How to use generate_instance method in localstack

Best Python code snippet using localstack_python

test_dependant_methods.py

Source:test_dependant_methods.py

...7    seq.append(data)8    return val9class TestDependantMethods(TestCase):10    @staticmethod11    def generate_instance(methods, dependencies):12        class Class(object):13            __metaclass__ = dm.ForcedDepends14            stage_depends = dict(dependencies)15            locals().update(methods.iteritems())16        return Class()17    def test_no_dependant_methods(self):18        self.assertTrue(self.generate_instance({}, {}))19    def test_return_checking(self):20        results = []21        o = self.generate_instance(22            dict((str(x), currying.post_curry(func, results, x))23                 for x in range(10)),24            dict((str(x), str(x - 1)) for x in xrange(1, 10)))25        getattr(o, "9")()26        self.assertEqual(results, range(10))27        results = []28        o = self.generate_instance(29            dict((str(x), currying.post_curry(func, results, x, False))30                 for x in range(10)),31            dict((str(x), str(x - 1)) for x in xrange(1, 10)))32        getattr(o, "9")()33        self.assertEqual(results, [0])34        getattr(o, "9")()35        self.assertEqual(results, [0, 0])36    def test_stage_awareness(self):37        results = []38        o = self.generate_instance(39            dict((str(x), currying.post_curry(func, results, x))40                 for x in range(10)),41            dict((str(x), str(x - 1)) for x in xrange(1, 10)))42        getattr(o, "1")()43        self.assertEqual(results, [0, 1])44        getattr(o, "2")()45        self.assertEqual(results, [0, 1, 2])46        getattr(o, "2")()47        self.assertEqual(results, [0, 1, 2])48        o.__set_stage_state__(["0", "1"])49        l = []50        o.__stage_step_callback__ = l.append51        getattr(o, "2")()52        self.assertEqual(results, [0, 1, 2, 2])53        self.assertEqual(l, ["2"])54    def test_stage_depends(self):55        results = []56        methods = dict((str(x), currying.post_curry(func, results, x))57                       for x in range(10))58        deps = dict((str(x), str(x - 1)) for x in xrange(1, 10))59        deps["1"] = ["0", "a"]60        methods["a"] = currying.post_curry(func, results, "a")61        o = self.generate_instance(methods, deps)62        getattr(o, "1")()63        self.assertEqual(results, [0, "a", 1])64        getattr(o, "2")()65        self.assertEqual(results, [0, "a", 1, 2])66    def test_ignore_deps(self):67        results = []68        o = self.generate_instance(69            dict((str(x), currying.post_curry(func, results, x))70                 for x in range(10)),71            dict((str(x), str(x - 1)) for x in xrange(1, 10)))72        getattr(o, '2')(ignore_deps=True)73        self.assertEqual([2], results)74    def test_no_deps(self):75        results = []76        o = self.generate_instance(77            dict((str(x), currying.post_curry(func, results, x))78                 for x in range(10)),79            {})80        getattr(o, '2')()...

generate_instance.py

Source:generate_instance.py

...7sigma = variance to be used in the normal distribution while generating an instance.8The function returns an instance of the airplane refueling problem as a list of 2-tuples.9"""10import numpy as np11def generate_instance(n, sigma, seed):12    np.random.seed(seed)13    p = list(np.random.randint(1,101,n))14    instance = []15    for i in p:16        instance.append((i,2**(np.random.normal(0,sigma))*i)) # consumption rate & volume17    return instance18#S119n_S1 = list(range(14))20S1 = []21for i in range(14):22    n_S1[i] = (n_S1[i]+1)*1023    S1.append([])24sigma_S1 = 0.125for i in range(len(n_S1)):26    for j in range(50):27        instance = generate_instance(n_S1[i],sigma_S1,j*n_S1[i])28        S1[i].append(instance)29print("endS1")30        31#sigma of S2 and S3       32sig = 0.133Sigma = []34while sig <=1:35    Sigma.append(sig)36    sig += 0.00137#S238size = {100,500,1000,2000,3000}39S2_100, S2_500, S2_1000, S2_2000, S2_3000 = [], [], [], [], []40for i in range(len(Sigma)):41    for j in range(1,6):42        instance = generate_instance(100,Sigma[i],int(j*1000*Sigma[i]))43        S2_100.append(instance)44print("end1")45for i in range(len(Sigma)):46    for j in range(1,6):47        instance = generate_instance(500,Sigma[i],int(j*5000*Sigma[i]))48        S2_500.append(instance)49print("end2")50for i in range(len(Sigma)):51    for j in range(1,6):52        instance = generate_instance(1000,Sigma[i],int(j*10000*Sigma[i]))53        S2_1000.append(instance)54print("end3")55        56for i in range(len(Sigma)):57    for j in range(1,6):58        instance = generate_instance(2000,Sigma[i],int(j*20000*Sigma[i]))59        S2_2000.append(instance)60print("end4")61for i in range(len(Sigma)):62    for j in range(1,6):63        instance = generate_instance(3000,Sigma[i],int(j*30000*Sigma[i]))64        S2_3000.append(instance)65print("end5")66        67#S368size_S3 = 50069S3 = [] 70for i in range(len(Sigma)):71    for j in range(1,6):72        instance = generate_instance(500,Sigma[i],int(j*50000*Sigma[i]))73        S3.append(instance)...

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