浅析Python多线程
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今天看了几篇博客,主要讲解线程的实例以及如何避免线程间的竞争,觉得感觉对自己很有用,所以在此先写先来以备以后自己查阅.
实例一:我们将要请求三个不同的url
1.单线程:
1 import time 2 from urllib.request import urlopen 3 4 5 def get_responses(): 6 urls = [ 7 ‘http://www.baidu.com‘, 8 ‘http://www.taobao.com‘, 9 ‘http://www.alibaba.com‘, 10 ] 11 start = time.time() 12 for url in urls: 13 print(url) 14 resp = urlopen(url) 15 print(resp.getcode()) #得到状态码 16 print("spent time:%s" % (time.time()-start)) 17 18 get_responses()
解释:
url顺序的被请求
除非cpu从一个url获得了回应,否则不会去请求下一个url
网络请求会花费较长的时间,所以cpu在等待网络请求的返回时间内一直处于闲置状态。
输出为:
http://www.baidu.com
200
http://www.taobao.com
200
http://www.alibaba.com
200
spent time:1.1927924156188965
2.多线程:
from urllib.request import urlopen import time from threading import Thread class GetUrlThread(Thread): def __init__(self, url): self.url = url super(GetUrlThread, self).__init__() def run(self): resp = urlopen(self.url) print(self.url, resp.getcode()) def get_responses(): urls = [ ‘http://www.baidu.com‘, ‘http://www.taobao.com‘, ‘http://www.alibaba.com‘, ] start = time.time() threads = [] for url in urls: t = GetUrlThread(url) threads.append(t) t.start() for t in threads: t.join() print("spent time:%s" % (time.time()-start)) get_responses()
解释:
意识到了程序在执行时间上的提升
我们写了一个多线程程序来减少cpu的等待时间,当我们在等待一个线程内的网络请求返回时,这时cpu可以切换到其他线程去进行其他线程内的网络请求。
我们期望一个线程处理一个url,所以实例化线程类的时候我们传了一个url。
线程运行意味着执行类里的run()方法。
无论如何我们想每个线程必须执行run()。
为每个url创建一个线程并且调用start()方法,这告诉了cpu可以执行线程中的run()方法了。
我们希望所有的线程执行完毕的时候再计算花费的时间,所以调用了join()方法。
join()可以通知主线程等待这个线程结束后,才可以执行下一条指令。
每个线程我们都调用了join()方法,所以我们是在所有线程执行完毕后计算的运行时间。
关于线程:
cpu可能不会在调用start()后马上执行run()方法。
你不能确定run()在不同线程建间的执行顺序。
对于单独的一个线程,可以保证run()方法里的语句是按照顺序执行的。
这就是因为线程内的url会首先被请求,然后打印出返回的结果。
输出为:
http://www.baidu.com 200
http://www.alibaba.com 200
http://www.taobao.com 200
spent time:0.6294200420379639
实例二:全局变量的线程安全问题(race condition)
1.BUG版:
from threading import Thread import time #define a global variable some_var = 0 class IncrementThread(Thread): def run(self): # we want to read a global variable # and then increment it global some_var read_var = some_var print("some_var in %s is %d" % (self.name, read_var)) time.sleep(0.1) some_var = read_var + 1 print("some_var in %s is %d" % (self.name, some_var)) def use_increment_thread(): threads = [] for i in range(50): t = IncrementThread() threads.append(t) t.start() for t in threads: t.join() print("After 50 modifications, some_var should have become 50") print("After 50 modifications, some_var is %d" % some_var) use_increment_thread()
解释:
有一个全局变量,所有的线程都想修改它。
所有的线程应该在这个全局变量上加 1 。
有50个线程,最后这个数值应该变成50,但是它却没有。
为什么没有达到50?
在some_var是15的时候,线程t1读取了some_var,这个时刻cpu将控制权给了另一个线程t2。
t2线程读到的some_var也是15
t1和t2都把some_var加到16
当时我们期望的是t1 t2两个线程使some_var + 2变成17
在这里就有了资源竞争。
相同的情况也可能发生在其它的线程间,所以出现了最后的结果小于50的情况。
输出为:
some_var in Thread-1 is 0
some_var in Thread-2 is 0
some_var in Thread-3 is 0
some_var in Thread-4 is 0
some_var in Thread-5 is 0
some_var in Thread-6 is 0
some_var in Thread-7 is 0
some_var in Thread-8 is 0
some_var in Thread-9 is 0
some_var in Thread-10 is 0
some_var in Thread-11 is 0
some_var in Thread-12 is 0
some_var in Thread-13 is 0
some_var in Thread-14 is 0
some_var in Thread-15 is 0
some_var in Thread-16 is 0
some_var in Thread-17 is 0
some_var in Thread-18 is 0
some_var in Thread-19 is 0
some_var in Thread-20 is 0
some_var in Thread-21 is 0
some_var in Thread-22 is 0
some_var in Thread-23 is 0
some_var in Thread-24 is 0
some_var in Thread-25 is 0
some_var in Thread-26 is 0
some_var in Thread-27 is 0
some_var in Thread-28 is 0
some_var in Thread-29 is 0
some_var in Thread-30 is 0
some_var in Thread-31 is 0
some_var in Thread-32 is 0
some_var in Thread-33 is 0
some_var in Thread-34 is 0
some_var in Thread-35 is 0
some_var in Thread-36 is 0
some_var in Thread-37 is 0
some_var in Thread-38 is 0
some_var in Thread-39 is 0
some_var in Thread-40 is 0
some_var in Thread-41 is 0
some_var in Thread-42 is 0
some_var in Thread-43 is 0
some_var in Thread-44 is 0
some_var in Thread-45 is 0
some_var in Thread-46 is 0
some_var in Thread-47 is 0
some_var in Thread-48 is 0
some_var in Thread-49 is 0
some_var in Thread-50 is 0
some_var in Thread-6 is 1
some_var in Thread-5 is 1
some_var in Thread-2 is 1
some_var in Thread-4 is 1
some_var in Thread-1 is 1
some_var in Thread-3 is 1
some_var in Thread-12 is 1
some_var in Thread-13 is 1
some_var in Thread-11 is 1
some_var in Thread-10 is 1
some_var in Thread-9 is 1
some_var in Thread-7 is 1
some_var in Thread-8 is 1
some_var in Thread-21 is 1
some_var in Thread-20 is 1
some_var in Thread-19 is 1
some_var in Thread-18 is 1
some_var in Thread-17 is 1
some_var in Thread-15 is 1
some_var in Thread-14 is 1
some_var in Thread-16 is 1
some_var in Thread-26 is 1
some_var in Thread-25 is 1
some_var in Thread-24 is 1
some_var in Thread-22 is 1
some_var in Thread-23 is 1
some_var in Thread-31 is 1
some_var in Thread-29 is 1
some_var in Thread-28 is 1
some_var in Thread-27 is 1
some_var in Thread-30 is 1
some_var in Thread-38 is 1
some_var in Thread-37 is 1
some_var in Thread-36 is 1
some_var in Thread-35 is 1
some_var in Thread-32 is 1
some_var in Thread-33 is 1
some_var in Thread-34 is 1
some_var in Thread-44 is 1
some_var in Thread-43 is 1
some_var in Thread-42 is 1
some_var in Thread-41 is 1
some_var in Thread-40 is 1
some_var in Thread-39 is 1
some_var in Thread-50 is 1
some_var in Thread-49 is 1
some_var in Thread-48 is 1
some_var in Thread-47 is 1
some_var in Thread-45 is 1
some_var in Thread-46 is 1
After 50 modifications, some_var should have become 50
After 50 modifications, some_var is 1
解决竞争带锁版:
1 from threading import Lock, Thread 2 import time 3 lock = Lock() 4 some_var = 0 5 6 class IncrementThread(Thread): 7 def run(self): 8 #we want to read a global variable 9 #and then increment it 10 global some_var 11 lock.acquire() 12 read_value = some_var 13 print("some_var in %s is %d" % (self.name, read_value)) 14 time.sleep(0.1) 15 some_var = read_value + 1 16 print("some_var in %s after increment is %d" % (self.name, some_var)) 17 lock.release() 18 19 def use_increment_thread(): 20 threads = [] 21 for i in range(50): 22 t = IncrementThread() 23 threads.append(t) 24 t.start() 25 for t in threads: 26 t.join() 27 print("After 50 modifications, some_var should have become 50") 28 print("After 50 modifications, some_var is %d" % (some_var,)) 29 30 use_increment_thread()
解释:
Lock 用来防止竞争条件
如果在执行一些操作之前,线程t1获得了锁。其他的线程在t1释放Lock之前,不会执行相同的操作
我们想要确定的是一旦线程t1已经读取了some_var,直到t1完成了修改some_var,其他的线程才可以读取some_var
这样读取和修改some_var成了逻辑上的原子操作。
输出为:
some_var in Thread-1 is 0
some_var in Thread-1 after increment is 1
some_var in Thread-2 is 1
some_var in Thread-2 after increment is 2
some_var in Thread-3 is 2
some_var in Thread-3 after increment is 3
some_var in Thread-4 is 3
some_var in Thread-4 after increment is 4
some_var in Thread-5 is 4
some_var in Thread-5 after increment is 5
some_var in Thread-6 is 5
some_var in Thread-6 after increment is 6
some_var in Thread-7 is 6
some_var in Thread-7 after increment is 7
some_var in Thread-8 is 7
some_var in Thread-8 after increment is 8
some_var in Thread-9 is 8
some_var in Thread-9 after increment is 9
some_var in Thread-10 is 9
some_var in Thread-10 after increment is 10
some_var in Thread-11 is 10
some_var in Thread-11 after increment is 11
some_var in Thread-12 is 11
some_var in Thread-12 after increment is 12
some_var in Thread-13 is 12
some_var in Thread-13 after increment is 13
some_var in Thread-14 is 13
some_var in Thread-14 after increment is 14
some_var in Thread-15 is 14
some_var in Thread-15 after increment is 15
some_var in Thread-16 is 15
some_var in Thread-16 after increment is 16
some_var in Thread-17 is 16
some_var in Thread-17 after increment is 17
some_var in Thread-18 is 17
some_var in Thread-18 after increment is 18
some_var in Thread-19 is 18
some_var in Thread-19 after increment is 19
some_var in Thread-20 is 19
some_var in Thread-20 after increment is 20
some_var in Thread-21 is 20
some_var in Thread-21 after increment is 21
some_var in Thread-22 is 21
some_var in Thread-22 after increment is 22
some_var in Thread-23 is 22
some_var in Thread-23 after increment is 23
some_var in Thread-24 is 23
some_var in Thread-24 after increment is 24
some_var in Thread-25 is 24
some_var in Thread-25 after increment is 25
some_var in Thread-26 is 25
some_var in Thread-26 after increment is 26
some_var in Thread-27 is 26
some_var in Thread-27 after increment is 27
some_var in Thread-28 is 27
some_var in Thread-28 after increment is 28
some_var in Thread-29 is 28
some_var in Thread-29 after increment is 29
some_var in Thread-30 is 29
some_var in Thread-30 after increment is 30
some_var in Thread-31 is 30
some_var in Thread-31 after increment is 31
some_var in Thread-32 is 31
some_var in Thread-32 after increment is 32
some_var in Thread-33 is 32
some_var in Thread-33 after increment is 33
some_var in Thread-34 is 33
some_var in Thread-34 after increment is 34
some_var in Thread-35 is 34
some_var in Thread-35 after increment is 35
some_var in Thread-36 is 35
some_var in Thread-36 after increment is 36
some_var in Thread-37 is 36
some_var in Thread-37 after increment is 37
some_var in Thread-38 is 37
some_var in Thread-38 after increment is 38
some_var in Thread-39 is 38
some_var in Thread-39 after increment is 39
some_var in Thread-40 is 39
some_var in Thread-40 after increment is 40
some_var in Thread-41 is 40
some_var in Thread-41 after increment is 41
some_var in Thread-42 is 41
some_var in Thread-42 after increment is 42
some_var in Thread-43 is 42
some_var in Thread-43 after increment is 43
some_var in Thread-44 is 43
some_var in Thread-44 after increment is 44
some_var in Thread-45 is 44
some_var in Thread-45 after increment is 45
some_var in Thread-46 is 45
some_var in Thread-46 after increment is 46
some_var in Thread-47 is 46
some_var in Thread-47 after increment is 47
some_var in Thread-48 is 47
some_var in Thread-48 after increment is 48
some_var in Thread-49 is 48
some_var in Thread-49 after increment is 49
some_var in Thread-50 is 49
some_var in Thread-50 after increment is 50
After 50 modifications, some_var should have become 50
After 50 modifications, some_var is 50
实例三:多线程环境下的原子操作
BUG版本:
1 from threading import Thread 2 import time 3 4 class CreateListThread(Thread): 5 def run(self): 6 self.entries = [] 7 for i in range(10): 8 # time.sleep(0.1) 9 self.entries.append(i) 10 for each in self.entries: 11 print(each, end = " ") 12 time.sleep(0.1) 13 14 def use_create_list_thread(): 15 for i in range(3): 16 t = CreateListThread() 17 t.start() 18 19 use_create_list_thread()
解释:
当一个线程正在打印的时候,cpu切换到了另一个线程,所以产生了不正确的结果。我们需要确保print self.entries是个逻辑上的原子操作,以防打印时被其他线程打断。
因为打印的速度太快,我在此有意放大了这个时间,加了一个time.sleep(0.1)
输出为:
0 0 0 1 1 1 2 2 2 3 3 3 4 4 4 5 5 5 6 6 6 7 7 7 8 8 8 9 9 9
2.加锁保证操作的原子性
1 from threading import Thread, Lock 2 import time 3 4 lock = Lock() 5 6 7 class CreateListThread(Thread): 8 def run(self): 9 self.entries = [] 10 for i in range(10): 11 time.sleep(0.1) 12 self.entries.append(i) 13 lock.acquire() 14 for each in self.entries: 15 print(each, end = " ") 16 time.sleep(0.1) 17 lock.release() 18 19 20 def use_create_list_thread(): 21 for i in range(3): 22 t = CreateListThread() 23 t.start() 24 25 use_create_list_thread()
输出为:
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9
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