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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):...
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