我正在使用python 3.6
我试图在下面显示的类方法中使用名称为SubmitJobsUsingMultiProcessing()的多处理,它进一步依次调用另一个类方法。
我一直遇到这个错误:输入错误:无法挑选_thread.RLock对象。
我不知道这意味着什么。我怀疑下面一行试图建立与网络服务器API的连接可能是负责任的,但我都在海上了解原因。
我不是一个合适的程序员(代码作为投资组合建模团队的一部分)所以如果这是一个明显的问题,请原谅我的无知,并提前多多感谢。
import multiprocessing as mp,functools
def SubmitJobsUsingMultiProcessing(self,PartitionsOfAnalysisDates,PickleTheJobIdsDict = True):
if (self.ExportSetResult == "SUCCESS"):
NumPools = mp.cpu_count()
PoolObj = mp.Pool(NumPools)
userId,clientId,password,expSetName = self.userId , self.clientId , self.password , self.expSetName
PartialFunctor = functools.partial(self.SubmitJobsAsOfDate,userId = userId,clientId = clientId,password = password,expSetName = expSetName)
Result = PoolObj.map(self.SubmitJobsAsOfDate, PartitionsOfAnalysisDates)
BatchJobIDs = OrderedDict((key, val) for Dct in Result for key, val in Dct.items())
f_pickle = open(self.JobIdPickleFileName, 'wb')
pickle.dump(BatchJobIDs, f_pickle, -1)
f_pickle.close()
def SubmitJobsAsOfDate(self,ListOfDatesForBatchJobs,userId,clientId,password,expSetName):
client = Client(self.url, proxy=self.proxysettings)
if (self.ExportSetResult != "SUCCESS"):
print("The export set creation was not successful...exiting")
sys.exit()
BatchJobIDs = OrderedDict()
NumJobsSubmitted = 0
CurrentProcessID = mp.current_process()
for AnalysisDate in ListOfDatesForBatchJobs:
jobName = "Foo_" + str(AnalysisDate)
print('Sending job from process : ', CurrentProcessID, ' : ', jobName)
jobId = client.service.SubmitExportJob(userId,clientId,password,expSetName, AnalysisDate, jobName, False)
BatchJobIDs[AnalysisDate] = jobId
NumJobsSubmitted += 1
'Sleep for 30 secs every 100 jobs'
if (NumJobsSubmitted % 100 == 0):
print('100 jobs have been submitted thus far from process : ', CurrentProcessID,'---Sleeping for 30 secs to avoid the SSL time out error')
time.sleep(30)
self.BatchJobIDs = BatchJobIDs
return BatchJobIDs
以下是trace ::
Traceback (most recent call last):
File "C:\Program Files\JetBrains\PyCharm 2017.2.3\helpers\pydev\pydevd.py", line 1599, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "C:\Program Files\JetBrains\PyCharm 2017.2.3\helpers\pydev\pydevd.py", line 1026, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "C:\Program Files\JetBrains\PyCharm 2017.2.3\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "C:/Users/trpff85/PycharmProjects/QuantEcon/BDTAPIMultiProcUsingPathos.py", line 289, in <module>
BDTProcessObj.SubmitJobsUsingMultiProcessing(Partitions)
File "C:/Users/trpff85/PycharmProjects/QuantEcon/BDTAPIMultiProcUsingPathos.py", line 190, in SubmitJobsUsingMultiProcessing
Result = PoolObj.map(self.SubmitJobsAsOfDate, PartitionsOfAnalysisDates)
File "C:\Users\trpff85\AppData\Local\Continuum\anaconda3\lib\multiprocessing\pool.py", line 266, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "C:\Users\trpff85\AppData\Local\Continuum\anaconda3\lib\multiprocessing\pool.py", line 644, in get
raise self._value
File "C:\Users\trpff85\AppData\Local\Continuum\anaconda3\lib\multiprocessing\pool.py", line 424, in _handle_tasks
put(task)
File "C:\Users\trpff85\AppData\Local\Continuum\anaconda3\lib\multiprocessing\connection.py", line 206, in send
self._send_bytes(_ForkingPickler.dumps(obj))
File "C:\Users\trpff85\AppData\Local\Continuum\anaconda3\lib\multiprocessing\reduction.py", line 51, in dumps
cls(buf, protocol).dump(obj)
TypeError: can't pickle _thread.RLock objects
答案 0 :(得分:2)
我正在努力解决类似的问题。 &lt; = 3.5中有一个错误,其中_thread.RLock对象在pickle时没有引发错误(它们不能)为了使Pool对象起作用,必须从主进程向它传递一个函数和参数,这依赖于酸洗(酸洗是序列化对象的一种方法)在我的例子中,RLock对象位于日志记录模块中的某个位置。我怀疑你的代码在3.5上运行正常。祝好运。见this bug resolution.