Пример #1
0
def buscar():
    print(
        'Opciones para buscar personas\n1: Buscar a todos\n2: Buscar por nombre\n3: Volver\n'
    )
    sel = None

    while sel not in ("1", "2", "3"):
        sel = input('Seleccione una opción:\n')
        if (sel == '1'):
            print(pyDatalog.ask("is_person(X)"))
        elif (sel == '2'):
            nombre = input("Escribe un nombre para consultar:\n")
            W = pyDatalog.ask("is_person('" + nombre + "')")

            if (str(W) == 'None'):
                op = None
                while op not in ("s", "n", "S", "N"):
                    op = input(
                        "No existe esta persona, ¿Desea agregarla?(S/N)")
                    if (op == 's' or op == 'S'):
                        agregar(nombre)
                    elif (op == "n" or op == "N"):
                        break
                    else:
                        print('Solo puede agregar S o N')
            else:
                print(W.answers)

        elif (sel == '3'):
            break
        else:
            print("Ingrese una opción valida")
Пример #2
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    def assertPatient(self, name, age, sick):
        Logic(self.first)
        #metodo que agrega un paciente a la base de conocimiento
        pyDatalog.assert_fact('age', name, age)
        pyDatalog.assert_fact('sick_of', name, sick)

        tq2 = "sick_of(" + name + ",Y)"
        tq3 = "require_limits_temperature(" + name + ",A,B)"
        tq4 = "require_temperature(" + name + ",A)"
        tq5 = "is_in_stage(" + name + ",A)"
        q2 = pyDatalog.ask(tq2)
        q3 = pyDatalog.ask(tq3)
        q4 = pyDatalog.ask(tq4)
        q5 = pyDatalog.ask(tq5)
        db = self.con.conexion()
        coleccion = db['sensor_temp']
        query = {"activo": "t"}
        data = {
            "$set": {
                "act0_status": "f",
                "act1_status": "f",
                "enfermedad": q2.answers[0][0],
                "temp_min": int(q3.answers[0][1]),
                "temp_max": int(q3.answers[0][0]),
                "temp_pref": int(q4.answers[0][0]),
                "stage": q5.answers[0][0]
            }
        }
        coleccion.update_one(query, data)
        print("mongodb updated")

        return 'saved'
Пример #3
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def addRecipe(name, ingredients, instructions):
    isAlreadyDefined = pyDatalog.ask("hasID('" + name + "', 'recipe', Z)")
    if (not isAlreadyDefined == None):
        print("This recipe is already defined")
        return isAlreadyDefined.answers[0][0]

    # insert recipe in database
    database = connectToDatabase()
    mydb = database[0]
    mycursor = database[1]
    sqlRezepte = "INSERT INTO `Rezepte` (`Name`, `Anleitung`) VALUES (%s, %s)"
    valRezepte = [(name, instructions)]
    mycursor.executemany(sqlRezepte, valRezepte)
    mydb.commit()
    recipeNumber = mycursor.lastrowid
    id = "recipe" + str(recipeNumber)

    # add recipe to datalog
    pyDatalog.assert_fact('hasID', name, "recipe", id)
    pyDatalog.assert_fact('recipeInstructions', name, instructions)

    # insert ingredients in database
    for i in ingredients:
        if isValidId(i[0]):
            if "ingredient" in i[0]:
                sqlEnthaeltLebensmittel = "INSERT INTO `enthaeltLebensmittel` (`RezeptId`, `LebensmittelId`, `Menge`) VALUES (%s, %s, %s)"
                valEnthaeltLebensmittel = [(recipeNumber, int(i[0][10:11]),
                                            i[1])]
                mycursor.executemany(sqlEnthaeltLebensmittel,
                                     valEnthaeltLebensmittel)
                mydb.commit()
            if "recipe" in i[0]:
                sqlEnthaeltrezept = "INSERT INTO `enthaeltRezept` (`RezeptId`, `KomponentenRezeptId`, `Menge`) VALUES (%s, %s, %s)"
                valEnthaeltrezept = [(recipeNumber, int(i[0][6:7]), i[1])]
                mycursor.executemany(sqlEnthaeltrezept, valEnthaeltrezept)
                mydb.commit()

            # add ingredient to datalog
            ingredient = pyDatalog.ask(("hasID(X, Y, '" + i[0] + "')"))
            pyDatalog.assert_fact('containsIngredient', name,
                                  ingredient.answers[0][0], i[1])
        else:
            print(i[0] + " is no valid id")

    # add weight to datalog
    ingredients = pyDatalog.ask("containsIngredient('" + name + "', Y, Z)")
    weight = 0
    if not ingredients == None:
        for i in ingredients.answers:
            weight += i[1]
    pyDatalog.assert_fact('weightPerServing', name, weight)
    pyDatalog.assert_fact('hasCaloriesPer100g', name, getCaloriesPer100g(name))

    if mydb.is_connected():
        mycursor.close()
        mydb.close()
    return id
Пример #4
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def getRecipeDetails(recipeID):
    recipeInstructions = pyDatalog.ask("hasID(X, 'recipe', '" + recipeID +
                                       "') & recipeInstructions(X, Y)")
    recipeIngredients = pyDatalog.ask("containsIngredient('" +
                                      recipeInstructions.answers[0][0] +
                                      "', Y, Z)")
    recipeIngredientsReturnValue = []
    if not recipeIngredients == None:
        recipeIngredientsReturnValue = recipeIngredients.answers
    return recipeInstructions.answers + recipeIngredientsReturnValue
Пример #5
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 def assert_ask(code, message='^$'):
     _error = False
     try:
         pyDatalog.ask(code)
     except Exception as e:
         e_message = e.message if hasattr(e, 'message') else e.args[0]
         if not re.match(message, e_message):
             print(e_message)
         _error = True
     assert _error
Пример #6
0
 def assert_ask(code, message='^$'):
     _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
def test():
    query = "parent(X, Y)"
    answers = pyDatalog.ask(query).answers
    for ans in answers:
        print(ans)
    print()
    print()
    query = 'decendent(X, "Fernanda del Carpio")'
    answers = sorted(pyDatalog.ask(query).answers)
    expected_answers = ("Aureliano (II)", )
    print(answers)
    pass
Пример #8
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def getCaloriesPer100g(recipeName):
    calorieSum = 0
    calories = pyDatalog.ask("baseIngredientWithCalories('" + recipeName +
                             "', X, Y)")
    if not calories == None:
        for c in calories.answers:
            calorieSum += c[1]
        return calorieSum * 100 / pyDatalog.ask("weightPerServing('" +
                                                recipeName +
                                                "', X)").answers[0][0]
    else:
        return 0
Пример #9
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 def readPatient(self, name):
     Logic(self.first)
     #metodo que consulta los datos del paciente actualmente presente en la base de conocimiento
     returnvalue = ""
     try:
         tq1 = "age(" + name + ",Y)"
         tq2 = "sick_of(" + name + ",Y)"
         q1 = pyDatalog.ask(tq1)
         q2 = pyDatalog.ask(tq2)
         returnvalue = "{'name':'" + name + "','age':'" + q1.answers[0][
             0] + "','sick':'" + q2.answers[0][0] + "'}"
     except:
         returnvalue = "NOPATIENT"
     return returnvalue
Пример #10
0
 def retractPatient(self, name):
     Logic(self.first)
     #Método para olvidar el paciente, recupera sus datos de la base de conocimiento y lo elimina
     returnvalue = ''
     try:
         tq1 = "age(" + name + ",Y)"
         tq2 = "sick_of(" + name + ",Y)"
         q1 = pyDatalog.ask(tq1)
         q2 = pyDatalog.ask(tq2)
         pyDatalog.retract_fact('age', name, q1.answers[0][0])
         pyDatalog.retract_fact('sick_of', name, q2.answers[0][0])
         return 'retracted'
     except:
         returnvalue = "NOPATIENT"
     return returnvalue
Пример #11
0
def addIngredient(name, calorie, glutenFree, lactoseFree, vegan, vegetarian):
    isAlreadyDefined = pyDatalog.ask("hasID('" + name + "', 'ingredient', Z)")
    if (not isAlreadyDefined == None):
        print("This ingredient is already defined")
        return isAlreadyDefined.answers[0][0]

    # insert ingredient in database
    database = connectToDatabase()
    mydb = database[0]
    mycursor = database[1]
    sqlZutat = "INSERT INTO `Lebensmittel` (`Name`, `KalorienPro100g`, `Fleisch`, `Tierprodukt`, `Gluten`, `Krebstiere`, `Eier`, `Fisch`, `Erdnuesse`, `Sojabohnen`, `Milch`, `Schalenfruechte`, `Sellerie`, `Sesamsamen`, `Schwefeldioxid`, `Lupinien`, `Weichtiere`) VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)"
    valZutat = [(name, calorie, 0 if vegetarian else 1, 0 if vegan else 1,
                 0 if glutenFree else 1, 0, 0, 0, 0, 0,
                 0 if lactoseFree else 1, 0, 0, 0, 0, 0, 0)]
    mycursor.executemany(sqlZutat, valZutat)
    mydb.commit()
    ingredientNumber = mycursor.lastrowid
    id = "ingredient" + str(ingredientNumber)

    # add ingredient to datalog
    pyDatalog.assert_fact('hasID', name, "ingredient", id)
    pyDatalog.assert_fact('hasCaloriesPer100g', name, calorie)
    if not glutenFree:
        pyDatalog.assert_fact('containsGluten', name)
    if not lactoseFree:
        pyDatalog.assert_fact('containsLactose', name)
    if not vegetarian:
        pyDatalog.assert_fact('containsMeat', name)
    if (not vegetarian) | (not vegan):
        pyDatalog.assert_fact('containsAnimalProduct', name)
    pyDatalog.assert_fact('weightPerServing', name, 1)
Пример #12
0
def queen(thread_name):
    n = int(random.random() * 8) + 1 # 1 to 8
    Logic()
    
    queens(X0)                      <= (X0._in(range(n)))
    queens(X0,X1)                   <= queens(X0)                   & next_queen(X0,X1)
    queens(X0,X1,X2)                <= queens(X0,X1)                & next_queen(X0,X1,X2)
    queens(X0,X1,X2,X3)             <= queens(X0,X1,X2)             & next_queen(X0,X1,X2,X3)
    queens(X0,X1,X2,X3,X4)          <= queens(X0,X1,X2,X3)          & next_queen(X0,X1,X2,X3,X4)
    queens(X0,X1,X2,X3,X4,X5)       <= queens(X0,X1,X2,X3,X4)       & next_queen(X0,X1,X2,X3,X4,X5)
    queens(X0,X1,X2,X3,X4,X5,X6)    <= queens(X0,X1,X2,X3,X4,X5)    & next_queen(X0,X1,X2,X3,X4,X5,X6)
    queens(X0,X1,X2,X3,X4,X5,X6,X7) <= queens(X0,X1,X2,X3,X4,X5,X6) & next_queen(X0,X1,X2,X3,X4,X5,X6,X7)
    
    next_queen(X0,X1)                   <= queens(X1)                       & ok(X0,1,X1)
    next_queen(X0,X1,X2)                <= next_queen(X1,X2)                & ok(X0,2,X2)
    next_queen(X0,X1,X2,X3)             <= next_queen(X1,X2,X3)             & ok(X0,3,X3)
    next_queen(X0,X1,X2,X3,X4)          <= next_queen(X1,X2,X3,X4)          & ok(X0,4,X4)
    next_queen(X0,X1,X2,X3,X4,X5)       <= next_queen(X1,X2,X3,X4,X5)       & ok(X0,5,X5)
    next_queen(X0,X1,X2,X3,X4,X5,X6)    <= next_queen(X1,X2,X3,X4,X5,X6)    & ok(X0,6,X6)
    next_queen(X0,X1,X2,X3,X4,X5,X6,X7) <= next_queen(X1,X2,X3,X4,X5,X6,X7) & ok(X0,7,X7)
    
    query = pyDatalog.ask("queens(%s)" % (",".join("X%s" % i for i in range(n))))
    answers = query.answers if query else [] 
    result = "OK" if len(answers) == [1,0,0,2,10,4,40,92][n-1] else "* not OK ! *"
    print("%s : n = %d %s " % (thread_name, n, result))
Пример #13
0
    def leer_perfil(self, datos):
        str_experto = datos[0]
        str_medico = ""
        
        if(datos[1] == "si" and datos[2]=="si" and datos[3] == "si"):
            str_medico = "si"
        elif(datos[1] == "si" and datos[2]=="no" and datos[3] == "si"):
            str_medico = "si"
        else:
            str_medico = "no"

        Logic(self.conocimiento)
        try:
            pyDatalog.assert_fact("resp_experto",str_experto)
            pyDatalog.assert_fact("resp_medico",str_medico)

            q = "tipo_usuario(X,Y)"

            rq_3 = pyDatalog.ask(q)

            arr_resp = [
                rq_3.answers[0][0],
                rq_3.answers[0][1]
            ]

            return arr_resp
        except:
            print("error")
Пример #14
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def __listarPalabrasComunesIdiomas(_idiomaA, _idiomaB):
    # Listar todas las palabras comunes entre dos idiomas
    consulta = ask('palabrasComunes(' + _idiomaA + ', ' + _idiomaB + ', R1)')
    if (consulta):
        return consulta.answers
    else:
        return "No hubo coincidencia."
Пример #15
0
def queen(thread_name):
    n = int(random.random() * 8) + 1 # 1 to 8
    Logic()
    
    queens(X0)                      <= (X0._in(range(n)))
    queens(X0,X1)                   <= queens(X0)                   & next_queen(X0,X1)
    queens(X0,X1,X2)                <= queens(X0,X1)                & next_queen(X0,X1,X2)
    queens(X0,X1,X2,X3)             <= queens(X0,X1,X2)             & next_queen(X0,X1,X2,X3)
    queens(X0,X1,X2,X3,X4)          <= queens(X0,X1,X2,X3)          & next_queen(X0,X1,X2,X3,X4)
    queens(X0,X1,X2,X3,X4,X5)       <= queens(X0,X1,X2,X3,X4)       & next_queen(X0,X1,X2,X3,X4,X5)
    queens(X0,X1,X2,X3,X4,X5,X6)    <= queens(X0,X1,X2,X3,X4,X5)    & next_queen(X0,X1,X2,X3,X4,X5,X6)
    queens(X0,X1,X2,X3,X4,X5,X6,X7) <= queens(X0,X1,X2,X3,X4,X5,X6) & next_queen(X0,X1,X2,X3,X4,X5,X6,X7)
    
    next_queen(X0,X1)                   <= queens(X1)                       & ok(X0,1,X1)
    next_queen(X0,X1,X2)                <= next_queen(X1,X2)                & ok(X0,2,X2)
    next_queen(X0,X1,X2,X3)             <= next_queen(X1,X2,X3)             & ok(X0,3,X3)
    next_queen(X0,X1,X2,X3,X4)          <= next_queen(X1,X2,X3,X4)          & ok(X0,4,X4)
    next_queen(X0,X1,X2,X3,X4,X5)       <= next_queen(X1,X2,X3,X4,X5)       & ok(X0,5,X5)
    next_queen(X0,X1,X2,X3,X4,X5,X6)    <= next_queen(X1,X2,X3,X4,X5,X6)    & ok(X0,6,X6)
    next_queen(X0,X1,X2,X3,X4,X5,X6,X7) <= next_queen(X1,X2,X3,X4,X5,X6,X7) & ok(X0,7,X7)
    
    query = pyDatalog.ask("queens(%s)" % (",".join("X%s" % i for i in range(n))))
    answers = query.answers if query else [] 
    result = "OK" if len(answers) == [1,0,0,2,10,4,40,92][n-1] else "* not OK ! *"
    print("%s : n = %d %s " % (thread_name, n, result))
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])
Пример #17
0
def __palabrasEnUnIdiomaOriginadasPorPalabra(_palabra, _idioma):
    #Obtener el conjunto de todas las palabras en un idioma originadas por una palabra específica
    consulta = ask('hijosIdioma(' + _palabra + ',' + _idioma + ', R)')
    if (consulta):
        return consulta.answers
    else:
        return "No se obtuvo coincidencias"
Пример #18
0
def __idiomasRelacionadosPalabra(_palabra):
    # Listar los idiomas relacionados con una palabra
    consulta = ask('_soloIdiomas(' + _palabra + ', R)')
    if (consulta):
        return consulta.answers
    else:
        return "No hay idiomas relacionados"
Пример #19
0
def __numeroPalabrasComunesIdiomas(_idiomaA, _idiomaB):
	# Contar todas las palabras comunes entre dos idiomas
	consulta = ask('contarPalabrasComunes('+_idiomaA+', '+_idiomaB+', R1)')
	if (consulta):
		return consulta.answers[0][0][0]
	else:
		return 0
Пример #20
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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'))
Пример #21
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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
Пример #22
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def __esHija(_idiomaHijo, _hijo, _idiomaPadre, _padre):
    # Determinar si una palabra es hij@ de otra
    if (ask('esHijo(' + _idiomaHijo + ',' + _hijo + ',' + _idiomaPadre + ',' +
            _padre + ', R)')):
        return "Sí es hija"
    else:
        return "No es hija"
Пример #23
0
def __sonPrimas(_idiomaA, _nombreA, _idiomaB, _nombreB):
    # Determinar si dos palabras son prim@s
    if (ask('sonPrimas(' + _idiomaA + ',' + _nombreA + ',' + _idiomaB + ',' +
            _nombreB + ')')):
        return "Son primas"
    else:
        return "No son primas"
Пример #24
0
def connectionsAnswer():
    connectionsAnswer = pyDatalog.ask('networkConnectsTo(ServiceA,ServiceB,C*K,IOK,AOK)')
    if connectionsAnswer == None:
        connections = []
    else:
        connections = connectionsAnswer.answers
    return connections
Пример #25
0
def check_logic(thread_name, n):
    query = pyDatalog.ask("queens(%s)" % (",".join("X%s" % i
                                                   for i in range(n))))
    answers = query.answers if query else []
    result = "OK" if len(answers) == [1, 0, 0, 2, 10, 4, 40, 92
                                      ][n - 1] else answers
    print("%s : n = %d %s " % (thread_name, n, result))
Пример #26
0
def __esTia(_idiomaTio, _tio, _idiomaSobrino, _sobrino):
    # Determinar si una palabra es tí@
    if (ask('esTio(' + _idiomaTio + ',' + _tio + ',' + _idiomaSobrino + ',' +
            _sobrino + ', R)')):
        return "Sí es tía"
    else:
        return "No es tía"
Пример #27
0
def __listarIdiomasAportaronOtro(_idioma):
    # LIstar todos los idiomas que aportaron a otro. Similar al anterior pero debe incluir porcentaje para todos los idiomas
    consulta = ask('contribucionXidioma(' + _idioma + ', R1, R2)')
    if (consulta):
        return consulta.answers
    else:
        return "Ninguno"
Пример #28
0
def __gradoPrimas(_nombreA, _nombreB):
    # Determina si son primas y en qué grado
    consulta = ask('gradoPrimos(' + _nombreA + ',' + _nombreB + ', R)')
    if (consulta):
        return "Son primas", consulta.answers[0][0]
    else:
        return "No son primas", 0
Пример #29
0
def __idiomaMasAporto(_idioma):
    # Idioma que más aportó a otro (e.g. latín a español). Medir basado en porcentaje
    consulta = ask('__mayorContribucion(' + _idioma + ', R1)')
    if (consulta):
        return consulta.answers[0][0]
    else:
        return "Ninguno"
Пример #30
0
def designOfExperiment(possibleCompromises,riskDict,debug=True):
    query = "networkConnectsTo(SourceService,TargetService,C*K,IOK,AOK)"
    components = pyDatalog.ask(query).answers
    getService0 = itemgetter(0)
    getService1 = itemgetter(1)
    componentsList = list(map(getService0,iter(components)))
    componentsList2 = list(map(getService1,iter(components)))
    componentsList.extend(componentsList2)
    componentsList = list(set(componentsList))
    #pprint.pprint(componentsList)
    compromisedComponents = list(map(getService0,iter(possibleCompromises)))
    possibleCompromisesDict = dict(possibleCompromises)
    ledger = []
    #pprint.pprint(compromisedComponents)
    #print(possibleCompromisesDict.get("internet"))
    #sumComponentUtilCompromised = 0
    #sumComponentUtilUncompromised = 0
    for component in componentsList:
        newPossibleCompromises = possibleCompromisesDict
        newPossibleCompromises[component] = 1.0
        componentUtilCompromised = 1.0 #For code development only
        #componentUtilCompromised = determineResidualUtility(newPossibleCompromises,riskDict,True)
        newPossibleCompromises = possibleCompromisesDict
        if component in compromisedComponents:
            del newPossibleCompromises[component]
        componentUtilUncompromised = 0.0 #For code development only
        #componentUtilUncompromised = determineResidualUtility(newPossibleCompromises,riskDict,True)
        ledger.append([component,componentUtilCompromised,componentUtilUncompromised])
    pprint.pprint(ledger)
Пример #31
0
def __sonHermanos(_idiomaA, _nombreA, _idiomaB, _nombreB):
    # Determinar si dos palabras son heman@s
    if (ask('sonHermanos(' + _idiomaA + ',' + _nombreA + ',' + _idiomaB + ',' +
            _nombreB + ', R)')):
        return "Son hermanas"
    else:
        return "No son hermanas"
Пример #32
0
def executeQuery(query, console):
    result = pyDatalog.ask(query)
    console.print("|--------------------Query---------------------\n|", query)
    console.print("|--------------------Result--------------------\n|", result)

    if result == None:
        return False
    return True
Пример #33
0
def retractAll(pname, arity):
  """
  retract all facts of given predicate name and arity from the LogKB.
  """
  vnames  = ["V" + str(x) for x in range(0,arity)]
  varlist = "(" + ",".join(vnames) + ")"
  query = pname + varlist
  ans = pyDatalog.ask(query)
  for r in ans.answers:
    pyDatalog.retract_fact(pname,*list(r))
Пример #34
0
def __idiomasRelacionadosPalabra(_palabra):
    # Listar los idiomas relacionados con una palabra
    consulta = ask('_soloIdiomas(' + _palabra + ', R)')
    if (consulta):
        words = []
        for r in consulta.answers:
            words.append(r[0])
        return words
    else:
        return "No hay idiomas relacionados"
Пример #35
0
def findall2(S,L):
  """
  Hackish PROLOG findall emulation.
  use cases: findall(C,V) -> Given a query String in S, ask the LogKB and resolve to a list of results in L.
  """
  if (S.is_const() and not L.is_const()):
    result = pyDatalog.ask(S.id).answers
    result.sort()
    yield (S,tuple(result))
  else:
    raise Exception("unhandled case in findall: {0},{1}".format(S.is_const(),L.is_const()))
Пример #36
0
 def analize_user(self, user, prediction):
     actions = []
     self.__assert_user(user, prediction)
     
     if ask('accept("{}")'.format(str(user.id))) != None:
         actions.append('Accept')
     else:
         actions.append('Reject')
         
     #if ask('log("{}")'.format(str(user.id))) != None:
     #    actions.append('Log')
         
     return actions
Пример #37
0
    def ask_predicate(self, predicate):
        """
        Queries PyDataLog for the given predicate by constructing a query fitting the pyDataLog Syntax.

        :param predicate: The predicate to be quried for
        :return: The Value of the given predicate if it exists in the Database, None otherwise.
        """
        query = predicate.name + "("
        query += ','.join([str(a) if not isinstance(a, Symbol) else "\'" + str(a) + "\'" \
                           for a in predicate.args])
        query += ", X)"
        answer = pyDatalog.ask(query)

        if answer is None:
            return None
        return self.transform_answer(answer.answers)
Пример #38
0
    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)
Пример #39
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)]

    """
Пример #40
0
def check_logic(thread_name, n):
    query = pyDatalog.ask("queens(%s)" % (",".join("X%s" % i for i in range(n))))
    answers = query.answers if query else [] 
    result = "OK" if len(answers) == [1,0,0,2,10,4,40,92][n-1] else answers
    print("%s : n = %d %s " % (thread_name, n, result))
Пример #41
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')])