def get_internal_person_from_external_iri(g:Graph, persons:set):
owl = get_schemas()['owl']
internals = set()
for person in persons:
for s,p,o in g.triples((None, owl.sameAs, URIRef(person))):
print(f'{s} <--- {person}')
internals.add(s)
return internals
def get_directors(g:Graph):
"""
obtiene todos los directores de mi base.
"""
ss = get_schemas()
s = ss['schema']
ds = [d for m,p,d in g.triples((None, s.director, None))]
return ds
def get_external_references(g:Graph, ds:Iterable):
"""
solo arma un mapa para poder mapear mas simple recursos externos a entidades internas mías.
"""
owl = get_schemas()['owl']
refs = {}
for d in ds:
for s,p,o in g.triples((d, owl.sameAs, None)):
refs[str(o)] = d
return refs
from common import get_persons_names, get_schemas, bind_schemas
def get_dbpedia_endpoint():
sparql = SPARQLWrapper("http://dbpedia.org/sparql")
sparql.setReturnFormat(JSON)
return sparql
if __name__ == '__main__':
g = Graph()
with open('data/dataset-original.ttl', 'r') as f:
g.parse(f, format='turtle')
sch = get_schemas()
schema = sch['schema']
names = get_persons_names(g, schema)
''' cargo las ocupaciones procesadas a mano '''
with open('data/db_pedia_occupations.json', 'r') as f:
occupations = json.load(f)['occupations']
subjects = {}
sql = get_dbpedia_endpoint()
cantidad = len(names)
procesado = 0
for my_subject, name in names:
print(f'procesando {procesado}/{cantidad}')
local_subjects = set()
if __name__ == '__main__':
g = Graph()
gdir = Graph()
bind_schemas(gdir)
with open('data/dataset-final.ttl','r') as f:
g.parse(f, format='turtle')
#with open('data/wikidata_subjects.ttl','r') as f:
# g.parse(f, format='turtle')
ss = get_schemas()
schema = ss['schema']
twss = ss['twss']
sql = get_wikidata_endpoint()
"""
punto 1 - ver notes_random.txt
"""
print("/////////////////////////////////////////\nPunto1\n//////////////////////////////////////////")
print(f'buscando datos específicos de wikidata sobre premios')
persons_with_award = get_wikidat_persons_with_award(sql)
directors_with_awards = set()
directors = get_directors(g)
if __name__ == '__main__':
print('leyendo archivo de subjects')
gsubjects = Graph()
with open('data/dbpedia_subjects.ttl','r') as f:
gsubjects.parse(f, format='turtle')
with open('data/wikidata_subjects.ttl','r') as f:
gsubjects.parse(f, format='turtle')
delay = 2
gdata = Graph()
bind_schemas(gdata)
owl = get_schemas()['owl']
endpoints = get_endpoints()
procesado = 0
cantidad = len(gsubjects)
for s,p,o in gsubjects.triples((None,OWL.sameAs,None)):
''' agrego la tripleta del sameAs así me queda interna la dataset '''
gdata.add((s, owl.sameAs, o))
my_subject = str(s)
subject = str(o)
print(f'procesando {procesado}/{cantidad}')
sql = select_endpoint(subject, endpoints)