def answerQuestion(peer_name, net, user_password):
	policy_filename = 'entities/' + peer_name + '/datalog_policy.data'
	data_filename = 'entities/' + peer_name + '/data.data'

	queryString = net.recv();
	queryList = queryString.split(network_protocol.SEPARATOR)
	print(queryList)

	trusted_peer_dict = getTrustedPeers(peer_name)
	for other_peer, trusted_with in trusted_peer_dict.items():
		data = getDataFromTrustedPeer(peer_name, other_peer, user_password)
		pruned_data = prune(data, trusted_with)
		add_facts(pruned_data)

	# Add our own data
	if(fileIO.fileExists(data_filename)):
		add_facts(fileIO.readFile(data_filename))

	pyDatalog.load(fileIO.readFile(policy_filename))

	print("Asking question: " + queryList[0])
	query_result = pyDatalog.ask(queryList[0]);
	print('Query result:',query_result)
	if(query_result != None):
		net.send(queryList[1])
	else:
		net.send(queryList[2])
Ejemplo n.º 2
0
 def assertDefaultPolicy(self,direction):
   if not self.assertedDefaultPolicy:
     last_clause = self.clauses[-1]
     if len(last_clause.matchers) == 0:
       for a in last_clause.actions:
         pyDatalog.load("+(default%sPolicy(%s,%s,%s))" % (direction,self.name,a.getActionTuple()[0],a.getActionTuple()[1]))
     self.assertedDefaultPolicy = True
Ejemplo n.º 3
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 def load(self, console):
     """Loads the clauses from the file"""
     start = time.time()
     pyDatalog.load(self.data)
     if console:
         console.print(self.included_files,
                   "Finished ", time.time() - start, " s")
Ejemplo n.º 4
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def fillComplexRules(parent_child, child_parent, all_relations, relations):

    rules = ""

    #Originated
    for relation in parent_child:
        if relations[relation]:
            rules += 'originated(X, Xi, Y, Yi) <= ' + relation + '(X, Xi, Y, Yi )\n'

    for relation in child_parent:
        if relations[relation]:
            if relation == "etymology":
                rules += 'originated(X, Xi, Y, Yi) <= etymological_origin_of(Y, Yi, X, Xi)\n'
            elif relation == "is_derived_from":
                rules += 'originated(X, Xi, Y, Yi) <= has_derived_form(Y, Yi, X, Xi)\n'
            else:
                rules += 'originated(X, Xi, Y, Yi) <= ' + relation + '(Y, Yi, X, Xi)\n'

    #Listing
    for relation in all_relations:
        if relations[relation]:

            if relation == "etymology":
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & etymological_origin_of(X, Xi, Y, Yi)\n'
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & etymological_origin_of(Y, Yi, X, Xi)\n'
            elif relation == "is_derived_from":
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & has_derived_form(X, Xi, Y, Yi)\n'
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & has_derived_form(Y, Yi, X, Xi)\n'
            else:
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & ' + relation + '(X, Xi, Y, Yi)\n'
                rules += 'listing(Xi, Y, Yi) <= ~listing(Xi, Y, Yi) & ' + relation + '(Y, Yi, X, Xi)\n'

    pyDatalog.load(rules)
def load_logic():
    pyDatalog.load("""
        mother(X, Y) <=  (parent(X, Y) & gender(X, 'Female'))
        father(X, Y) <=  (parent(X, Y) & gender(X, 'Male'))
        married(X,Y) <= married(Y, X)
        husband(X,Y) <= married(X, Y) & gender(X, 'Male')
        wife(X,Y) <= husband(Y, X)
        child(Y, X) <= parent(X, Y)
        parent(X,Y) <= child(Y,X)
        decendent(X, Y) <= ancestor(Y, X)
        sibling(X,Y) <= (father(Z, X) & father(Z, Y) & ~(X==Y)) &  (mother(W, X) & mother(W, Y) & ~(X==Y))
        cousin(X, Y) <= parent(Z, X) & parent(W,Y) & sibling(Z, W)
        aunt(X,Y) <=  parent(Z, Y) & sibling(Z, X)  & gender(X, 'Female')
        aunt(X,Y) <=  uncle(Z, Y) & married(Z, X)
        uncle(X,Y) <=  parent(Z, Y) & sibling(Z, X) & gender(X, 'Male')
        uncle(X,Y) <=  aunt(Z, Y) & married(Z, X)
        ancestor(X, Y) <= (parent(W,Y) & (X==W))
        ancestor(X, Y) <= (parent(W,Y) & ancestor(X, W))
        brother(X,Y) <= sibling(X,Y) & gender(X, 'Male')
        sister(X, Y) <= sibling(X,Y) & gender(X, 'Female')
        inbred(X) <= (father(Y, X) & buendia_blood(Y, True)) &(mother(W, X) & buendia_blood(W, True))
        bastard(X) <= father(W,X) &  mother(Y, X) & ~married(W, Y)
        buendia_blood(X, True) <= parent(Y, X) & buendia_blood(Y, True)
        buendia(X, True) <= buendia_blood(X, True)
        buendia(X, True) <= married(X, Y) & buendia_blood(Y, True)
        son(X, Y) <= child(X, Y) &  gender(X, 'Male')
        daughter(X, Y) <= child(X, Y) &  gender(X, 'Female')
        """)
Ejemplo n.º 6
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    def __init__(self):
        print('Base de conocimientos')

        self.conocimiento=Logic(True)
    
        pyDatalog.load("""
            + usar_computadora('experto','si')
            + usar_computadora('inexperto','no')

            es_experto(Y) <= usar_computadora(Y,Z) & resp_experto(Z)

            # Es médico
            + terminologia('medico','si')
            + pacientes('medico','si')
            + recetar('medico','si')

            # No es médico
            + terminologia('persona','no')
            + pacientes('persona','no')
            + recetar('persona','no')

            es_medico(X) <= terminologia(X,A) & pacientes(X,A) & recetar(X,A) & resp_medico(A)
            

            tipo_usuario(X,Y) <= es_medico(X) & es_experto(Y)
        """)
Ejemplo n.º 7
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def materialize(facts, clauses, parser):
    logger.info('Asserting facts ..')
    for f in facts:
        # Each fact is asserted using the index of the subject, predicate and object for avoiding syntax issues
        s_idx = parser.entity_to_index[f.argument_names[0]]
        p_idx = parser.predicate_to_index[f.predicate_name]
        o_idx = parser.entity_to_index[f.argument_names[1]]
        # Asserting p(S, P, O)
        pyDatalog.assert_fact('p', s_idx, p_idx, o_idx)

    rules_str = '\n'.join(
        [clause_to_str(clause, parser) for clause in clauses])
    pyDatalog.load(rules_str)

    # Asking for all P(s, p, o) triples which hold true in the Knowledge Graph
    logger.info('Querying triples ..')
    _ans = pyDatalog.ask('p(S, P, O)')

    index_to_predicate = {
        idx: p
        for p, idx in parser.predicate_to_index.items()
    }
    index_to_entity = {idx: e for e, idx in parser.entity_to_index.items()}

    # Generating a list of inferred facts by replacing each entity and predicate index with their corresponding symbols
    inferred_facts = [
        Fact(index_to_predicate[p], [index_to_entity[s], index_to_entity[o]])
        for (s, p, o) in sorted(_ans.answers)
    ]
    return inferred_facts
Ejemplo n.º 8
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def loadFacts(fileName):
  """
  Convenience function to open a fact file and load it into the LogKB.
  """
  facts = open(fileName)
  pyDatalog.load(facts.read())
  facts.close()
Ejemplo n.º 9
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def loadFacts(fileName):
    """
  Convenience function to open a fact file and load it into the LogKB.
  """
    facts = open(fileName)
    pyDatalog.load(facts.read())
    facts.close()
Ejemplo n.º 10
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 def _(): # the function name is ignored
     pyDatalog.load(mc)
     #pyDatalog.load("""
     #+ (factorial[1]==1)
     #(factorial[N] == F) <= (N > 1) & (F == N*factorial[N-1])
     #""")
     print(pyDatalog.ask('factorial[4]==F'))
Ejemplo n.º 11
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 def __init__(self, rulesPath='../user.rules'):
     Logic()
     with open(rulesPath, 'r') as f:
         rules = "\n".join(f.readlines())
         
     load(rules)
     print "Rules for the user loaded"
     print rules
Ejemplo n.º 12
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    def __init__(self, rulesPath='../user.rules'):
        Logic()
        with open(rulesPath, 'r') as f:
            rules = "\n".join(f.readlines())

        load(rules)
        print "Rules for the user loaded"
        print rules
Ejemplo n.º 13
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def setup(instanceFile):
    pyDatalog.load(open(instanceFile,"r").read())
    #Rules for the Architectural Style
    pyDatalog.load(open("architectureStyle.py","r").read())
    #Rules for Vulnerabilities (Architectural Style)
    pyDatalog.load(open("vulnerabilityStyle.py","r").read())
    #Rules for Functionalities
    pyDatalog.load(open("functionalStyle.py","r").read())
    #Make sure every component has every plausible vulnerability
    pyDatalog.load(open("applyAllVulnerabilities.py","r").read())
Ejemplo n.º 14
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 def assert_error(code, message='^$'):
     _error = False
     try:
         pyDatalog.load(code)
     except Exception as e:
         e_message = e.message if hasattr(e, 'message') else e.args[0] # python 2 and 3
         if not re.match(message, e_message):
             print(e_message) 
         _error = True
     assert _error
Ejemplo n.º 15
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 def assert_error(code, message='^$'):
     _error = False
     try:
         pyDatalog.load(code)
     except Exception as e:
         e_message = e.message if hasattr(e, 'message') else e.args[0] # python 2 and 3
         if not re.match(message, e_message):
             print(e_message) 
         _error = True
     assert _error
Ejemplo n.º 16
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 def load(self, console):
     """Loads the clauses from the file"""
     start = time.time()
     try:
         pyDatalog.load(self.data)
         if console:
             console.print(self.included_files,
                           "Finished ", time.time() - start, " s")
     except BaseException as exception:
         print(exception)
Ejemplo n.º 17
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    def test_sudoku(self):
        from pyDatalog import pyDatalog
        from examples.RLP import sudoku_example
        from reloop.languages.rlp.logkb import PyDatalogLogKb

        for u in range(1, 10):
            pyDatalog.assert_fact('num', u)

        for u in range(1, 4):
            pyDatalog.assert_fact('boxind', u)

        pyDatalog.assert_fact('initial', 1, 1, 5)
        pyDatalog.assert_fact('initial', 2, 1, 6)
        pyDatalog.assert_fact('initial', 4, 1, 8)
        pyDatalog.assert_fact('initial', 5, 1, 4)
        pyDatalog.assert_fact('initial', 6, 1, 7)
        pyDatalog.assert_fact('initial', 1, 2, 3)
        pyDatalog.assert_fact('initial', 3, 2, 9)
        pyDatalog.assert_fact('initial', 7, 2, 6)
        pyDatalog.assert_fact('initial', 3, 3, 8)
        pyDatalog.assert_fact('initial', 2, 4, 1)
        pyDatalog.assert_fact('initial', 5, 4, 8)
        pyDatalog.assert_fact('initial', 8, 4, 4)
        pyDatalog.assert_fact('initial', 1, 5, 7)
        pyDatalog.assert_fact('initial', 2, 5, 9)
        pyDatalog.assert_fact('initial', 4, 5, 6)
        pyDatalog.assert_fact('initial', 6, 5, 2)
        pyDatalog.assert_fact('initial', 8, 5, 1)
        pyDatalog.assert_fact('initial', 9, 5, 8)
        pyDatalog.assert_fact('initial', 2, 6, 5)
        pyDatalog.assert_fact('initial', 5, 6, 3)
        pyDatalog.assert_fact('initial', 8, 6, 9)
        pyDatalog.assert_fact('initial', 7, 7, 2)
        pyDatalog.assert_fact('initial', 3, 8, 6)
        pyDatalog.assert_fact('initial', 7, 8, 8)
        pyDatalog.assert_fact('initial', 9, 8, 7)
        pyDatalog.assert_fact('initial', 4, 9, 3)
        pyDatalog.assert_fact('initial', 5, 9, 1)
        pyDatalog.assert_fact('initial', 6, 9, 6)
        pyDatalog.assert_fact('initial', 8, 9, 5)

        pyDatalog.load("""
            box(I, J, U, V) <= boxind(U) & boxind(V) & num(I) & num(J) & (I > (U-1)*3) & (I <= U*3) & (J > (V-1)*3) & (J <= V*3)
        """)

        logkb = PyDatalogLogKb()
        grounder = BlockGrounder(logkb)
        # Note: CVXOPT needs to be compiled with glpk support. See the CVXOPT documentation.
        solver = CvxoptSolver(solver_solver='glpk')

        model = sudoku_example.sudoku(grounder, solver)

        self.assertEqual(model, 0, "ERROR : Sudoku couldn't be solved")
Ejemplo n.º 18
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    def test_sudoku(self):
        from pyDatalog import pyDatalog
        from examples.RLP import sudoku_example
        from reloop.languages.rlp.logkb import PyDatalogLogKb

        for u in range(1, 10):
            pyDatalog.assert_fact('num', u)

        for u in range(1, 4):
            pyDatalog.assert_fact('boxind', u)

        pyDatalog.assert_fact('initial', 1, 1, 5)
        pyDatalog.assert_fact('initial', 2, 1, 6)
        pyDatalog.assert_fact('initial', 4, 1, 8)
        pyDatalog.assert_fact('initial', 5, 1, 4)
        pyDatalog.assert_fact('initial', 6, 1, 7)
        pyDatalog.assert_fact('initial', 1, 2, 3)
        pyDatalog.assert_fact('initial', 3, 2, 9)
        pyDatalog.assert_fact('initial', 7, 2, 6)
        pyDatalog.assert_fact('initial', 3, 3, 8)
        pyDatalog.assert_fact('initial', 2, 4, 1)
        pyDatalog.assert_fact('initial', 5, 4, 8)
        pyDatalog.assert_fact('initial', 8, 4, 4)
        pyDatalog.assert_fact('initial', 1, 5, 7)
        pyDatalog.assert_fact('initial', 2, 5, 9)
        pyDatalog.assert_fact('initial', 4, 5, 6)
        pyDatalog.assert_fact('initial', 6, 5, 2)
        pyDatalog.assert_fact('initial', 8, 5, 1)
        pyDatalog.assert_fact('initial', 9, 5, 8)
        pyDatalog.assert_fact('initial', 2, 6, 5)
        pyDatalog.assert_fact('initial', 5, 6, 3)
        pyDatalog.assert_fact('initial', 8, 6, 9)
        pyDatalog.assert_fact('initial', 7, 7, 2)
        pyDatalog.assert_fact('initial', 3, 8, 6)
        pyDatalog.assert_fact('initial', 7, 8, 8)
        pyDatalog.assert_fact('initial', 9, 8, 7)
        pyDatalog.assert_fact('initial', 4, 9, 3)
        pyDatalog.assert_fact('initial', 5, 9, 1)
        pyDatalog.assert_fact('initial', 6, 9, 6)
        pyDatalog.assert_fact('initial', 8, 9, 5)

        pyDatalog.load("""
            box(I, J, U, V) <= boxind(U) & boxind(V) & num(I) & num(J) & (I > (U-1)*3) & (I <= U*3) & (J > (V-1)*3) & (J <= V*3)
        """)

        logkb = PyDatalogLogKb()
        grounder = BlockGrounder(logkb)
        # Note: CVXOPT needs to be compiled with glpk support. See the CVXOPT documentation.
        solver = CvxoptSolver(solver_solver='glpk')

        model = sudoku_example.sudoku(grounder, solver)

        self.assertEqual(model, 0, "ERROR : Sudoku couldn't be solved")
Ejemplo n.º 19
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def determineResidualUtilityOnceTest(rD,query="",debug=True):
    rMax = addRisksToLogic(rD)
    maxUtility = sumAllUtilities()
    #rMax = 4
    for c,p in rD.items():
        s = "probCapability[" + str(c) + "] = " + str(p)
        pyDatalog.load(s)
    #This needs to change
    if query == "":
        query = "attackPaths(SourceService,TargetService,P,E,AttackerMoves,TotalC)"
    #query = "worstCasePath[\"3\"] == Y"
    #query = "worstCasePath[TotalC] == Y"
    #query = "worstCasePathCombo[X,Combo] == Y"
    #query = "worstCasePathCombo[" + str(3) + ",[businessWorkstations]" + "] == Y"
    print("Query: " + query)
    #query = "worstCasePathSpecific[X,SourceService]==Y"
    utilitiesByAttackerCapabilityAnswers = pyDatalog.ask(query)
    if utilitiesByAttackerCapabilityAnswers != None:
        utilitiesByAttackerCapability = utilitiesByAttackerCapabilityAnswers.answers
    estimatedValue = 0
    if debug:
        print("Query calculated.")
    if utilitiesByAttackerCapabilityAnswers != None:
        if debug:
            print("Query Answers:")
            #print("Utilities compromised by attacker capability:")
            #pprint.pprint(utilitiesByAttackerCapability)
            if len(utilitiesByAttackerCapability) > 0:
                #print(sorted(utilitiesByAttackerCapability,key=itemgetter(0)))
                pprint.pprint(sorted(utilitiesByAttackerCapability,key=itemgetter(0)))
            else:
                print("No answers")
            #print("Number of items: " + str(len(utilitiesByAttackerCapability)))
        #Undo highlight later
        #estimatedValue = sum(map(itemgetter(1),utilitiesByAttackerCapability))

        #for capability in range(rMax+1):
            #query2 = "worstCasePath[" + str(capability) + "] == X"
            #wCPsAnswers = pyDatalog.ask(query2)
            #if wCPsAnswers != None:
                #wCPs = wCPsAnswers.answers
                #print "************"
                #print("Worst case paths by attacker capability " + str(capability) + ": ")
                #pprint.pprint(str(wCPs))
    
    #Undo highlight later
    #estimatedValue = maxUtility - estimatedValue
    #if debug:
    #    print("Single Scenario Expected Value: " + str(estimatedValue))
    return estimatedValue
Ejemplo n.º 20
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def alimentarBD():

    load("""

		hijo2(P,H,R) <= padre(X,I,X2,H) & (I==P)

		hermano(X, Y, H) <= padre(Z, X) & padre (Z,Y) & (X!=Y)
		hijo(X, Y, H) <= padre(Z,Y) & (X==Z)
		tio(T, S, H) <= padre(P, S) & hermano(P, T, A) & (P!=T) 
		primo(X,Y,R) <= padre(Q,X) & padre(Z,Y) & (Q!=Y) & hermano(Q,Z,R)

		primoGrado(X,Y,H) <= padre(P,X) & padre(A,Y) & hermano(A,P,H) 
		primoGrado(X,Y,R) <= padre(P,X) & padre(A,Y)  & hermano(P, A, Q) &primoGrado(A,P,H)
		""")
Ejemplo n.º 21
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    def runsource(self, source, filename='console', symbol='single'):
        pySource = """
pyDatalog.load('''
%s
''')
""" % source
        try:
            code.InteractiveConsole.runsource(self, pySource, filename, symbol)
        except Exception as e:
            print(e)
Ejemplo n.º 22
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    def runsource(self, source, filename='console', symbol='single'):
        pySource = """
pyDatalog.load('''
%s
''')
""" % source
        try:
            code.InteractiveConsole.runsource(self, pySource, filename, symbol)
        except Exception as e:
            print(e)
Ejemplo n.º 23
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    def ask(self, query_symbols, logical_query, coeff_expr=None):
        """
        Builds a pyDataLog program from the logical_query and loads it. Then executes the query for the query_symbols.

        :param query_symbols: The symbols to be queried.
        :type query_symbols: list(SubSymbol)
        :param logical_query:
        :type:
        :return:
        """
        helper_len = 0
        tmp = None
        if not query_symbols:
            return None
        if coeff_expr is None:
            helper_len = len(query_symbols)
            helper_predicate = 'helper(' + ','.join(
                [str(v) for v in query_symbols]) + ')'
            tmp = helper_predicate + " <= " + self.transform_query(
                logical_query)
        else:
            helper_len = len(query_symbols) + 1
            syms = OrderedSet(query_symbols)
            syms.add('COEFF_EXPR')
            helper_predicate = 'helper(' + ','.join([str(v)
                                                     for v in syms]) + ')'
            index_query = self.transform_query(logical_query)
            coeff_query = "(COEFF_EXPR == " + str(coeff_expr) + ")"
            if index_query is None:
                tmp = helper_predicate + " <= " + coeff_query
            else:
                tmp = helper_predicate + " <= " + " & ".join(
                    [index_query, coeff_query])
        log.debug("pyDatalog query: " + tmp)
        pyDatalog.load(tmp)
        answer = pyDatalog.ask(helper_predicate)
        pyEngine.Pred.reset_clauses(pyEngine.Pred("helper", helper_len))

        if answer is None:
            return []

        return self.transform_answer(answer.answers)
Ejemplo n.º 24
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def addRisksToLogic(rD):
    riskStr = ""
    maxR = 0
    totalProb = float(0)
    #print(rD.items())
    for cap, prob in list(rD.items()):
        #pyDatalog.assert_fact(pC(cap,prob))
        #MaxR?
        #probCapability[cap] = prob
        #print("probCapability[" + str(cap) + "] = " + str(prob) + "\n")
        riskStr += "probCapability[" + str(cap) + "] = " + str(prob) + "\n"
        if cap > maxR:
            maxR = cap
        totalProb += prob
    #print("MaxR=" + str(maxR) + "\n")
    riskStr += "MaxR=" + str(maxR) + "\n"
    #if totalProb != 1.00:
    #    print("FAIL: Probabilities add to " + str(totalProb))
    #else:
        #print("OK: Probabilities add to 1.00")
    pyDatalog.load(riskStr)
    return maxR
Ejemplo n.º 25
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def eval_datalog(data, rule):
    """
    Evaluation using pyDatalog.
    :param data: a list of tuple string
    :param rule: a rule node
    :return: a list of resulting tuple string
    """
    assert isinstance(data, list)
    assert isinstance(rule, RuleNode)

    def extract_query_predicate(rule):
        # print(rule)
        return QUERY_PRED.match(rule).group(1)

    # def db2str(tuples):
    #     return "\n".join(["+%s(%s,%s)" % (p, s, o) for (s, p, o) in tuples])

    def result2tuplestring(result):
        # print(rule)
        # query_pred = extract_query_predicate(rule.left)
        for (s, o) in result:
            yield (s, rule.left, o)

    pyDatalog.clear()
    # loguru.logger.debug('Size of loaded data: %d' % len(data))
    for (s, p, o) in data:
        pyDatalog.assert_fact(p, s, o)
    pyDatalog.load(str(rule))

    result = pyDatalog.ask(rule.left + '(X, Y)')

    if not result:
        loguru.logger.debug("Empty evaluation")
        return []

    # if rule.left == config.query_relation_name:
    #     pyDatalog.ask(config.query_relation_name + "(" + config.subject + ", Y)")

    return list(result2tuplestring(result.answers))
Ejemplo n.º 26
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    def ask(self, query_symbols, logical_query, coeff_expr=None):
        """
        Builds a pyDataLog program from the logical_query and loads it. Then executes the query for the query_symbols.

        :param query_symbols: The symbols to be queried.
        :type query_symbols: list(SubSymbol)
        :param logical_query:
        :type:
        :return:
        """
        helper_len = 0
        tmp = None
        if not query_symbols:
            return None
        if coeff_expr is None:
            helper_len = len(query_symbols)
            helper_predicate = 'helper(' + ','.join([str(v) for v in query_symbols]) + ')'
            tmp = helper_predicate + " <= " + self.transform_query(logical_query)
        else:
            helper_len = len(query_symbols) + 1
            syms = OrderedSet(query_symbols)
            syms.add('COEFF_EXPR')
            helper_predicate = 'helper(' + ','.join([str(v) for v in syms]) + ')'
            index_query = self.transform_query(logical_query)
            coeff_query = "(COEFF_EXPR == " + str(coeff_expr) + ")"
            if index_query is None:
                tmp = helper_predicate + " <= " + coeff_query
            else:
                tmp = helper_predicate + " <= " + " & ".join([index_query, coeff_query])
        log.debug("pyDatalog query: " + tmp)
        pyDatalog.load(tmp)
        answer = pyDatalog.ask(helper_predicate)
        pyEngine.Pred.reset_clauses(pyEngine.Pred("helper", helper_len))

        if answer is None:
            return []

        return self.transform_answer(answer.answers)
Ejemplo n.º 27
0
def fillComplexRules(parent_child, child_parent, all_relations, relations):

    rules = ""
    for relation in all_relations:
        if relations[relation]:
            rules += 'palabras(X,I) <= ~palabras(X,I) & ' + relation + '(X,I,A,B)\n'
            rules += 'palabras(X,I) <= ~palabras(X,I) & ' + relation + '(A,B,X,I)\n'
            rules += 'igualesEntreIdiomas(I1,I2,X) <= palabras(X,I1) & palabras(X,I2)\n'
            rules += 'porcentaje(X, Y, Z) <= (Z == X / Y*100)\n'

    for relation in parent_child:
        if relations[relation]:
            rules += 'aporte(I1,I2,Y) <= ' + relation + '(_,I1,Y,I2) & ~(I2 == I1)\n'
    for relation in child_parent:
        if relations[relation]:
            if relation == "etymology":
                rules += 'aporte(I1,I2,Y) <= etymological_origin_of(Y,I2, _,I1) & ~(I2 == I1)\n'
            elif relation == "is_derived_from":
                rules += 'aporte(I1,I2,Y) <= has_derived_form(Y,I2, _,I1) & ~(I2 == I1)\n'
            else:
                rules += 'aporte(I1,I2,Y) <= ' + relation + '(Y,I2, _,I1) & ~(I2 == I1)\n'
    pyDatalog.load(rules)
    return
Ejemplo n.º 28
0
def determineResidualUtilityHelper(rD,maxUtility,debug=True):
    rMax = addRisksToLogic(rD)
    #rMax = 4
    for c,p in rD.items():
        s = "probCapability[" + str(c) + "] = " + str(p)
        pyDatalog.load(s)
    query = "weightedWorstCasePath[X]==Y"
    utilitiesByAttackerCapabilityAnswers = pyDatalog.ask(query)
    if utilitiesByAttackerCapabilityAnswers != None:
        utilitiesByAttackerCapability = utilitiesByAttackerCapabilityAnswers.answers
    estimatedValue = 0
    if debug:
        print("Attacks calculated.")
    if utilitiesByAttackerCapabilityAnswers != None:
        if debug:
            print("Utilities compromised by attacker capability:")
            #pprint.pprint(utilitiesByAttackerCapability)
            if len(utilitiesByAttackerCapability) > 0:
                pprint.pprint(sorted(utilitiesByAttackerCapability,key=itemgetter(0)))
            else:
                print("None")
            #print("Number of items: " + str(len(utilitiesByAttackerCapability)))
        estimatedValue = sum(map(itemgetter(1),utilitiesByAttackerCapability))

        #for capability in range(rMax+1):
            #query2 = "worstCasePath[" + str(capability) + "] == X"
            #wCPsAnswers = pyDatalog.ask(query2)
            #if wCPsAnswers != None:
                #wCPs = wCPsAnswers.answers
                #print "************"
                #print("Worst case paths by attacker capability " + str(capability) + ": ")
                #pprint.pprint(str(wCPs))
    estimatedValue = maxUtility - estimatedValue
    if debug:
        print("Single Scenario Expected Value: " + str(estimatedValue))
    return estimatedValue
Ejemplo n.º 29
0
def runDatalog(facts, rules, predicates):
    """виконує логічне виведення в pyDatalog. Повертає список тріплетів.
    facts - список Datalog-фактів,
    rules - список Datalog-правил,
    predicates - список предикатів, для яких будуть шукатись факти"""

    #if not predicates:
    #    predicates={p for s,p,o in facts}|{r.split('(')[0] for r in rules}

    from pyDatalog.pyDatalog import assert_fact, load, ask, clear
    code = '\n'.join(facts) + '\n' + '\n'.join(rules)  # факти і правила
    load(code)
    allFacts = set()
    for pred in predicates:
        # try:
        res = ask('%s(X,Y)' % pred).answers
        # except AttributeError: #Predicate without definition
        #     continue
        for subj, obj in res:
            allFacts.add((subj.encode('utf-8'), pred.encode('utf-8'),
                          obj.encode('utf-8')))
            print subj, pred, obj
    clear()
    return allFacts
Ejemplo n.º 30
0
def test():

    # test of expressions
    pyDatalog.load("""
        + p(a) # p is a proposition
    """)
    assert pyDatalog.ask('p(a)') == set([('a',)])
    
    pyDatalog.assert_fact('p', 'a', 'b')
    assert pyDatalog.ask('p(a, "b")') == set([('a', 'b')])
    pyDatalog.retract_fact('p', 'a', 'b')
    assert pyDatalog.ask('p(a, "b")') == None
    
    """unary facts                                                            """
    
    @pyDatalog.program()
    def unary(): 
        +z()
        assert ask(z()) == set([()])
        
        + p(a) 
        # check that unary queries work
        assert ask(p(a)) == set([('a',)])
        assert ask(p(X)) == set([('a',)])
        assert ask(p(Y)) == set([('a',)])
        assert ask(p(_X)) == set([('a',)])
        assert ask(p(b)) == None
        assert ask(p(a) & p(b)) == None
        
        + p(b)
        assert ask(p(X), _fast=True) == set([('a',), ('b',)])
        
        + p(b) # facts are unique
        assert ask(p(X)) == set([('a',), ('b',)])
        
        - p(b) # retract a unary fact
        assert ask(p(X)) == set([('a',)])
        
        - p(a)
        assert ask(p(X)) == None
        + p(a)
        
        # strings and integers
        + p('c')
        assert ask(p(c)) == set([('c',)])
        
        + p(1)
        assert ask(p(1)) == set([(1,)])
        
        + n(None)
        assert ask(n(X)) == set([(None,)])
        assert ask(n(None)) == set([(None,)])
        
        # spaces and uppercase in strings
        + farmer('Moshe dayan')
        + farmer('omar')
        assert ask(farmer(X)) == set([('Moshe dayan',), ('omar',)])

    # execute queries in a python program
    moshe_is_a_farmer = pyDatalog.ask("farmer('Moshe dayan')")
    assert moshe_is_a_farmer == set([('Moshe dayan',)])

    """ binary facts                                                         """
    
    @pyDatalog.program()
    def binary(): 
        + q(a, b)
        assert ask(q(a, b)) == set([('a', 'b')])
        assert ask(q(X, b)) == set([('a', 'b')])
        assert ask(q(a, Y)) == set([('a', 'b')])
        assert ask(q(a, c)) == None
        assert ask(q(X, Y)) == set([('a', 'b')])
        
        + q(a,c)
        assert ask(q(a, Y)) == set([('a', 'b'), ('a', 'c')])
        
        - q(a,c)
        assert ask(q(a, Y)) == set([('a', 'b')])
        
        assert ask(q(X, X)) == None 
        +q(a, a)
        assert ask(q(X, X)) == set([('a', 'a')])
        -q(a, a) 
        
    """ (in)equality                                             """

    @pyDatalog.program()
    def equality():
        assert ask(X==1) == set([(1,)]) 
        assert ask(X==Y) == None
        assert ask(X==Y+1) == None
        assert ask((X==1) & (Y==1) & (X==Y)) == set([(1,1)])
        assert ask((X==1) & (Y==2) & (X==Y-1)) == set([(1,2)])
        #assert ask((X==1) & (Y==2) & (X+2==Y+1)) == set([(1,2)])
        assert ask((X==2) & (Y==X/2)) == set([(2,1)])
        assert ask((X==2) & (Y==X//2)) == set([(2,1)])
        
        assert ask((X==1) & (Y==1+X)) == set([(1,2)])
        assert ask((X==1) & (Y==1-X)) == set([(1,0)])
        assert ask((X==1) & (Y==2*X)) == set([(1,2)])
        assert ask((X==2) & (Y==2/X)) == set([(2,1)])
        assert ask((X==2) & (Y==2//X)) == set([(2,1)])
        
    """ Conjunctive queries                                             """

    @pyDatalog.program()
    def conjuctive(): 
        assert ask(q(X, Y) & p(X)) == set([('a', 'b')])

        assert ask(p(X) & p(a)) == set([('a',),('c',),(1,)])
        assert ask(p(X) & p(Y) & (X==Y)) == set([('a', 'a'), ('c', 'c'), (1, 1)])
        assert ask(p(X) & p(Y) & (X==Y) & (Y==a)) == set([('a', 'a')])

        assert ask(q(X, Y)) == set([('a', 'b')])
        assert ask(q(X, Y) & p(X)) == set([('a', 'b')])
    
    @pyDatalog.program()
    def equality2():
        assert ask((X==1) & (X<X+1)) == set([(1,)]) 
        assert ask((X==1) & (Y==X)) == set([(1,1)]) 
        assert ask((X==1) & (Y==X+1)) == set([(1,2)])
        assert ask((X==1) & (Y==X+1) & (X<Y)) == set([(1,2)])
        assert ask((X==1) & (X<1)) == None
        assert ask((X==1) & (X<=1)) == set([(1,)])
        assert ask((X==1) & (X>1)) == None
        assert ask((X==1) & (X>=1)) == set([(1,)])
#       assert ask(X==(1,2)) == set([((1,2), (1,2))])
        assert ask(X in (1,)) == set([(1,)])
        assert ask((X==1) & (X not in (2,))) == set([(1,)])
        assert ask((X==1) & ~(X in (2,))) == set([(1,)])
        assert ask((X==1) & (X not in (1,))) == None
        assert ask((X==1) & ~(X in (1,))) == None

    @pyDatalog.program()
    def equality3():
        # equality (must be between parenthesis):
        s(X) <= (X == a)
        assert ask(s(X)) == set([('a',)])
        s(X) <= (X == 1)
        assert ask(s(X)) == set([(1,), ('a',)])
        
        s(X, Y) <= p(X) & (X == Y)
        assert ask(s(a, a)) == set([('a', 'a')])
        assert ask(s(a, b)) == None
        assert ask(s(X,a)) == set([('a', 'a')])
        assert ask(s(X, Y)) == set([('a', 'a'),('c', 'c'),(1, 1)])

    assert pyDatalog.ask('p(a)') == set([('a',)])

    """ clauses                                                         """
    
    @pyDatalog.program()
    def clauses(): 
    
        p2(X) <= p(X)
        assert ask(p2(a)) == set([('a',)])
        p2(X) <= p(X)
        
        r(X, Y) <= p(X) & p(Y)
        assert ask(r(a, a)) == set([('a', 'a')])
        assert ask(r(a, c)) == set([('a', 'c')])
        r(X, b) <= p(X)
        assert ask(r(a, b)) == set([('a', 'b')])
        
        - (r(X, b) <= p(X))
        assert ask(r(a, b)) == None
        
        # TODO more tests

        # integer variable
        for i in range(10):
            + successor(i+1, i)
        assert ask(successor(2, 1)) == set([(2, 1)])
        
        # built-in
        assert abs(-3)==3
        assert math.sin(3)==math.sin(3)
        
    
    """ in                                                         """
    
    pyDatalog.assert_fact('is_list', (1,2))

    @pyDatalog.program()
    def _in(): 
        assert ((X==1) & (X in (1,2))) == [(1,)]
        _in(X) <= (X in [1,2])
        assert ask(_in(1)) == set([(1,)])
        assert ask(_in(9)) == None
        assert ask(_in(X)) == set([(1,), (2,)])
        
        _in2(X) <= is_list(Y) & (X in Y)
        assert ask(_in2(X)) == set([(1,), (2,)])

        assert ask((Y==(1,2)) & (X==1) & (X in Y)) == set([((1, 2), 1)])
        assert ask((Y==(1,2)) & (X==1) & (X in Y+(3,))) == set([((1, 2), 1)])
                
    """ recursion                                                         """
    
    @pyDatalog.program()
    def recursion(): 
        + even(0)
        even(N) <= successor(N, N1) & odd(N1)
        odd(N) <= ~ even(N)
        assert ask(even(0)) == set([(0,)])
        assert ask(even(X)) == set([(4,), (10,), (6,), (0,), (2,), (8,)])
        assert ask(even(10)) == set([(10,)])
        assert ask(odd(1)) == set([(1,)])
        assert ask(odd(5)) == set([(5,)])
        assert ask(even(5)) == None
    
    """ recursion with expressions                                         """
    # reset the engine
    pyDatalog.clear()
    @pyDatalog.program()
    def recursive_expression(): 
        
        predecessor(X,Y) <= (X==Y-1)
        assert ask(predecessor(X,11)) == set([(10, 11)])
        
        p(X,Z) <= (Y==Z-1) & (X==Y-1)
        assert ask(p(X,11)) == set([(9, 11)])
        
        # odd and even
        + even(0)
        even(N) <= (N > 0) & odd(N-1)
        assert ask(even(0)) == set([(0,)])
        odd(N) <= (N > 0) & ~ even(N)
        assert ask(even(0)) == set([(0,)])
        assert ask(odd(1)) == set([(1,)])
        assert ask(odd(5)) == set([(5,)])
        assert ask(even(5)) == None
        assert ask((X==3) & odd(X+2)) == set([(3,)])
        
    # Factorial
    pyDatalog.clear()
    @pyDatalog.program()
    def factorial(): 
#        (factorial[N] == F) <= (N < 1) & (F == -factorial[-N])
#        + (factorial[1]==1)
#        (factorial[N] == F) <= (N > 1) & (F == N*factorial[N-1])
#        assert ask(factorial[1] == F) == set([(1, 1)])
#        assert ask(factorial[4] == F) == set([(4, 24)])
#        assert ask(factorial[-4] == F) == set([(-4, -24)])
        pass
    
    # Fibonacci
    pyDatalog.clear()
    @pyDatalog.program()
    def fibonacci(): 
        (fibonacci[N] == F) <= (N == 0) & (F==0)
        (fibonacci[N] == F) <= (N == 1) & (F==1)
        (fibonacci[N] == F) <= (N > 1) & (F == fibonacci[N-1]+fibonacci[N-2])
        assert ask(fibonacci[1] == F) == set([(1, 1)])
        assert ask(fibonacci[4] == F) == set([(4, 3)])
        assert ask(fibonacci[18] == F) == set([(18, 2584)])

    # string manipulation
    @pyDatalog.program()
    def _lambda(): 
        split(X, Y,Z) <= (X == Y+'-'+Z)
        assert ask(split(X, 'a', 'b')) == set([('a-b', 'a', 'b')])
        split(X, Y,Z) <= (Y == (lambda X: X.split('-')[0])) & (Z == (lambda X: X.split('-')[1]))
        assert ask(split('a-b', Y, Z)) == set([('a-b', 'a', 'b')])
        assert ask(split(X, 'a', 'b')) == set([('a-b', 'a', 'b')])
        
        (two[X]==Z) <= (Z==X+(lambda X: X))
        assert ask(two['A']==Y) == set([('A','AA')])

    """ negation                                                     """    
    
    @pyDatalog.program()
    def _negation():
        +p(a, b)
        assert ask(~p(X, b)) == None
        assert ask(~p(X, c)) == set([('X', 'c')])

    pyDatalog.load("""
        + even(0)
        even(N) <= (N > 0) & (N1==N-1) & odd(N1)
        odd(N) <= (N2==N+2) & ~ even(N) & (N2>0)
    """)
    assert pyDatalog.ask('~ odd(7)', _fast=True) == None
    assert pyDatalog.ask('~ odd(2)', _fast=True) == set([(2,)])
    assert pyDatalog.ask('odd(3)', _fast=True) == set([(3,)])
    assert pyDatalog.ask('odd(3)'             ) == set([(3,)])
    assert pyDatalog.ask('odd(5)', _fast=True) == set([(5,)])
    assert pyDatalog.ask('odd(5)'            ) == set([(5,)])
    assert pyDatalog.ask('even(5)', _fast=True) == None
    assert pyDatalog.ask('even(5)'            ) == None
    
    """ functions                                                         """
    pyDatalog.clear()
    @pyDatalog.program()
    def function(): 
        + (f[a]==b)
        assert ask(f[X]==Y) == set([('a', 'b')])
        assert ask(f[X]==b) == set([('a', 'b')]) #TODO remove 'b' from result
        assert ask(f[a]==X) == set([('a', 'b')])
        assert ask(f[a]==b) == set([('a', 'b')])
    
        + (f[a]==c)
        assert ask(f[a]==X) == set([('a', 'c')])
        
        + (f[a]==a)
        assert ask(f[f[a]]==X) == set([('a',)])
        assert ask(f[X]==f[a]) == set([('a',)])
        assert ask(f[X]==f[a]+'') == set([('a',)])
        - (f[a]==a)
        assert ask(f[f[a]]==X) == None

        + (f[a]==None)
        assert (ask(f[a]==X)) == set([('a',None)])
        + (f[a]==(1,2))
        assert (ask(f[a]==X)) == set([('a',(1,2))])
        assert (ask(f[X]==(1,2))) == set([('a',(1,2))])

        + (f[a]==c)

        + (f2[a,x]==b)
        assert ask(f2[a,x]==b) == set([('a', 'x', 'b')])
    
        + (f2[a,x]==c)
        assert ask(f2[a,x]==X) == set([('a', 'x', 'c')])
        
        g[X] = f[X]+f[X]
        assert(ask(g[a]==X)) == set([('a', 'cc')])
        
        h(X,Y) <= (f[X]==Y)
        assert (ask(h(X,'c'))) == set([('a', 'c')])
        assert (ask(h(X,Y))) == set([('a', 'c')])
        
    @pyDatalog.program()
    def function_comparison(): 
        assert ask(f[X]==Y) == set([('a', 'c')])
        assert ask(f[a]<'d') == set([('c',)])
        assert ask(f[a]>'a') == set([('c',)])
        assert ask(f[a]>='c') == set([('c',)])
        assert ask(f[a]>'c') == None
        assert ask(f[a]<='c') == set([('c',)])
        assert ask(f[a]>'c') == None
        assert ask(f[a] in ['c',]) == set([('c',)])
        
        assert ask((f[X]=='c') & (f[Y]==f[X])) == set([('a', 'a')])
        assert ask((f[X]=='c') & (f[Y]==f[X]+'')) == set([('a', 'a')])
        assert ask((f[X]=='c') & (f[Y]==(lambda X : 'c'))) == set([('a', 'a')])

        assert ask(f[X]==Y+'') == None
        assert ask((Y=='c') &(f[X]==Y+'')) == set([('c', 'a')])
        assert ask((Y=='c') &(f[X]<=Y+'')) == set([('c', 'a')])
        assert ask((Y=='c') &(f[X]<Y+'')) == None
        assert ask((Y=='c') &(f[X]<'d'+Y+'')) == set([('c', 'a')])
        assert ask((Y==('a','c')) & (f[X] in Y)) == set([(('a', 'c'), 'a')])
        assert ask((Y==('a','c')) & (f[X] in (Y+('z',)))) == set([(('a', 'c'), 'a')])

        assert ask(f[X]==f[X]+'') == set([('a',)])

    @pyDatalog.program()
    def function_negation(): 
        assert not(ask(~(f[a]<'d'))) 
        assert not(ask(~(f[X]<'d'))) 
        assert ask(~(f[a] in('d',)))
        
    """ aggregates                                                         """
    
    pyDatalog.clear()
    @pyDatalog.program()
    def sum(): 
        + p(a, c, 1)
        + p(b, b, 4)
        + p(a, b, 1)

        assert(sum(1,2)) == 3
        (a_sum[X] == sum(Y, key=Z)) <= p(X, Z, Y)
        assert ask(a_sum[X]==Y) == set([('a', 2), ('b', 4)])
        assert ask(a_sum[a]==X) == set([('a', 2)])
        assert ask(a_sum[a]==2) == set([('a', 2)])
        assert ask(a_sum[X]==4) == set([('b', 4)])
        assert ask(a_sum[c]==X) == None
        assert ask((a_sum[X]==2) & (p(X, Z, Y))) == set([('a', 'c', 1), ('a', 'b', 1)])

        (a_sum2[X] == sum(Y, for_each=X)) <= p(X, Z, Y)
        assert ask(a_sum2[a]==X) == set([('a', 1)])

        (a_sum3[X] == sum(Y, key=(X,Z))) <= p(X, Z, Y)
        assert ask(a_sum3[X]==Y) == set([('a', 2), ('b', 4)])
        assert ask(a_sum3[a]==X) == set([('a', 2)])

    @pyDatalog.program()
    def len(): 
        assert(len((1,2))) == 2
        (a_len[X] == len(Z)) <= p(X, Z, Y)
        assert ask(a_len[X]==Y) == set([('a', 2), ('b', 1)])
        assert ask(a_len[a]==X) == set([('a', 2)])
        assert ask(a_len[X]==1) == set([('b', 1)])
        assert ask(a_len[X]==5) == None
        
        (a_lenY[X] == len(Y)) <= p(X, Z, Y)
        assert ask(a_lenY[a]==X) == set([('a', 1)])
        assert ask(a_lenY[c]==X) == None
        
        (a_len2[X,Y] == len(Z)) <= p(X, Y, Z)
        assert ask(a_len2[a,b]==X) == set([('a', 'b', 1)])
        assert ask(a_len2[a,X]==Y) == set([('a', 'b', 1), ('a', 'c', 1)])

        + q(a, c, 1)
        + q(a, b, 2)
        + q(b, b, 4)

    @pyDatalog.program()
    def concat(): 
        (a_concat[X] == concat(Y, key=Z, sep='+')) <= q(X, Y, Z)
        assert ask(a_concat[X]==Y) == set([('b', 'b'), ('a', 'c+b')])
        assert ask(a_concat[a]=='c+b') == set([('a', 'c+b')])
        assert ask(a_concat[a]==X) == set([('a', 'c+b')])
        assert ask(a_concat[X]==b) == set([('b', 'b')])

        (a_concat2[X] == concat(Y, order_by=(Z,), sep='+')) <= q(X, Y, Z)
        assert ask(a_concat2[a]==X) == set([('a', 'c+b')])

        (a_concat3[X] == concat(Y, key=(-Z,), sep='-')) <= q(X, Y, Z)
        assert ask(a_concat3[a]==X) == set([('a', 'b-c')])

    @pyDatalog.program()
    def min(): 
        assert min(1,2) == 1
        (a_min[X] == min(Y, key=Z)) <= q(X, Y, Z)
        assert ask(a_min[X]==Y) == set([('b', 'b'), ('a', 'c')])
        assert ask(a_min[a]=='c') == set([('a', 'c')])
        assert ask(a_min[a]==X) == set([('a', 'c')])
        assert ask(a_min[X]=='b') == set([('b', 'b')])
        
        (a_minD[X] == min(Y, order_by=-Z)) <= q(X, Y, Z)
        assert ask(a_minD[a]==X) == set([('a', 'b')])
        
        (a_min2[X, Y] == min(Z, key=(X,Y))) <= q(X, Y, Z)
        assert ask(a_min2[Y, b]==X) == set([('a', 'b', 2),('b', 'b', 4)])
        assert ask(a_min2[Y, Y]==X) == set([('b', 'b', 4)]), "a_min2"
        
        (a_min3[Y] == min(Z, key=(-X,Z))) <= q(X, Y, Z)
        assert ask(a_min3[b]==Y) == set([('b', 4)]), "a_min3"
        
    @pyDatalog.program()
    def max(): 
        assert max(1,2) == 2
        (a_max[X] == max(Y, key=-Z)) <= q(X, Y, Z)
        assert ask(a_max[a]==X) == set([('a', 'c')])
        
        (a_maxD[X] == max(Y, order_by=Z)) <= q(X, Y, Z)
        assert ask(a_maxD[a]==X) == set([('a', 'b')])

    @pyDatalog.program()
    def rank(): 
        (a_rank1[Z] == rank(for_each=Z, order_by=Z)) <= q(X, Y, Z)
        assert ask(a_rank1[X]==Y) == set([(1, 0), (2, 0), (4, 0)])
        assert ask(a_rank1[X]==0) == set([(1, 0), (2, 0), (4, 0)])
        assert ask(a_rank1[1]==X) == set([(1, 0)])
        assert ask(a_rank1[1]==0) == set([(1, 0)])
        assert ask(a_rank1[1]==1) == None

        # rank
        (a_rank[X,Y] == rank(for_each=(X,Y2), order_by=Z2)) <= q(X, Y, Z) & q(X,Y2,Z2)
        assert ask(a_rank[X,Y]==Z) == set([('a', 'b', 1), ('a', 'c', 0), ('b', 'b', 0)])
        assert ask(a_rank[a,b]==1) == set([('a', 'b', 1)])
        assert ask(a_rank[a,b]==Y) == set([('a', 'b', 1)])
        assert ask(a_rank[a,X]==0) == set([('a', 'c', 0)])
        assert ask(a_rank[a,X]==Y) == set([('a', 'b', 1), ('a', 'c', 0)])
        assert ask(a_rank[X,Y]==1) == set([('a', 'b', 1)])
        assert ask(a_rank[a,y]==Y) == None
        # reversed
        (b_rank[X,Y] == rank(for_each=(X,Y2), order_by=-Z2)) <= q(X, Y, Z) & q(X,Y2,Z2)
        assert ask(b_rank[X,Y]==Z) == set([('a', 'b', 0), ('a', 'c', 1), ('b', 'b', 0)])
        assert ask(b_rank[a,b]==0) == set([('a', 'b', 0)])
        assert ask(b_rank[a,b]==Y) == set([('a', 'b', 0)])
        assert ask(b_rank[a,X]==1) == set([('a', 'c', 1)])
        assert ask(b_rank[a,X]==Y) == set([('a', 'b', 0), ('a', 'c', 1)])
        assert ask(b_rank[X,Y]==0) == set([('a', 'b', 0), ('b', 'b', 0)])
        assert ask(b_rank[a,y]==Y) == None

    @pyDatalog.program()
    def running_sum(): 
        # running_sum
        (a_run_sum[X,Y] == running_sum(Z2, for_each=(X,Y2), order_by=Z2)) <= q(X, Y, Z) & q(X,Y2,Z2)
        assert ask(a_run_sum[X,Y]==Z) == set([('a', 'b', 3), ('a', 'c', 1), ('b', 'b', 4)])
        assert ask(a_run_sum[a,b]==3) == set([('a', 'b', 3)])
        assert ask(a_run_sum[a,b]==Y) == set([('a', 'b', 3)])
        assert ask(a_run_sum[a,X]==1) == set([('a', 'c', 1)])
        assert ask(a_run_sum[a,X]==Y) == set([('a', 'b', 3), ('a', 'c', 1)])
        assert ask(a_run_sum[X,Y]==4) == set([('b', 'b', 4)])
        assert ask(a_run_sum[a,y]==Y) == None

        (b_run_sum[X,Y] == running_sum(Z2, for_each=(X,Y2), order_by=-Z2)) <= q(X, Y, Z) & q(X,Y2,Z2)
        assert ask(b_run_sum[X,Y]==Z) == set([('a', 'b', 2), ('a', 'c', 3), ('b', 'b', 4)])
        assert ask(b_run_sum[a,b]==2) == set([('a', 'b', 2)])
        assert ask(b_run_sum[a,b]==Y) == set([('a', 'b', 2)])
        assert ask(b_run_sum[a,X]==3) == set([('a', 'c', 3)])
        assert ask(b_run_sum[a,X]==Y) == set([('a', 'b', 2), ('a', 'c', 3)])
        assert ask(b_run_sum[X,Y]==4) == set([('b', 'b', 4)])
        assert ask(b_run_sum[a,y]==Y) == None

    """ simple in-line queries                                        """
    X = pyDatalog.Variable()
    assert ((X==1) >= X) == 1
    assert ((X==1) & (X!=2) >= X) == 1
    assert set(X._in((1,2))) == set([(1,),(2,)])
    assert ((X==1) & (X._in ((1,2)))) == [(1,)]

    """ interface with python classes                                        """

    class A(pyDatalog.Mixin):
        def __init__(self, b):
            super(A, self).__init__()
            self.b = b
        def __repr__(self):
            return self.b
        @pyDatalog.program() # indicates that the following method contains pyDatalog clauses
        def _():
            (A.c[X]==N) <= (A.b[X]==N)
            (A.len[X]==len(N)) <= (A.b[X]==N)
        @classmethod
        def _pyD_x1(cls, X):
            if X.is_const() and X.id.b == 'za':
                yield (X.id,)
            else:
                for X in pyDatalog.metaMixin.__refs__[cls]:
                    if X.b == 'za':
                        yield (X,)
            
    a = A('a')
    b = A('b')
    assert a.c == 'a'
    X, Y = pyDatalog.variables(2)
    assert (A.c[X]=='a') == [(a,)]
    assert (A.c[X]=='a')[0] == (a,)
    assert list(X.data) == [a]
    assert X.v() == a
    assert ((A.c[a]==X) >= X) == 'a'
    assert ((A.c[a]==X) & (A.c[a]==X) >= X) == 'a'
    assert ((A.c[a]==X) & (A.c[b]==X) >= X) == None
    (A.c[X]=='b') & (A.b[X]=='a')
    assert list(X.data) == []
    (A.c[X]=='a') & (A.b[X]=='a')
    assert list(X.data) == [a]
    result = (A.c[X]=='a') & (A.b[X]=='a')
    assert result == [(a,)]
    assert (A.c[a] == 'a') == [()]
    assert (A.b[a] == 'a') == [()]
    assert (A.c[a]=='a') & (A.b[a]=='a') == [()]
    assert (A.b[a]=='f') == []
    assert ((A.c[a]=='a') & (A.b[a]=='f')) == []
    
    """ filters on python classes                                        """
    assert (A.b[X]!=Y) == [(a, None), (b, None)]
    assert (A.b[X]!='a') == [(b,)]
    assert (A.b[X]!='z') == [(a,), (b,)]
    assert (A.b[a]!='a') == []
    assert list(A.b[b]!='a') == [()]
    assert ((A.b[b]!='a') & (A.b[b]!='z')) == [()]

    assert (A.b[X]<Y) == [(a, None), (b, None)]
    assert (A.b[X]<'a') == []
    assert (A.b[X]<'z') == [(a,), (b,)]
    assert (A.b[a]<'b') == [()]
    assert (A.b[b]<'a') == []
    assert ((A.b[b]<'z') & (A.b[b]!='z')) == [()]

    assert (A.b[X]<='a') == [(a,)]
    assert (A.b[X]<='z') == [(a,), (b,)]
    assert (A.b[a]<='b') == [()]
    assert (A.b[b]<='a') == []
    assert ((A.b[b]<='z') & (A.b[b]!='z')) == [()]

    assert (A.b[X]>'a') == [(b,)]
    assert (A.b[X]>='a') == [(a,), (b,)]

    assert (A.c[X]<='a') == [(a,)]
    assert (A.c[X]<='a'+'') == [(a,)]

    assert (A.c[X]._in(('a',))) == [(a,)]
    assert (A.c[X]._in(('a',)+('z',))) == [(a,)]
    assert ((Y==('a',)) & (A.c[X]._in(Y))) == [(('a',), a)] # TODO make ' in ' work
    
    assert ((Y==('a',)) & (A.c[X]._in(Y+('z',)))) == [(('a',), a)] # TODO make ' in ' work
    assert (A.c[X]._in(('z',))) == []

    # more complex queries
    assert ((Y=='a') & (A.b[X]!=Y)) == [('a', b)] # order of appearance of the variables !
    
    assert (A.len[X]==Y) == [(b, 1), (a, 1)]
    assert (A.len[a]==Y) == [(1,)]

    """ subclass                                              """

    class Z(A):
        def __init__(self, z):
            super(Z, self).__init__(z+'a')
            self.z = z
        def __repr__(self):
            return self.z
        @pyDatalog.program() # indicates that the following method contains pyDatalog clauses
        def _():
            (Z.w[X]==N) <= (Z.z[X]!=N)
        @classmethod
        def _pyD_query(cls, pred_name, args):
            if pred_name == 'Z.pred':
                if args[0].is_const() and args[0].id.b != 'za':
                    yield (args[0].id,)
                else:
                    for X in pyDatalog.metaMixin.__refs__[cls]:
                        if X.b != 'za':
                            yield (X,)
            else:
                raise AttributeError
    
    z = Z('z')
    assert z.z == 'z'
    assert (Z.z[X]=='z') == [(z,)]
    assert ((Z.z[X]=='z') & (Z.z[X]>'a')) == [(z,)]
    assert list(X.data) == [z]
    try:
        a.z == 'z'
    except Exception as e:
        e_message = e.message if hasattr(e, 'message') else e.args[0]
        if e_message != "Predicate without definition (or error in resolver): A.z[1]==/2":
            print(e_message)
    else:
        assert False
    
    try:
        (Z.z[a] == 'z') == None
    except Exception as e:
        e_message = e.message if hasattr(e, 'message') else e.args[0]
        if e_message != "Object is incompatible with the class that is queried.":
            print(e_message)
    else:
        assert False

    assert (Z.b[X]==Y) == [(z, 'za')]
    assert (Z.c[X]==Y) == [(z, 'za')]
    assert ((Z.c[X]==Y) & (Z.c[X]>'a')) == [(z, 'za')]
    assert (Z.c[X]>'a') == [(z,)]
    assert ((Z.c[X]>'a') & (A.c[X]=='za')) == [(z,)]
    assert (A.c[X]=='za') == [(z,)]
    assert (A.c[z]=='za') == [()]
    assert (z.b) == 'za'
    assert (z.c) == 'za'
    
    w = Z('w')
    w = Z('w') # duplicated to test __refs__[cls]
    assert(Z.x(X)) == [(z,)]
    assert not (~Z.x(z))
    assert ~Z.x(w)
    assert ~ (Z.z[w]=='z')
    assert(Z.pred(X)) == [(w,)] # not duplicated !
    assert(Z.pred(X) & ~ (Z.z[X]>='z')) == [(w,)]
    assert(Z.x(X) & ~(Z.pred(X))) == [(z,)]

    assert (Z.len[X]==Y) == [(w, 1), (z, 1)]
    assert (Z.len[z]==Y) == [(1,)]
    
    # TODO print (A.b[w]==Y)
            
    """ python resolvers                                              """
    
    @pyDatalog.predicate()
    def p(X,Y):
        yield (1,2)
        yield (2,3)
    
    assert pyDatalog.ask('p(X,Y)') == set([(1, 2), (2, 3)])
    assert pyDatalog.ask('p(1,Y)') == set([(1, 2)])
    assert pyDatalog.ask('p(1,2)') == set([(1, 2)])
    
    """ error detection                                              """
    
    @pyDatalog.program()
    def _(): 
        pass
    error = False
    try:
        _()
    except: error = True
    assert error

    def assert_error(code, message='^$'):
        _error = False
        try:
            pyDatalog.load(code)
        except Exception as e:
            e_message = e.message if hasattr(e, 'message') else e.args[0] # python 2 and 3
            if not re.match(message, e_message):
                print(e_message) 
            _error = True
        assert _error
        
    def assert_ask(code, message='^$'):
        _error = False
        try:
            pyDatalog.ask(code)
        except Exception as e: 
            e_message = e.message if hasattr(e, 'message') else e.args[0]
            if not re.match(message, e_message):
                print(e_message) 
            _error = True
        assert _error
        
    assert_error('ask(z(a),True)', 'Too many arguments for ask \!')
    assert_error('ask(z(a))', 'Predicate without definition \(or error in resolver\): z/1')
    assert_error("+ farmer(farmer(moshe))", "Syntax error: Literals cannot have a literal as argument : farmer\[\]")
    assert_error("+ manager[Mary]==John", "Left-hand side of equality must be a symbol or function, not an expression.")
    assert_error("manager[X]==Y <= (X==Y)", "Syntax error: please verify parenthesis around \(in\)equalities")
    assert_error("p(X) <= (Y==2)", "Can't create clause")
    assert_error("p(X) <= X==1 & X==2", "Syntax error: please verify parenthesis around \(in\)equalities")
    assert_error("p(X) <= (manager[X]== min(X))", "Error: argument missing in aggregate")
    assert_error("p(X) <= (manager[X]== max(X, order_by=X))", "Aggregation cannot appear in the body of a clause")
    assert_error("q(min(X, order_by=X)) <= p(X)", "Syntax error: Incorrect use of aggregation\.")
    assert_error("manager[X]== min(X, order_by=X) <= manager(X)", "Syntax error: please verify parenthesis around \(in\)equalities")
    assert_error("(manager[X]== min(X, order_by=X+2)) <= manager(X)", "order_by argument of aggregate must be variable\(s\), not expression\(s\).")
    assert_error("ask(X<1)", 'Error: left hand side of comparison must be bound: =X<1/1')
    assert_error("ask(X<Y)", 'Error: left hand side of comparison must be bound: =X<Y/2')
    assert_error("ask(1<Y)", 'Error: left hand side of comparison must be bound: =Y>1/1')
    assert_error("ask( (A.c[X]==Y) & (Z.c[X]==Y))", "TypeError: First argument of Z.c\[1\]==\('.','.'\) must be a Z, not a A ")
    assert_ask("A.u[X]==Y", "Predicate without definition \(or error in resolver\): A.u\[1\]==/2")
    assert_ask("A.u[X,Y]==Z", "Predicate without definition \(or error in resolver\): A.u\[2\]==/3")
    assert_error('(a_sum[X] == sum(Y, key=Y)) <= p(X, Z, Y)', "Error: Duplicate definition of aggregate function.")
    assert_error('(two(X)==Z) <= (Z==X+(lambda X: X))', 'Syntax error near equality: consider using brackets. two\(X\)')
    assert_error('p(X) <= sum(X, key=X)', 'Invalid body for clause')
    assert_error('ask(- manager[X]==1)', "Left-hand side of equality must be a symbol or function, not an expression.")
    assert_error("p(X) <= (X=={})", "unhashable type: 'dict'")

    """ SQL Alchemy                    """

    from sqlalchemy import create_engine
    from sqlalchemy import Column, Integer, String, ForeignKey
    from sqlalchemy.ext.declarative import declarative_base
    from sqlalchemy.orm import sessionmaker, relationship
    
    engine = create_engine('sqlite:///:memory:', echo=False) # create database in memory
    Session = sessionmaker(bind=engine)
    session = Session()

    Base = declarative_base(cls=pyDatalog.Mixin, metaclass=pyDatalog.sqlMetaMixin)
    Base.session = session
        
    class Employee(Base): # --> Employee inherits from the Base class
        __tablename__ = 'employee'
        
        name = Column(String, primary_key=True)
        manager_name = Column(String, ForeignKey('employee.name'))
        salary = Column(Integer)
        
        def __init__(self, name, manager_name, salary):
            super(Employee, self).__init__()
            self.name = name
            self.manager_name = manager_name # direct manager of the employee, or None
            self.salary = salary # monthly salary of the employee
        def __repr__(self): # specifies how to display the employee
            return "Employee: %s" % self.name
    
        @pyDatalog.program() # --> the following function contains pyDatalog clauses
        def Employee():
            (Employee.manager[X]==Y) <= (Employee.manager_name[X]==Z) & (Z==Employee.name[Y])
            # the salary class of employee X is computed as a function of his/her salary
            # this statement is a logic equality, not an assignment !
            Employee.salary_class[X] = Employee.salary[X]//1000
            
            # all the indirect managers of employee X are derived from his manager, recursively
            Employee.indirect_manager(X,Y) <= (Employee.manager[X]==Y) & (Y != None)
            Employee.indirect_manager(X,Y) <= (Employee.manager[X]==Z) & Employee.indirect_manager(Z,Y) & (Y != None)
            
            # count the number of reports of X
            (Employee.report_count[X] == len(Y)) <= Employee.indirect_manager(Y,X)
            
            Employee.p(X,Y) <= (Y <= Employee.salary[X] + 1)
            

    Base.metadata.create_all(engine) 
    
    John = Employee('John', None, 6800)
    Mary = Employee('Mary', 'John', 6300)
    Sam = Employee('Sam', 'Mary', 5900)
    
    session.add(John)
    session.add(Mary)
    session.add(Sam)
    session.commit()
    
    assert (John.salary_class ==6) 
    
    X = pyDatalog.Variable()
    result = (Employee.salary[X] == 6300) # notice the similarity to a pyDatalog query
    assert result == [(Mary,), ]
    assert (X._value() == [Mary,]) # prints [Employee: Mary]
    assert (X.v() == Mary) # prints Employee:Mary

    result = (Employee.indirect_manager(Mary, X))
    assert result == [(John,), ]
    assert (X.v() == John) # prints [Employee: John]
    
    Mary.salary_class = ((Employee.salary_class[Mary]==X) >= X)
    Mary.salary = 10000
    assert Mary.salary_class != ((Employee.salary_class[Mary]==X) >= X)

    X, Y, N = pyDatalog.variables(3)
    result = (Employee.salary[X]==6800) & (Employee.name[X]==N)
    assert result == [(John,'John'), ]
    assert N.v() == 'John'
    
    result = (Employee.salary[X]==Employee.salary[X])
    assert result == [(John,), (Mary,), (Sam,)]
    
    result = (Employee.p(X,1))
    assert result == [(John,), (Mary,), (Sam,)]
    
    result = (Employee.salary[X]<Employee.salary[X]+1)
    assert result == [(John,), (Mary,), (Sam,)]
    
    result = (Employee.salary[John]==N) & Employee.p(John, N)
    assert result == [(6800,)]
    result = (Employee.salary[X]==6800) & (Employee.salary[X]==N) & Employee.p(X, N) 
    assert result == [(John, 6800)]

    """
Ejemplo n.º 31
0
        else:
            new_source = source

        try:
            code.InteractiveConsole.runsource(self, new_source, filename, symbol)
        except Exception as e:
            print(e)

pyEngine.Auto_print = True

if __name__ == "__main__":

    parser = argparse.ArgumentParser(description='FoundationDB Query Console')
    parser.add_argument('-p', '--python', help='''Python module to be imported.
        pyDatalog.create_atoms must be called for any Datalog included.''')
    parser.add_argument('-d', '--datalog', help='''File with Datalog statements
        (only) to be loaded. Atoms will be automatically created.''')
    args = parser.parse_args()
    if args.python:
        import_all_from(args.python)
    if args.datalog:
        with open(args.datalog, 'r') as f:
            dl_defs = f.read()
        f.closed
        pyDatalog.load(dl_defs)
        globalize_atoms(compile(dl_defs, '<string>', 'exec'))

    console = fdbqueryConsole(locals=locals())
    console.set_mode('query')
    console.interact('')
Ejemplo n.º 32
0
from pyDatalog import pyDatalog


pyDatalog.create_terms('croakes, eatflies, frog, chrips, sings, canary, green, yellow, P, X')

pyDatalog.load("""
frog(X) <= croakes(X) & eatflies(X)
canary(X) <= sings(X) & chrips(X)
green(X) <= frog(X)
yellow(X) <= canary(X)
                """)

pyDatalog.assert_fact('croakes', 'Fritz')
pyDatalog.assert_fact('eatflies', 'Fritz')

pyDatalog.assert_fact('sings', 'Paul')
pyDatalog.assert_fact('chrips', 'Paul')

query = 'yellow(X)'
answers = pyDatalog.ask(query).answers

print(answers)

print(pyDatalog.ask('green(X)'))
Ejemplo n.º 33
0
Employee.indirect_manager(Mary, X)
print(X) # prints [John]

# Who are the employees of John with a salary below 6000 ?
result = (Employee.salary[X] < 6000) & Employee.indirect_manager(X, John)
print(result) # prints [(Sam,)]
print(X) # prints [Sam]
print((Employee.salary_class[X] == 5) & Employee.indirect_manager(X, John) >= X) # Sam

# verify that the manager of Mary is John
assert Employee.manager[Mary]==John

# who is his own indirect manager ?
Employee.indirect_manager(X, X)
print(X) # prints []

# who has 2 reports ?
Employee.report_count[X] == 2
print(X) # prints [John]

# what is the total salary of the employees of John ?
# note : it is better to place aggregation clauses in the class definition 
pyDatalog.load("(Employee.budget[X] == sum(N, for_each=Y)) <= (Employee.indirect_manager(Y, X)) & (Employee.salary[Y]==N)")
Employee.budget[John]==X
print(X) # prints [12200]

# who has the lowest salary ?
pyDatalog.load("(lowest[1] == min(X, order_by=N)) <= (Employee.salary[X]==N)")
# must use ask() because inline queries cannot use unprefixed literals 
print(pyDatalog.ask("lowest[1]==X")) # prints set([(1, 'Sam')])
Ejemplo n.º 34
0
pdl.load('''
    + male(daniel)
    + male(nicolas)
    + male(alain)
    + male(luigi)
    + male(johnny)
    + male(sacha)
    + male(ernest)
    + male(robert)
    + male(gilbert)

    + female(suzanne)
    + female(christine)
    + female(keiko)
    + female(rose_marie)
    + female(sylvie)
    + female(muriel)
    + female(magali)
    + female(maya)
    + female(nana)
    + female(suzanne_madeleine)
    + female(violette)
    + female(jacqueline)

    + husband(nicolas, keiko)
    + husband(johnny, luigi)
    + husband(maurice, jacqueline)
    + husband(gilbert, rose_marie)

    + father(gilbert, muriel)
    + father(gilbert, sylvie)
    + mother(rose_marie, muriel)
    + mother(rose_marie, sylvie)

    + father(ernest, suzanne)
    + father(ernest, jacqueline)
    + mother(suzanne_madeleine, suzanne)
    + mother(suzanne_madeleine, jacqueline)

    + father(robert, daniel)
    + father(robert, gilbert)
    + mother(violette, daniel)
    + mother(violette, gilbert)

    + father(daniel, nicolas)
    + father(daniel, alain)
    + father(daniel, christine)
    + mother(suzanne, nicolas)
    + mother(suzanne, alain)
    + mother(suzanne, christine)

    + father(johnny, luigi)
    + father(johnny, magali)
    + mother(christine, luigi)
    + mother(christine, magali)

    + father(nicolas, sacha)
    + father(nicolas, maya)
    + father(nicolas, nana)
    + mother(keiko, sacha)
    + mother(keiko, maya)
    + mother(keiko, nana)

    parent(X, Y) <= (father(X, Y))
    parent(X, Y) <= (mother(X, Y))

    print(parent(Parent, Child) & (Child == nicolas))
    print()

    grand_parent(X, Y) <= (parent(X, Z) & parent(Z, Y))
    grand_father(X, Y) <= (grand_parent(X, Y) & male(X))
    grand_mother(X, Y) <= (grand_parent(X, Y) & female(X))

    print(grand_parent(GrandParent, GrandChild) & (GrandChild == nicolas))
    print()
    print(grand_father(GrandFather, GrandChild) & (GrandChild == nicolas))
    print()
    print(grand_mother(GrandMother, GrandChild) & (GrandChild == nicolas))
    print()

    sibling(X, Y) <= (parent(Z, X) & parent(Z, Y) & (X != Y))
    brother(X, Y) <= (male(X) & sibling(X, Y))
    sister(X, Y) <= (female(X) & sibling(X, Y))

    print(sibling(Sibling, X) & (X == nicolas))
    print()
    print(brother(Brother, X) & (X == nicolas))
    print()
    print(sister(Sister, X) & (X == nicolas))
    print()

    uncle(X, Y) <= (parent(Z, Y) & brother(X, Z))
    uncle(X, Y) <= (parent(Z, Y) & sibling(A, Z) & husband(X, A))
    aunt(X, Y) <= (parent(Z, Y) & sister(X, Z))
    aunt(X, Y) <= (parent(Z, Y) & sibling(A, Z) & husband(A, X))

    print(uncle(Uncle, X) & (X == nicolas))
    print()
    print(aunt(Aunt, X) & (X == nicolas))
    print()

    ancestor(X, Y) <= (parent(X, Y))
    ancestor(X, Y) <= (parent(X, Z) & ancestor(Z, Y))

    print(ancestor(MaleAncestor, X) & (X == nicolas) & male(MaleAncestor))
    print()

    descendant(X, Y) <= (ancestor(Y, X))

    print(descendant(FemaleDescendant, X) & (X == daniel) & female(FemaleDescendant))
    print()
''')
Ejemplo n.º 35
0
        return self.statements

    def asDatacode(self):
        datacode = "\n".join(self.statements)
        print datacode
        return datacode
    
    def asTerms(self):
        allterms = ",".join(set(self.terms))
        #print allterms
        return allterms
 
csvToDatalog = CsvToDatalog()
csvToDatalog.load()
pyDatalog.create_terms(csvToDatalog.asTerms())
pyDatalog.load(csvToDatalog.asDatacode())

pyDatalog.create_terms('SC', 'NAME', 'FRONT', 'HORIZ', 'VERT', 'VP')
#print shapes(SC,NAME,FRONT,HORIZ,VERT,VP)

pyDatalog.create_terms('nextShape','startShape')

shape_brothers = defaultdict(list)
for shape in shapes(SC,NAME,FRONT,HORIZ,VERT,VP).data:
    new_conf = (shape[2],shape[3],shape[4],shape[5])
    shape_brothers[new_conf].append(shape[1])

for shape in shape_brothers.items():
    items = shape[1]
    items.sort()
    + startShape(items[0])
Ejemplo n.º 36
0
from pyDatalog.pyDatalog import create_terms, ask, load, assert_fact, clear

if __name__ == "__main__":
    clear()
    create_terms('X, frog, canary, green, yellow, chirps, sings, croakes, eatFlies')

    load("""
        frog(X) <= croakes(X) & eatFlies(X)
        canary(X) <= chirps(X) & sings(X)
        green(X) <= frog(X)
        yellow(X) <= canary(X)
    """)

    assert_fact('croakes', 'fritz')
    assert_fact('eatFlies', 'fritz')

    print("frog: ", ask('frog(X)'))
    print("green: ", ask('green(X)'))
    print("green: ", ask("green('cuitcuit')"))

#
print(indirect_manager('Sam', Y))
#print(indirect_manager(X,'John'))

indirect_manager('Sam', Y)
resultado = Y.data[1]
print("resultado", resultado)

# + parent(bill, 'John Adams')
pyDatalog.assert_fact('parent', 'bill', 'John Adams')
print(pyDatalog.ask('parent(bill,X)'))

# specify what an ancestor is
pyDatalog.load("""
    ancestor(X,Y) <= parent(X,Y)
    ancestor(X,Y) <= parent(X,Z) & ancestor(Z,Y)
""")

# prints a set with one element : the ('bill', 'John Adams') tuple
W = pyDatalog.ask('parent(bill,X)')
print(W.answers[0][0])
#
W = pyDatalog.ask('ancestor(bill,X)')
print('Bill es ancestro de:', W.answers[0][0])

# - parent(bill, 'John Adams')
pyDatalog.retract_fact('parent', 'bill', 'John Adams')

W = pyDatalog.ask('parent(bill,X)')
if (W.__str__() != 'None'):
    print(W.__str__())
Ejemplo n.º 38
0
# Who are the employees of John with a salary below 6000 ?
result = (Employee.salary[X] < 6000) & Employee.indirect_manager(X, John)
print(result)  # prints [(Sam,)]
print(X)  # prints [Sam]
print((Employee.salary_class[X] == 5) & Employee.indirect_manager(X, John) >=
      X)  # Sam

# verify that the manager of Mary is John
assert Employee.manager[Mary] == John

# who is his own indirect manager ?
Employee.indirect_manager(X, X)
print(X)  # prints []

# who has 2 reports ?
Employee.report_count[X] == 2
print(X)  # prints [John]

# what is the total salary of the employees of John ?
# note : it is better to place aggregation clauses in the class definition
pyDatalog.load(
    "(Employee.budget[X] == sum(N, for_each=Y)) <= (Employee.indirect_manager(Y, X)) & (Employee.salary[Y]==N)"
)
Employee.budget[John] == X
print(X)  # prints [12200]

# who has the lowest salary ?
pyDatalog.load("(lowest[1] == min(X, order_by=N)) <= (Employee.salary[X]==N)")
# must use ask() because inline queries cannot use unprefixed literals
print(pyDatalog.ask("lowest[1]==X"))  # prints set([(1, 'Sam')])
Ejemplo n.º 39
0
def loadBigString(string, cnt):
    try:
        load(string)
    except Exception:
        import traceback
        print(traceback.format_exc())
Ejemplo n.º 40
0
#>> Terms of Dimension
#Person
pd.create_terms("person, specialty, contract, division, all_persons") 
pd.create_terms("personSpec, personContract, specDiv")

#Drug
pd.create_terms("drug, drtype, all_drugs")
pd.create_terms("drugType")

#>> Terms for Facts
pd.create_terms("admDrug, bills")

#>> Reading Dimension and Facts
dim = open("Dimension.txt", 'r').read()
pd.load(dim)
facts = open("Facts.txt", 'r').read()
pd.load(facts)

print(facts)
print("==========================================================================")

#>>Rule
pd.create_terms("Date, Specialist, DrType, Patient, Amount, Age, Drug, PrescribedBy, Gen, billsT, admDrug1, admDrugT")

admDrug1(Date, PrescribedBy, Drug, Patient) <= bills(Date, Specialist, DrType, Patient, Amount) & personSpec(PrescribedBy, Specialist) & drugType(Drug, DrType)

admDrugT(Date, PrescribedBy, Drug, Patient, Age) <= admDrug(Date, PrescribedBy, Drug, Patient, Age) & ~(admDrug1(Date, PrescribedBy, Drug, Patient))

#>> Generation (Rule ID: G_01)
billsT(Date, Specialist, DrType, Patient, "G_01", Gen) <= (admDrugT(Date, PrescribedBy, Drug, Patient, Age) & personSpec(PrescribedBy, Specialist) & drugType(Drug, DrType) & (Gen=="G_01"))
from pyDatalog.pyDatalog import create_terms, load, ask, assert_fact

create_terms(
    'X, croakes, eatFlies, green, frog, sings, chirps, yellow, canary')

load("""
""")

frog(X) <= croakes(X) & eatFlies(X)
canary(X) <= sings(X) & chirps(X)
green(X) <= frog(X)
yellow(X) <= canary(X)

assert_fact('croakes', 'fritz')
assert_fact('eatFlies', 'fritz')

+sings('titi')
+chirps('titi')

+frog('Toto')
# assert_fact('sings','Jean' )
# assert_fact('chirps','Jean' )

query = 'yellow(X)'
answers = ask(query).answers
print(answers)

print(ask('frog(X)'))

print(ask("frog('fritz')"))
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 29 14:34:10 2019

@author: Margot
"""

from pyDatalog import pyDatalog
pyDatalog.clear()
pyDatalog.create_terms(
    'X, P, rectangle,  angleDroit, quelconque,  equilateral, deuxcote, troiscote, isocele, rectangleIsocele, triangle'
)

pyDatalog.load("""
""")

rectangle(X) <= angleDroit(X)
isocele(X) <= deuxcote(X)
rectangleIsocele(X) <= angleDroit(X) & deuxcote(X)
equilateral(X) <= troiscote(X)

pyDatalog.assert_fact('deuxcote', 'triangle')
pyDatalog.assert_fact('angleDroit', 'triangle')

query = 'isocele(X)'
answers = pyDatalog.ask(query).answers
print(answers)