def test_parameter(self):
from tardis.tardis_portal import models
exp = models.Experiment(title='test exp1',
institution_name='Australian Synchrotron',
approved=True,
created_by=self.user,
public=True,
)
exp.save()
dataset = models.Dataset(description="dataset description",
experiment=exp)
dataset.save()
df_file = models.Dataset_File(dataset=dataset,
filename='file.txt',
url='path/file.txt',
)
df_file.save()
df_schema = models.Schema(namespace='http://www.cern.ch/felzmann/schema1.xml',
type=models.Schema.DATAFILE)
df_schema.save()
ds_schema = models.Schema(namespace='http://www.cern.ch/felzmann/schema2.xml',
type=models.Schema.DATASET)
ds_schema.save()
exp_schema = models.Schema(namespace='http://www.cern.ch/felzmann/schema3.xml',
type=models.Schema.EXPERIMENT)
exp_schema.save()
df_parname = models.ParameterName(schema=df_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
df_parname.save()
ds_parname = models.ParameterName(schema=ds_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
ds_parname.save()
exp_parname = models.ParameterName(schema=exp_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
exp_parname.save()
df_parset = models.DatafileParameterSet(schema=df_schema,
dataset_file=df_file)
df_parset.save()
ds_parset = models.DatasetParameterSet(schema=ds_schema,
dataset=dataset)
ds_parset.save()
exp_parset = models.ExperimentParameterSet(schema=exp_schema,
experiment=exp)
exp_parset.save()
from base64 import b64encode
from os import path
from os import remove
filename = path.join(path.dirname(__file__), 'test.jpg')
df_parameter = models.DatafileParameter(name=df_parname,
parameterset=df_parset,
string_value=b64encode(open(filename).read()))
df_parameter.save()
ds_parameter = models.DatasetParameter(name=ds_parname,
parameterset=ds_parset,
string_value=b64encode(open(filename).read()))
ds_parameter.save()
exp_parameter = models.ExperimentParameter(name=exp_parname,
parameterset=exp_parset,
string_value=b64encode(open(filename).read()))
exp_parameter.save()
self.assertEqual("<img src='/test/DatafileImage/load/%i/' />" % df_parameter.id,
df_parameter.get())
self.assertEqual("<img src='/test/DatasetImage/load/%i/' />" % ds_parameter.id,
ds_parameter.get())
self.assertEqual("<img src='/test/ExperimentImage/load/%i/' />" % exp_parameter.id,
exp_parameter.get())
remove(path.join(exp.get_or_create_directory(), df_parameter.string_value))
remove(path.join(exp.get_or_create_directory(), ds_parameter.string_value))
remove(path.join(exp.get_or_create_directory(), exp_parameter.string_value))
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
def test_parameter(self):
from tardis.tardis_portal import models
exp = models.Experiment(
title='test exp1',
institution_name='Australian Synchrotron',
approved=True,
created_by=self.user,
public_access=models.Experiment.PUBLIC_ACCESS_NONE,
)
exp.save()
dataset = models.Dataset(description="dataset description")
dataset.save()
dataset.experiments.add(exp)
dataset.save()
df_file = models.DataFile(dataset=dataset,
filename='file.txt',
size=42,
md5sum='bogus')
df_file.save()
df_schema = models.Schema(
namespace='http://www.cern.ch/felzmann/schema1.xml',
type=models.Schema.DATAFILE)
df_schema.save()
ds_schema = models.Schema(
namespace='http://www.cern.ch/felzmann/schema2.xml',
type=models.Schema.DATASET)
ds_schema.save()
exp_schema = models.Schema(
namespace='http://www.cern.ch/felzmann/schema3.xml',
type=models.Schema.EXPERIMENT)
exp_schema.save()
df_parname = models.ParameterName(
schema=df_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
df_parname.save()
ds_parname = models.ParameterName(
schema=ds_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
ds_parname.save()
exp_parname = models.ParameterName(
schema=exp_schema,
name='name',
full_name='full_name',
units='image/jpg',
data_type=models.ParameterName.FILENAME)
exp_parname.save()
df_parset = models.DatafileParameterSet(schema=df_schema,
datafile=df_file)
df_parset.save()
ds_parset = models.DatasetParameterSet(schema=ds_schema,
dataset=dataset)
ds_parset.save()
exp_parset = models.ExperimentParameterSet(schema=exp_schema,
experiment=exp)
exp_parset.save()
from os import path
with self.settings(METADATA_STORE_PATH=path.dirname(__file__)):
filename = 'test.jpg'
df_parameter = models.DatafileParameter(name=df_parname,
parameterset=df_parset,
string_value=filename)
df_parameter.save()
ds_parameter = models.DatasetParameter(name=ds_parname,
parameterset=ds_parset,
string_value=filename)
ds_parameter.save()
exp_parameter = models.ExperimentParameter(name=exp_parname,
parameterset=exp_parset,
string_value=filename)
exp_parameter.save()
self.assertEqual(
"<a href='/display/DatafileImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/DatafileImage/load/%i/' /></a>"
% # noqa
(df_parameter.id, df_parameter.id),
df_parameter.get())
self.assertEqual(
"<a href='/display/DatasetImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/DatasetImage/load/%i/' /></a>"
% # noqa
(ds_parameter.id, ds_parameter.id),
ds_parameter.get())
self.assertEqual(
"<a href='/display/ExperimentImage/load/%i/' target='_blank'><img style='width: 300px;' src='/display/ExperimentImage/load/%i/' /></a>"
% # noqa
(exp_parameter.id, exp_parameter.id),
exp_parameter.get())