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"""
An RDFLib ConjunctiveGraph is an (unnamed) aggregation of all the Named Graphs
within a Store. The :meth:`~rdflib.graph.ConjunctiveGraph.get_context`
method can be used to get a particular named graph for use, such as to add
triples to, or the default graph can be used.
This example shows how to create Named Graphs and work with the
conjunction (union) of all the graphs.
"""
from rdflib import Literal, Namespace, URIRef
from rdflib.graph import ConjunctiveGraph, Graph
from rdflib.plugins.stores.memory import Memory
if __name__ == "__main__":
LOVE = Namespace("http://love.com#")
LOVERS = Namespace("http://love.com/lovers/")
mary = URIRef("http://love.com/lovers/mary")
john = URIRef("http://love.com/lovers/john")
cmary = URIRef("http://love.com/lovers/mary")
cjohn = URIRef("http://love.com/lovers/john")
store = Memory()
g = ConjunctiveGraph(store=store)
g.bind("love", LOVE)
g.bind("lovers", LOVERS)
# Add a graph containing Mary's facts to the Conjunctive Graph
gmary = Graph(store=store, identifier=cmary)
# Mary's graph only contains the URI of the person she loves, not his cute name
gmary.add((mary, LOVE.hasName, Literal("Mary")))
gmary.add((mary, LOVE.loves, john))
# Add a graph containing John's facts to the Conjunctive Graph
gjohn = Graph(store=store, identifier=cjohn)
# John's graph contains his cute name
gjohn.add((john, LOVE.hasCuteName, Literal("Johnny Boy")))
# Enumerate contexts
print("Contexts:")
for c in g.contexts():
print(f"-- {c.identifier} ")
print("===================")
# Separate graphs
print("John's Graph:")
print(gjohn.serialize())
print("===================")
print("Mary's Graph:")
print(gmary.serialize())
print("===================")
print("Full Graph")
print(g.serialize())
print("===================")
print("Query the conjunction of all graphs:")
xx = None
for x in g[mary : LOVE.loves / LOVE.hasCuteName]: # type: ignore[misc]
xx = x
print("Q: Who does Mary love?")
print("A: Mary loves {}".format(xx))
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