Python FileSpec.scope方法代码示例

# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import scope [as 别名]
 def convertToJobFileSpec(self,datasetSpec,setType=None,useEventService=False):
     jobFileSpec = JobFileSpec()
     jobFileSpec.fileID     = self.fileID
     jobFileSpec.datasetID  = datasetSpec.datasetID
     jobFileSpec.jediTaskID = datasetSpec.jediTaskID
     jobFileSpec.lfn        = self.lfn
     jobFileSpec.GUID       = self.GUID
     if setType == None:
         jobFileSpec.type   = self.type
     else:
         jobFileSpec.type   = setType
     jobFileSpec.scope      = self.scope
     jobFileSpec.fsize      = self.fsize
     jobFileSpec.checksum   = self.checksum
     jobFileSpec.attemptNr  = self.attemptNr
     # dataset attribute
     if datasetSpec != None:
         # dataset
         if not datasetSpec.containerName in [None,'']:
             jobFileSpec.dataset = datasetSpec.containerName
         else:
             jobFileSpec.dataset = datasetSpec.datasetName
         if self.type in datasetSpec.getInputTypes() or setType in datasetSpec.getInputTypes():
             # prodDBlock
             jobFileSpec.prodDBlock = datasetSpec.datasetName
             # storage token    
             if not datasetSpec.storageToken in ['',None]:
                 jobFileSpec.dispatchDBlockToken = datasetSpec.storageToken 
         else:
             # destinationDBlock
             jobFileSpec.destinationDBlock = datasetSpec.datasetName
             # storage token    
             if not datasetSpec.storageToken in ['',None]:
                 jobFileSpec.destinationDBlockToken = datasetSpec.storageToken.split('/')[0] 
             # destination
             if not datasetSpec.destination in ['',None]:
                 jobFileSpec.destinationSE = datasetSpec.destination
             # set prodDBlockToken for Event Service
             if useEventService and datasetSpec.getObjectStore() != None:
                 jobFileSpec.prodDBlockToken = 'objectstore^{0}'.format(datasetSpec.getObjectStore())
             # allow no output
             if datasetSpec.isAllowedNoOutput():
                 jobFileSpec.allowNoOutput()
     # return
     return jobFileSpec

# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import scope [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.........

# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import scope [as 别名]

#.........这里部分代码省略.........
        if app.dbrelease == 'LATEST':
            try:
                latest_dbrelease = getLatestDBReleaseCaching()
            except:
                from pandatools import Client
                latest_dbrelease = Client.getLatestDBRelease()
            m = re.search('(.*):DBRelease-(.*)\.tar\.gz', latest_dbrelease)
            if m:
                self.dbrelease_dataset = m.group(1)
                self.dbrelease = m.group(2)
            else:
                raise ApplicationConfigurationError(None, "Error retrieving LATEST DBRelease. Try setting application.dbrelease manually.")
        else:
            self.dbrelease_dataset = app.dbrelease_dataset
            self.dbrelease = app.dbrelease
        jspec.jobParameters = app.job_parameters

        if self.dbrelease:
            if self.dbrelease == 'current':
                jspec.jobParameters += ' --DBRelease=current' 
            else:
                if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
                    jspec.jobParameters += ' --DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
                else:
                    jspec.jobParameters += ' DBRelease=DBRelease-%s.tar.gz' % (self.dbrelease,)
                dbspec = FileSpec()
                dbspec.lfn = 'DBRelease-%s.tar.gz' % self.dbrelease
                dbspec.dataset = self.dbrelease_dataset
                dbspec.prodDBlock = jspec.prodDBlock
                dbspec.type = 'input'
                jspec.addFile(dbspec)

        if job.inputdata:
            m = re.search('(.*)\.(.*)\.(.*)\.(.*)\.(.*)\.(.*)',
                          job.inputdata.dataset[0])
            if not m:
                logger.error("Error retrieving run number from dataset name")
                #raise ApplicationConfigurationError(None, "Error retrieving run number from dataset name")
                runnumber = 105200
            else:
                runnumber = int(m.group(2))
            if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
                jspec.jobParameters += ' --runNumber %d' % runnumber
            else:
                jspec.jobParameters += ' RunNumber=%d' % runnumber
        
        # Output files.
        randomized_lfns = []
        ilfn = 0
        for lfn, lfntype in zip(app.output_files,app.output_type):
            ofspec = FileSpec()
            if app.randomize_lfns:
                randomized_lfn = lfn + ('.%s.%d.%s' % (job.backend.site, int(time.time()), commands.getoutput('uuidgen 2> /dev/null')[:4] ) )
            else:
                randomized_lfn = lfn
            ofspec.lfn = randomized_lfn
            randomized_lfns.append(randomized_lfn)
            ofspec.destinationDBlock = jspec.destinationDBlock
            ofspec.destinationSE = jspec.destinationSE
            ofspec.dataset = jspec.destinationDBlock
            ofspec.type = 'output'
            jspec.addFile(ofspec)
            if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
                jspec.jobParameters += ' --output%sFile %s' % (lfntype, randomized_lfns[ilfn])
            else:
                jspec.jobParameters += ' output%sFile=%s' % (lfntype, randomized_lfns[ilfn])
            ilfn=ilfn+1

        # Input files.
        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):
                ifspec = FileSpec()
                ifspec.lfn = lfn
                ifspec.GUID = guid
                ifspec.fsize = size
                ifspec.md5sum = checksum
                ifspec.scope = scope
                ifspec.dataset = jspec.prodDBlock
                ifspec.prodDBlock = jspec.prodDBlock
                ifspec.type = 'input'
                jspec.addFile(ifspec)
            if app.input_type:
                itype = app.input_type
            else:
                itype = m.group(5)
            if jspec.transformation.endswith("_tf.py") or jspec.transformation.endswith("_tf"):
                jspec.jobParameters += ' --input%sFile %s' % (itype, ','.join(job.inputdata.names))
            else:
                jspec.jobParameters += ' input%sFile=%s' % (itype, ','.join(job.inputdata.names))

        # Log files.
        lfspec = FileSpec()
        lfspec.lfn = '%s.job.log.tgz' % jspec.jobName
        lfspec.destinationDBlock = jspec.destinationDBlock
        lfspec.destinationSE  = jspec.destinationSE
        lfspec.dataset = jspec.destinationDBlock
        lfspec.type = 'log'
        jspec.addFile(lfspec)
        
        return jspec

# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import scope [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.........

# 需要导入模块: from taskbuffer.FileSpec import FileSpec [as 别名]
# 或者: from taskbuffer.FileSpec.FileSpec import scope [as 别名]
job.prodSourceLabel   = 'user'
job.computingSite     = site
job.cloud             = cloud
job.cmtConfig         = 'x86_64-slc6-gcc48-opt'
job.specialHandling   = 'ddm:rucio'
#job.transferType      = 'direct'

ifile = 'HITS.06828093._000096.pool.root.1'
fileI = FileSpec()
fileI.GUID = 'AC5B3759-B606-BA42-8681-4BD86455AE02'
fileI.checksum = 'ad:5d000974'
fileI.dataset = 'user.mlassnig:user.mlassnig.pilot.test.single.hits'
fileI.fsize = 94834717
fileI.lfn = ifile
fileI.prodDBlock = job.prodDBlock
fileI.scope = 'mc15_13TeV'
fileI.type = 'input'
job.addFile(fileI)

ofile = 'RDO_%s.root' % commands.getoutput('uuidgen')
fileO = FileSpec()
fileO.dataset = job.destinationDBlock
fileO.destinationDBlock = job.destinationDBlock
fileO.destinationSE = job.destinationSE
fileO.lfn = ofile
fileO.type = 'output'
job.addFile(fileO)

fileOL = FileSpec()
fileOL.lfn = "%s.job.log.tgz" % job.jobName
fileOL.destinationDBlock = job.destinationDBlock