def __call__(self):
# 1. find all IBlobDataset/ IRemotedDataset/ IDataset objects within context
pc = getToolByName(self.context, 'portal_catalog')
brains = pc.searchResults(path='/'.join(self.context.getPhysicalPath()),
object_provides=IBlobDataset.__identifier__)
fname = None
try:
# create tmp file
fd, fname = tempfile.mkstemp()
fo = os.fdopen(fd, 'w')
zfile = zipfile.ZipFile(fo, 'w')
metadata = {}
# the file/folder name for the zip
zfilename = self.context.title
# iterate over files and add to zip
for brain in brains:
content = brain.getObject()
# ob.file should be a NamedFile ... need to get fs name for that
blobfile = content.file.openDetached()
arcname = '/'.join((zfilename, 'data', content.file.filename))
zfile.write(blobfile.name, arcname)
blobfile.close()
metadata[arcname] = getdsmetadata(content)
# all files are in ....
# TODO: add experiment result metadata
# put metadata into zip
# provenance data stored on result container
provdata = IProvenanceData(self.context)
if not provdata.data is None:
zfile.writestr('/'.join((zfilename, 'prov.ttl')),
provdata.data)
# add mets.xml
metsview = getMultiAdapter((self.context, self.request), name="mets.xml")
zfile.writestr('/'.join((zfilename, 'mets.xml')),
metsview.render())
# finish zip file
zfile.close()
fo.close()
# create response
self.request.response.setHeader('Content-Type', 'application/zip')
self.request.response.setHeader('Content-Disposition', 'attachment; filename="{}.zip"'.format(zfilename))
self.request.response.setHeader('Content-Length', '{}'.format(os.path.getsize(fname)))
return tmpfile_stream_iterator(fname)
except Exception as e:
# something went wrong ...
# clean up and re-raise
if os.path.exists(fname):
os.remove(fname)
raise e
def _createProvenance(self, result):
provdata = IProvenanceData(result)
from rdflib import URIRef, Literal, Namespace, Graph
from rdflib.namespace import RDF, RDFS, FOAF, DCTERMS, XSD
from rdflib.resource import Resource
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
# the user is our agent
member = api.user.get_current()
username = member.getProperty('fullname') or member.getId()
user = Resource(graph, LOCAL['user'])
user.add(RDF['type'], PROV['Agent'])
user.add(RDF['type'], FOAF['Person'])
user.add(FOAF['name'], Literal(username))
user.add(FOAF['mbox'],
URIRef('mailto:{}'.format(member.getProperty('email'))))
# add software as agent
software = Resource(graph, LOCAL['software'])
software.add(RDF['type'], PROV['Agent'])
software.add(RDF['type'], PROV['SoftwareAgent'])
software.add(FOAF['name'], Literal('BCCVL ALA Importer'))
# script content is stored somewhere on result and will be exported with zip?
# ... or store along with pstats.json ? hidden from user
# -> execenvironment after import -> log output?
# -> source code ... maybe some link expression? stored on result ? separate entity?
activity = Resource(graph, LOCAL['activity'])
activity.add(RDF['type'], PROV['Activity'])
# TODO: this is rather queued or created time for this activity ... could capture real start time on running status update (or start transfer)
now = datetime.now().replace(microsecond=0)
activity.add(PROV['startedAtTime'],
Literal(now.isoformat(), datatype=XSD['dateTime']))
activity.add(PROV['hasAssociationWith'], user)
activity.add(PROV['hasAssociationWith'], software)
# add job parameters to activity
provdata.data = graph.serialize(format="turtle")
def _createProvenance(self, result):
provdata = IProvenanceData(result)
from rdflib import URIRef, Literal, Namespace, Graph
from rdflib.namespace import RDF, RDFS, FOAF, DCTERMS, XSD
from rdflib.resource import Resource
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
# the user is our agent
member = api.user.get_current()
username = member.getProperty('fullname') or member.getId()
user = Resource(graph, LOCAL['user'])
user.add(RDF['type'], PROV['Agent'])
user.add(RDF['type'], FOAF['Person'])
user.add(FOAF['name'], Literal(username))
user.add(FOAF['mbox'],
URIRef('mailto:{}'.format(member.getProperty('email'))))
# add software as agent
software = Resource(graph, LOCAL['software'])
software.add(RDF['type'], PROV['Agent'])
software.add(RDF['type'], PROV['SoftwareAgent'])
software.add(FOAF['name'], Literal('BCCVL ALA Importer'))
# script content is stored somewhere on result and will be exported with zip?
# ... or store along with pstats.json ? hidden from user
# -> execenvironment after import -> log output?
# -> source code ... maybe some link expression? stored on result ? separate entity?
activity = Resource(graph, LOCAL['activity'])
activity.add(RDF['type'], PROV['Activity'])
# TODO: this is rather queued or created time for this activity ... could capture real start time on running status update (or start transfer)
now = datetime.now().replace(microsecond=0)
activity.add(PROV['startedAtTime'],
Literal(now.isoformat(), datatype=XSD['dateTime']))
activity.add(PROV['hasAssociationWith'], user)
activity.add(PROV['hasAssociationWith'], software)
# add job parameters to activity
provdata.data = graph.serialize(format="turtle")
def _download_results(self, context, zfile):
# FIXME: This is a rather lengthy process, and should probably be turned into a background task... (maybe as part of a datamanager service?)
# 1. find all IBlobDataset/ IRemotedDataset/ IDataset objects within context
pc = getToolByName(context, 'portal_catalog')
brains = pc.searchResults(path='/'.join(context.getPhysicalPath()),
object_provides=[
IBlobDataset.__identifier__,
IRemoteDataset.__identifier__
])
metadata = {}
# the file/folder name for the zip
zfilename = context.title
# iterate over files and add to zip
for brain in brains:
content = brain.getObject()
if IBlobDataset.providedBy(content):
# If data is stored locally:
arcname = '/'.join((zfilename, 'data', content.file.filename))
# ob.file should be a NamedFile ... need to get fs name for that
blobfile = content.file.openDetached()
zfile.write(blobfile.name, arcname)
blobfile.close()
elif IRemoteDataset.providedBy(content):
# TODO: duplicate code from
remoteUrl = getattr(content, 'remoteUrl', None)
if remoteUrl is None:
raise NotFound(self, 'remoteUrl', self.request)
# get arcname from remoteUrl
arcname = '/'.join(
(zfilename, 'data', os.path.basename(remoteUrl)))
# FIXME: should check dataset downloaiable flag here,
# but assumption is, that this function can only be called on an experiment result folder....
# TODO: duplicate code in browser/dataset.py:RemoteDatasetDownload.__call__
# TODO: may not work in general... it always uses swift as remote url
tool = getUtility(ISwiftUtility)
try:
url = tool.generate_temp_url(url=remoteUrl)
except:
url = remoteUrl
# url is now the location from which we can fetch the file
temp_file, _ = urlretrieve(url)
zfile.write(temp_file, arcname)
os.remove(temp_file)
else:
# unknown type of Dataset
# just skip it
# TODO: Log warning or debug?
continue
metadata[arcname] = getdsmetadata(content)
# all files are in ....
# TODO: add experiment result metadata
# put metadata into zip
# provenance data stored on result container
provdata = IProvenanceData(context)
if not provdata.data is None:
zfile.writestr('/'.join((zfilename, 'prov.ttl')),
provdata.data.encode('utf-8'))
# add experiment metadata
expmetadata = IExperimentMetadata(context)
if not expmetadata.data is None:
zfile.writestr('/'.join((zfilename, 'expmetadata.txt')),
expmetadata.data.encode('utf-8'))
# add mets.xml
metsview = getMultiAdapter((context, self.request), name="mets.xml")
zfile.writestr('/'.join((zfilename, 'mets.xml')),
metsview.render().encode('utf-8'))
# add experiment parameters
params = IExperimentParameter(context)
if not params.data is None:
zfile.writestr('/'.join((zfilename, 'params.json')),
params.data.encode('utf-8'))
def __call__(self):
self.request.response.setHeader("Content-type",
"text/turtle; charset=utf-8")
provdata = IProvenanceData(self.context)
return provdata.data
def __iter__(self):
"""missing docstring."""
for item in self.previous:
# check if we have a dataset
if item['_type'] not in ('org.bccvl.content.dataset',
'org.bccvl.content.remotedataset'):
# not a dataset
yield item
continue
pathkey = self.pathkey(*item.keys())[0]
# no path .. can't do anything
if not pathkey:
yield item
continue
path = item[pathkey]
# Skip the Plone site object itself
if not path:
yield item
continue
obj = self.context.unrestrictedTraverse(path.encode().lstrip('/'),
None)
# FIXME: this is really not a great way to check where to find provenenace data
# check if we are inside an experiment (means we import result)
if IExperiment.providedBy(self.context.__parent__):
# result import
context = self.context
else:
# dataset import?
context = obj
# TODO: do some sanity checks
provdata = IProvenanceData(context)
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
graph.parse(data=provdata.data or '', format='turtle')
activity = Resource(graph, LOCAL['activity'])
# FIXME: shouldn't I use uuid instead of id?
entity = Resource(graph, LOCAL[obj.id])
# create this dataset as new entity -> output of activity
entity.add(RDF['type'], PROV['Entity'])
# generated by
entity.add(PROV['wasGeneratedBy'], activity)
# PROV['prov:wasAttributedTo'] to user and software?
# File metadata
entity.add(DCTERMS['creator'], Literal(obj.Creator()))
entity.add(DCTERMS['title'], Literal(obj.title))
entity.add(DCTERMS['description'], Literal(obj.description))
entity.add(DCTERMS['rights'], Literal(obj.rights))
if obj.portal_type == 'org.bccvl.content.dataset':
entity.add(DCTERMS['format'], Literal(obj.file.contentType))
else:
# FIXME: this doesn't seem to do the right thing
entity.add(DCTERMS['format'], Literal(obj.format))
# TODO: add metadata about file?
# genre, layers, emsc, gcm, year
# set activities end time
# first one wins
if activity.value(PROV['endedAtTime']) is None:
activity.add(
PROV['endedAtTime'],
Literal(datetime.now().replace(microsecond=0).isoformat(),
datatype=XSD['dateTime']))
# TODO: extend activity metadata with execution environment data
# (logfile import?, pstats import) .. and script + params.json file
# ALA import url
pd = item.get('_ala_provenance', {})
if pd:
entity.add(BCCVL['download_url'], Literal(pd['url']))
# store prov data
provdata.data = graph.serialize(format="turtle")
yield item
def __iter__(self):
"""missing docstring."""
for item in self.previous:
# check if we have a dataset
if item['_type'] not in ('org.bccvl.content.dataset',
'org.bccvl.content.remotedataset'):
# not a dataset
yield item
continue
pathkey = self.pathkey(*item.keys())[0]
# no path .. can't do anything
if not pathkey:
yield item
continue
path = item[pathkey]
# Skip the Plone site object itself
if not path:
yield item
continue
obj = self.context.unrestrictedTraverse(
path.encode().lstrip('/'), None)
# FIXME: this is really not a great way to check where to find provenenace data
# check if we are inside an experiment (means we import result)
if IExperiment.providedBy(self.context.__parent__):
# result import
context = self.context
else:
# dataset import?
context = obj
# TODO: do some sanity checks
provdata = IProvenanceData(context)
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
graph.parse(data=provdata.data or '', format='turtle')
activity = Resource(graph, LOCAL['activity'])
# FIXME: shouldn't I use uuid instead of id?
entity = Resource(graph, LOCAL[obj.id])
# create this dataset as new entity -> output of activity
entity.add(RDF['type'], PROV['Entity'])
# generated by
entity.add(PROV['wasGeneratedBy'], activity)
# PROV['prov:wasAttributedTo'] to user and software?
# File metadata
entity.add(DCTERMS['creator'], Literal(obj.Creator()))
entity.add(DCTERMS['title'], Literal(obj.title))
entity.add(DCTERMS['description'], Literal(obj.description))
entity.add(DCTERMS['rights'], Literal(obj.rights))
if obj.portal_type == 'org.bccvl.content.dataset':
entity.add(DCTERMS['format'], Literal(obj.file.contentType))
else:
# FIXME: this doesn't seem to do the right thing
entity.add(DCTERMS['format'], Literal(obj.format))
# TODO: add metadata about file?
# genre, layers, emsc, gcm, year
# set activities end time
# first one wins
if activity.value(PROV['endedAtTime']) is None:
activity.add(PROV['endedAtTime'],
Literal(datetime.now().replace(microsecond=0).isoformat(), datatype=XSD['dateTime']))
# TODO: extend activity metadata with execution environment data
# (logfile import?, pstats import) .. and script + params.json file
# ALA import url
pd = item.get('_ala_provenance', {})
if pd:
entity.add(BCCVL['download_url'], Literal(pd['url']))
# store prov data
provdata.data = graph.serialize(format="turtle")
yield item
def _createProvenance(self, result):
provdata = IProvenanceData(result)
from rdflib import URIRef, Literal, Namespace, Graph
from rdflib.namespace import RDF, RDFS, FOAF, DCTERMS, XSD
from rdflib.resource import Resource
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
# the user is our agent
member = api.user.get_current()
username = member.getProperty('fullname') or member.getId()
user = Resource(graph, LOCAL['user'])
user.add(RDF['type'], PROV['Agent'])
user.add(RDF['type'], FOAF['Person'])
user.add(FOAF['name'], Literal(username))
user.add(FOAF['mbox'],
URIRef('mailto:{}'.format(member.getProperty('email'))))
# add software as agent
software = Resource(graph, LOCAL['software'])
software.add(RDF['type'], PROV['Agent'])
software.add(RDF['type'], PROV['SoftwareAgent'])
software.add(FOAF['name'], Literal('BCCVL Job Script'))
# script content is stored somewhere on result and will be exported with zip?
# ... or store along with pstats.json ? hidden from user
# -> execenvironment after import -> log output?
# -> source code ... maybe some link expression? stored on result ? separate entity?
activity = Resource(graph, LOCAL['activity'])
activity.add(RDF['type'], PROV['Activity'])
# TODO: this is rather queued or created time for this activity ... could capture real start time on running status update (or start transfer)
now = datetime.now().replace(microsecond=0)
activity.add(PROV['startedAtTime'],
Literal(now.isoformat(), datatype=XSD['dateTime']))
activity.add(PROV['hasAssociationWith'], user)
activity.add(PROV['hasAssociationWith'], software)
# add job parameters to activity
for idx, (key, value) in enumerate(result.job_params.items()):
param = Resource(graph, LOCAL[u'param_{}'.format(idx)])
activity.add(BCCVL['algoparam'], param)
param.add(BCCVL['name'], Literal(key))
# We have only dataset references as parameters
if key in ('data_table', ):
param.add(BCCVL['value'], LOCAL[dsuuid])
else:
param.add(BCCVL['value'], Literal(value))
# iterate over all input datasets and add them as entities
for key in ('data_table', ):
dsbrain = uuidToCatalogBrain(result.job_params[key])
if not dsbrain:
continue
ds = dsbrain.getObject()
dsprov = Resource(graph, LOCAL[result.job_params[key]])
dsprov.add(RDF['type'], PROV['Entity'])
#dsprov.add(PROV['..'], Literal(''))
dsprov.add(DCTERMS['creator'], Literal(ds.Creator()))
dsprov.add(DCTERMS['title'], Literal(ds.title))
dsprov.add(DCTERMS['description'], Literal(ds.description))
dsprov.add(DCTERMS['rights'],
Literal(ds.rights)) # ds.rightsstatement
dsprov.add(DCTERMS['format'], Literal(ds.file.contentType))
# location / source
# graph.add(uri, DCTERMS['source'], Literal(''))
# TODO: genre ...
# TODO: resolution
# species metadata
md = IBCCVLMetadata(ds)
# dsprov.add(BCCVL['scientificName'], Literal(md['species']['scientificName']))
# dsprov.add(BCCVL['taxonID'], URIRef(md['species']['taxonID']))
# ... species data, ... species id
for layer in md.get('layers_used', ()):
dsprov.add(BCCVL['layer'], LOCAL[layer])
# link with activity
activity.add(PROV['used'], dsprov)
provdata.data = graph.serialize(format="turtle")
def _createProvenance(self, result):
provdata = IProvenanceData(result)
from rdflib import URIRef, Literal, Namespace, Graph
from rdflib.namespace import RDF, RDFS, FOAF, DCTERMS, XSD
from rdflib.resource import Resource
PROV = Namespace(u"http://www.w3.org/ns/prov#")
BCCVL = Namespace(u"http://ns.bccvl.org.au/")
LOCAL = Namespace(u"urn:bccvl:")
graph = Graph()
# the user is our agent
member = api.user.get_current()
username = member.getProperty('fullname') or member.getId()
user = Resource(graph, LOCAL['user'])
user.add(RDF['type'], PROV['Agent'])
user.add(RDF['type'], FOAF['Person'])
user.add(FOAF['name'], Literal(username))
user.add(FOAF['mbox'],
URIRef('mailto:{}'.format(member.getProperty('email'))))
# add software as agent
software = Resource(graph, LOCAL['software'])
software.add(RDF['type'], PROV['Agent'])
software.add(RDF['type'], PROV['SoftwareAgent'])
software.add(FOAF['name'], Literal('BCCVL Job Script'))
# script content is stored somewhere on result and will be exported with zip?
# ... or store along with pstats.json ? hidden from user
# -> execenvironment after import -> log output?
# -> source code ... maybe some link expression? stored on result ? separate entity?
activity = Resource(graph, LOCAL['activity'])
activity.add(RDF['type'], PROV['Activity'])
# TODO: this is rather queued or created time for this activity ... could capture real start time on running status update (or start transfer)
now = datetime.now().replace(microsecond=0)
activity.add(PROV['startedAtTime'],
Literal(now.isoformat(), datatype=XSD['dateTime']))
activity.add(PROV['hasAssociationWith'], user)
activity.add(PROV['hasAssociationWith'], software)
# add job parameters to activity
for idx, (key, value) in enumerate(result.job_params.items()):
param = Resource(graph, LOCAL[u'param_{}'.format(idx)])
activity.add(BCCVL['algoparam'], param)
param.add(BCCVL['name'], Literal(key))
# We have only dataset references as parameters
if key in ('data_table',):
param.add(BCCVL['value'], LOCAL[dsuuid])
else:
param.add(BCCVL['value'], Literal(value))
# iterate over all input datasets and add them as entities
for key in ('data_table',):
dsbrain = uuidToCatalogBrain(result.job_params[key])
if not dsbrain:
continue
ds = dsbrain.getObject()
dsprov = Resource(graph, LOCAL[result.job_params[key]])
dsprov.add(RDF['type'], PROV['Entity'])
#dsprov.add(PROV['..'], Literal(''))
dsprov.add(DCTERMS['creator'], Literal(ds.Creator()))
dsprov.add(DCTERMS['title'], Literal(ds.title))
dsprov.add(DCTERMS['description'], Literal(ds.description))
dsprov.add(DCTERMS['rights'], Literal(ds.rights)) # ds.rightsstatement
dsprov.add(DCTERMS['format'], Literal(ds.file.contentType))
# location / source
# graph.add(uri, DCTERMS['source'], Literal(''))
# TODO: genre ...
# TODO: resolution
# species metadata
md = IBCCVLMetadata(ds)
# dsprov.add(BCCVL['scientificName'], Literal(md['species']['scientificName']))
# dsprov.add(BCCVL['taxonID'], URIRef(md['species']['taxonID']))
# ... species data, ... species id
for layer in md.get('layers_used',()):
dsprov.add(BCCVL['layer'], LOCAL[layer])
# link with activity
activity.add(PROV['used'], dsprov)
provdata.data = graph.serialize(format="turtle")
