def process(self, i, o):
query_store = self.app.db.store
if hasattr(query_store, 'endpoint'):
query_store = database.create_query_store(self.app.db.store)
db_graph = rdflib.ConjunctiveGraph(store=query_store)
db_graph.NS = self.app.NS
setlr.actions[whyis.sparql] = db_graph
setlr.actions[whyis.NanopublicationManager] = self.app.nanopub_manager
setlr.actions[whyis.Nanopublication] = self.app.nanopub_manager.new
setl_graph = i.graph
# setlr.run_samples = True
resources = setlr._setl(setl_graph)
# retire old copies
old_np_map = {}
to_retire = []
for new_np, assertion, orig in self.app.db.query(
'''select distinct ?np ?assertion ?original_uri where {
?np np:hasAssertion ?assertion.
?assertion a np:Assertion;
prov:wasGeneratedBy/a ?setl;
prov:wasQuotedFrom ?original_uri.
}''',
initBindings=dict(setl=i.identifier),
initNs=dict(prov=prov, np=np)):
old_np_map[orig] = assertion
to_retire.append(new_np)
if len(to_retire) > 100:
self.app.nanopub_manager.retire(*to_retire)
to_retire = []
self.app.nanopub_manager.retire(*to_retire)
# print resources
for output_graph in setl_graph.subjects(prov.wasGeneratedBy,
i.identifier):
print(output_graph)
if setl_graph.resource(output_graph)[rdflib.RDF.type:whyis.
NanopublicationCollection]:
self.app.nanopub_manager.publish(resources[output_graph])
else:
out = resources[output_graph]
out_conjunctive = rdflib.ConjunctiveGraph(
store=out.store, identifier=output_graph)
to_publish = []
triples = 0
for new_np in self.app.nanopub_manager.prepare(
out_conjunctive):
self.explain(new_np, i, o)
to_publish.append(new_np)
# triples += len(new_np)
# if triples > 10000:
self.app.nanopub_manager.publish(*to_publish)
for resource, obj in list(resources.items()):
if hasattr(i, 'close'):
print("Closing", resource)
try:
i.close()
except:
pass
def process(self, i, o):
query_store = database.create_query_store(self.app.db.store)
db_graph = rdflib.ConjunctiveGraph(store=query_store)
db_graph.NS = self.app.NS
setlr.actions[whyis.sparql] = db_graph
setl_graph = i.graph
#setlr.run_samples = True
resources = setlr._setl(setl_graph)
# retire old copies
old_np_map = {}
for new_np, assertion, orig in self.app.db.query(
'''select distinct ?np ?assertion ?original_uri where {
?np np:hasAssertion ?assertion.
?assertion a np:Assertion;
prov:wasGeneratedBy/a ?setl;
prov:wasQuotedFrom ?original_uri.
}''',
initBindings=dict(setl=i.identifier),
initNs=dict(prov=prov, np=np)):
old_np_map[orig] = assertion
self.app.nanopub_manager.retire(new_np)
#print resources
for output_graph in setl_graph.subjects(prov.wasGeneratedBy,
i.identifier):
out = resources[output_graph]
out_conjunctive = rdflib.ConjunctiveGraph(store=out.store,
identifier=output_graph)
#print "Generated graph", out.identifier, len(out), len(out_conjunctive)
nanopub_prepare_graph = rdflib.ConjunctiveGraph(store="Sleepycat")
nanopub_prepare_graph_tempdir = tempfile.mkdtemp()
nanopub_prepare_graph.store.open(nanopub_prepare_graph_tempdir,
True)
mappings = {}
to_publish = []
triples = 0
for new_np in self.app.nanopub_manager.prepare(
out_conjunctive,
mappings=mappings,
store=nanopub_prepare_graph.store):
self.explain(new_np, i, o)
orig = [
orig for orig, new in mappings.items()
if new == new_np.assertion.identifier
]
if len(orig) == 0:
continue
orig = orig[0]
print orig
if isinstance(orig, rdflib.URIRef):
new_np.pubinfo.add((new_np.assertion.identifier,
prov.wasQuotedFrom, orig))
if orig in old_np_map:
new_np.pubinfo.add(
(new_np.assertion.identifier, prov.wasRevisionOf,
old_np_map[orig]))
print "Publishing %s with %s assertions." % (
new_np.identifier, len(new_np.assertion))
to_publish.append(new_np)
#triples += len(new_np)
#if triples > 10000:
self.app.nanopub_manager.publish(*to_publish)
print 'Published'