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())