lock_1....") time.sleep(2) print("func_1 等待 lock_2.......") lock_2.acquire() print("func_1 申请了 lock_2.......") lock_2.release() print("func_1 释放了 lock_2") lock_1.release() print("func_1 释放了 lock_1") print("func_1 done..........") def func_2(): print("func_2 starting.........") lock_2.acquire() print("func_2 申请了 lock_2....") time.sleep(4) print("func_2 等待 lock_1.......") lock_1.acquire() print("func_2 申请了 lock_1.......") lock_1.release() print("func_2 释放了 lock_1") lock_2.release() print("func_2 释放了 lock_2") print("func_2 done..........") if __name__ == "__main__": print("主程序启动..............") t1 = threading.Thread(target=func_1, args=()) t2 = threading.Thread(target=func_2, args=()) t1.start() t2.start() t1.join() t2.join() print("主程序启动..............")
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主程序启动.............. func_1 starting......... func_1 申请了 lock_1.... func_2 starting......... func_2 申请了 lock_2.... func_1 等待 lock_2....... func_2 等待 lock_1.......
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- 锁的等待时间问题,案例15
import threading import time lock_1 = threading.Lock() lock_2 = threading.Lock() def func_1(): print("func_1 starting.........") lock_1.acquire(timeout=4) print("func_1 申请了 lock_1....") time.sleep(2) print("func_1 等待 lock_2.......") rst = lock_2.acquire(timeout=2) if rst: print("func_1 已经得到锁 lock_2") lock_2.release() print("func_1 释放了锁 lock_2") else: print("func_1 注定没申请到lock_2.....") lock_1.release() print("func_1 释放了 lock_1") print("func_1 done..........") def func_2(): print("func_2 starting.........") lock_2.acquire() print("func_2 申请了 lock_2....") time.sleep(4) print("func_2 等待 lock_1.......") lock_1.acquire() print("func_2 申请了 lock_1.......") lock_1.release() print("func_2 释放了 lock_1") lock_2.release() print("func_2 释放了 lock_2") print("func_2 done..........") if __name__ == "__main__": print("主程序启动..............") t1 = threading.Thread(target=func_1, args=()) t2 = threading.Thread(target=func_2, args=()) t1.start() t2.start() t1.join() t2.join() print("主程序结束..............")
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主程序启动.............. func_1 starting......... func_1 申请了 lock_1.... func_2 starting......... func_2 申请了 lock_2.... func_1 等待 lock_2....... func_1 注定没申请到lock_2..... func_1 释放了 lock_1 func_2 等待 lock_1....... func_1 done.......... func_2 申请了 lock_1....... func_2 释放了 lock_1 func_2 释放了 lock_2 func_2 done.......... 主程序结束..............
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- semphore
- 允许一个资源对多有几个多线程同时使用
- 案例16
import threading import time # 参数定义最多几个线程同时使用资源 semaphore = threading.Semaphore(3) def func(): if semaphore.acquire(): for i in range(5): print(threading.currentThread().getName() + 'get semaphore') time.sleep(15) semaphore.release() print(threading.currentThread().getName() + 'release semaphore') for i in range(8): t1 = threading.Thread(target=func) t1.start()
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Thread-1get semaphore Thread-1get semaphore Thread-1get semaphore Thread-1get semaphore Thread-1get semaphore Thread-2get semaphore Thread-2get semaphore Thread-2get semaphore Thread-2get semaphore Thread-2get semaphore Thread-3get semaphore Thread-3get semaphore Thread-3get semaphore Thread-3get semaphore Thread-3get semaphore Thread-2release semaphoreThread-1release semaphore Thread-5get semaphore Thread-5get semaphore Thread-5get semaphore Thread-5get semaphore Thread-5get semaphore Thread-4get semaphore Thread-4get semaphore Thread-4get semaphore Thread-4get semaphore Thread-4get semaphore Thread-3release semaphoreThread-6get semaphore Thread-6get semaphore Thread-6get semaphore Thread-6get semaphore Thread-6get semaphore ...
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- threading.Timer
- 案例17
import threading import time def func(): print("I am running.........") time.sleep(4) print("I am done...") if __name__ == "__main__": t = threading.Timer(6, func) t.start() i = 0 while True: print("{0}*****************".format(i)) time.sleep(3) i += 1
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0***************** 1***************** I am running......... 2***************** 3***************** I am done... 4***************** 5***************** 6***************** 7***************** 8***************** ...
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- Timer是利用多线程,在指定时间后启动一个功能
- 案例17
- 可重入锁
- 一个锁,可以被一个线程多次申请
- 主要解决递归调用的时候,需要申请锁的情况
- 案例18
import threading import time class MyThread(threading.Thread): def run(self): global num time.sleep(1) if mutex.acquire(1): num = num+1 msg = self.name+' set num to '+str(num) print(msg) mutex.acquire() mutex.release() mutex.release() num = 0 mutex = threading.RLock() def testTh(): for i in range(5): t = MyThread() t.start() if __name__ == "__main__": testTh()
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Thread-1 set num to 1 Thread-3 set num to 2 Thread-2 set num to 3 Thread-4 set num to 4 Thread-5 set num to 5
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文章来源: ruochen.blog.csdn.net,作者:若尘,版权归原作者所有,如需转载,请联系作者。
原文链接:ruochen.blog.csdn.net/article/details/99465855
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