python使用multiprocessing进行多进程编程（1）

multiprocessing模块实现了对多进程编程的封装，让我们可以非常方便的使用多进程进行编程。它的使用方法非常类似threading模块。

1.创建一个进程

import multiprocessing

def worker():
    """worker function"""
    print ‘Worker‘
    return

if __name__ == ‘__main__‘:
    jobs = []
    for i in range(5):
        p = multiprocessing.Process(target=worker)
        jobs.append(p)
        p.start()

输出结果：

$ python multiprocessing_simple.py

Worker
Worker
Worker
Worker
Worker

2.传递参数给子进程

import multiprocessing

def worker(num):
    """thread worker function"""
    print 'Worker:', num
    return

if __name__ == '__main__':
    jobs = []
    for i in range(5):
        p = multiprocessing.Process(target=worker, args=(i,))
        jobs.append(p)
        p.start()

运行结果：

$ python multiprocessing_simpleargs.py

Worker: 0
Worker: 1
Worker: 2
Worker: 3
Worker: 4

注意：所传递的参数必需是可以序列化的

3.后台进程

默认情况下，主进程会等待所有子进程运行完毕后退出。如果需要让子进程独立在后台运行，可以如下操作。

import multiprocessing
import time
import sys

def daemon():
    p = multiprocessing.current_process()
    print 'Starting:', p.name, p.pid
    sys.stdout.flush()
    time.sleep(2)
    print 'Exiting :', p.name, p.pid
    sys.stdout.flush()

def non_daemon():
    p = multiprocessing.current_process()
    print 'Starting:', p.name, p.pid
    sys.stdout.flush()
    print 'Exiting :', p.name, p.pid
    sys.stdout.flush()

if __name__ == '__main__':
    d = multiprocessing.Process(name='daemon', target=daemon)
    d.daemon = True

    n = multiprocessing.Process(name='non-daemon', target=non_daemon)
    n.daemon = False

    d.start()
    time.sleep(1)
    n.start()

运行结果：

$ python multiprocessing_daemon.py

Starting: daemon 13866
Starting: non-daemon 13867
Exiting : non-daemon 13867

可以看到，daemon并没有exiting输出。

4.等待进程

import multiprocessing
import time
import sys

def daemon():
    print 'Starting:', multiprocessing.current_process().name
    time.sleep(2)
    print 'Exiting :', multiprocessing.current_process().name

def non_daemon():
    print 'Starting:', multiprocessing.current_process().name
    print 'Exiting :', multiprocessing.current_process().name

if __name__ == '__main__':
    d = multiprocessing.Process(name='daemon', target=daemon)
    d.daemon = True

    n = multiprocessing.Process(name='non-daemon', target=non_daemon)
    n.daemon = False

    d.start()
    time.sleep(1)
    n.start()

    d.join()
    n.join()

join方法会等待对应的进程执行完毕，然后进行下一步操作。

运行结果：

$ python multiprocessing_daemon_join.py

Starting: non-daemon
Exiting : non-daemon
Starting: daemon
Exiting : daemon

join方法还可以指定timeout参数，等待一段时间，如果子进程还没有执行完毕，那么就会返回。

import multiprocessing
import time
import sys

def daemon():
    print 'Starting:', multiprocessing.current_process().name
    time.sleep(2)
    print 'Exiting :', multiprocessing.current_process().name

def non_daemon():
    print 'Starting:', multiprocessing.current_process().name
    print 'Exiting :', multiprocessing.current_process().name

if __name__ == '__main__':
    d = multiprocessing.Process(name='daemon', target=daemon)
    d.daemon = True

    n = multiprocessing.Process(name='non-daemon', target=non_daemon)
    n.daemon = False

    d.start()
    n.start()

    d.join(1)
    print 'd.is_alive()', d.is_alive()
    n.join()

5.关闭子进程

import multiprocessing
import time

def slow_worker():
    print 'Starting worker'
    time.sleep(0.1)
    print 'Finished worker'

if __name__ == '__main__':
    p = multiprocessing.Process(target=slow_worker)
    print 'BEFORE:', p, p.is_alive()

    p.start()
    print 'DURING:', p, p.is_alive()

    p.terminate()
    print 'TERMINATED:', p, p.is_alive()

    p.join()
    print 'JOINED:', p, p.is_alive()

输出：

$ python multiprocessing_terminate.py

BEFORE: <Process(Process-1, initial)> False
DURING: <Process(Process-1, started)> True
TERMINATED: <Process(Process-1, started)> True
JOINED: <Process(Process-1, stopped[SIGTERM])> False

6.进程返回状态

0，没有错误产生

>0，进程产生了一个错误

<0，进程被杀死

import multiprocessing
import sys
import time

def exit_error():
    sys.exit(1)

def exit_ok():
    return

def return_value():
    return 1

def raises():
    raise RuntimeError('There was an error!')

def terminated():
    time.sleep(3)

if __name__ == '__main__':
    jobs = []
    for f in [exit_error, exit_ok, return_value, raises, terminated]:
        print 'Starting process for', f.func_name
        j = multiprocessing.Process(target=f, name=f.func_name)
        jobs.append(j)
        j.start()

    jobs[-1].terminate()

    for j in jobs:
        j.join()
        print '%s.exitcode = %s' % (j.name, j.exitcode)

输出：

$ python multiprocessing_exitcode.py

Starting process for exit_error
Starting process for exit_ok
Starting process for return_value
Starting process for raises
Starting process for terminated
Process raises:
Traceback (most recent call last):
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python
2.7/multiprocessing/process.py", line 258, in _bootstrap
    self.run()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python
2.7/multiprocessing/process.py", line 114, in run
    self._target(*self._args, **self._kwargs)
  File "multiprocessing_exitcode.py", line 24, in raises
    raise RuntimeError('There was an error!')
RuntimeError: There was an error!
exit_error.exitcode = 1
exit_ok.exitcode = 0
return_value.exitcode = 0
raises.exitcode = 1
terminated.exitcode = -15

python使用multiprocessing进行多进程编程（1）