Python多处理:同步类文件对象

Question

我正在尝试创建一个像object这样的文件,它在测试期间分配给sys.stdout/sys.stderr以提供确定性输出.它并不意味着快速,可靠.到目前为止我几乎可以工作,但我需要一些帮助摆脱最后几个边缘错误.

这是我目前的实施.

try:
    from cStringIO import StringIO
except ImportError:
    from StringIO import StringIO

from os import getpid
class MultiProcessFile(object):
    """
    helper for testing multiprocessing

    multiprocessing poses a problem for doctests, since the strategy
    of replacing sys.stdout/stderr with file-like objects then
    inspecting the results won't work: the child processes will
    write to the objects, but the data will not be reflected
    in the parent doctest-ing process.

    The solution is to create file-like objects which will interact with
    multiprocessing in a more desirable way.

    All processes can write to this object, but only the creator can read.
    This allows the testing system to see a unified picture of I/O.
    """
    def __init__(self):
        # per advice at:
        #    http://docs.python.org/library/multiprocessing.html#all-platforms
        from multiprocessing import Queue
        self.__master = getpid()
        self.__queue = Queue()
        self.__buffer = StringIO()
        self.softspace = 0

    def buffer(self):
        if getpid() != self.__master:
            return

        from Queue import Empty
        from collections import defaultdict
        cache = defaultdict(str)
        while True:
            try:
                pid, data = self.__queue.get_nowait()
            except Empty:
                break
            cache[pid] += data
        for pid in sorted(cache):
            self.__buffer.write( '%s wrote: %r\n' % (pid, cache[pid]) )
    def write(self, data):
        self.__queue.put((getpid(), data))
    def __iter__(self):
        "getattr doesn't work for iter()"
        self.buffer()
        return self.__buffer
    def getvalue(self):
        self.buffer()
        return self.__buffer.getvalue()
    def flush(self):
        "meaningless"
        pass

......以及快速测试脚本:

#!/usr/bin/python2.6

from multiprocessing import Process
from mpfile import MultiProcessFile

def printer(msg):
    print msg

processes = []
for i in range(20):
    processes.append( Process(target=printer, args=(i,), name='printer') )

print 'START'
import sys
buffer = MultiProcessFile()
sys.stdout = buffer

for p in processes:
    p.start()
for p in processes:
    p.join()

for i in range(20):
    print i,
print

sys.stdout = sys.__stdout__
sys.stderr = sys.__stderr__
print 
print 'DONE'
print
buffer.buffer()
print buffer.getvalue()

这种方法在95%的时间内完美运行,但它有三个边缘问题.我必须在快速while循环中运行测试脚本来重现这些.

1. 3%的时间,父进程输出没有完全反映出来.我假设这是因为在Queue-flushing线程可以赶上之前消耗了数据.我没有办法等待没有死锁的线程.
2. .5%的时间,有一个来自multiprocess.Queue实现的追溯
3. .01%的时间,PID回绕,因此按PID排序会产生错误的排序.

在最糟糕的情况下(赔率:7000万分之一),输出看起来像这样:

START

DONE

302 wrote: '19\n'
32731 wrote: '0 1 2 3 4 5 6 7 8 '
32732 wrote: '0\n'
32734 wrote: '1\n'
32735 wrote: '2\n'
32736 wrote: '3\n'
32737 wrote: '4\n'
32738 wrote: '5\n'
32743 wrote: '6\n'
32744 wrote: '7\n'
32745 wrote: '8\n'
32749 wrote: '9\n'
32751 wrote: '10\n'
32752 wrote: '11\n'
32753 wrote: '12\n'
32754 wrote: '13\n'
32756 wrote: '14\n'
32757 wrote: '15\n'
32759 wrote: '16\n'
32760 wrote: '17\n'
32761 wrote: '18\n'

Exception in thread QueueFeederThread (most likely raised during interpreter shutdown):
Traceback (most recent call last):
  File "/usr/lib/python2.6/threading.py", line 532, in __bootstrap_inner
  File "/usr/lib/python2.6/threading.py", line 484, in run
      File "/usr/lib/python2.6/multiprocessing/queues.py", line 233, in _feed
<type 'exceptions.TypeError'>: 'NoneType' object is not callable

在python2.7中,异常略有不同:

Exception in thread QueueFeederThread (most likely raised during interpreter shutdown):
Traceback (most recent call last):
  File "/usr/lib/python2.7/threading.py", line 552, in __bootstrap_inner
  File "/usr/lib/python2.7/threading.py", line 505, in run
  File "/usr/lib/python2.7/multiprocessing/queues.py", line 268, in _feed
<type 'exceptions.IOError'>: [Errno 32] Broken pipe

如何摆脱这些边缘情况？

Answer 1

解决方案分为两部分.我已成功运行测试程序20万次而没有任何输出变化.

简单的部分是使用multiprocessing.current_process()._ identity来对消息进行排序.这不是已发布API的一部分,但它是每个进程的唯一确定性标识符.这解决了PID缠绕并给出错误的输出顺序的问题.

解决方案的另一部分是使用multiprocessing.Manager().Queue()而不是multiprocessing.Queue.这解决了上面的问题#2,因为管理器位于一个单独的进程中,因此避免了在拥有进程中使用队列时的一些不良特殊情况.#3是固定的,因为Queue完全耗尽,并且在python开始关闭并关闭stdin之前,馈线线程自然死亡.