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。到目前为止我所拥有的几乎有效,但我需要一些帮助来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
...还有一个快速测试脚本:
#!/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%的情况下完美运行,但它有三个边缘问题。我必须在一个快速的while循环中运行测试脚本来重现这些。
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?
答案 0 :(得分:9)
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,因此在使用拥有进程中的队列时避免了一些不良的特殊情况。 #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。
答案 1 :(得分:0)
我在使用Python 2.7时遇到的multiprocessing
错误远远少于Python 2.6。话虽如此,我用来避免“Exception in thread QueueFeederThread
”问题的解决方案是sleep
在使用Queue
的每个进程中暂时,可能为0.01秒。确实,使用sleep
是不可取的,甚至不可靠,但观察到指定的持续时间对我来说在实践中运作得足够好。你也可以尝试0.1秒。