def _create_answer_group(tx_service, grpc_answer_group):
grpc_owner_concept = grpc_answer_group.owner
owner_concept = ConceptFactory.create_local_concept(grpc_owner_concept)
grpc_answers = list(grpc_answer_group.answers)
answer_list = [
AnswerConverter.convert(tx_service, grpc_answer)
for grpc_answer in grpc_answers
]
return AnswerGroup(owner_concept, answer_list)
def create_explanation(tx_service, grpc_explanation_res):
""" Convert gRPC explanation response to explanation object """
grpc_list_of_concept_maps = grpc_explanation_res.explanation
native_list_of_concept_maps = []
for grpc_concept_map in grpc_list_of_concept_maps:
native_list_of_concept_maps.append(
AnswerConverter._create_concept_map(tx_service,
grpc_concept_map))
rule = ConceptFactory.create_local_concept(grpc_explanation_res.rule)
if len(rule.id) == 0:
rule = None
return Explanation(native_list_of_concept_maps, rule)
def _create_concept_map(tx_service, grpc_concept_map_msg):
""" Create a Concept Dictionary from the grpc response """
var_concept_map = grpc_concept_map_msg.map
answer_map = {}
for (variable, grpc_concept) in var_concept_map.items():
answer_map[variable] = ConceptFactory.create_local_concept(
grpc_concept)
query_pattern = grpc_concept_map_msg.pattern
has_explanation = grpc_concept_map_msg.hasExplanation
return ConceptMap(answer_map, query_pattern, has_explanation,
tx_service)
def __init__(self, grpc_concept):
super(Thing, self).__init__(grpc_concept)
self._inferred = grpc_concept.inferred_res.inferred
from grakn.service.Session.Concept import ConceptFactory
self._type = ConceptFactory.create_local_concept(
grpc_concept.type_res.type)
