def explore_dblp():
graph = KnowledgeGraph(graph_name='dblp',
graph_uri='http://dblp.l3s.de',
prefixes={
"xsd":
"http://www.w3.org/2001/XMLSchema#",
"swrc":
"http://swrc.ontoware.org/ontology#",
"rdf":
"http://www.w3.org/1999/02/22-rdf-syntax-ns#",
"dc":
"http://purl.org/dc/elements/1.1/",
"dcterm":
"http://purl.org/dc/terms/",
"dblprc":
"http://dblp.l3s.de/d2r/resource/conferences/"
})
endpoint = 'http://10.161.202.101:8890/sparql/'
port = 8890
output_format = HttpClientDataFormat.PANDAS_DF
max_rows = 1000000
timeout = 12000
client = HttpClient(endpoint_url=endpoint,
port=port,
return_format=output_format,
timeout=timeout,
max_rows=max_rows)
classes = graph.classes_and_freq().sort({'frequency': 'DESC'})
#class_with_max_freq = graph.classes_and_freq().max('frequency').to_sparql()
attributes_of_papers = graph.features('swrc:InProceedings')
attributes_of_papers_with_freq = graph.features_and_freq(
'swrc:InProceedings')
papers = graph.entities('swrc:InProceedings')
#papers_with_features = graph.entities_and_features('swrc:InProceedings').to_sparql()
num_papers = graph.num_entities('swrc:InProceedings')
print("{}".format(classes.to_sparql()))
df = classes.execute(client, return_format=output_format)
#print("{}".format(attributes_of_papers.to_sparql()))
#df = attributes_of_papers.execute(client, return_format=output_format)
print(df)
def test_convenience_functions():
graph = KnowledgeGraph(graph_name='dbpedia')
entities = graph.entities('dbpo:BasketballPlayer',
entities_col_name='player')
print(entities.to_sparql())
features = graph.features('dbpo:BasketballPlayer',
features_col_name='feature_uri')
print(features.to_sparql())
entities_feats = graph.entities_and_features(
'dbpo:BasketballPlayer', [('dbpp:nationality', 'nationality'),
('dbpp:birthPlace', 'place'),
('dbpp:birthDate', 'birthDate'),
('dbpp:team', 'team')])
print(entities_feats.to_sparql())
classes_freq = graph.classes_and_freq()
print(classes_freq.to_sparql())
feats_freq = graph.features_and_freq('dbpo:BasketballPlayer')
print(feats_freq.to_sparql())
n_entities = graph.num_entities('dbpo:BasketballPlayer')
print(n_entities.to_sparql())
