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The Rete network.  The constructor takes an N3 rule graph, an identifier (a BNode by default), an 
initial Set of Rete tokens that serve as the 'working memory', and an rdflib Graph to 
add inferred triples to - by forward-chaining via Rete evaluation algorithm), 

src/f/u/FuXi-HEAD/lib/Rete/RuleStore.py   FuXi(Download)
        ruleGraph.parse(n3Stream, format='n3')
    if makeNetwork:
        from .Network import ReteNetwork
        closureDeltaGraph = Graph()
        network = ReteNetwork(ruleStore, inferredTarget=closureDeltaGraph)

src/f/u/FuXi-1.4.1.production/lib/Rete/__init__.py   FuXi(Download)
from Network import ReteNetwork, InferredGoal
from BetaNode import BetaNode
from AlphaNode import AlphaNode,ReteToken,BuiltInAlphaNode
from ReteVocabulary import RETE_NS
 

src/r/d/RDF.py-HEAD/FuXi/Rete/__init__.py   RDF.py(Download)
from Network import ReteNetwork, InferredGoal
from BetaNode import BetaNode
from AlphaNode import AlphaNode,ReteToken,BuiltInAlphaNode
from ReteVocabulary import RETE_NS