本文整理汇总了Python中taskbuffer.FileSpec.FileSpec.status方法的典型用法代码示例。如果您正苦于以下问题:Python FileSpec.status方法的具体用法?Python FileSpec.status怎么用?Python FileSpec.status使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类taskbuffer.FileSpec.FileSpec
的用法示例。
在下文中一共展示了FileSpec.status方法的5个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: prepare
# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import status [as 别名]
def prepare(self,app,appsubconfig,appmasterconfig,jobmasterconfig):
'''prepare the subjob specific configuration'''
from pandatools import Client
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('AthenaPandaRTHandler prepare called for %s', job.getFQID('.'))
# in case of a simple job get the dataset content, otherwise subjobs are filled by the splitter
if job.inputdata and not job._getRoot().subjobs:
if not job.inputdata.names:
contents = job.inputdata.get_contents(overlap=False, size=True)
for ds in contents.keys():
for f in contents[ds]:
job.inputdata.guids.append( f[0] )
job.inputdata.names.append( f[1][0] )
job.inputdata.sizes.append( f[1][1] )
job.inputdata.checksums.append( f[1][2] )
job.inputdata.scopes.append( f[1][3] )
site = job._getRoot().backend.site
job.backend.site = site
job.backend.actualCE = site
cloud = job._getRoot().backend.requirements.cloud
job.backend.requirements.cloud = cloud
# if no outputdata are given
if not job.outputdata:
job.outputdata = DQ2OutputDataset()
job.outputdata.datasetname = job._getRoot().outputdata.datasetname
#if not job.outputdata.datasetname:
else:
job.outputdata.datasetname = job._getRoot().outputdata.datasetname
if not job.outputdata.datasetname:
raise ApplicationConfigurationError('DQ2OutputDataset has no datasetname')
jspec = JobSpec()
jspec.jobDefinitionID = job._getRoot().id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.transformation = '%s/runGen-00-00-02' % Client.baseURLSUB
if job.inputdata:
jspec.prodDBlock = job.inputdata.dataset[0]
else:
jspec.prodDBlock = 'NULL'
jspec.destinationDBlock = job.outputdata.datasetname
if job.outputdata.location:
if not job._getRoot().subjobs or job.id == 0:
logger.warning('You have specified outputdata.location. Note that Panda may not support writing to a user-defined output location.')
jspec.destinationSE = job.outputdata.location
else:
jspec.destinationSE = site
jspec.prodSourceLabel = configPanda['prodSourceLabelRun']
jspec.processingType = configPanda['processingType']
jspec.assignedPriority = configPanda['assignedPriorityRun']
jspec.cloud = cloud
# memory
if job.backend.requirements.memory != -1:
jspec.minRamCount = job.backend.requirements.memory
# cputime
if job.backend.requirements.cputime != -1:
jspec.maxCpuCount = job.backend.requirements.cputime
jspec.computingSite = site
# library (source files)
if job.backend.libds:
flib = FileSpec()
flib.lfn = self.fileBO.lfn
flib.GUID = self.fileBO.GUID
flib.type = 'input'
flib.status = self.fileBO.status
flib.dataset = self.fileBO.destinationDBlock
flib.dispatchDBlock = self.fileBO.destinationDBlock
jspec.addFile(flib)
elif job.backend.bexec:
flib = FileSpec()
flib.lfn = self.library
flib.type = 'input'
flib.dataset = self.libDataset
flib.dispatchDBlock = self.libDataset
jspec.addFile(flib)
# input files FIXME: many more input types
if job.inputdata:
for guid, lfn, size, checksum, scope in zip(job.inputdata.guids,job.inputdata.names,job.inputdata.sizes, job.inputdata.checksums, job.inputdata.scopes):
finp = FileSpec()
finp.lfn = lfn
finp.GUID = guid
finp.scope = scope
# finp.fsize =
# finp.md5sum =
finp.dataset = job.inputdata.dataset[0]
#.........这里部分代码省略.........
示例2: prepare
# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import status [as 别名]
def prepare(self,app,appconfig,appmasterconfig,jobmasterconfig):
'''prepare the subjob specific configuration'''
# PandaTools
from pandatools import Client
from pandatools import AthenaUtils
from taskbuffer.JobSpec import JobSpec
from taskbuffer.FileSpec import FileSpec
job = app._getParent()
logger.debug('AthenaMCPandaRTHandler prepare called for %s', job.getFQID('.'))
try:
assert self.outsite
except:
logger.error("outsite not set. Aborting")
raise Exception()
job.backend.site = self.outsite
job.backend.actualCE = self.outsite
cloud = job._getRoot().backend.requirements.cloud
job.backend.requirements.cloud = cloud
# now just filling the job from AthenaMC data
jspec = JobSpec()
jspec.jobDefinitionID = job._getRoot().id
jspec.jobName = commands.getoutput('uuidgen 2> /dev/null')
jspec.AtlasRelease = 'Atlas-%s' % app.atlas_rel
if app.transform_archive:
jspec.homepackage = 'AnalysisTransforms'+app.transform_archive
elif app.prod_release:
jspec.homepackage = 'AnalysisTransforms-AtlasProduction_'+str(app.prod_release)
jspec.transformation = '%s/runAthena-00-00-11' % Client.baseURLSUB
#---->???? prodDBlock and destinationDBlock when facing several input / output datasets?
jspec.prodDBlock = 'NULL'
if job.inputdata and len(app.inputfiles)>0 and app.inputfiles[0] in app.dsetmap:
jspec.prodDBlock = app.dsetmap[app.inputfiles[0]]
# How to specify jspec.destinationDBlock when more than one type of output is available? Panda prod jobs seem to specify only the last output dataset
outdset=""
for type in ["EVNT","RDO","HITS","AOD","ESD","NTUP"]:
if type in app.outputpaths.keys():
outdset=string.replace(app.outputpaths[type],"/",".")
outdset=outdset[1:-1]
break
if not outdset:
try:
assert len(app.outputpaths.keys())>0
except:
logger.error("app.outputpaths is empty: check your output datasets")
raise
type=app.outputpaths.keys()[0]
outdset=string.replace(app.outputpaths[type],"/",".")
outdset=outdset[1:-1]
jspec.destinationDBlock = outdset
jspec.destinationSE = self.outsite
jspec.prodSourceLabel = 'user'
jspec.assignedPriority = 1000
jspec.cloud = cloud
# memory
if job.backend.requirements.memory != -1:
jspec.minRamCount = job.backend.requirements.memory
jspec.computingSite = self.outsite
jspec.cmtConfig = AthenaUtils.getCmtConfig(athenaVer=app.atlas_rel)
# library (source files)
flib = FileSpec()
flib.lfn = self.library
# flib.GUID =
flib.type = 'input'
# flib.status =
flib.dataset = self.libDataset
flib.dispatchDBlock = self.libDataset
jspec.addFile(flib)
# input files FIXME: many more input types
for lfn in app.inputfiles:
useguid=app.turls[lfn].replace("guid:","")
finp = FileSpec()
finp.lfn = lfn
finp.GUID = useguid
finp.dataset = app.dsetmap[lfn]
finp.prodDBlock = app.dsetmap[lfn]
finp.prodDBlockToken = 'local'
finp.dispatchDBlock = app.dsetmap[lfn]
finp.type = 'input'
finp.status = 'ready'
jspec.addFile(finp)
# add dbfiles if any:
for lfn in app.dbfiles:
useguid=app.dbturls[lfn].replace("guid:","")
finp = FileSpec()
finp.lfn = lfn
finp.GUID = useguid
finp.dataset = app.dsetmap[lfn]
#.........这里部分代码省略.........
示例3: FileSpec
# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import status [as 别名]
fileOZ.dataset = job.destinationDBlock
fileOZ.type = 'output'
job.addFile(fileOZ)
files = [
'testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00001.pool.root.1',
'testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00002.pool.root.1',
'testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00003.pool.root.1',
]
for lfn in files:
fileI = FileSpec()
fileI.dataset = job.prodDBlock
fileI.prodDBlock = job.prodDBlock
fileI.lfn = lfn
fileI.type = 'input'
fileI.status = 'ready'
job.addFile(fileI)
fileL = FileSpec()
fileL.dataset = 'user.TadashiMaeno.lib._000157'
fileL.prodDBlock = 'user.TadashiMaeno.lib._000157'
fileL.lfn = 'user.TadashiMaeno.lib._000157.lib.tgz'
fileL.type = 'input'
fileL.status = 'ready'
job.addFile(fileL)
job.jobParameters=""" -l user.TadashiMaeno.lib._000157.lib.tgz -r run/ -j " AnalysisSkeleton_jobOptions.py" -i "['testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00001.pool.root.1', 'testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00002.pool.root.1', 'testIdeal_06.005001.pythia_minbias.recon.AOD.v12000103._00003.pool.root.1']" -o "{'AANT': [('AANTupleStream', 'AANT', '%s')]}" """ % fileOZ.lfn
jobList.append(job)
示例4: FileSpec
# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import status [as 别名]
file.destinationDBlock = job.destinationDBlock
file.destinationSE = job.destinationSE
file.dataset = job.destinationDBlock
file.type = 'output'
job.addFile(file)
fileOL = FileSpec()
fileOL.lfn = "%s.job.log.tgz" % job.jobName
fileOL.destinationDBlock = job.destinationDBlock
fileOL.destinationSE = job.destinationSE
fileOL.dataset = job.destinationDBlock
fileOL.type = 'log'
job.addFile(fileOL)
fileL = FileSpec()
fileL.dataset = 'user.TadashiMaeno.acas0003.lib._000134'
fileL.prodDBlock = fileL.dataset
fileL.lfn = 'user.TadashiMaeno.acas0003.lib._000134.lib.tgz'
fileL.type = 'input'
fileL.status = 'ready'
job.addFile(fileL)
job.jobParameters=("-l %s " % fileL.lfn) + """-r run/ -j "%20AnalysisSkeleton_topOptions.py" -i "[]" -m "[]" -n "[]" -o "{'AANT': [('AANTupleStream', 'AANT', """ + ("""'%s')]}" -c""" % file.lfn)
jobList.append(job)
s,o = Client.submitJobs(jobList)
print "---------------------"
print s
for x in o:
print "PandaID=%s" % x[0]
示例5: send_job
# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import status [as 别名]
def send_job(jobid, siteid):
_logger.debug('Jobid: ' + str(jobid))
site = sites_.get(siteid)
job = jobs_.get(int(jobid))
cont = job.container
files_catalog = cont.files
fscope = getScope(job.owner.username)
datasetName = '{}:{}'.format(fscope, cont.guid)
distributive = job.distr.name
release = job.distr.release
# Prepare runScript
parameters = job.distr.command
parameters = parameters.replace("$COMMAND$", job.params)
parameters = parameters.replace("$USERNAME$", job.owner.username)
parameters = parameters.replace("$WORKINGGROUP$", job.owner.working_group)
# Prepare metadata
metadata = dict(user=job.owner.username)
# Prepare PanDA Object
pandajob = JobSpec()
pandajob.jobDefinitionID = int(time.time()) % 10000
pandajob.jobName = cont.guid
pandajob.transformation = client_config.DEFAULT_TRF
pandajob.destinationDBlock = datasetName
pandajob.destinationSE = site.se
pandajob.currentPriority = 1000
pandajob.prodSourceLabel = 'user'
pandajob.computingSite = site.ce
pandajob.cloud = 'RU'
pandajob.VO = 'atlas'
pandajob.prodDBlock = "%s:%s" % (fscope, pandajob.jobName)
pandajob.coreCount = job.corecount
pandajob.metadata = json.dumps(metadata)
#pandajob.workingGroup = job.owner.working_group
if site.encode_commands:
# It requires script wrapper on cluster side
pandajob.jobParameters = '%s %s %s "%s"' % (cont.guid, release, distributive, parameters)
else:
pandajob.jobParameters = parameters
has_input = False
for fcc in files_catalog:
if fcc.type == 'input':
f = fcc.file
guid = f.guid
fileIT = FileSpec()
fileIT.lfn = f.lfn
fileIT.dataset = pandajob.prodDBlock
fileIT.prodDBlock = pandajob.prodDBlock
fileIT.type = 'input'
fileIT.scope = fscope
fileIT.status = 'ready'
fileIT.GUID = guid
pandajob.addFile(fileIT)
has_input = True
if fcc.type == 'output':
f = fcc.file
fileOT = FileSpec()
fileOT.lfn = f.lfn
fileOT.destinationDBlock = pandajob.prodDBlock
fileOT.destinationSE = pandajob.destinationSE
fileOT.dataset = pandajob.prodDBlock
fileOT.type = 'output'
fileOT.scope = fscope
fileOT.GUID = f.guid
pandajob.addFile(fileOT)
# Save replica meta
fc.new_replica(f, site)
if not has_input:
# Add fake input
fileIT = FileSpec()
fileIT.lfn = "fake.input"
fileIT.dataset = pandajob.prodDBlock
fileIT.prodDBlock = pandajob.prodDBlock
fileIT.type = 'input'
fileIT.scope = fscope
fileIT.status = 'ready'
fileIT.GUID = "fake.guid"
pandajob.addFile(fileIT)
# Prepare lof file
fileOL = FileSpec()
fileOL.lfn = "%s.log.tgz" % pandajob.jobName
fileOL.destinationDBlock = pandajob.destinationDBlock
fileOL.destinationSE = pandajob.destinationSE
fileOL.dataset = '{}:logs'.format(fscope)
fileOL.type = 'log'
fileOL.scope = 'panda'
pandajob.addFile(fileOL)
#.........这里部分代码省略.........