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 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