def search_records(cls, query):
c = DemographicConnector()
res = c.sparql(query)
m = parse_rdf(res)
# for each person, look up their demographics object.
from smart.models.record_object import RecordObject
people = m.triples((None, rdf['type'], sp.Demographics))
pobj = RecordObject[sp.Demographics]
return_graph = bound_graph()
for person in people:
p = person[0] # subject
# Connect to RDF Store
pid = re.search("\/records\/(.*?)\/demographics", str(p)).group(1)
print "matched ", p," to ", pid
c = RecordStoreConnector(Record.objects.get(id=pid))
# Pull out demographics
p_uri = p.n3() # subject URI
p_subgraph = parse_rdf(c.sparql(pobj.query_one(p_uri)))
print "subq: " , pobj.query_one(p_uri)
print "subgraph: ", serialize_rdf(p_subgraph)
# Append to search result graph
return_graph += p_subgraph
print "got", serialize_rdf(return_graph)
return serialize_rdf(return_graph)
def rdf_delete(record_connector, query, save=True):
to_delete = parse_rdf(record_connector.sparql(query))
deleted = bound_graph()
for r in to_delete:
deleted.add(r)
record_connector.pending_removes.append(r)
if (save): record_connector.execute_transaction()
return rdf_response(serialize_rdf(deleted))
def rdf_post(record_connector, new_g):
for s in new_g:
record_connector.pending_adds.append(s)
record_connector.execute_transaction()
return rdf_response(serialize_rdf(new_g))