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python队列、线程间通信Queue,多进程模块multiprocessing

2017-03-29 15:43 776 查看
python队列

队列是线程间最常用的数据交换形式,Queue是提供队列的操作模块。三种队列:

1、FIFO
2、LIFO
3、Priority

In [3]: import Queue

In [4]: queue= Queue.Queue()

In [5]: queue.empty()
Out[5]: True

In [6]: queue.full()
Out[6]: False

In [7]:

In [7]:

In [7]:

In [7]: queue= Queue.Queue(5)

In [9]: queue.maxsize
Out[9]: 5

In [10]: help(Queue.Queue)

In [11]: queue.empty()
Out[11]: True

In [12]: queue.full()
Out[12]: False

In [13]: queue.maxsize
Out[13]: 5

In [14]: queue.put('aa')

In [15]: queue.empty()
Out[15]: False

In [16]: queue.full()
Out[16]: False

In [17]: queue.maxsize
Out[17]: 5

In [18]: queue.qsize()
Out[18]: 1

In [19]: queue.get()
Out[19]: 'aa'

In [20]: help(queue.put)

In [21]: queue.put(1)

In [22]: queue.put(2)

In [23]: queue.put(3)

In [24]: queue.put(4)

In [25]: queue.put(5)

In [26]: queue.full()
Out[26]: True

In [27]: queue.put(6,1,3)  #保存数据6到队列中,1表示允许阻塞,3表示阻塞3秒后打印报错raise Full
---------------------------------------------------------------------------
Full                                      Traceback (most recent call last)
<ipython-input-27-0bc7da809a7b> in <module>()
----> 1 queue.put(6,1,3)

/opt/amos/python2.7/lib/python2.7/Queue.pyc in put(self, item, block, timeout)
132                         remaining = endtime - _time()
133                         if remaining <= 0.0:
--> 134                             raise Full
135                         self.not_full.wait(remaining)
136             self._put(item)

Full:

In [28]:

In [28]:

In [28]: queue.get()
Out[28]: 1

In [29]: queue.get()
Out[29]: 2

In [30]: queue.get()
Out[30]: 3

In [31]: queue.get()
Out[31]: 4

In [32]: queue.get()
Out[32]: 5

In [34]: queue.qsize()
Out[34]: 0

In [35]: queue.get(1,3) #1表示允许queue的get阻塞,阻塞3秒表示打印错误raise Empty
---------------------------------------------------------------------------
Empty                                     Traceback (most recent call last)
<ipython-input-35-abf44e15db1f> in <module>()
----> 1 queue.get(1,3)

/opt/amos/python2.7/lib/python2.7/Queue.pyc in get(self, block, timeout)
174                     remaining = endtime - _time()
175                     if remaining <= 0.0:
--> 176                         raise Empty
177                     self.not_empty.wait(remaining)
178             item = self._get()


[root@133 managehosts]# vim queue01.py
#!/usr/bin/env python
import threading
import Queue
import time
import random

class consumer(threading.Thread):#等号右边的queue是参数,即def __init__(self,queue)这里出现的,把这个参数赋值给self.queue这个属性。
def __init__(self, queue):
threading.Thread.__init__(self)#threading.Thread.__init__(self)这种写法是类的继承,类的继承还有一种写法,回顾一下,看看类继承那个视频。
self.queue = queue  #等号右边的queue是参数,即def __init__(self,queue)这里出现的,把这个参数赋值给self.queue这个属性。

def run(self):
while True:
if self.queue.empty():
break
data = self.queue.get()
print data
time.sleep(1)

if __name__ == '__main__':
queue = Queue.Queue(10)
for i in xrange(10):
queue.put(random.randint(1,9))#保存1-9的随机数到queue中,保存10次
for i in range(3):        #创建3个线程,这3个线程就像3条河流,会同时向前走的,所以同时会产生3个数字,多线程就是每个线程都会运行的。
c = consumer(queue)
c.start()
#c.start(),是开启一个线程,循环开3个线程与不用循环,开3个线程,是一样的。
#第一次循环里,c.start()已经执行完了,再执行第二循环,无所谓把对象覆盖了,因为c.start()已经执行完了
#队列是全局队列,每个线程都可以访问这个队列
[root@133 managehosts]# python queue01.py
5
8
2
2
6
6
5
6
9
5


例子:开启3个线程去队列取数据,取的结果为空,则推出,由于queue队列的输入是10个随机数(1-9),所以3个线程取到10个数后,就break
[root@133 managehosts]# vim queue02.py
#!/usr/bin/env python
import threading
import Queue
import time
import random

class consumer(threading.Thread):
def __init__(self, queue):
threading.Thread.__init__(self)
self.queue = queue

def run(self):
while True:
data = self.queue.get()
if data == None:
break
print self.name,data,time.ctime()

if __name__ == '__main__':
queue = Queue.Queue(10)
for i in range(3):
c = consumer(queue)
c.start()

for i in xrange(10):
queue.put(random.randint(1,9))
time.sleep(1)
queue.put(None)
queue.put(None)
queue.put(None)

[root@133 managehosts]# python queue02.py
Thread-1 7 Wed Mar 29 17:43:46 2017
Thread-2 3 Wed Mar 29 17:43:47 2017
Thread-3 7 Wed Mar 29 17:43:48 2017
Thread-1 9 Wed Mar 29 17:43:49 2017
Thread-2 4 Wed Mar 29 17:43:50 2017
Thread-3 1 Wed Mar 29 17:43:51 2017
Thread-1 8 Wed Mar 29 17:43:52 2017
Thread-2 3 Wed Mar 29 17:43:53 2017
Thread-3 1 Wed Mar 29 17:43:54 2017
Thread-1 6 Wed Mar 29 17:43:55 2017


Queue的例子
实现一个线程不断生成一个随机数到一个队列中
实现一个线程从上面的队列中不断的取出奇数
实现另一个线程从上面的队列中不断取出偶数
cat queue03.py
#!/usr/bin/env python
import threading
import random
import Queue
import time

def producer(name,queue):
for i in xrange(10):
num = random.randint(1,10)
th_name = name + '-' +threading.currentThread().getName()
print "%s: %s ----> %s" % (time.ctime(), th_name,num)
queue.put(num)
time.sleep(1)

def odd(name,queue):
th_name = name + '-' + threading.currentThread().getName()
while True:
try:
val_odd = queue.get(1,5)
if val_odd % 2 !=0:
print "%s: %s  ---> %s" %(time.ctime(), th_name, val_odd)
else:
queue.put(val_odd)
time.sleep(1)
except:
print "%s: %s finished" % (time.ctime(), th_name)
break

def even(name,queue):
th_name = name + '-' + threading.currentThread().getName()
while True:
try:
val_even = queue.get(1,5)
if val_even % 2 ==0:
print "%s: %s  ---> %s" %(time.ctime(), th_name, val_even)
time.sleep(1)
else:
queue.put(val_even)
time.sleep(1)
except:
print "%s: %s finished" % (time.ctime(), th_name)
break
def main():
q = Queue.Queue(10)
t_pro = threading.Thread(target=producer,args=('pro',q))
t_odd = threading.Thread(target=odd,args=('odd',q))
t_even = threading.Thread(target=even,args=('even',q))
t_pro.start()
t_odd.start()
t_even.start()

if __name__== '__main__':
main()

[root@133 managehosts]# python queue03.py
Wed Mar 29 19:52:38 2017: pro-Thread-1 ----> 2
Wed Mar 29 19:52:38 2017: even-Thread-3  ---> 2

Wed Mar 29 19:52:39 2017: pro-Thread-1 ----> 6
Wed Mar 29 19:52:39 2017: even-Thread-3  ---> 6
Wed Mar 29 19:52:40 2017: pro-Thread-1 ----> 6
Wed Mar 29 19:52:40 2017: even-Thread-3  ---> 6
Wed Mar 29 19:52:41 2017: pro-Thread-1 ----> 8
Wed Mar 29 19:52:41 2017: even-Thread-3  ---> 8
Wed Mar 29 19:52:42 2017: pro-Thread-1 ----> 8
Wed Mar 29 19:52:42 2017: even-Thread-3  ---> 8
Wed Mar 29 19:52:43 2017: pro-Thread-1 ----> 3
Wed Mar 29 19:52:43 2017: odd-Thread-2  ---> 3
Wed Mar 29 19:52:44 2017: pro-Thread-1 ----> 4
Wed Mar 29 19:52:44 2017: even-Thread-3  ---> 4
Wed Mar 29 19:52:45 2017: pro-Thread-1 ----> 8
Wed Mar 29 19:52:45 2017: even-Thread-3  ---> 8
Wed Mar 29 19:52:46 2017: pro-Thread-1 ----> 8
Wed Mar 29 19:52:46 2017: even-Thread-3  ---> 8
Wed Mar 29 19:52:47 2017: pro-Thread-1 ----> 5
Wed Mar 29 19:52:47 2017: odd-Thread-2  ---> 5
Wed Mar 29 19:52:52 2017: odd-Thread-2 finished
Wed Mar 29 19:52:52 2017: even-Thread-3 finished


python的全局解释性锁GIL,无论有多少个cpu,只有一个cpu能轮训处理多个线程。
multiprocessing可以让多个cpu处理多个进程。(方法和threading差不多)
[root@133 managehosts]# vim multiprocessing01.py
#!/usr/bin/env python

import multiprocessing
import os
import time

def func(i):
print 'hello',i,os.getpid(),os.getppid()
time.sleep(1)

for i in xrange(10):
p = multiprocessing.Process(target=func,args=(i,))
p.start()

[root@133 managehosts]# python multiprocessing01.py #主进程ppid都是31382,子进程pid不同
hello 0 31383 31382
hello 1 31384 31382
hello 2 31385 31382
hello 3 31386 31382
hello 4 31387 31382
hello 5 31388 31382
hello 6 31389 31382
hello 7 31390 31382
hello 8 31391 31382
hello 9 31392 31382
多线程(一个cpu切换运行多个线程)
[root@133 ~]# vim threading-multiprocessing02.py
#!/usr/bin/env python
import threading
import multiprocessing
import os
import time

def func():
while True:
1 + 1

for i in range(20):
t = threading.Thread(target=func,args=())
t.start()
print "process id is %s" % os.getpid()

[root@133 managehosts]# python threading-multiprocessing02.py
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994
process id is 31994

[root@133 ~]# top
top - 20:34:53 up 406 days,  1:45,  2 users,  load average: 0.12, 0.08, 0.02
Tasks: 248 total,   2 running, 246 sleeping,   0 stopped,   0 zombie
Cpu0  : 26.5%us, 17.3%sy,  0.0%ni, 56.1%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu1  : 23.3%us, 14.6%sy,  0.0%ni, 62.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu2  :  8.4%us, 10.8%sy,  0.0%ni, 80.8%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu3  : 18.2%us, 15.0%sy,  0.0%ni, 66.8%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu4  :  6.1%us,  9.6%sy,  0.0%ni, 84.3%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu5  :  9.6%us,  7.8%sy,  0.0%ni, 82.6%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu6  :  5.0%us,  6.3%sy,  0.0%ni, 88.7%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu7  :  6.5%us,  4.5%sy,  0.0%ni, 89.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Mem:  20455792k total, 19930312k used,   525480k free,   315820k buffers
Swap:  8388604k total,   157072k used,  8231532k free, 16260864k cached

PID USER      PR  NI  VIRT  RES  SHR S %CPU %MEM    TIME+  COMMAND
10303 amos      20   0 7490m 1.1g 8096 S  0.0  5.5  16:57.94 mysqld
20678 qemu      20   0 4862m 644m 4124 R  9.3  3.2  14493:02 qemu-kvm
3164 qemu      20   0 4685m 328m 1240 S 10.3  1.6  49795:22 qemu-kvm
18481 root      20   0 2797m  48m 3096 S  0.0  0.2   0:05.15 salt-master
18484 root      20   0 2797m  47m 3080 S  0.0  0.2   0:05.03 salt-master
18487 root      20   0 2796m  47m 3088 S  0.0  0.2   0:04.96 salt-master
18477 root      20   0 2797m  47m 3088 S  0.0  0.2   0:05.10 salt-master
18478 root      20   0 2796m  47m 3096 S  0.0  0.2   0:05.30 salt-master
31994 root      20   0 3402m  43m 1944 S 171.6  0.2   1:15.35 python
多进程(多个进程使用多个cpu同时运行程序)
[root@133 managehosts]# vim multiprocessing03.py
#!/usr/bin/env python
import threading
import multiprocessing
import os
import time
from multiprocessing import Process
import os
def func():
while True:
1 + 1
for i in range(20):
t = Process(target=func,args=())
t.start()
[root@133 managehosts]# python multiprocessing03.py

#同时有多个进程在运行,
[root@133 managehosts]# ps aux | grep python
root     32591  0.0  0.0 133228  5440 pts/6    S+   20:50   0:00 python multiprocessing03.py
root     32592 34.0  0.0 133228  3936 pts/6    R+   20:50   0:14 python multiprocessing03.py
root     32593 43.4  0.0 133228  3940 pts/6    R+   20:50   0:18 python multiprocessing03.py
root     32594 37.7  0.0 133228  3940 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32595 40.1  0.0 133228  3940 pts/6    R+   20:50   0:17 python multiprocessing03.py
root     32596 33.8  0.0 133228  3940 pts/6    R+   20:50   0:14 python multiprocessing03.py
root     32597 38.5  0.0 133228  3944 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32598 40.0  0.0 133228  3948 pts/6    R+   20:50   0:17 python multiprocessing03.py
root     32599 46.0  0.0 133228  3948 pts/6    R+   20:50   0:19 python multiprocessing03.py
root     32600 46.0  0.0 133228  3952 pts/6    R+   20:50   0:19 python multiprocessing03.py
root     32601 37.5  0.0 133228  3952 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32602 39.9  0.0 133228  3956 pts/6    R+   20:50   0:17 python multiprocessing03.py
root     32603 38.3  0.0 133228  3960 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32604 37.0  0.0 133228  3964 pts/6    R+   20:50   0:15 python multiprocessing03.py
root     32605 38.3  0.0 133228  3964 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32606 32.9  0.0 133228  3964 pts/6    R+   20:50   0:14 python multiprocessing03.py
root     32607 37.7  0.0 133228  3968 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32608 39.2  0.0 133228  3968 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32609 39.4  0.0 133228  3972 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32610 37.3  0.0 133228  3972 pts/6    R+   20:50   0:16 python multiprocessing03.py
root     32611 34.3  0.0 133228  3972 pts/6    R+   20:50   0:14 python multiprocessing03.py

#负载增加,load不断升高,0.0%id空闲cpu为0,全部cpu被使用,
[root@133 managehosts]# top
top - 20:52:18 up 406 days,  2:03,  2 users,  load average: 16.32, 5.79, 2.07
Tasks: 266 total,  21 running, 245 sleeping,   0 stopped,   0 zombie
Cpu0  : 96.4%us,  3.6%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu1  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu2  : 97.7%us,  2.3%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu3  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu4  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu5  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu6  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Cpu7  :100.0%us,  0.0%sy,  0.0%ni,  0.0%id,  0.0%wa,  0.0%hi,  0.0%si,  0.0%st
Mem:  20455792k total, 19900920k used,   554872k free,   315820k buffers
Swap:  8388604k total,   157072k used,  8231532k free, 16260928k cached

PID USER      PR  NI  VIRT  RES  SHR S %CPU %MEM    TIME+  COMMAND
32599 root      20   0  130m 3948  536 R 47.1  0.0   0:46.09 python
32600 root      20   0  130m 3952  536 R 46.7  0.0   0:46.08 python
32604 root      20   0  130m 3964  536 R 43.8  0.0   0:35.82 python
32605 root      20   0  130m 3964  536 R 42.8  0.0   0:38.77 python
32598 root      20   0  130m 3948  536 R 41.8  0.0   0:39.72 python
32601 root      20   0  130m 3952  536 R 40.4  0.0   0:38.84 python
32610 root      20   0  130m 3972  536 R 40.4  0.0   0:38.91 python
32593 root      20   0  130m 3940  536 R 39.8  0.0   0:40.42 python
32595 root      20   0  130m 3940  536 R 39.8  0.0   0:39.61 python
32607 root      20   0  130m 3968  536 R 39.4  0.0   0:37.95 python
32597 root      20   0  130m 3944  536 R 39.1  0.0   0:38.28 python
32609 root      20   0  130m 3972  536 R 39.1  0.0   0:38.30 python
32611 root      20   0  130m 3972  536 R 37.5  0.0   0:34.07 python
32602 root      20   0  130m 3956  536 R 37.1  0.0   0:41.16 python
32608 root      20   0  130m 3968  536 R 37.1  0.0   0:38.57 python
32603 root      20   0  130m 3960  536 R 36.8  0.0   0:39.07 python
32596 root      20   0  130m 3940  536 R 36.5  0.0   0:36.10 python
32592 root      20   0  130m 3936  532 R 35.8  0.0   0:33.52 python
32606 root      20   0  130m 3964  536 R 33.8  0.0   0:33.52 python
32594 root      20   0  130m 3940  536 R 32.5  0.0   0:35.69 python
20678 qemu      20   0 4862m 644m 4124 S  5.6  3.2  14494:46 qemu-kvm
3164 qemu      20   0 4685m 328m 1240 S  5.0  1.6  49797:00 qemu-kvm
35 root      20   0     0    0    0 S  0.3  0.0   2877:33 events/0
进程池Pool
multiprocessing.Pool很方便饿同时处理几百个和上千个并行的操作,脚本的复杂性大大降低。
pool = multiprocessing.Pool(process=3) //设置最大进程数3

pool.close() //会等待池中的worker进程执行结束后再关闭pool
pool.terminate()//直接关闭pool
pool.join() //等待进程池中的worker进程执行完毕,阻塞主进程,但必须使用在pool.close()或则pool.terminate()之后
[root@133 managehosts]# vim multiprocessing-pool.py
#!/usr/bin/env python

import multiprocessing
from subprocess import Popen,PIPE

def run(id):
p = Popen('vim', stdout=PIPE,stderr=PIPE)
p.communicate()
print "Task: %s " %id

pool = multiprocessing.Pool()
for i in xrange(10):
pool.apply_async(func=run, args=(i,))
print "Wait....."
pool.close()
pool.join()
print "Done"
[root@133 managehosts]# python multiprocessing-pool.py
Wait.....

8核心运行8个进程
[root@133 managehosts]# ps aux | grep vim
root      1068  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1069  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1070  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1071  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1072  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1073  0.1  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1074  0.1  0.0 138996  4968 pts/6    S+   21:19   0:00 vim
root      1076  0.1  0.0 138996  4968 pts/6    S+   21:19   0:00 vim
root      1101  0.0  0.0 103316   904 pts/5    S+   21:20   0:00 grep vim

[root@133 managehosts]# ps -ef | grep python
root      1056 32539  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1057  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1058  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1059  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1060  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1061  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1062  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1063  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py
root      1064  1056  0 21:19 pts/6    00:00:00 python multiprocessing-pool.py

杀掉一个子进程后,又产生一个进程
[root@133 managehosts]# kill 1068
[root@133 managehosts]# ps aux | grep vim
root      1069  0.0  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1070  0.0  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1071  0.0  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1072  0.0  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1073  0.0  0.0 138996  4964 pts/6    S+   21:19   0:00 vim
root      1074  0.0  0.0 138996  4968 pts/6    S+   21:19   0:00 vim
root      1076  0.0  0.0 138996  4968 pts/6    S+   21:19   0:00 vim
root      1231  0.5  0.0 138996  4968 pts/6    S+   21:24   0:00 vim
root      1234  0.0  0.0 103316   904 pts/5    S+   21:24   0:00 grep vim
[root@133 managehosts]#
[root@133 managehosts]# python multiprocessing-pool.py
Wait.....
Task: 1
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