def process_graph(self, inputGraph):
instances = self.getInstances(inputGraph)
results = []
for i in instances:
print "Processing", i.identifier, self
output_nanopub = Nanopublication()
o = output_nanopub.assertion.resource(
i.identifier) # OutputClass(i.identifier)
error = False
try:
result = self.process_nanopub(i, o, output_nanopub)
except Exception as e:
output_nanopub.add(
(output_nanopub.assertion.identifier,
self.app.NS.sioc.content, rdflib.Literal(str(e))))
logging.exception(
"Error processing resource %s in nanopub %s" %
(i.identifier, inputGraph.identifier))
error = True
print "Output Graph", output_nanopub.identifier, len(
output_nanopub)
for new_np in self.app.nanopub_manager.prepare(
rdflib.ConjunctiveGraph(store=output_nanopub.store)):
if len(new_np.assertion) == 0 and not error:
continue
self.explain(new_np, i, o)
new_np.add((new_np.identifier, sio.isAbout, i.identifier))
#print new_np.serialize(format="trig")
if not self.dry_run:
self.app.nanopub_manager.publish(new_np)
results.append(new_np)
return results
def run(self, input_file, file_format="trig", was_revision_of=None):
if was_revision_of is not None:
wasRevisionOf = set(flask.current_app.db.objects(predicate=np.hasAssertion,
subject=rdflib.URIRef(was_revision_of)))
if len(wasRevisionOf) == 0:
print "Could not find active nanopublication to revise:", was_revision_of
return
was_revision_of = wasRevisionOf
g = rdflib.ConjunctiveGraph(identifier=rdflib.BNode().skolemize(), store="Sleepycat")
graph_tempdir = tempfile.mkdtemp()
g.store.open(graph_tempdir, True)
#g = rdflib.ConjunctiveGraph(identifier=rdflib.BNode().skolemize())
g1 = g.parse(location=input_file, format=file_format, publicID=flask.current_app.NS.local)
if len(list(g.subjects(rdflib.RDF.type, np.Nanopublication))) == 0:
print "Could not find existing nanopublications.", len(g1), len(g)
new_np = Nanopublication(store=g1.store)
new_np.add((new_np.identifier, rdflib.RDF.type, np.Nanopublication))
new_np.add((new_np.identifier, np.hasAssertion, g1.identifier))
new_np.add((g1.identifier, rdflib.RDF.type, np.Assertion))
nanopub_prepare_graph = rdflib.ConjunctiveGraph(store="Sleepycat")
nanopub_prepare_graph_tempdir = tempfile.mkdtemp()
nanopub_prepare_graph.store.open(nanopub_prepare_graph_tempdir, True)
nanopubs = []
for npub in flask.current_app.nanopub_manager.prepare(g, store=nanopub_prepare_graph.store):
if was_revision_of is not None:
for r in was_revision_of:
print "Marking as revision of", r
npub.pubinfo.add((npub.assertion.identifier, flask.current_app.NS.prov.wasRevisionOf, r))
print 'Prepared', npub.identifier
nanopubs.append(npub)
flask.current_app.nanopub_manager.publish(*nanopubs)
print "Published", npub.identifier
def _prep_nanopub(self, nanopub_uri, graph):
nanopub = Nanopublication(store=graph.store, identifier=nanopub_uri)
about = nanopub.nanopub_resource.value(app.NS.sio.isAbout)
print nanopub.assertion_resource.identifier, about
self._prep_graph(nanopub.assertion_resource, about.identifier)
self._prep_graph(nanopub.pubinfo_resource, nanopub.assertion_resource.identifier)
self._prep_graph(nanopub.provenance_resource, nanopub.assertion_resource.identifier)
nanopub.pubinfo.add((nanopub.assertion.identifier, app.NS.dc.contributor, current_user.resUri))
return nanopub
def process(self, i, o):
npub = Nanopublication(store=o.graph.store)
triples = self.app.db.query(
'''CONSTRUCT {\n%s\n} WHERE {\n%s \nFILTER NOT EXISTS {\n%s\n\t}\nFILTER (regex(str(%s), "^(%s)")) .\n}''' % (
self.construct, self.where, self.construct, self.resource, i.identifier), initNs=self.prefixes)
for s, p, o, c in triples:
print("Deductor Adding ", s, p, o)
npub.assertion.add((s, p, o))
npub.provenance.add((npub.assertion.identifier, prov.value,
rdflib.Literal(flask.render_template_string(self.explanation, **self.get_context(i)))))
def process_nanopub(self, i, o, new_np):
assertion = i.graph
nanopub = Nanopublication(i.graph.store, i.identifier)
quads = nanopub.serialize(format="nquads")
i.identifier.split('/')[-1]
fileid = self.app.nanopub_depot.create(
quads,
i.identifier.split('/')[-1] + '.nq', "application/n-quads")
o.add(rdflib.RDF.type, whyis.ArchivedNanopublication)
new_np.pubinfo.add(
(new_np.identifier, rdflib.RDF.type, whyis.FRIRNanopublication))
expressions = dict([
(part.identifier, self.expression_digest(part)) for part in
[nanopub.assertion, nanopub.provenance, nanopub.pubinfo]
])
expressions[nanopub.identifier] = sum(expressions.values())
nanopub_expression_uri = pexp[hex(expressions[nanopub.identifier])[2:]]
for work, expression in expressions.items():
exp = pexp[hex(expression)[2:]]
o.graph.add((work, frbr.realization, exp))
o.graph.add((work, rdflib.RDF.type, frbr.Work))
o.graph.add((exp, rdflib.RDF.type, frbr.Expression))
with self.app.nanopub_depot.get(fileid) as stored_file:
manifestation_id = self.manifestation_digest(stored_file)
manifestation = pmanif[hex(manifestation_id)[2:]]
o.graph.add((nanopub_expression_uri, frbr.embodiment, manifestation))
o.graph.add((manifestation, rdflib.RDF.type, pv.File))
o.graph.add((manifestation, whyis.hasFileID, rdflib.Literal(fileid)))
o.graph.add(
(manifestation, dc.created, rdflib.Literal(datetime.utcnow())))
o.graph.add((manifestation, NS.ov.hasContentType,
rdflib.Literal("application/n-quads")))
o.graph.add((manifestation, rdflib.RDF.type,
NS.mediaTypes["application/n-quads"]))
o.graph.add((NS.mediaTypes["application/n-quads"], rdflib.RDF.type,
dc.FileFormat))
def process(self, i, o):
self.app.db.store.nsBindings = {}
npub = Nanopublication(store=o.graph.store)
triples = self.app.db.query(
'''%s CONSTRUCT {\n%s\n} WHERE {\n%s \nFILTER NOT EXISTS {\n%s\n\t}\nFILTER(str(%s)="%s") .\n}'''
% (self.prefixes, self.construct, self.where, self.construct,
self.resource, i.identifier)
) # init.bindings = prefix, dict for identifier (see graph.query in rdflib)
for s, p, o, c in triples:
print "Deductor Adding ", s, p, o
npub.assertion.add((s, p, o))
npub.provenance.add(
(npub.assertion.identifier, prov.value,
rdflib.Literal(
flask.render_template_string(self.explanation,
**self.get_context(i)))))
def process(self, i, o):
values = self.app.db.query('''
SELECT ?prefix ?sdd_file ?data_file ?content_type ?delimiter
WHERE {
?data_file dcterms:conformsTo ?sdd_file ;
ov:hasContentType ?content_type ;
csvw:delimiter ?delimiter .
?dataset dcat:distribution ?data_file ;
void:uriSpace ?prefix .
MINUS {
?setl_script prov:wasDerivedFrom ?sdd_file;
a setl:SemanticETLScript.
?dataset prov:wasGeneratedBy ?setl_script;
prov:wasGeneratedBy ?template.
?template a setl:Transform;
prov:used/prov:wasGeneratedBy ?extract.
?extract a setl:Extract;
prov:used ?data_file.
}
}
''',
initBindings={"sdd_file": i.identifier},
initNs=NS.prefixes)
for prefix, sdd_file, data_file, content_type, delimiter in values:
resource = self.app.get_resource(sdd_file)
fileid = resource.value(self.app.NS.whyis.hasFileID)
if fileid is not None:
sdd_data = self.app.file_depot.get(fileid.value)
else:
sdd_data = sdd_file
output = sdd2setl(sdd_data, prefix.value, data_file,
content_type.value, delimiter.value)
npub = Nanopublication()
npub.assertion.parse(data=output, format="turtle")
sdd_setl = npub.assertion.value(predicate=rdflib.RDF.type,
object=setl.SemanticETLScript)
npub.assertion.add((sdd_setl, prov.wasDerivedFrom, sdd_file))
new_nps = self.app.nanopub_manager.prepare(npub)
self.app.nanopub_manager.publish(*new_nps)
def run(self, input_file, file_format="trig", was_revision_of=None):
if was_revision_of is not None:
wasRevisionOf = set(flask.current_app.db.objects(predicate=np.hasAssertion,
subject=rdflib.URIRef(was_revision_of)))
if len(wasRevisionOf) == 0:
print "Could not find active nanopublication to revise:", was_revision_of
return
was_revision_of = wasRevisionOf
g = rdflib.ConjunctiveGraph(identifier=rdflib.BNode().skolemize())
g1 = g.parse(location=input_file, format=file_format)
if len(list(g1.subjects(rdflib.RDF.type, np.Nanopublication))) == 0:
new_np = Nanopublication(store=g1.store)
new_np.add((new_np.identifier, rdflib.RDF.type, np.Nanopublication))
new_np.add((new_np.identifier, np.hasAssertion, g1.identifier))
new_np.add((g1.identifier, rdflib.RDF.type, np.Assertion))
for npub in flask.current_app.nanopub_manager.prepare(g):
if was_revision_of is not None:
for r in was_revision_of:
print "Marking as revision of", r
npub.pubinfo.add((npub.assertion.identifier, flask.current_app.NS.prov.wasRevisionOf, r))
flask.current_app.nanopub_manager.publish(npub)
print "Published", npub.identifier
def process_graph(self, inputGraph):
instances = self.getInstances(inputGraph)
results = []
for i in instances:
print "Processing", i.identifier, self
output_nanopub = Nanopublication()
o = output_nanopub.assertion.resource(
i.identifier) # OutputClass(i.identifier)
result = self.process_nanopub(i, o, output_nanopub)
print "Output Graph", output_nanopub.identifier, len(
output_nanopub)
for new_np in self.app.nanopub_manager.prepare(
rdflib.ConjunctiveGraph(store=output_nanopub.store)):
if len(new_np.assertion) == 0:
continue
self.explain(new_np, i, o)
new_np.add((new_np.identifier, sio.isAbout, i.identifier))
#print new_np.serialize(format="trig")
if not self.dry_run:
self.app.nanopub_manager.publish(new_np)
results.append(new_np)
return results
