mutilprocess像线程一样管理进程，这个是mutilprocess的核心，他与threading很是相像，对多核CPU的利用率会比threading好的多。

介绍

Python的multiprocessing模块不但支持多进程，其中managers子模块还支持把多进程分布到多台机器上。一个服务进程可以作为调度者，将任务分布到其他多个机器的多个进程中，依靠网络通信。

想到这，就在想是不是可以使用此模块来实现一个简单的作业调度系统。

实现

Job

首先创建一个Job类，为了测试简单，只包含一个job id属性

job.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
class Job:
def __init__(self, job_id):
self.job_id = job_id

Master

Master用来派发作业和显示运行完成的作业信息

master.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
from Queue import Queue
from multiprocessing.managers import BaseManager
from job import Job

class Master:

def __init__(self):
# 派发出去的作业队列
self.dispatched_job_queue = Queue()
# 完成的作业队列
self.finished_job_queue = Queue()
def get_dispatched_job_queue(self):
return self.dispatched_job_queue
def get_finished_job_queue(self):
return self.finished_job_queue
def start(self):
# 把派发作业队列和完成作业队列注册到网络上
BaseManager.register(\'get_dispatched_job_queue\', callable=self.get_dispatched_job_queue)
BaseManager.register(\'get_finished_job_queue\', callable=self.get_finished_job_queue)
# 监听端口和启动服务
manager = BaseManager(address=(\'0.0.0.0\', 8888), authkey=\'jobs\')
manager.start()
# 使用上面注册的方法获取队列
dispatched_jobs = manager.get_dispatched_job_queue()
finished_jobs = manager.get_finished_job_queue()
# 这里一次派发10个作业，等到10个作业都运行完后，继续再派发10个作业
job_id = 0
while True:
for i in range(0, 10):
job_id = job_id + 1
job = Job(job_id)
print(\'Dispatch job: %s\' % job.job_id)
dispatched_jobs.put(job)
while not dispatched_jobs.empty():
job = finished_jobs.get(60)
print(\'Finished Job: %s\' % job.job_id)
manager.shutdown()
if __name__ == \"__main__\":
master = Master()
master.start()

Slave

Slave用来运行master派发的作业并将结果返回

slave.py

#!/usr/bin/env python
# -*- coding: utf-8 -*-
import time
from Queue import Queue
from multiprocessing.managers import BaseManager
from job import Job

class Slave:

def __init__(self):
# 派发出去的作业队列
self.dispatched_job_queue = Queue()
# 完成的作业队列
self.finished_job_queue = Queue()

def start(self):

# 把派发作业队列和完成作业队列注册到网络上
BaseManager.register(\'get_dispatched_job_queue\')
BaseManager.register(\'get_finished_job_queue\')
# 连接master
server = \'127.0.0.1\'
print(\'Connect to server %s...\' % server)
manager = BaseManager(address=(server, 8888), authkey=\'jobs\')
manager.connect()
# 使用上面注册的方法获取队列
dispatched_jobs = manager.get_dispatched_job_queue()
finished_jobs = manager.get_finished_job_queue()
# 运行作业并返回结果，这里只是模拟作业运行，所以返回的是接收到的作业
while True:
job = dispatched_jobs.get(timeout=1)
print(\'Run job: %s \' % job.job_id)
time.sleep(1)
finished_jobs.put(job)
if __name__ == \"__main__\":
slave = Slave()
slave.start()

测试

分别打开三个linux终端，第一个终端运行master，第二个和第三个终端用了运行slave，运行结果如下

master

$ python master.py 
Dispatch job: 1
Dispatch job: 2
Dispatch job: 3
Dispatch job: 4
Dispatch job: 5
Dispatch job: 6
Dispatch job: 7
Dispatch job: 8
Dispatch job: 9
Dispatch job: 10
Finished Job: 1
Finished Job: 2
Finished Job: 3
Finished Job: 4
Finished Job: 5
Finished Job: 6
Finished Job: 7
Finished Job: 8
Finished Job: 9
Dispatch job: 11
Dispatch job: 12
Dispatch job: 13
Dispatch job: 14
Dispatch job: 15
Dispatch job: 16
Dispatch job: 17
Dispatch job: 18
Dispatch job: 19
Dispatch job: 20
Finished Job: 10
Finished Job: 11
Finished Job: 12
Finished Job: 13
Finished Job: 14
Finished Job: 15
Finished Job: 16
Finished Job: 17
Finished Job: 18
Dispatch job: 21
Dispatch job: 22
Dispatch job: 23
Dispatch job: 24
Dispatch job: 25
Dispatch job: 26
Dispatch job: 27
Dispatch job: 28
Dispatch job: 29
Dispatch job: 30

slave1

$ python slave.py 
Connect to server 127.0.0.1...
Run job: 1 
Run job: 2 
Run job: 3 
Run job: 5 
Run job: 7 
Run job: 9 
Run job: 11 
Run job: 13 
Run job: 15 
Run job: 17 
Run job: 19 
Run job: 21 
Run job: 23 

slave2

$ python slave.py 
Connect to server 127.0.0.1...
Run job: 4 
Run job: 6 
Run job: 8 
Run job: 10 
Run job: 12 
Run job: 14 
Run job: 16 
Run job: 18 
Run job: 20 
Run job: 22 
Run job: 24 

以上内容是小编给大家介绍的Python使用multiprocessing实现一个最简单的分布式作业调度系统，希望对大家有所帮助！