Python ConjunctiveGraph.predicates方法代码示例

# 需要导入模块: from rdflib.graph import ConjunctiveGraph [as 别名]
# 或者: from rdflib.graph.ConjunctiveGraph import predicates [as 别名]
def get_properties_from_input(file, input_format):
    input_graph = ConjunctiveGraph()
    input_graph.parse(file, format=input_format)

    # collapse to single list
    property_set = set()
    for row in input_graph.predicates():
        property_set.add(row)

    return property_set

# 需要导入模块: from rdflib.graph import ConjunctiveGraph [as 别名]
# 或者: from rdflib.graph.ConjunctiveGraph import predicates [as 别名]
def make_property_graph(properties, args):
    graph = ConjunctiveGraph()
    output_graph = ConjunctiveGraph()

    ontologies = [
        'https://raw.githubusercontent.com/monarch-initiative/SEPIO-ontology/master/src/ontology/sepio.owl',
        'https://raw.githubusercontent.com/monarch-initiative/GENO-ontology/develop/src/ontology/geno.owl',
        'http://purl.obolibrary.org/obo/ro.owl',
        'http://purl.obolibrary.org/obo/iao.owl',
        'http://purl.obolibrary.org/obo/ero.owl',
        'https://raw.githubusercontent.com/jamesmalone/OBAN/master/ontology/oban_core.ttl',
        'http://purl.obolibrary.org/obo/pco.owl',
        'http://purl.obolibrary.org/obo/xco.owl'
    ]

    for ontology in ontologies:
        print("parsing: " + ontology)
        try:
            graph.parse(ontology, format=rdflib_util.guess_format(ontology))
        except SAXParseException as e:
            logger.error(e)
            logger.error('Retrying: ' + ontology)
            graph.parse(ontology, format="turtle")
        except OSError as e:  # URLError:
            # simple retry
            logger.error(e)
            logger.error('Retrying: ' + ontology)
            graph.parse(ontology, format=rdflib_util.guess_format(ontology))

    # Get object properties
    output_graph = add_property_to_graph(
        graph.subjects(RDF['type'], OWL['ObjectProperty']),
        output_graph, OWL['ObjectProperty'], properties)

    # Get annotation properties
    output_graph = add_property_to_graph(
        graph.subjects(RDF['type'], OWL['AnnotationProperty']),
        output_graph, OWL['AnnotationProperty'], properties)

    # Get data properties
    output_graph = add_property_to_graph(
        graph.subjects(RDF['type'], OWL['DatatypeProperty']),
        output_graph, OWL['DatatypeProperty'], properties)

    # Hardcoded properties
    output_graph.add(
        (URIRef('https://monarchinitiative.org/MONARCH_cliqueLeader'),
            RDF['type'], OWL['AnnotationProperty']))

    output_graph.add(
        (URIRef('https://monarchinitiative.org/MONARCH_anonymous'),
            RDF['type'], OWL['AnnotationProperty']))

    # Check monarch data triple
    data_url = "https://data.monarchinitiative.org/ttl/{0}".format(
        re.sub(r".*/", "", args.input))
    new_url = "https://data.monarchinitiative.org/ttl/{0}".format(
        re.sub(r".*/", "", args.output))
    if (URIRef(data_url), RDF.type, OWL['Ontology']) in output_graph:
        output_graph.remove(URIRef(data_url), RDF.type, OWL['Ontology'])

    output_graph.add((URIRef(new_url), RDF.type, OWL['Ontology']))

    for row in output_graph.predicates(
            DC['source'], OWL['AnnotationProperty']):
        if row == RDF['type']:
            output_graph.remove(
                (DC['source'], RDF['type'], OWL['AnnotationProperty']))

    output_graph.add((DC['source'], RDF['type'], OWL['ObjectProperty']))

    return output_graph

# 需要导入模块: from rdflib.graph import ConjunctiveGraph [as 别名]
# 或者: from rdflib.graph.ConjunctiveGraph import predicates [as 别名]

# Now, with just that, lets see how the system
# recorded *way* too many details about what
# you just asserted as fact.
#

from pprint import pprint
pprint(list(primer))


# just think .whatever((s, p, o))
# here we report on what we know

pprint(list(primer.subjects()))
pprint(list(primer.predicates()))
pprint(list(primer.objects()))

# and other things that make sense

# what do we know about pat?
pprint(list(primer.predicate_objects(myNS.pat)))

# who is what age?
pprint(list(primer.subject_objects(myNS.age)))



# Okay, so lets now work with a bigger
# dataset from the example, and start
# with a fresh new graph.