def do_test_json(cat, num, inputpath, expectedpath, context, options): base = TC_BASE + inputpath input_obj = _load_json(inputpath) input_graph = ConjunctiveGraph() to_rdf( input_obj, input_graph, base=base, context_data=context, produce_generalized_rdf=True, ) expected_json = _load_json(expectedpath) use_native_types = True # CONTEXT in input_obj result_json = from_rdf( input_graph, context, base=TC_BASE + inputpath, use_native_types=options.get("useNativeTypes", use_native_types), use_rdf_type=options.get("useRdfType", False), ) def _prune_json(data): if CONTEXT in data: data.pop(CONTEXT) if GRAPH in data: data = data[GRAPH] # def _remove_empty_sets(obj): return data expected_json = _prune_json(expected_json) result_json = _prune_json(result_json) _compare_json(expected_json, result_json)
def _construct(compiler, sources, query=None): dataset = ConjunctiveGraph() if not isinstance(sources, list): sources = [sources] for sourcedfn in sources: source = sourcedfn['source'] graph = dataset.get_context(URIRef(sourcedfn.get('dataset') or source)) if isinstance(source, (dict, list)): context_data = sourcedfn['context'] if not isinstance(context_data, list): context_data = compiler.load_json(context_data )['@context'] context_data = [compiler.load_json(ctx)['@context'] if isinstance(ctx, unicode) else ctx for ctx in context_data] to_rdf(source, graph, context_data=context_data) elif isinstance(source, Graph): graph += source else: graph += compiler.cached_rdf(source) if not query: return graph with compiler.path(query).open() as fp: result = dataset.query(fp.read()) g = Graph() for spo in result: g.add(spo) return g
def _test_parser(cat, num, inputpath, expectedpath, context, options): input_obj = _load_json(inputpath) expected_graph = _load_nquads(expectedpath) base = TC_BASE + inputpath result_graph = ConjunctiveGraph() to_rdf(input_obj, result_graph, base=base, context_data=context, produce_generalized_rdf = options.get('produceGeneralizedRdf', False)) assert isomorphic( result_graph, expected_graph), "Expected:\n%s\nGot:\n%s" % ( expected_graph.serialize(format='turtle'), result_graph.serialize(format='turtle'))
def _test_json(cat, num, inputpath, expectedpath, context, options): base = TC_BASE + inputpath input_obj = _load_json(inputpath) input_graph = ConjunctiveGraph() to_rdf(input_obj, input_graph, base=base, context_data=context) expected_json = _load_json(expectedpath) result_json = from_rdf(input_graph, context, base=TC_BASE + inputpath, use_native_types=options.get('useNativeTypes', False), use_rdf_type=options.get('useRdfType', False)) def _prune_json(data): if CONTEXT in data: data.pop(CONTEXT) if GRAPH in data: data = data[GRAPH] return data expected_json = _prune_json(expected_json) result_json = _prune_json(result_json) _compare_json(expected_json, result_json)
def _test_json(cat, num, inputpath, expectedpath, context, options): base = TC_BASE + inputpath input_obj = _load_json(inputpath) input_graph = ConjunctiveGraph() to_rdf(input_obj, input_graph, base=base, context_data=context, produce_generalized_rdf=True) expected_json = _load_json(expectedpath) use_native_types = True # CONTEXT in input_obj result_json = from_rdf(input_graph, context, base=TC_BASE + inputpath, use_native_types=options.get('useNativeTypes', use_native_types), use_rdf_type=options.get('useRdfType', False)) def _prune_json(data): if CONTEXT in data: data.pop(CONTEXT) if GRAPH in data: data = data[GRAPH] #def _remove_empty_sets(obj): return data expected_json = _prune_json(expected_json) result_json = _prune_json(result_json) _compare_json(expected_json, result_json)
"label": "rdfs:label", } } organizations = [] with open(sys.argv[1]) as infile: for count, row in enumerate(csv.DictReader(infile)): name = row['org_name'] oid = row['org_ID'] org_uri = 'org{}'.format(oid) org_type = row['org_vivo_uri'] org = {} org['uri'] = org_uri org['a'] = org_type org['label'] = name org.update(org_ctx) organizations.append(org) g = Graph() g.namespace_manager = ns_mgr out = to_rdf(organizations, g) print out.serialize(format='turtle')
def graph_from_ld(data): g = ConjunctiveGraph() out = to_rdf(data, g) return g
e.update(faculty_ctx) vc['hasEmail'] = vcard_email_uri fac.append(e) #Phone phone = row.get('phone') if phone != '': p = {} p['uri'] = vcard_phone_uri p['a'] = ["vcard:Telephone", "vcard:Work", "vcard:Voice"] p['telephone'] = phone p.update(faculty_ctx) fac.append(p) #Fax - really, 2014. fax = row.get('fax') if fax != '': f = {} f['uri'] = vcard_fax_uri f['a'] = ["vcard:Telephone", "vcard:Work", "vcard:Fax"] f['telephone'] = fax f.update(faculty_ctx) fac.append(f) vc['hasPhone'] = [vcard_phone_uri, vcard_fax_uri] g = Graph() out = to_rdf(fac, g) out.namespace_manager = ns_mgr print out.serialize(format='turtle')
#Phone phone = row.get('phone') if phone != '': p = {} p['uri'] = vcard_phone_uri p['a'] = ["vcard:Telephone", "vcard:Work", "vcard:Voice"] p['telephone'] = phone p.update(faculty_ctx) fac.append(p) #Fax - really, 2014. fax = row.get('fax') if fax != '': f = {} f['uri'] = vcard_fax_uri f['a'] = ["vcard:Telephone", "vcard:Work", "vcard:Fax"] f['telephone'] = fax f.update(faculty_ctx) fac.append(f) vc['hasPhone'] = [vcard_phone_uri, vcard_fax_uri] g = Graph() out = to_rdf(fac, g) out.namespace_manager = ns_mgr print out.serialize(format='turtle')
def to_graph(self, prepped): g = to_rdf(prepped, Graph()) return g
import json import yaml from rdflib import Graph from rdflib_jsonld import parser import sys ctxpath = sys.argv[1] fpath = sys.argv[2] with open(fpath) as fp: data = yaml.load(fp) with open(ctxpath) as fp: ctx = json.load(fp) graph = Graph() parser.to_rdf(data, graph, context_data=ctx) print graph.serialize(format='turtle')
"a": "@type", "uri": "@id", "vivo": "http://vivoweb.org/ontology/core#", "rdfs": "http://www.w3.org/2000/01/rdf-schema#", "label": "rdfs:label", } } organizations = [] with open(sys.argv[1]) as infile: for count, row in enumerate(csv.DictReader(infile)): name = row['org_name'] oid = row['org_ID'] org_uri = 'org{}'.format(oid) org_type = row['org_vivo_uri'] org = {} org['uri'] = org_uri org['a'] = org_type org['label'] = name org.update(org_ctx) organizations.append(org) g = Graph() g.namespace_manager = ns_mgr out = to_rdf(organizations, g) print out.serialize(format='turtle')
for row in csv.DictReader(infile): print row #tax_id = row.get('EIN') #print "tax_id: " + str(tax_id) d = {} d['uri'] = uuid_uri() d['label'] = row.get('NAME') print "NAME: " + str(d['label']) d['a'] = 'foaf:Organization' d.update(org_ctx) vco = uuid_uri() vcard_address = {} vcard_address['uri'] = uuid_uri() #vco['vcard:hasAddress'] = vcard_address d['vco'] = vco orgs.append(d) print orgs g = Graph() out = to_rdf(orgs, g) #out.namespace_manager = ns_mgr print out.serialize(format='turtle')