def endElementNS(self, name, qname):
# just get the element name without the namespace
elName = name[1]
if elName == 'dmdSec':
self.inDmdSec = False
# if we currently processing an experiment structure, let's
# save the institution value before we finalise the experiment
if self.processExperimentStruct:
self.metsObject.institution = self.institution
# let's save the experiment in the DB
if self.tardisExpId:
self.modelExperiment = models.Experiment.objects.get(
pk=self.tardisExpId)
else:
self.modelExperiment = models.Experiment()
self.modelExperiment.id = self.tardisExpId
self.modelExperiment.url = self.metsObject.url
self.modelExperiment.approved = True
self.modelExperiment.title = self.metsObject.title
self.modelExperiment.institution_name = \
self.metsObject.institution
self.modelExperiment.description = self.metsObject.description
self.modelExperiment.start_time = self.metsObject.start_time
self.modelExperiment.end_time = self.metsObject.end_time
self.modelExperiment.created_by = self.createdBy
self.modelExperiment.save()
self.holder.experimentDatabaseId = self.modelExperiment.id
x = 0
for author in self.metsObject.authors:
author_experiment = models.Author_Experiment(
experiment=self.modelExperiment,
author=author, order=x)
author_experiment.save()
x = x + 1
elif self.processDatasetStruct:
# let's save the dataset in the DB
self.modelDataset = models.Dataset(
description=self.metsObject.title,
immutable=settings.IMMUTABLE_METS_DATASETS)
self.modelDataset.save()
self.modelDataset.experiments.add(self.modelExperiment)
self.modelDataset.save()
# let's also save the modelDataset in a dictionary so that we
# can look it up easily later on when we start processing
# the datafiles.
self.datasetLookupDict[self.metsObject.id] = self.modelDataset
self.metsObject = None
self.processExperimentStruct = False
self.processDatasetStruct = False
elif elName == 'title' and self.inDmdSec:
self.grabTitle = False
elif elName == 'startTime' and self.processExperimentStruct:
self.grabStartTime = False
elif elName == 'endTime' and self.processExperimentStruct:
self.grabEndTime = False
elif elName == 'url' and self.processExperimentStruct:
self.grabExperimentUrl = False
elif elName == 'abstract' and self.processExperimentStruct:
self.grabAbstract = False
elif elName == 'name' and self.processExperimentStruct:
self.inName = False
elif elName == 'namePart' and self.inName:
self.grabMightBeAuthor = False
elif elName == 'roleTerm' and self.inName:
self.grabRoleTerm = False
self.mightBeAuthor = None
elif elName == 'name' and self.inInstitution:
self.grabInstitution = False
elif elName == 'agent':
self.inInstitution = False
elif elName == 'amdSec':
# we're done processing the metadata entries
self.inAmdSec = False
# let's reset the cached experiment model object
self.modelExperiment = None
logger.info(self.holder.metadataMap)
for mdId in self.holder.metadataMap:
if mdId.startswith('NOMD-'):
df = self.holder.metadataMap[mdId][0]
if df.dataset.id in self.datasetLookupDict:
# look up the dataset this file belongs to
thisFilesDataset = self.datasetLookupDict[
df.dataset.id]
size = df.size
if not df.size:
size = 0
def checksum(obj, type_):
# Check if the checksum is of type
if obj.checksumType != type_:
return ''
checksum = obj.checksum.lower()
# Ensure the checksum is hexdecimal
if not re.match('[0-9a-f]+$', checksum):
return ''
# Get algorithm
try:
name = type_.replace('-','').lower()
alg = getattr(hashlib, name)
except:
return ''
# Check checksum is the correct length
hex_length = alg('').digest_size * 2
if hex_length != len(checksum):
return ''
# Should be valid checksum of given type
return checksum
sync_url, proto = get_sync_url_and_protocol(
get_sync_root(),
df.url)
self.modelDatafile = models.Dataset_File(
dataset=thisFilesDataset,
filename=df.name,
size=size,
md5sum=checksum(df, 'MD5'),
sha512sum=checksum(df,
'SHA-512'))
logger.info('=== saving datafile: %s' % df.name)
self.modelDatafile.save()
replica = models.Replica(
datafile=self.modelDatafile,
url=sync_url,
protocol=proto,
location=self.syncLocation)
replica.save()
elif elName == 'techMD' and self.inAmdSec:
self.inTechMd = False
self.metadataId = None
self.metsObject = None
self.processMetadata = False
elif elName == 'xmlData' and self.inTechMd:
self.inXmlData = False
elif elName != self.xmlDataChildElement and \
self.customHandler is not None:
self.customHandler.endElement(elName)
elif elName == self.xmlDataChildElement and self.inXmlData:
if self.customHandler is not None:
self.tempMetadataHolder = self.customHandler.metadataDict
try:
schema = models.Schema.objects.get(
namespace__exact=self.elementNamespace)
# get the associated parameter names for the given schema
parameterNames = \
models.ParameterName.objects.filter(
schema__namespace__exact=schema.namespace).order_by('id')
# let's create a trigger holder which we can use to check
# if we still need to create another parameterset entry in the
# DB
createParamSetFlag = {'experiment': True, 'dataset': True,
'datafile': True}
datasetParameterSet = None
datafileParameterSet = None
if self.metadataId in self.holder.metadataMap:
for metsObject in self.holder.metadataMap[self.metadataId]:
self.metsObject = metsObject
metsObjectClassName = self.metsObject.__class__.__name__
if metsObjectClassName == 'Experiment':
if createParamSetFlag['experiment']:
# create a new parameter set for the metadata
parameterSet = \
models.ExperimentParameterSet(
schema=schema,
experiment=self.modelExperiment)
parameterSet.save()
# now let's process the experiment parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('ExperimentParameter',
parameterName, parameterValues,
parameterSet)
createParamSetFlag['experiment'] = False
else:
# this is not even allowed as there's only going
# to be one experiment per METS file
raise Exception('forbidden state!')
elif metsObjectClassName == 'Dataset':
if createParamSetFlag['dataset']:
dataset = self.datasetLookupDict[
self.metsObject.id]
# create a new parameter set for the
# dataset metadata
datasetParameterSet = \
models.DatasetParameterSet(schema=schema,
dataset=dataset)
datasetParameterSet.save()
# now let's process the dataset parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('DatasetParameter',
parameterName, parameterValues,
datasetParameterSet)
# disable creation for the next visit
createParamSetFlag['dataset'] = False
elif metsObjectClassName == 'Datafile':
# this will be a good time to save the
# "hard" metadata of this datafile so that
# when we start adding "soft" metadata
# parameters to it, we already have an
# entry for it in the DB
logger.info('=== found datafile: %s' % self.metsObject.name)
# look up the dataset this file belongs to
thisFilesDataset = self.datasetLookupDict[
self.metsObject.dataset.id]
# also check if the file already exists
datafile = thisFilesDataset.dataset_file_set.filter(
filename=self.metsObject.name, size=self.metsObject.size)
if datafile.count() == 0:
size = self.metsObject.size
if not self.metsObject.size:
size = 0
def checksum(obj, type_):
# Check if the checksum is of type
if obj.checksumType != type_:
return ''
checksum = obj.checksum.lower()
# Ensure the checksum is hexdecimal
if not re.match('[0-9a-f]+$', checksum):
return ''
# Get algorithm
try:
name = type_.replace('-','').lower()
alg = getattr(hashlib, name)
except:
return ''
# Check checksum is the correct length
hex_length = alg('').digest_size * 2
if hex_length != len(checksum):
return ''
# Should be valid checksum of given type
return checksum
sync_url, proto = get_sync_url_and_protocol(
self.syncRootDir,
self.metsObject.url)
self.modelDatafile = models.Dataset_File(
dataset=thisFilesDataset,
filename=self.metsObject.name,
size=size,
md5sum=checksum(self.metsObject, 'MD5'),
sha512sum=checksum(self.metsObject,
'SHA-512'))
logger.info('=== saving datafile: %s' % self.metsObject.name)
self.modelDatafile.save()
replica = models.Replica(
datafile=self.modelDatafile,
url=sync_url,
protocol=proto,
location=self.syncLocation)
replica.save()
else:
self.modelDatafile = thisFilesDataset.dataset_file_set.get(
filename=self.metsObject.name, size=self.metsObject.size)
# TODO: we need to note here that we are
# only creating a datafile entry in the DB
# for files that have corresponding
# metadata. if we are to create a file
# entry for files with no metadata, we'll
# need to get the unaccessed datafiles
# from datasetLookupDict.
if createParamSetFlag['datafile']:
# create a new parameter set for the metadata
datafileParameterSet = \
models.DatafileParameterSet(schema=schema,
dataset_file=self.modelDatafile)
datafileParameterSet.save()
# now let's process the datafile parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('DatafileParameter',
parameterName, parameterValues,
datafileParameterSet)
createParamSetFlag['datafile'] = False
except models.Schema.DoesNotExist:
logger.warning('unsupported schema being ingested ' +
self.elementNamespace)
# reset the current xmlData child element so that if a new
# parameter set is read, we can process it again
self.xmlDataChildElement = None
self.customHandler = None
elif elName == self.parameterName and \
self.xmlDataChildElement is not None:
# reset self.parameterName to None so the next parameter can be
# processed
self.parameterName = None
elif line.startswith('</experiment>'):
if current == 'dataset':
d = Dataset(experiment=experiment,
description=dataset['description'])
d.save()
else:
if self.null_check(datafile['name']):
filename = datafile['name']
else:
filename = datafile['path']
sync_url, proto = get_sync_url_and_protocol(
sync_root,
datafile['path'])
dfile = Dataset_File(dataset=d,
filename=filename,
url=sync_url,
size=datafile['size'],
protocol=proto)
dfile.save()
current_df_id = dfile.id
if 'metadata' in datafile:
for md in datafile['metadata']:
xmlns = getXmlnsFromTechXMLRaw(md)
def endElementNS(self, name, qname):
# just get the element name without the namespace
elName = name[1]
if elName == 'dmdSec':
self.inDmdSec = False
# if we currently processing an experiment structure, let's
# save the institution value before we finalise the experiment
if self.processExperimentStruct:
self.metsObject.institution = self.institution
# let's save the experiment in the DB
if self.tardisExpId:
self.modelExperiment = models.Experiment.objects.get(
pk=self.tardisExpId)
else:
self.modelExperiment = models.Experiment()
self.modelExperiment.id = self.tardisExpId
self.modelExperiment.url = self.metsObject.url
self.modelExperiment.approved = True
self.modelExperiment.title = self.metsObject.title
self.modelExperiment.institution_name = \
self.metsObject.institution
self.modelExperiment.description = self.metsObject.description
self.modelExperiment.start_time = self.metsObject.start_time
self.modelExperiment.end_time = self.metsObject.end_time
self.modelExperiment.created_by = self.createdBy
self.modelExperiment.save()
self.holder.experimentDatabaseId = self.modelExperiment.id
x = 0
for author in self.metsObject.authors:
author_experiment = models.Author_Experiment(
experiment=self.modelExperiment,
author=author, order=x)
author_experiment.save()
x = x + 1
elif self.processDatasetStruct:
# let's save the dataset in the DB
self.modelDataset = models.Dataset(
description=self.metsObject.title,
immutable=settings.IMMUTABLE_METS_DATASETS)
self.modelDataset.save()
self.modelDataset.experiments.add(self.modelExperiment)
self.modelDataset.save()
# let's also save the modelDataset in a dictionary so that we
# can look it up easily later on when we start processing
# the datafiles.
self.datasetLookupDict[self.metsObject.id] = self.modelDataset
self.metsObject = None
self.processExperimentStruct = False
self.processDatasetStruct = False
elif elName == 'title' and self.inDmdSec:
self.grabTitle = False
elif elName == 'startTime' and self.processExperimentStruct:
self.grabStartTime = False
elif elName == 'endTime' and self.processExperimentStruct:
self.grabEndTime = False
elif elName == 'url' and self.processExperimentStruct:
self.grabExperimentUrl = False
elif elName == 'abstract' and self.processExperimentStruct:
self.grabAbstract = False
elif elName == 'name' and self.processExperimentStruct:
self.inName = False
elif elName == 'namePart' and self.inName:
self.grabMightBeAuthor = False
elif elName == 'roleTerm' and self.inName:
self.grabRoleTerm = False
self.mightBeAuthor = None
elif elName == 'name' and self.inInstitution:
self.grabInstitution = False
elif elName == 'agent':
self.inInstitution = False
elif elName == 'amdSec':
# we're done processing the metadata entries
self.inAmdSec = False
# let's reset the cached experiment model object
self.modelExperiment = None
elif elName == 'techMD' and self.inAmdSec:
self.inTechMd = False
self.metadataId = None
self.metsObject = None
self.processMetadata = False
elif elName == 'xmlData' and self.inTechMd:
self.inXmlData = False
elif elName != self.xmlDataChildElement and \
self.customHandler is not None:
self.customHandler.endElement(elName)
elif elName == self.xmlDataChildElement and self.inXmlData:
if self.customHandler is not None:
self.tempMetadataHolder = self.customHandler.metadataDict
try:
schema = models.Schema.objects.get(
namespace__exact=self.elementNamespace)
# get the associated parameter names for the given schema
parameterNames = \
models.ParameterName.objects.filter(
schema__namespace__exact=schema.namespace).order_by('id')
# let's create a trigger holder which we can use to check
# if we still need to create another parameterset entry in the
# DB
createParamSetFlag = {'experiment': True, 'dataset': True,
'datafile': True}
datasetParameterSet = None
datafileParameterSet = None
if self.metadataId in self.holder.metadataMap:
for metsObject in self.holder.metadataMap[self.metadataId]:
self.metsObject = metsObject
metsObjectClassName = self.metsObject.__class__.__name__
if metsObjectClassName == 'Experiment':
if createParamSetFlag['experiment']:
# create a new parameter set for the metadata
parameterSet = \
models.ExperimentParameterSet(
schema=schema,
experiment=self.modelExperiment)
parameterSet.save()
# now let's process the experiment parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('ExperimentParameter',
parameterName, parameterValues,
parameterSet)
createParamSetFlag['experiment'] = False
else:
# this is not even allowed as there's only going
# to be one experiment per METS file
raise Exception('forbidden state!')
elif metsObjectClassName == 'Dataset':
if createParamSetFlag['dataset']:
dataset = self.datasetLookupDict[
self.metsObject.id]
# create a new parameter set for the
# dataset metadata
datasetParameterSet = \
models.DatasetParameterSet(schema=schema,
dataset=dataset)
datasetParameterSet.save()
# now let's process the dataset parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('DatasetParameter',
parameterName, parameterValues,
datasetParameterSet)
# disable creation for the next visit
createParamSetFlag['dataset'] = False
elif metsObjectClassName == 'Datafile':
# this will be a good time to save the
# "hard" metadata of this datafile so that
# when we start adding "soft" metadata
# parameters to it, we already have an
# entry for it in the DB
# look up the dataset this file belongs to
thisFilesDataset = self.datasetLookupDict[
self.metsObject.dataset.id]
# also check if the file already exists
datafile = thisFilesDataset.dataset_file_set.filter(
filename=self.metsObject.name, size=self.metsObject.size)
if datafile.count() == 0:
size = self.metsObject.size
if not self.metsObject.size:
size = 0
def checksum(obj, type_):
# Check if the checksum is of type
if obj.checksumType != type_:
return ''
checksum = obj.checksum.lower()
# Ensure the checksum is hexdecimal
if not re.match('[0-9a-f]+$', checksum):
return ''
# Get algorithm
try:
name = type_.replace('-','').lower()
alg = getattr(hashlib, name)
except:
return ''
# Check checksum is the correct length
hex_length = alg('').digest_size * 2
if hex_length != len(checksum):
return ''
# Should be valid checksum of given type
return checksum
sync_url, proto = get_sync_url_and_protocol(
self.syncRootDir,
self.metsObject.url)
self.modelDatafile = models.Dataset_File(
dataset=thisFilesDataset,
filename=self.metsObject.name,
url=sync_url,
size=size,
md5sum=checksum(self.metsObject, 'MD5'),
sha512sum=checksum(self.metsObject,
'SHA-512'),
protocol=proto)
self.modelDatafile.save()
else:
self.modelDatafile = thisFilesDataset.dataset_file_set.get(
filename=self.metsObject.name, size=self.metsObject.size)
# TODO: we need to note here that we are
# only creating a datafile entry in the DB
# for files that have corresponding
# metadata. if we are to create a file
# entry for files with no metadata, we'll
# need to get the unaccessed datafiles
# from datasetLookupDict.
if createParamSetFlag['datafile']:
# create a new parameter set for the metadata
datafileParameterSet = \
models.DatafileParameterSet(schema=schema,
dataset_file=self.modelDatafile)
datafileParameterSet.save()
# now let's process the datafile parameters
for parameterName in parameterNames:
if parameterName.name in \
self.tempMetadataHolder:
parameterValues = self.tempMetadataHolder[
parameterName.name]
self._saveParameters('DatafileParameter',
parameterName, parameterValues,
datafileParameterSet)
createParamSetFlag['datafile'] = False
except models.Schema.DoesNotExist:
logger.warning('unsupported schema being ingested ' +
self.elementNamespace)
# reset the current xmlData child element so that if a new
# parameter set is read, we can process it again
self.xmlDataChildElement = None
self.customHandler = None
elif elName == self.parameterName and \
self.xmlDataChildElement is not None:
# reset self.parameterName to None so the next parameter can be
# processed
self.parameterName = None
exp['abstract'] = ab
elif line.startswith('</experiment>'):
if current == 'dataset':
d = Dataset(experiment=experiment,
description=dataset['description'])
d.save()
else:
if self.null_check(datafile['name']):
filename = datafile['name']
else:
filename = datafile['path']
sync_url, proto = get_sync_url_and_protocol(
sync_root, datafile['path'])
dfile = Dataset_File(dataset=d,
filename=filename,
url=sync_url,
size=datafile['size'],
protocol=proto)
dfile.save()
current_df_id = dfile.id
if 'metadata' in datafile:
for md in datafile['metadata']:
xmlns = getXmlnsFromTechXMLRaw(md)
try:
