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How to use test_normal method in green

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preprocess-ten-folds.py

Source:preprocess-ten-folds.py

1#!/usr/bin/python2# encoding: utf-83'''4Created on May 26, 20165@author: yanruibo6'''7import os8import random9from ast import MultiTree10import numpy as np11import json12def serialize_list(list_content, filename):13    fw = open(filename, 'w')14    for item in list_content:15        fw.write(item + "\n")16    fw.flush()17    fw.close()18    19def get_list_from_file(filename):20    fr = open(filename, 'r')21    lines = fr.readlines()22    lines = [line.strip() for line in lines]23    fr.close()24    ret_lines = []25    for line in lines:26        if(line != ""):27            ret_lines.append(line)28    return ret_lines29def generate_dataset():30    normal_feature_vector_dir = "./all-feature-vector/normal/"31    normal_packagenames = os.listdir(normal_feature_vector_dir)32    vulnerable_feature_vector_dir = "./all-feature-vector/vulnerable/"33    vulnerable_packagenames = os.listdir(vulnerable_feature_vector_dir)34    35    train_normal = random.sample(normal_packagenames, len(normal_packagenames) / 2)36    test_normal = list(set(normal_packagenames) - set(train_normal))37    train_vulnerable = random.sample(vulnerable_packagenames, len(vulnerable_packagenames) / 2)38    test_vulnerable = list(set(vulnerable_packagenames) - set(train_vulnerable))39    40    serialize_list(train_normal, "./dataset/train_normal")41    serialize_list(test_normal, "./dataset/test_normal")42    serialize_list(train_vulnerable, "./dataset/train_vulnerable")43    serialize_list(test_vulnerable, "./dataset/test_vulnerable")44    45    46def generate_dataset_ten_fold():47    normal_feature_vector_dir = "./all-feature-vector/normal/"48    normal_packagenames = os.listdir(normal_feature_vector_dir)49    vulnerable_feature_vector_dir = "./all-feature-vector/vulnerable/"50    vulnerable_packagenames = os.listdir(vulnerable_feature_vector_dir)51    normal_ten_percent = len(normal_packagenames) / 1052    vulnerable_ten_percent = len(vulnerable_packagenames) / 1053    normal_begin_pos = 054    vulnerable_begin_pos = 055    for i in range(10):56        if i == 9:57            test_normal = normal_packagenames[normal_begin_pos + i * normal_ten_percent:]58            train_normal = list(set(normal_packagenames) - set(test_normal))59            test_vulnerable = vulnerable_packagenames[vulnerable_begin_pos + i * vulnerable_ten_percent:]60            train_vulnerable = list(set(vulnerable_packagenames) - set(test_vulnerable))61            serialize_list(train_normal, "./dataset/train_normal" + str(i))62            serialize_list(test_normal, "./dataset/test_normal" + str(i))63            serialize_list(train_vulnerable, "./dataset/train_vulnerable" + str(i))64            serialize_list(test_vulnerable, "./dataset/test_vulnerable" + str(i))65        66        else:67            test_normal = normal_packagenames[normal_begin_pos + i * normal_ten_percent:normal_begin_pos + (i + 1) * normal_ten_percent]68            train_normal = list(set(normal_packagenames) - set(test_normal))69            test_vulnerable = vulnerable_packagenames[vulnerable_begin_pos + i * vulnerable_ten_percent:vulnerable_begin_pos + (i + 1) * vulnerable_ten_percent]70            train_vulnerable = list(set(vulnerable_packagenames) - set(test_vulnerable))71            serialize_list(train_normal, "./dataset/train_normal" + str(i))72            serialize_list(test_normal, "./dataset/test_normal" + str(i))73            serialize_list(train_vulnerable, "./dataset/train_vulnerable" + str(i))74            serialize_list(test_vulnerable, "./dataset/test_vulnerable" + str(i))75    76def feature_select(i, method, k=400):77    78    features = get_list_from_file("./all_ngrams/all_ngrams")79    train_normal = get_list_from_file("./dataset/train_normal" + str(i))80    # test_normal = get_list_from_file("./dataset/test_normal"+str(i))81    train_vulnerable = get_list_from_file("./dataset/train_vulnerable" + str(i))82    # test_vulnerable = get_list_from_file("./dataset/test_vulnerable"+str(i))83    normal_feature_vector_dir = "./all-feature-vector/normal/"84    vulnerable_feature_vector_dir = "./all-feature-vector/vulnerable/"85    86    trainX = []87    trainY = []88    for packagename in train_normal:89        one_vector = np.loadtxt(fname=normal_feature_vector_dir + packagename, dtype=np.int)90        trainX.append(one_vector)91        trainY.append(0)92    for packagename in train_vulnerable:93        one_vector = np.loadtxt(fname=vulnerable_feature_vector_dir + packagename, dtype=np.int)94        trainX.append(one_vector)95        trainY.append(1)96    trainX = np.array(trainX)97    trainY = np.array(trainY)98    dataSet = np.c_[trainX, trainY]99    100    if(method == "infogain"):101        from TextAnalysisInfoGain2 import IG102        dataSet = dataSet.tolist()103        best_feature_indexes, selected_data = IG(dataSet, k)104        best_features = [features[index] for index in best_feature_indexes]105        serialize_list(best_features, "./selected-features/infogain" + str(i))106        np.savetxt("./selected-features/train_infogain.dat" + str(i), X=selected_data, fmt="%d", delimiter=',', newline='\n')107        return best_features, selected_data108    elif(method == "chi"):109        from TextAnalysisChi import chi110        best_feature_indexes, selected_data = chi(dataSet, k)111        best_features = [features[index] for index in best_feature_indexes]112        serialize_list(best_features, "./selected-features/chi" + str(i))113        np.savetxt("./selected-features/train_chi.dat" + str(i), X=selected_data, fmt="%d", delimiter=',', newline='\n')114        return best_features, selected_data115    elif(method == "df"):116        from TextAnalysisDF import df117        best_feature_indexes, selected_data = df(dataSet, k)118        best_features = [features[index] for index in best_feature_indexes]119        serialize_list(best_features, "./selected-features/df" + str(i))120        np.savetxt("./selected-features/train_df.dat" + str(i), X=selected_data, fmt="%d", delimiter=',', newline='\n')121        return best_features, selected_data122        123    124def test_feature_selection_infogain(i):125    '''126    import time127    startTimeStamp = time.time()128    best_features, selected_data = feature_select(i,"infogain")129    130    endTimeStamp = time.time()131    total_time = endTimeStamp - startTimeStamp132    ft = open("log_time_feature_selection_infogain_" + str(endTimeStamp), "w")133    ft.write("Total Time : " + str(total_time) + "\n")134    ft.close()135    '''136    best_features, selected_data = feature_select(i, "infogain")137    return best_features, selected_data138def test_feature_selection_chi(i):139    '''140    import time141    startTimeStamp = time.time()142    best_features, selected_data = feature_select(i,"chi")143    144    endTimeStamp = time.time()145    total_time = endTimeStamp - startTimeStamp146    ft = open("log_time_feature_selection_chi_" + str(endTimeStamp), "w")147    ft.write("Total Time : " + str(total_time) + "\n")148    ft.close()149    '''150    best_features, selected_data = feature_select(i, "chi")151    return best_features, selected_data152def test_feature_selection_df(i):153    '''154    import time155    startTimeStamp = time.time()156    best_features, selected_data = feature_select(i,"chi")157    158    endTimeStamp = time.time()159    total_time = endTimeStamp - startTimeStamp160    ft = open("log_time_feature_selection_chi_" + str(endTimeStamp), "w")161    ft.write("Total Time : " + str(total_time) + "\n")162    ft.close()163    '''164    best_features, selected_data = feature_select(i, "df")165    return best_features, selected_data166# contains feature selection167def generate_matrix_infogain(i):168    # feature selection169    best_features, selected_data = test_feature_selection_infogain(i)170    print "feature selection done!"171#     import time172#     startTimeStamp = time.time()173    174    train_normal = get_list_from_file("./dataset/train_normal" + str(i))175    test_normal = get_list_from_file("./dataset/test_normal" + str(i))176    train_vulnerable = get_list_from_file("./dataset/train_vulnerable" + str(i))177    test_vulnerable = get_list_from_file("./dataset/test_vulnerable" + str(i))178    print "get dataset end!"179    180    selected_ngrams = best_features181    train_added_columns = []182    normal_js_dir_suffix = "./js/normal/"183    vulnerable_js_dir_suffix = "./js/vulnerable/"184    count = 0185    trainY = []186    for packagename in train_normal:187        js_dir = normal_js_dir_suffix + packagename + ".js"188        print count, js_dir189        count += 1190        json_str = os.popen('node analyze.js ' + js_dir).read()191        py_dict = json.loads(json_str)192        tree = MultiTree(py_dict)193        one_vector = []194        one_vector.append(tree.get_max_width())195        one_vector.append(tree.get_max_depth())196        train_added_columns.append(one_vector)197        trainY.append(0)198    for packagename in train_vulnerable:199        js_dir = vulnerable_js_dir_suffix + packagename + ".js"200        print count, js_dir201        count += 1202        json_str = os.popen('node analyze.js ' + js_dir).read()203        py_dict = json.loads(json_str)204        tree = MultiTree(py_dict)205        one_vector = []206        one_vector.append(tree.get_max_width())207        one_vector.append(tree.get_max_depth())208        train_added_columns.append(one_vector)209        trainY.append(1)210    train_added_columns = np.array(train_added_columns)211    train_matrix = np.c_[selected_data, train_added_columns]212    train_matrix = np.c_[train_matrix, trainY]213    np.savetxt("./train-test-matrix/train_infogain.dat" + str(i), X=train_matrix, fmt="%d", delimiter=',', newline='\n')214    print "generate train matrix done!"215    216    test_matrix = []217    normal_ngrams_dir = "./ngrams/normal/"218    vulnerable_ngrams_dir = "./ngrams/vulnerable/"219    for packagename in test_normal:220        test_vector = []221        one_list = get_list_from_file(normal_ngrams_dir + packagename)222        for gram in selected_ngrams:223            test_vector.append(one_list.count(gram))224        js_dir = normal_js_dir_suffix + packagename + ".js"225        print count, js_dir226        count += 1227        json_str = os.popen('node analyze.js ' + js_dir).read()228        py_dict = json.loads(json_str)229        tree = MultiTree(py_dict)        230        test_vector.append(tree.get_max_width())231        test_vector.append(tree.get_max_depth())232        test_vector.append(0)    233        test_matrix.append(test_vector)234    235    for packagename in test_vulnerable:236        test_vector = []237        one_list = get_list_from_file(vulnerable_ngrams_dir + packagename)238        for gram in selected_ngrams:239            test_vector.append(one_list.count(gram))240        241        js_dir = vulnerable_js_dir_suffix + packagename + ".js"242        print count, js_dir243        count += 1244        json_str = os.popen('node analyze.js ' + js_dir).read()245        py_dict = json.loads(json_str)246        tree = MultiTree(py_dict)        247        test_vector.append(tree.get_max_width())248        test_vector.append(tree.get_max_depth())249        test_vector.append(1)    250        test_matrix.append(test_vector)251    252    test_matrix = np.array(test_matrix)253    np.savetxt("./train-test-matrix/test_infogain.dat" + str(i), X=test_matrix, fmt="%d", delimiter=',', newline='\n')254    print "generate test matrix done!"255    256    257#     endTimeStamp = time.time()258#     total_time = endTimeStamp - startTimeStamp259#     ft = open("log_time_generate_matrix_infogain_" + str(endTimeStamp), "w")260#     ft.write("Total Time : " + str(total_time) + "\n")261#     ft.close()262    263    264# contains feature selection265def generate_matrix_chi(i):266    # feature selection267    best_features, selected_data = test_feature_selection_chi(i)268    print "feature selection done!"269#     import time270#     startTimeStamp = time.time()271    272    train_normal = get_list_from_file("./dataset/train_normal" + str(i))273    test_normal = get_list_from_file("./dataset/test_normal" + str(i))274    train_vulnerable = get_list_from_file("./dataset/train_vulnerable" + str(i))275    test_vulnerable = get_list_from_file("./dataset/test_vulnerable" + str(i))276    print "get dataset end!"277    278    selected_ngrams = best_features279    train_added_columns = []280    normal_js_dir_suffix = "./js/normal/"281    vulnerable_js_dir_suffix = "./js/vulnerable/"282    count = 0283    trainY = []284    for packagename in train_normal:285        js_dir = normal_js_dir_suffix + packagename + ".js"286        print count, js_dir287        count += 1288        json_str = os.popen('node analyze.js ' + js_dir).read()289        py_dict = json.loads(json_str)290        tree = MultiTree(py_dict)291        one_vector = []292        one_vector.append(tree.get_max_width())293        one_vector.append(tree.get_max_depth())294        train_added_columns.append(one_vector)295        trainY.append(0)296    for packagename in train_vulnerable:297        js_dir = vulnerable_js_dir_suffix + packagename + ".js"298        print count, js_dir299        count += 1300        json_str = os.popen('node analyze.js ' + js_dir).read()301        py_dict = json.loads(json_str)302        tree = MultiTree(py_dict)303        one_vector = []304        one_vector.append(tree.get_max_width())305        one_vector.append(tree.get_max_depth())306        train_added_columns.append(one_vector)307        trainY.append(1)308    train_added_columns = np.array(train_added_columns)309    train_matrix = np.c_[selected_data, train_added_columns]310    train_matrix = np.c_[train_matrix, trainY]311    np.savetxt("./train-test-matrix/train_chi.dat" + str(i), X=train_matrix, fmt="%d", delimiter=',', newline='\n')312    print "generate train matrix done!"313    314    test_matrix = []315    normal_ngrams_dir = "./ngrams/normal/"316    vulnerable_ngrams_dir = "./ngrams/vulnerable/"317    for packagename in test_normal:318        test_vector = []319        one_list = get_list_from_file(normal_ngrams_dir + packagename)320        for gram in selected_ngrams:321            test_vector.append(one_list.count(gram))322        js_dir = normal_js_dir_suffix + packagename + ".js"323        print count, js_dir324        count += 1325        json_str = os.popen('node analyze.js ' + js_dir).read()326        py_dict = json.loads(json_str)327        tree = MultiTree(py_dict)        328        test_vector.append(tree.get_max_width())329        test_vector.append(tree.get_max_depth())330        test_vector.append(0)    331        test_matrix.append(test_vector)332    333    for packagename in test_vulnerable:334        test_vector = []335        one_list = get_list_from_file(vulnerable_ngrams_dir + packagename)336        for gram in selected_ngrams:337            test_vector.append(one_list.count(gram))338        339        js_dir = vulnerable_js_dir_suffix + packagename + ".js"340        print count, js_dir341        count += 1342        json_str = os.popen('node analyze.js ' + js_dir).read()343        py_dict = json.loads(json_str)344        tree = MultiTree(py_dict)        345        test_vector.append(tree.get_max_width())346        test_vector.append(tree.get_max_depth())347        test_vector.append(1)    348        test_matrix.append(test_vector)349    350    test_matrix = np.array(test_matrix)351    np.savetxt("./train-test-matrix/test_chi.dat" + str(i), X=test_matrix, fmt="%d", delimiter=',', newline='\n')352    print "generate test matrix done!"353    354    355#     endTimeStamp = time.time()356#     total_time = endTimeStamp - startTimeStamp357#     ft = open("log_time_generate_matrix_infogain_" + str(endTimeStamp), "w")358#     ft.write("Total Time : " + str(total_time) + "\n")359#     ft.close()360    361# contains feature selection362def generate_matrix_df(i):363    # feature selection364    best_features, selected_data = test_feature_selection_df(i)365    print "feature selection done!"366#     import time367#     startTimeStamp = time.time()368    369    train_normal = get_list_from_file("./dataset/train_normal" + str(i))370    test_normal = get_list_from_file("./dataset/test_normal" + str(i))371    train_vulnerable = get_list_from_file("./dataset/train_vulnerable" + str(i))372    test_vulnerable = get_list_from_file("./dataset/test_vulnerable" + str(i))373    print "get dataset end!"374    375    selected_ngrams = best_features376    train_added_columns = []377    normal_js_dir_suffix = "./js/normal/"378    vulnerable_js_dir_suffix = "./js/vulnerable/"379    count = 0380    trainY = []381    for packagename in train_normal:382        js_dir = normal_js_dir_suffix + packagename + ".js"383        print count, js_dir384        count += 1385        json_str = os.popen('node analyze.js ' + js_dir).read()386        py_dict = json.loads(json_str)387        tree = MultiTree(py_dict)388        one_vector = []389        one_vector.append(tree.get_max_width())390        one_vector.append(tree.get_max_depth())391        train_added_columns.append(one_vector)392        trainY.append(0)393    for packagename in train_vulnerable:394        js_dir = vulnerable_js_dir_suffix + packagename + ".js"395        print count, js_dir396        count += 1397        json_str = os.popen('node analyze.js ' + js_dir).read()398        py_dict = json.loads(json_str)399        tree = MultiTree(py_dict)400        one_vector = []401        one_vector.append(tree.get_max_width())402        one_vector.append(tree.get_max_depth())403        train_added_columns.append(one_vector)404        trainY.append(1)405    train_added_columns = np.array(train_added_columns)406    train_matrix = np.c_[selected_data, train_added_columns]407    train_matrix = np.c_[train_matrix, trainY]408    np.savetxt("./train-test-matrix/train_df.dat" + str(i), X=train_matrix, fmt="%d", delimiter=',', newline='\n')409    print "generate train matrix done!"410    411    test_matrix = []412    normal_ngrams_dir = "./ngrams/normal/"413    vulnerable_ngrams_dir = "./ngrams/vulnerable/"414    for packagename in test_normal:415        test_vector = []416        one_list = get_list_from_file(normal_ngrams_dir + packagename)417        for gram in selected_ngrams:418            test_vector.append(one_list.count(gram))419        js_dir = normal_js_dir_suffix + packagename + ".js"420        print count, js_dir421        count += 1422        json_str = os.popen('node analyze.js ' + js_dir).read()423        py_dict = json.loads(json_str)424        tree = MultiTree(py_dict)        425        test_vector.append(tree.get_max_width())426        test_vector.append(tree.get_max_depth())427        test_vector.append(0)    428        test_matrix.append(test_vector)429    430    for packagename in test_vulnerable:431        test_vector = []432        one_list = get_list_from_file(vulnerable_ngrams_dir + packagename)433        for gram in selected_ngrams:434            test_vector.append(one_list.count(gram))435        436        js_dir = vulnerable_js_dir_suffix + packagename + ".js"437        print count, js_dir438        count += 1439        json_str = os.popen('node analyze.js ' + js_dir).read()440        py_dict = json.loads(json_str)441        tree = MultiTree(py_dict)        442        test_vector.append(tree.get_max_width())443        test_vector.append(tree.get_max_depth())444        test_vector.append(1)    445        test_matrix.append(test_vector)446    447    test_matrix = np.array(test_matrix)448    np.savetxt("./train-test-matrix/test_df.dat" + str(i), X=test_matrix, fmt="%d", delimiter=',', newline='\n')449    print "generate test matrix done!"450    451    452    453    454def generate_matrix_infogain_ten():455    for i in range(10):456        generate_matrix_infogain(i)457def generate_matrix_chi_ten():458    for i in range(10):459        generate_matrix_chi(i)460        461def generate_matrix_df_ten():462    for i in range(10):463        generate_matrix_df(i)464if __name__ == '__main__':465    # generate_dataset_ten_fold()466    # generate_matrix_infogain_ten()467    #generate_matrix_chi_ten()468    generate_matrix_df_ten()...

test_TIterator.py

Source:test_TIterator.py

...15    name: str16    ruby: TOption[str]17    address: TOption[Address]18class TestToCsv:19    def test_normal(self):20        d = Human.from_iterable_dicts(21            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]22        )23        assert (24            d.to_csv(["id", "name", "ruby"])25            == """261,ä¸é,272,äºé,ããã28""".lstrip()29        )30        assert d.to_csv(["id", "name", "ruby"]) == ""31    def test_ignore_extra_params(self):32        d = Human.from_iterable_dicts(33            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]34        )35        assert (36            d.to_csv(["id", "name"])37            == """381,ä¸é392,äºé40""".lstrip()41        )42        assert d.to_csv(["id", "name"]) == ""43    def test_with_header(self):44        d = Human.from_iterable_dicts(45            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]46        )47        assert (48            d.to_csv(["id", "name", "ruby"], with_header=True)49            == """50id,name,ruby511,ä¸é,522,äºé,ããã53""".lstrip()54        )55        assert (56            d.to_csv(["id", "name", "ruby"], with_header=True)57            == """58id,name,ruby59""".lstrip()60        )61    def test_with_space(self):62        d = Human.from_iterable_dicts(63            [{"id": 1, "name": " ä¸ é "}, {"id": 2, "name": " äº é ", "ruby": "ããã"}]64        )65        assert (66            d.to_csv(["id", "name", "ruby"])67            == """681, ä¸ é ,692, äº é ,ããã70""".lstrip()71        )72        assert d.to_csv(["id", "name", "ruby"]) == ""73    def test_crlf(self):74        d = Human.from_iterable_dicts(75            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]76        )77        assert (78            d.to_csv(["id", "name", "ruby"], crlf=True)79            == """801,ä¸é,\r812,äºé,ããã\r82""".lstrip()83        )84        assert d.to_csv(["id", "name", "ruby"], crlf=True) == ""85    def test_tsv(self):86        d = Human.from_iterable_dicts(87            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]88        )89        assert (90            d.to_csv(["id", "name", "ruby"], tsv=True)91            == """921\tä¸é\t932\täºé\tããã94""".lstrip()95        )96        assert d.to_csv(["id", "name", "ruby"], tsv=True) == ""97    def test_including_dict(self):98        d = Human.from_iterable_dicts(99            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "address": {"name": "ä½æ"}}]100        )101        assert (102            d.to_csv(["id", "name", "address"])103            == """1041,ä¸é,1052,äºé,{'name': 'ä½æ'}106""".lstrip()107        )108        assert d.to_csv(["id", "name", "address"]) == ""109    def test_including_list(self):110        d = Spot.from_iterable_dicts(111            [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]112        )113        assert (114            d.to_csv(["names", "address"])115            == """116['spot1'],{'name': 'address1'}117"['spot21','spot22']",118""".lstrip()119        )120        assert d.to_csv(["names", "address"]) == ""121class TestToCsvf:122    """123    Requirements: `from_csvf_to_iterator` are fine124    """125    def test_normal(self, tmpdir):126        origin = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]127        it: TIterator[Human] = Human.from_iterable_dicts(origin)128        fpath = os.path.join(tmpdir.mkdir("tmp").strpath, "test.csv")129        assert (130            it.to_csvf(131                fpath, fieldnames=["name", "id", "ruby"], encoding="euc-jp", with_header=False132            )133            == fpath134        )135        assert (136            Human.from_csvf_to_iterator(137                fpath, fieldnames=["name", "id", "ruby"], encoding="euc-jp"138            ).to_dicts()139            == origin140        )141class TestNextAt:142    def test_normal(self):143        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]144        assert Spot.from_iterable_dicts(d).next_at(1).get().to_dict() == {145            "names": ["spot21", "spot22"]146        }147    def test_not_found(self):148        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]149        assert Spot.from_iterable_dicts(d).next_at(2).is_none()150class TestForEach:151    def test_normal(self):152        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]153        ret = []154        assert Spot.from_iterable_dicts(d).for_each(lambda s: ret.append(s.names[0])) is None155        assert ret == ["spot1", "spot21"]156class TestMap:157    def test_normal(self):158        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]159        assert Spot.from_iterable_dicts(d).map(lambda s: s.names).to_list() == [160            ["spot1"],161            ["spot21", "spot22"],162        ]163class TestEMap:164    def test_normal(self):165        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]166        assert Spot.from_iterable_dicts(d).emap(lambda s, i: (i + 1, s.names)).to_list() == [167            (1, ["spot1"]),168            (2, ["spot21", "spot22"]),169        ]170class TestFlatten:171    def test_normal(self):172        assert TIterator([[1, 2], [3, 4]]).flatten().to_list() == [1, 2, 3, 4]173class TestFlatMap:174    def test_normal(self):175        ds = Human.from_iterable_dicts(176            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]177        )178        assert ds.flat_map(lambda x: [x.id, x.name]).to_list() == [1, "ä¸é", 2, "äºé"]179class TestFilter:180    def test_normal(self):181        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]182        assert Spot.from_iterable_dicts(d).filter(lambda s: s.address.get()).to_dicts() == [183            {"names": ["spot1"], "address": {"name": "address1"}}184        ]185class TestReject:186    def test_normal(self):187        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]188        assert Spot.from_iterable_dicts(d).reject(lambda s: s.address.get()).to_dicts() == [189            {"names": ["spot21", "spot22"]}190        ]191class TestHead:192    def test_normal(self):193        d = [194            {"names": ["spot1"], "address": {"name": "address1"}},195            {"names": ["spot21", "spot22"]},196            {"names": ["spot31", "spot32"]},197            {"names": ["spot4"], "address": {"name": "address1"}},198        ]199        assert Spot.from_iterable_dicts(d).head().get().to_dict() == {200            "names": ["spot1"],201            "address": {"name": "address1"},202        }203class TestTake:204    def test_normal(self):205        d = [206            {"names": ["spot1"], "address": {"name": "address1"}},207            {"names": ["spot21", "spot22"]},208            {"names": ["spot31", "spot32"]},209            {"names": ["spot4"], "address": {"name": "address1"}},210        ]211        assert Spot.from_iterable_dicts(d).take(3).to_dicts() == [212            {"names": ["spot1"], "address": {"name": "address1"}},213            {"names": ["spot21", "spot22"]},214            {"names": ["spot31", "spot32"]},215        ]216class TestTakeWhile:217    def test_normal(self):218        d = [219            {"names": ["spot11", "spot12"], "address": {"name": "address1"}},220            {"names": ["spot21", "spot22"]},221            {"names": ["spot31"]},222            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},223        ]224        assert [225            {"names": ["spot11", "spot12"], "address": {"name": "address1"}},226            {"names": ["spot21", "spot22"]},227        ] == Spot.from_iterable_dicts(d).take_while(lambda x: x.names.size() > 1).to_dicts()228class TestTail:229    def test_normal(self):230        d = [231            {"names": ["spot1"], "address": {"name": "address1"}},232            {"names": ["spot21", "spot22"]},233            {"names": ["spot31", "spot32"]},234            {"names": ["spot4"], "address": {"name": "address1"}},235        ]236        assert Spot.from_iterable_dicts(d).tail(3).to_dicts() == [237            {"names": ["spot21", "spot22"]},238            {"names": ["spot31", "spot32"]},239            {"names": ["spot4"], "address": {"name": "address1"}},240        ]241class TestUniq:242    def test_normal(self):243        """ Don't forget `d[0] != d[1]`244        """245        d = [246            {"names": ["spot1"], "address": {"name": "address1"}},247            {"names": ["spot1"], "address": {"name": "address1"}},248            {"names": ["spot4"], "address": {"name": "address1"}},249        ]250        assert Spot.from_iterable_dicts(d).uniq().to_dicts() == [251            {"names": ["spot1"], "address": {"name": "address1"}},252            {"names": ["spot1"], "address": {"name": "address1"}},253            {"names": ["spot4"], "address": {"name": "address1"}},254        ]255class TestUniqBy:256    def test_normal(self):257        d = [258            {"names": ["spot1"], "address": {"name": "address1"}},259            {"names": ["spot1"], "address": {"name": "address1"}},260            {"names": ["spot4"], "address": {"name": "address1"}},261        ]262        assert Spot.from_iterable_dicts(d).uniq_by(lambda x: x.to_json()).to_dicts() == [263            {"names": ["spot1"], "address": {"name": "address1"}},264            {"names": ["spot4"], "address": {"name": "address1"}},265        ]266class TestPartition:267    def test_normal(self):268        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]269        rejected, fulfilled = Spot.from_iterable_dicts(d).partition(lambda s: s.address.get())270        assert fulfilled.to_dicts() == [{"names": ["spot1"], "address": {"name": "address1"}}]271        assert rejected.to_dicts() == [{"names": ["spot21", "spot22"]}]272class TestGroupBy:273    def test_normal(self):274        d = [275            {"names": ["spot1"], "address": {"name": "address1"}},276            {"names": ["spot21", "spot22"]},277            {"names": ["spot31", "spot32"]},278            {"names": ["spot4"], "address": {"name": "address1"}},279        ]280        assert Spot.from_iterable_dicts(d).group_by(lambda s: str(len(s.names))).to_dict(281            ignore_none=True282        ) == {283            "1": [284                {"names": ["spot1"], "address": {"name": "address1"}},285                {"names": ["spot4"], "address": {"name": "address1"}},286            ],287            "2": [{"names": ["spot21", "spot22"]}, {"names": ["spot31", "spot32"]}],288        }289        assert Spot.from_iterable_dicts(d).group_by(lambda s: str(len(s.names)))["1"].map(290            lambda x: x.names291        ).to_dicts() == [["spot1"], ["spot4"]]292class TestKeyBy:293    def test_normal(self):294        d = [295            {"names": ["spot1"], "address": {"name": "address1"}},296            {"names": ["spot21", "spot22"]},297            {"names": ["spot31", "spot32"]},298            {"names": ["spot4"], "address": {"name": "address1"}},299        ]300        assert Spot.from_iterable_dicts(d).key_by(lambda s: str(len(s.names))).to_dict(301            ignore_none=True302        ) == {303            "1": {"names": ["spot4"], "address": {"name": "address1"}},304            "2": {"names": ["spot31", "spot32"]},305        }306class TestOrderBy:307    def test_normal(self):308        d = [309            {"names": ["spot1"], "address": {"name": "address1"}},310            {"names": ["spot21", "spot22", "spot23"]},311            {"names": ["spot31", "spot32", "spot33", "spot34"]},312            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},313        ]314        assert Spot.from_iterable_dicts(d).order_by(lambda x: len(x.names)).to_dicts() == [315            {"names": ["spot1"], "address": {"name": "address1"}},316            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},317            {"names": ["spot21", "spot22", "spot23"]},318            {"names": ["spot31", "spot32", "spot33", "spot34"]},319        ]320    def test_reverse(self):321        d = [322            {"names": ["spot1"], "address": {"name": "address1"}},323            {"names": ["spot21", "spot22", "spot23"]},324            {"names": ["spot31", "spot32", "spot33", "spot34"]},325            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},326        ]327        assert Spot.from_iterable_dicts(d).order_by(328            lambda x: len(x.names), reverse=True329        ).to_dicts() == [330            {"names": ["spot31", "spot32", "spot33", "spot34"]},331            {"names": ["spot21", "spot22", "spot23"]},332            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},333            {"names": ["spot1"], "address": {"name": "address1"}},334        ]335class TestConcat:336    def test_normal(self):337        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]338        e = [{"names": ["spot31", "spot32"]}]339        assert Spot.from_iterable_dicts(d).concat(Spot.from_iterable_dicts(e)).to_dicts() == [340            {"names": ["spot1"], "address": {"name": "address1"}},341            {"names": ["spot21", "spot22"]},342            {"names": ["spot31", "spot32"]},343        ]344    def test_first(self):345        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]346        e = [{"names": ["spot31", "spot32"]}]347        assert Spot.from_iterable_dicts(d).concat(348            Spot.from_iterable_dicts(e), first=True349        ).to_dicts() == [350            {"names": ["spot31", "spot32"]},351            {"names": ["spot1"], "address": {"name": "address1"}},352            {"names": ["spot21", "spot22"]},353        ]354class TestReduce:355    def test_normal(self):356        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]357        assert Spot.from_iterable_dicts(d).reduce(lambda r, x: r + len(x.names), 100) == 103358class TestSum:359    def test_normal(self):360        assert TIterator([1, 2, 3]).sum() == 6361class TestSumBy:362    def test_normal(self):363        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]364        assert Spot.from_iterable_dicts(d).sum_by(lambda x: len(x.names)) == 3365class TestCountBy:366    def test_normal(self):367        d = [368            {"names": ["spot1"], "address": {"name": "address1"}},369            {"names": ["spot21", "spot22"]},370            {"names": ["spot31", "spot32"]},371        ]372        assert Spot.from_iterable_dicts(d).count_by(lambda x: len(x.names)) == {1: 1, 2: 2}373class TestJoin:374    def test_normal(self):375        assert TIterator(["a", "bc", "def"]).join("---") == "a---bc---def"376    def test_including_not_str(self):377        with pytest.raises(TypeError):378            TIterator(["1", 2, "3"]).join("---")379class TestFind:380    def test_normal(self):381        d = [382            {"names": ["spot1"], "address": {"name": "address1"}},383            {"names": ["spot21", "spot22"]},384            {"names": ["spot31", "spot32", "spot33"]},385        ]386        assert Spot.from_iterable_dicts(d).find(lambda x: len(x.names) == 2).get().to_dict(387            ignore_none=True388        ) == {"names": ["spot21", "spot22"]}389    def test_not_found(self):390        d = [391            {"names": ["spot1"], "address": {"name": "address1"}},392            {"names": ["spot21", "spot22"]},393            {"names": ["spot31", "spot32"]},394        ]395        assert Spot.from_iterable_dicts(d).find(lambda x: len(x.names) == 3).is_none()396class TestAll:397    def test_true(self):398        d = [399            {"names": ["spot1"], "address": {"name": "address1"}},400            {"names": ["spot21", "spot22"]},401            {"names": ["spot31", "spot32"]},402        ]403        assert Spot.from_iterable_dicts(d).all(lambda x: x.names) is True404    def test_false(self):405        d = [406            {"names": ["spot1"], "address": {"name": "address1"}},407            {"names": ["spot21", "spot22"]},408            {"names": ["spot31", "spot32"]},409        ]410        assert Spot.from_iterable_dicts(d).all(lambda x: len(x.names) > 1) is False411class TestAny:412    def test_true(self):413        d = [414            {"names": ["spot1"], "address": {"name": "address1"}},415            {"names": ["spot21", "spot22"]},416            {"names": ["spot31", "spot32"]},417        ]418        assert Spot.from_iterable_dicts(d).any(lambda x: len(x.names) > 1) is True419    def test_false(self):420        d = [421            {"names": ["spot1"], "address": {"name": "address1"}},422            {"names": ["spot21", "spot22"]},423            {"names": ["spot31", "spot32"]},424        ]425        assert Spot.from_iterable_dicts(d).any(lambda x: len(x.names) > 2) is False426class TestIntersection:427    def test_normal(self):428        assert TIterator([1, 2, 3, 4, 5]).intersection([2, 4, 6]).to_list() == [2, 4]429    def test_empty(self):430        assert TIterator([1, 2, 3, 4, 5]).intersection([7, 8]).to_list() == []431class TestNotIntersection:432    def test_normal(self):433        assert TIterator([1, 2, 3, 4, 5]).not_intersection([2, 4, 6]).to_list() == [1, 3, 5]434    def test_empty(self):435        assert TIterator([1, 2, 3, 4, 5]).not_intersection([1, 2, 3, 4, 5]).to_list() == []436class TestReverse:437    def test_normal(self):438        assert TIterator([1, 2, 3]).reverse().to_list() == [3, 2, 1]439    def test_empty(self):...

test_TList.py

Source:test_TList.py

...14    name: str15    ruby: TOption[str]16    address: TOption[Address]17class Test__Add__:18    def test_normal(self):19        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]20        e = [{"names": ["spot31", "spot32"]}]21        sd = Spot.from_dicts(d)22        se = Spot.from_dicts(e)23        actual = sd + se24        assert sd.to_dicts() == [25            {"names": ["spot1"], "address": {"name": "address1"}},26            {"names": ["spot21", "spot22"]},27        ]28        assert se.to_dicts() == [{"names": ["spot31", "spot32"]}]29        assert isinstance(actual, TList)30        assert actual.to_dicts() == [31            {"names": ["spot1"], "address": {"name": "address1"}},32            {"names": ["spot21", "spot22"]},33            {"names": ["spot31", "spot32"]},34        ]35    def test_exchange_rule(self):36        assert [1, 2] == TList([1]) + TList([2])37        assert [1, 2] == [1] + TList([2])38        assert [1, 2] == TList([1]) + [2]39class TestToCsv:40    def test_normal(self):41        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]42        assert (43            Human.from_dicts(d).to_csv(["id", "name", "ruby"])44            == """451,ä¸é,462,äºé,ããã47""".lstrip()48        )49    def test_ignore_extra_params(self):50        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]51        assert (52            Human.from_dicts(d).to_csv(["id", "name"])53            == """541,ä¸é552,äºé56""".lstrip()57        )58    def test_with_header(self):59        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]60        assert (61            Human.from_dicts(d).to_csv(["id", "name", "ruby"], with_header=True)62            == """63id,name,ruby641,ä¸é,652,äºé,ããã66""".lstrip()67        )68    def test_with_space(self):69        d = [{"id": 1, "name": " ä¸ é "}, {"id": 2, "name": " äº é ", "ruby": "ããã"}]70        assert (71            Human.from_dicts(d).to_csv(["id", "name", "ruby"])72            == """731, ä¸ é ,742, äº é ,ããã75""".lstrip()76        )77    def test_crlf(self):78        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]79        assert (80            Human.from_dicts(d).to_csv(["id", "name", "ruby"], crlf=True)81            == """821,ä¸é,\r832,äºé,ããã\r84""".lstrip()85        )86    def test_tsv(self):87        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]88        assert (89            Human.from_dicts(d).to_csv(["id", "name", "ruby"], tsv=True)90            == """911\tä¸é\t922\täºé\tããã93""".lstrip()94        )95    def test_including_dict(self):96        d = [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "address": {"name": "ä½æ"}}]97        assert (98            Human.from_dicts(d).to_csv(["id", "name", "address"])99            == """1001,ä¸é,1012,äºé,{'name': 'ä½æ'}102""".lstrip()103        )104    def test_including_list(self):105        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]106        assert (107            Spot.from_dicts(d).to_csv(["names", "address"])108            == """109['spot1'],{'name': 'address1'}110"['spot21','spot22']",111""".lstrip()112        )113class TestToCsvf:114    """115    Requirements: `from_csvf_to_list` are fine116    """117    def test_normal(self, tmpdir):118        r: TList[Human] = Human.from_dicts(119            [{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}]120        )121        fpath = os.path.join(tmpdir.mkdir("tmp").strpath, "test.csv")122        assert (123            r.to_csvf(124                fpath, fieldnames=["name", "id", "ruby"], encoding="euc-jp", with_header=False125            )126            == fpath127        )128        assert (129            Human.from_csvf_to_list(130                fpath, fieldnames=["name", "id", "ruby"], encoding="euc-jp"131            ).to_dicts()132            == r.to_dicts()133        )134class TestGet:135    def test_normal(self):136        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]137        assert Spot.from_dicts(d).get(1).get().to_dict() == {"names": ["spot21", "spot22"]}138    def test_not_found(self):139        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]140        assert Spot.from_dicts(d).get(2).is_none()141class TestForEach:142    def test_normal(self):143        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]144        ret = []145        assert Spot.from_dicts(d).for_each(lambda s: ret.append(s.names[0])) is None146        assert ret == ["spot1", "spot21"]147class TestMap:148    def test_normal(self):149        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]150        assert Spot.from_dicts(d).map(lambda s: s.names) == [["spot1"], ["spot21", "spot22"]]151class TestEMap:152    def test_normal(self):153        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]154        assert Spot.from_dicts(d).emap(lambda s, i: (i + 1, s.names)) == [155            (1, ["spot1"]),156            (2, ["spot21", "spot22"]),157        ]158class TestFlatten:159    def test_normal(self):160        assert TList([[1, 2], [3, 4]]).flatten() == [1, 2, 3, 4]161class TestFlatMap:162    def test_normal(self):163        ds = Human.from_dicts([{"id": 1, "name": "ä¸é"}, {"id": 2, "name": "äºé", "ruby": "ããã"}])164        assert ds.flat_map(lambda x: [x.id, x.name]) == [1, "ä¸é", 2, "äºé"]165class TestFilter:166    def test_normal(self):167        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]168        assert Spot.from_dicts(d).filter(lambda s: s.address.get()).to_dicts() == [169            {"names": ["spot1"], "address": {"name": "address1"}}170        ]171class TestReject:172    def test_normal(self):173        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]174        assert Spot.from_dicts(d).reject(lambda s: s.address.get()).to_dicts() == [175            {"names": ["spot21", "spot22"]}176        ]177class TestHead:178    def test_normal(self):179        d = [180            {"names": ["spot1"], "address": {"name": "address1"}},181            {"names": ["spot21", "spot22"]},182            {"names": ["spot31", "spot32"]},183            {"names": ["spot4"], "address": {"name": "address1"}},184        ]185        assert Spot.from_dicts(d).head().get().to_dict() == {186            "names": ["spot1"],187            "address": {"name": "address1"},188        }189class TestTake:190    def test_normal(self):191        d = [192            {"names": ["spot1"], "address": {"name": "address1"}},193            {"names": ["spot21", "spot22"]},194            {"names": ["spot31", "spot32"]},195            {"names": ["spot4"], "address": {"name": "address1"}},196        ]197        assert Spot.from_dicts(d).take(3).to_dicts() == [198            {"names": ["spot1"], "address": {"name": "address1"}},199            {"names": ["spot21", "spot22"]},200            {"names": ["spot31", "spot32"]},201        ]202class TestTakeWhile:203    def test_normal(self):204        d = [205            {"names": ["spot11", "spot12"], "address": {"name": "address1"}},206            {"names": ["spot21", "spot22"]},207            {"names": ["spot31"]},208            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},209        ]210        assert [211            {"names": ["spot11", "spot12"], "address": {"name": "address1"}},212            {"names": ["spot21", "spot22"]},213        ] == Spot.from_dicts(d).take_while(lambda x: x.names.size() > 1).to_dicts()214class TestTail:215    def test_normal(self):216        d = [217            {"names": ["spot1"], "address": {"name": "address1"}},218            {"names": ["spot21", "spot22"]},219            {"names": ["spot31", "spot32"]},220            {"names": ["spot4"], "address": {"name": "address1"}},221        ]222        assert Spot.from_dicts(d).tail(3).to_dicts() == [223            {"names": ["spot21", "spot22"]},224            {"names": ["spot31", "spot32"]},225            {"names": ["spot4"], "address": {"name": "address1"}},226        ]227class TestUniq:228    def test_normal(self):229        """ Don't forget `d[0] != d[1]`230        """231        d = [232            {"names": ["spot1"], "address": {"name": "address1"}},233            {"names": ["spot1"], "address": {"name": "address1"}},234            {"names": ["spot4"], "address": {"name": "address1"}},235        ]236        assert Spot.from_dicts(d).uniq().to_dicts() == [237            {"names": ["spot1"], "address": {"name": "address1"}},238            {"names": ["spot1"], "address": {"name": "address1"}},239            {"names": ["spot4"], "address": {"name": "address1"}},240        ]241class TestUniqBy:242    def test_normal(self):243        d = [244            {"names": ["spot1"], "address": {"name": "address1"}},245            {"names": ["spot1"], "address": {"name": "address1"}},246            {"names": ["spot4"], "address": {"name": "address1"}},247        ]248        assert Spot.from_dicts(d).uniq_by(lambda x: x.to_json()).to_dicts() == [249            {"names": ["spot1"], "address": {"name": "address1"}},250            {"names": ["spot4"], "address": {"name": "address1"}},251        ]252class TestPartition:253    def test_normal(self):254        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]255        rejected, fulfilled = Spot.from_dicts(d).partition(lambda s: s.address.get())256        assert fulfilled.to_dicts() == [{"names": ["spot1"], "address": {"name": "address1"}}]257        assert rejected.to_dicts() == [{"names": ["spot21", "spot22"]}]258class TestGroupBy:259    def test_normal(self):260        d = [261            {"names": ["spot1"], "address": {"name": "address1"}},262            {"names": ["spot21", "spot22"]},263            {"names": ["spot31", "spot32"]},264            {"names": ["spot4"], "address": {"name": "address1"}},265        ]266        assert Spot.from_dicts(d).group_by(lambda s: str(len(s.names))).to_dict(267            ignore_none=True268        ) == {269            "1": [270                {"names": ["spot1"], "address": {"name": "address1"}},271                {"names": ["spot4"], "address": {"name": "address1"}},272            ],273            "2": [{"names": ["spot21", "spot22"]}, {"names": ["spot31", "spot32"]}],274        }275class TestKeyBy:276    def test_normal(self):277        d = [278            {"names": ["spot1"], "address": {"name": "address1"}},279            {"names": ["spot21", "spot22"]},280            {"names": ["spot31", "spot32"]},281            {"names": ["spot4"], "address": {"name": "address1"}},282        ]283        assert Spot.from_dicts(d).key_by(lambda s: str(len(s.names))).to_dict(ignore_none=True) == {284            "1": {"names": ["spot4"], "address": {"name": "address1"}},285            "2": {"names": ["spot31", "spot32"]},286        }287class TestOrderBy:288    def test_normal(self):289        d = [290            {"names": ["spot1"], "address": {"name": "address1"}},291            {"names": ["spot21", "spot22", "spot23"]},292            {"names": ["spot31", "spot32", "spot33", "spot34"]},293            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},294        ]295        assert Spot.from_dicts(d).order_by(lambda x: len(x.names)).to_dicts() == [296            {"names": ["spot1"], "address": {"name": "address1"}},297            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},298            {"names": ["spot21", "spot22", "spot23"]},299            {"names": ["spot31", "spot32", "spot33", "spot34"]},300        ]301    def test_reverse(self):302        d = [303            {"names": ["spot1"], "address": {"name": "address1"}},304            {"names": ["spot21", "spot22", "spot23"]},305            {"names": ["spot31", "spot32", "spot33", "spot34"]},306            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},307        ]308        assert Spot.from_dicts(d).order_by(lambda x: len(x.names), reverse=True).to_dicts() == [309            {"names": ["spot31", "spot32", "spot33", "spot34"]},310            {"names": ["spot21", "spot22", "spot23"]},311            {"names": ["spot41", "spot42"], "address": {"name": "address1"}},312            {"names": ["spot1"], "address": {"name": "address1"}},313        ]314class TestConcat:315    def test_normal(self):316        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]317        e = [{"names": ["spot31", "spot32"]}]318        assert Spot.from_dicts(d).concat(Spot.from_dicts(e)).to_dicts() == [319            {"names": ["spot1"], "address": {"name": "address1"}},320            {"names": ["spot21", "spot22"]},321            {"names": ["spot31", "spot32"]},322        ]323    def test_first(self):324        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]325        e = [{"names": ["spot31", "spot32"]}]326        assert Spot.from_dicts(d).concat(Spot.from_dicts(e), first=True).to_dicts() == [327            {"names": ["spot31", "spot32"]},328            {"names": ["spot1"], "address": {"name": "address1"}},329            {"names": ["spot21", "spot22"]},330        ]331class TestReduce:332    def test_normal(self):333        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]334        assert Spot.from_dicts(d).reduce(lambda r, x: r + len(x.names), 100) == 103335class TestSum:336    def test_normal(self):337        assert TList([1, 2, 3]).sum() == 6338class TestSumBy:339    def test_normal(self):340        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]341        assert Spot.from_dicts(d).sum_by(lambda x: len(x.names)) == 3342class TestCountBy:343    def test_normal(self):344        d = [345            {"names": ["spot1"], "address": {"name": "address1"}},346            {"names": ["spot21", "spot22"]},347            {"names": ["spot31", "spot32"]},348        ]349        assert Spot.from_dicts(d).count_by(lambda x: len(x.names)) == {1: 1, 2: 2}350class TestSize:351    def test_normal(self):352        d = [{"names": ["spot1"], "address": {"name": "address1"}}, {"names": ["spot21", "spot22"]}]353        assert Spot.from_dicts(d).size() == 2354class TestJoin:355    def test_normal(self):356        assert TList(["a", "bc", "def"]).join("---") == "a---bc---def"357    def test_including_not_str(self):358        with pytest.raises(TypeError):359            TList(["1", 2, "3"]).join("---")360class TestFind:361    def test_normal(self):362        d = [363            {"names": ["spot1"], "address": {"name": "address1"}},364            {"names": ["spot21", "spot22"]},365            {"names": ["spot31", "spot32", "spot33"]},366        ]367        assert Spot.from_dicts(d).find(lambda x: len(x.names) == 2).get().to_dict(368            ignore_none=True369        ) == {"names": ["spot21", "spot22"]}370    def test_not_found(self):371        d = [372            {"names": ["spot1"], "address": {"name": "address1"}},373            {"names": ["spot21", "spot22"]},374            {"names": ["spot31", "spot32"]},375        ]376        assert Spot.from_dicts(d).find(lambda x: len(x.names) == 3).is_none()377class TestAll:378    def test_true(self):379        d = [380            {"names": ["spot1"], "address": {"name": "address1"}},381            {"names": ["spot21", "spot22"]},382            {"names": ["spot31", "spot32"]},383        ]384        assert Spot.from_dicts(d).all(lambda x: x.names) is True385    def test_false(self):386        d = [387            {"names": ["spot1"], "address": {"name": "address1"}},388            {"names": ["spot21", "spot22"]},389            {"names": ["spot31", "spot32"]},390        ]391        assert Spot.from_dicts(d).all(lambda x: len(x.names) > 1) is False392class TestAny:393    def test_true(self):394        d = [395            {"names": ["spot1"], "address": {"name": "address1"}},396            {"names": ["spot21", "spot22"]},397            {"names": ["spot31", "spot32"]},398        ]399        assert Spot.from_dicts(d).any(lambda x: len(x.names) > 1) is True400    def test_false(self):401        d = [402            {"names": ["spot1"], "address": {"name": "address1"}},403            {"names": ["spot21", "spot22"]},404            {"names": ["spot31", "spot32"]},405        ]406        assert Spot.from_dicts(d).any(lambda x: len(x.names) > 2) is False407class TestIntersection:408    def test_normal(self):409        assert TList([1, 2, 3, 4, 5]).intersection([2, 4, 6]) == [2, 4]410    def test_empty(self):411        assert TList([1, 2, 3, 4, 5]).intersection([7, 8]) == []412class TestNotIntersection:413    def test_normal(self):414        assert TList([1, 2, 3, 4, 5]).not_intersection([2, 4, 6]) == [1, 3, 5]415    def test_empty(self):416        assert TList([1, 2, 3, 4, 5]).not_intersection([1, 2, 3, 4, 5]) == []417class TestReverse:418    def test_normal(self):419        assert TList([1, 2, 3]).reverse() == [3, 2, 1]420    def test_empty(self):...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.