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
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
class Job:
def __init__(self, job_id):
self.job_id = job_id
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Master
Master用来派发作业和显示运行完成的作业信息
master.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from Queue import Queue
from multiprocessing.managers import BaseManager
from job import Job
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class Master:
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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()
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Slave
Slave用来运行master派发的作业并将结果返回
slave.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import time
from Queue import Queue
from multiprocessing.managers import BaseManager
from job import Job
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class Slave:
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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()
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def start(self):
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# 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()
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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
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$ 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
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slave1
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$ 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
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slave2
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$ 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
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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！