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"""
This example shows how a custom evaluation function can be added to
handle certain SPARQL Algebra elements.
A custom function is added that adds ``rdfs:subClassOf`` "inference" when
asking for ``rdf:type`` triples.
Here the custom eval function is added manually, normally you would use
setuptools and entry_points to do it:
i.e. in your setup.py::
entry_points = {
'rdf.plugins.sparqleval': [
'myfunc = mypackage:MyFunction',
],
}
"""
# EvalBGP https://rdflib.readthedocs.io/en/stable/_modules/rdflib/plugins/sparql/evaluate.html
# Custom fct for rdf:type with auto infer super-classes: https://github.com/RDFLib/rdflib/blob/master/examples/custom_eval.py
# BGP = Basic Graph Pattern
# Docs rdflib custom fct: https://rdflib.readthedocs.io/en/stable/intro_to_sparql.html
# StackOverflow: https://stackoverflow.com/questions/43976691/custom-sparql-functions-in-rdflib/66988421#66988421
# Another project: https://github.com/bas-stringer/scry/blob/master/query_handler.py
# https://www.w3.org/TR/sparql11-service-description/#example-turtle
# Federated query: https://www.w3.org/TR/2013/REC-sparql11-federated-query-20130321/#defn_service
# XML method: https://rdflib.readthedocs.io/en/stable/apidocs/rdflib.plugins.sparql.results.html#module-rdflib.plugins.sparql.results.xmlresults
import rdflib
from rdflib import Literal, URIRef
from rdflib.plugins.sparql import parser
from rdflib.plugins.sparql.algebra import pprintAlgebra, translateQuery
from rdflib.plugins.sparql.evaluate import evalBGP
# inferredSubClass = rdflib.RDFS.subClassOf * "*" # any number of rdfs.subClassOf
biolink = URIRef("https://w3id.org/biolink/vocab/")
class Result:
pass
def add_to_graph(ctx, drug, disease, score):
bnode = rdflib.BNode()
ctx.graph.add((bnode, rdflib.RDF.type, rdflib.RDF.Statement))
ctx.graph.add((bnode, rdflib.RDF.subject, drug))
ctx.graph.add((bnode, rdflib.RDF.predicate, biolink + "treats"))
ctx.graph.add((bnode, rdflib.RDF.object, disease))
ctx.graph.add((bnode, biolink + "category", biolink + "ChemicalToDiseaseOrPhenotypicFeatureAssociation"))
ctx.graph.add((bnode, biolink + "has_confidence_level", score))
def get_triples(disease):
drug = URIRef("http://bio2rdf.org/drugbank:DB00001")
score = Literal("1.0")
r = Result()
r.drug = drug
r.disease = disease
r.score = score
results = []
results.append(r)
return results
# def parseRelationalExpr(expr):
def custom_eval(ctx, part):
""" """
# print (part.name)
if part.name == "Project":
ctx.myvars = []
# search extend for variable binding
if part.name == "Extend" and hasattr(part, "expr") and not isinstance(part.expr, list):
ctx.myvars.append(part.expr)
# search for filter
if part.name == "Filter" and hasattr(part, "expr"):
if hasattr(part.expr, "expr"):
if part.expr.expr["op"] == "=":
part.expr.expr["expr"]
d = part.expr.expr["other"]
ctx.myvars.append(d)
else:
if part.expr["op"] == "=":
part.expr["expr"]
d = part.expr["other"]
ctx.myvars.append(d)
# search the BGP for the variable of interest
if part.name == "BGP":
triples = []
for t in part.triples:
if t[1] == rdflib.RDF.object:
disease = t[2]
# check first if the disease term is specified in the bgp triple
if isinstance(disease, rdflib.term.URIRef):
ctx.myvars.append(disease)
# fetch instances
for d in ctx.myvars:
results = get_triples(d)
for r in results:
add_to_graph(ctx, r.drug, r.disease, r.score)
triples.append(t)
return evalBGP(ctx, triples)
raise NotImplementedError()
if __name__ == "__main__":
# add function directly, normally we would use setuptools and entry_points
rdflib.plugins.sparql.CUSTOM_EVALS["exampleEval"] = custom_eval
g = rdflib.Graph()
q = """PREFIX openpredict: <https://w3id.org/um/openpredict/>
PREFIX biolink: <https://w3id.org/biolink/vocab/>
PREFIX omim: <http://bio2rdf.org/omim:>
SELECT ?disease ?drug ?score
{
?association a rdf:Statement ;
rdf:subject ?drug ;
rdf:predicate ?predicate ;
#rdf:object omim:246300 ;
rdf:object ?disease ;
biolink:category biolink:ChemicalToDiseaseOrPhenotypicFeatureAssociation ;
biolink:has_confidence_level ?score .
#?disease dcat:identifier "OMIM:246300" .
BIND(omim:1 AS ?disease)
#FILTER(?disease = omim:2 || ?disease = omim:3)
#VALUES ?disease { omim:5 omim:6 omim:7 }
}"""
pq = parser.parseQuery(q)
tq = translateQuery(pq)
pprintAlgebra(tq)
# Find all FOAF Agents
for x in g.query(q):
print(x)
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