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How to use test_validate method in molecule
Best Python code snippet using molecule_python
report_before_the_report.py
Source:report_before_the_report.py 
1#!/usr/bin/env python2# coding: utf-83# In[1]:4import pandas as pd5import numpy as np6import scipy.stats as stats7import matplotlib.pyplot as plt8import seaborn as sns9import warnings10warnings.filterwarnings("ignore")11from sklearn.model_selection import train_test_split12from sklearn.tree import DecisionTreeClassifier, plot_tree, export_text13from sklearn.ensemble import RandomForestClassifier14from sklearn.linear_model import LogisticRegression15from sklearn.neighbors import KNeighborsClassifier16from sklearn.linear_model import LogisticRegression17from sklearn.neighbors import KNeighborsClassifier18from sklearn.metrics import classification_report, confusion_matrix, accuracy_score19from env import host, user, password20import acquire21import prepare22import exp_mod23import report_wdate24# # inital data retrieval and analysis25# In[2]:26telco_df=acquire.get_telco_data()27# In[3]:28telco_df.info()29# In[4]:30telco_df.describe(include='object').T31# In[5]:32telco_df.churn33# In[6]:34def initial_data(data):35 telco_df=acquire.get_telco_data()36 print('this data frame has',telco_df.shape[0],'rows and', telco_df.shape[1],'columns')37 print(' ')38 print(telco_df.info())39 print(' ')40 print(telco_df.describe())41 print(' ')42 print(telco_df.describe(include='object').T)43 print(' ')44 print(telco_df.columns)45 print('ended of initial report')46 print(' ')47# In[7]:48initial_data(telco_df)49# # Prepare Data50# In[8]:51prep_telco=prepare.prep_telco(telco_df)52prep_telco53# In[9]:54prep_telco=prep_telco.drop(columns=['phone_service.1','multiple_lines.1','internet_service_type_id.1','payment_type_id.1','online_backup.1','device_protection.1','tech_support.1','streaming_tv.1','streaming_movies.1','contract_type_id.1','paperless_billing.1','total_charges.1','monthly_charges.1','total_charges.1'],inplace=True)55# In[10]:56telco_train,telco_validate,telco_test=prepare.split_telco(prep_telco)57telco_train58# In[ ]:59# # Explore Data60# In[11]:61telco_train.info()62# In[12]:63telco_train['month']=(telco_train.total_charges/telco_train.monthly_charges)64telco_validate['month']=(telco_validate.total_charges/telco_validate.monthly_charges)65telco_test['month']=(telco_test.total_charges/telco_test.monthly_charges)66# In[13]:67telco_train.month.value_counts()68# In[14]:69telco_train.month.value_counts().nunique()70# In[15]:71telco_train.columns72# In[16]:73telco_train.contract_type74# In[17]:75telco_train[telco_train.month==1].describe().T76# In[18]:77telco_train[telco_train.month>1].describe().T78# In[19]:79telco_train[telco_train.month>1].describe().T==telco_train[telco_train.month==1].describe().T80# In[20]:81telco_train[telco_train.month==1].churn_Yes.value_counts()82# In[21]:83telco_train[telco_train.churn_Yes==1].describe().T84# In[22]:85len(telco_train[telco_train.month==1])/len(telco_train[telco_train.churn_Yes==1])86# In[23]:87telco_train[telco_train.churn_Yes==0].describe().T==telco_train[telco_train.churn_Yes==1].describe().T88# In[24]:89g=sns.JointGrid(data=telco_train, x="month", y="tenure", space=0, ratio=17,hue='churn_Yes')90g.plot_joint(sns.scatterplot, size=telco_train["churn_Yes"], sizes=(50, 120),91 color="g", alpha=.6, legend=False)92g.plot_marginals(sns.rugplot, height=1, color="g", alpha=.6)93# In[25]:94g=sns.JointGrid(data=telco_train, x="month", y="partner_Yes", space=0, ratio=17,hue='churn_Yes')95g.plot_joint(sns.scatterplot, size=telco_train["churn_Yes"], sizes=(50, 120),96 color="g", alpha=.6, legend=True)97g.plot_marginals(sns.rugplot, height=1, color="g", alpha=.6)98# In[26]:99telco_train_m=telco_train[telco_train.month<=1]100telco_train_m[telco_train_m.churn_Yes==1].describe().T101# In[27]:102telco_train_m[telco_train_m.churn_Yes==1].contract_type.value_counts()103# In[28]:104222/688105# In[29]:106report_wdate.signup_date_train(telco_train)107report_wdate.signup_date_val(telco_validate)108report_wdate.signup_date_test(telco_test)109# In[30]:110report_wdate.compareid(telco_train).nunique()111# In[31]:112sns.displot(113 data=telco_train,114 x="monthly_charges", hue="churn_Yes",115 kind="kde", height=6,116 multiple="fill", clip=(0, None),117 palette="ch:rot=-.25,hue=1,light=.75",118)119# In[32]:120sns.violinplot(data=telco_train, x='online_security_Yes',y='churn_Yes',palette="light:g", inner="points", orient="h")121# In[33]:122sns.displot(123 data=telco_train,124 x="tenure", hue="churn_Yes",125 kind="kde", height=6,126 multiple="fill", clip=(0, None),127 palette="ch:rot=-.25,hue=1,light=.75",128)129# In[34]:130sns.displot(131 data=telco_train,132 x="month", hue="churn_Yes",133 kind="kde", height=6,134 multiple="fill", clip=(0, None),135 palette="ch:rot=-.25,hue=1,light=.75",136)137# In[35]:138sns.violinplot(data=telco_train, x='signup_month',y='churn_Yes',palette="light:g", inner="points", orient="h")139# In[36]:140sns.lineplot(data=telco_train, x="signup_month", y="month",hue='churn_Yes')141# In[37]:142sns.relplot(x="signup_month", y="contract_type", hue="churn_Yes",143 sizes=(40, 400), alpha=.5, palette="muted",144 height=6, data=telco_train)145# In[38]:146sns.relplot(x="month", y="contract_type", hue="churn_Yes",147 sizes=(40, 400), alpha=.5, palette="muted",148 height=6, data=telco_train)149# In[39]:150stats.mannwhitneyu(telco_train.month, telco_train.tenure)151# # Model152# In[40]:153telco_train.churn_Yes.mode()154# In[41]:155telco_x_train = telco_train.select_dtypes(exclude=['object']).drop(columns=['churn_Yes'])156telco_y_train = telco_train.select_dtypes(exclude=['object']).churn_Yes157telco_x_validate = telco_validate.select_dtypes(exclude=['object']).drop(columns=['churn_Yes'])158telco_y_validate = telco_validate.select_dtypes(exclude=['object']).churn_Yes159telco_x_test = telco_test.select_dtypes(exclude=['object']).drop(columns=['churn_Yes'])160telco_y_test = telco_test.select_dtypes(exclude=['object']).churn_Yes161# In[42]:162(telco_y_train==0).mean()163# In[43]:164clf_telco = DecisionTreeClassifier(max_depth=3, random_state=123)165clf_telco = clf_telco.fit(telco_x_train, telco_y_train)166# In[44]:167plt.figure(figsize=(13, 7))168plot_tree(clf_telco, feature_names=telco_x_train.columns, rounded=True)169# In[45]:170telco_y_pred = pd.DataFrame({'churn': telco_y_train,'baseline': 0, 'model_1':clf_telco.predict(telco_x_train)})171telco_y_pred172# In[46]:173y_pred_proba = clf_telco.predict_proba(telco_x_train)174y_pred_proba[0:5]175# In[47]:176print('Accuracy of Decision Tree classifier on training set: {:.2f}'177 .format(clf_telco.score(telco_x_train, telco_y_train)))178# In[48]:179confusion_matrix(telco_y_pred.churn, telco_y_pred.model_1)180# In[49]:181print(classification_report(telco_y_pred.churn,telco_y_pred.model_1))182# In[50]:183pd.DataFrame(confusion_matrix(telco_y_pred.churn, telco_y_pred.model_1), index=['actual_notchurn','acutal_churn'], columns=['prep_notchurn','prep_churn'])184# In[51]:185telco_TN = 2923186telco_FP = 207187telco_FN = 642188telco_TP = 453189# In[52]:190telco_all = telco_TP + telco_FP + telco_FN + telco_TN191telco_acc = (telco_TP + telco_TN) / telco_all192telco_TurePositiveRate = telco_recall = telco_TP/ (telco_TP + telco_FN)193telco_FalsePositiveRate = telco_FP / (telco_FP + telco_TN)194telco_TrueNegativeRate = telco_TN / (telco_TN + telco_FP)195telco_FalseNegativeRate = telco_FN / (telco_FN + telco_TP)196telco_precision = telco_TP / (telco_TP + telco_FP)197telco_f1_score = 2 * (telco_precision*telco_recall) / (telco_precision+telco_recall)198telco_support_pos = telco_TP + telco_FN199telco_support_neg = telco_FP + telco_TN200# In[53]:201print('accuracy is:',telco_acc,'Ture Positive Rate is:',telco_TurePositiveRate,'False Positive Rate is:',telco_FalsePositiveRate,'/n',202 'True Negative Rate is:',telco_TrueNegativeRate,'False Negative Rate is:',telco_FalseNegativeRate,'precision is:',telco_precision,'/n',203 'f1_score is:',telco_f1_score,'support_pos is:',telco_support_pos,'support_neg is:',telco_support_neg)204# In[54]:205print(classification_report(telco_y_train, telco_y_pred.model_1))206# In[55]:207# random forest208# In[56]:209from sklearn.model_selection import train_test_split210from sklearn.ensemble import RandomForestClassifier211from sklearn.metrics import classification_report212from sklearn.metrics import confusion_matrix213from sklearn.metrics import ConfusionMatrixDisplay214rf = RandomForestClassifier(bootstrap=True, 215 class_weight=None, 216 criterion='gini',217 min_samples_leaf=1,218 n_estimators=100,219 max_depth=10, 220 random_state=123)221rf.fit(telco_x_train, telco_y_train)222# In[57]:223clf_telco.score(telco_x_train,telco_y_train)224# In[58]:225telco_y_predict=rf.predict(telco_x_train)226# In[59]:227print(classification_report(telco_y_train,telco_y_predict))228# In[60]:229confusion_matrix(telco_y_train,telco_y_predict)230# In[61]:231ConfusionMatrixDisplay(confusion_matrix(telco_y_train,telco_y_predict),display_labels=rf.classes_).plot()232# In[62]:233TN = 3018234FP = 112235FN = 293236TP = 802237# In[63]:238all = TP + FP + FN + TN239acc = (TP + TN) / all240TurePositiveRate = recall = TP/ (TP + FN)241FalsePositiveRate = FP / (FP + TN)242TrueNegativeRate = TN / (TN + FP)243FalseNegativeRate = FN / (FN + TP)244precision = TP / (TP + FP)245f1_score = 2 * (precision*recall) / (precision+recall)246support_pos = TP + FN247support_neg = FP + TN248# In[64]:249print('accuracy is:',acc,'Ture Positive Rate is:',TurePositiveRate,'False Positive Rate is:',FalsePositiveRate,'/n',250 'True Negative Rate is:',TrueNegativeRate,'False Negative Rate is:',FalseNegativeRate,'precision is:',precision,'/n',251 'f1_score is:',f1_score,'support_pos is:',support_pos,'support_neg is:',support_neg)252# In[65]:253for model in range (2,11):254 rf=RandomForestClassifier(max_depth=model, random_state=123)255 rf=rf.fit(telco_x_train,telco_y_train)256 y_predict=rf.predict(telco_x_train)257 print('model depth',model)258 print(classification_report(telco_y_train, telco_y_predict))259# In[66]:260model=[]261for num in range (2,20):262 rf=RandomForestClassifier(max_depth=num,random_state=123)263 rf=rf.fit(telco_x_train,telco_y_train)264 train_accuracy=rf.score(telco_x_train,telco_y_train)265 validate_accuracy=rf.score(telco_x_validate,telco_y_validate)266 result = {267 "max_depth": num,268 "train_accuracy": train_accuracy,269 "validate_accuracy": validate_accuracy270 }271 model.append(result)272test_validate = pd.DataFrame(model)273test_validate["difference"] = test_validate.train_accuracy - test_validate.validate_accuracy274test_validate275# In[67]:276sns.relplot(x='max_depth',y='difference',data=test_validate)277# In[68]:278model=[]279max_depth=25280for num in range (2,max_depth):281 mdepth=max_depth-num282 min_leaf=num283 rf=RandomForestClassifier(max_depth=mdepth,min_samples_leaf=min_leaf,random_state=123)284 rf=rf.fit(telco_x_train,telco_y_train)285 train_accuracy=rf.score(telco_x_train,telco_y_train)286 validate_accuracy=rf.score(telco_x_validate,telco_y_validate)287 result = {288 'min_samples_leaf':min_leaf,289 'max_depth': mdepth,290 "train_accuracy": train_accuracy,291 "validate_accuracy": validate_accuracy292 }293 model.append(result)294test_validate = pd.DataFrame(model)295test_validate["difference"] = test_validate.train_accuracy - test_validate.validate_accuracy296test_validate297# In[69]:298sns.relplot(x='max_depth',y='difference',data=test_validate)299# In[70]:300knn = KNeighborsClassifier(n_neighbors=5, weights='uniform')301knn.fit(telco_x_train, telco_y_train)302# In[71]:303y_pred= knn.predict(telco_x_train)304y_valid=knn.predict(telco_x_validate)305# In[72]:306print('Accuracy of KNN classifier on training set: {:.2f}'307 .format(knn.score(telco_x_train, telco_y_train)))308# In[73]:309model=[]310for num in range (2,20):311 knn = KNeighborsClassifier(n_neighbors=num, weights='uniform')312 knn=knn.fit(telco_x_train, telco_y_train)313 train_accuracy=knn.score(telco_x_train,telco_y_train)314 validate_accuracy=knn.score(telco_x_validate,telco_y_validate)315 result = {316 "max_depth": num,317 "train_accuracy": train_accuracy,318 "validate_accuracy": validate_accuracy319 }320 model.append(result)321test_validate = pd.DataFrame(model)322test_validate["difference"] = test_validate.train_accuracy - test_validate.validate_accuracy323test_validate324# In[74]:325sns.relplot(x='max_depth',y='difference',data=test_validate)326# In[75]:...
mastermind_test.py
Source:mastermind_test.py
...18from engine import Engine19'''20Generic function for printing results21'''22def test_validate(msg, expected, result):23 print(msg + ": "),24 if result == expected:25 print("PASSED")26 else:27 print("FAILED (" + str(expected) + " vs " + str(result) + ")")28 sys.exit()29'''30Test rows input31'''32def test_valid_rows():33 e = Engine()34 test_validate("Testing validate rows with invalid char", False, e._Engine__validate_and_assign_rows("a"))35 test_validate("Testing validate rows with 0 rows", False, e._Engine__validate_and_assign_rows("0"))36 for rows in range(1, 100):37 r = str(rows)38 test_validate("Testing validate rows with number " + r, rows in e._Engine__valid_rows, e._Engine__validate_and_assign_rows(r))39'''40Test variations input41'''42def test_valid_variations():43 e = Engine()44 test_validate("Testing validate variations with invalid char", False, e._Engine__validate_and_assign_variations("a"))45 for variations in range(1, 100):46 v = str(variations)47 test_validate("Testing validate variations with number " + v, variations >= 2, e._Engine__validate_and_assign_variations(v))48'''49Test code input50'''51def test_valid_code():52 e = Engine()53 e._Engine__variations = 5054 test_validate("Testing validate code with invalid char", False, e._Engine__validate_and_assign_code("a b c"))55 arr_too_short = [x for x in range(0, e._Engine__code_len_min - 1)]56 arr_too_sort_s = " ".join([str(a) for a in arr_too_short])57 test_validate("Testing validate code with an array too short", False, e._Engine__validate_and_assign_code(arr_too_sort_s))58 arr_too_long = [x for x in range(0, e._Engine__code_len_max + 1)]59 arr_too_long_s = " ".join([str(a) for a in arr_too_long])60 test_validate("Testing validate code with an array too long", False, e._Engine__validate_and_assign_code(arr_too_long_s))61 arr = [x for x in range(0, 100)]62 for i in range(e._Engine__code_len_min, e._Engine__code_len_max + 1):63 for idx in range(0, 100, i):64 subarr = arr[idx:idx + i]65 subarr_s = " ".join([str(x) for x in subarr])66 test_validate("Testing validate code with " + subarr_s, subarr[len(subarr) - 1] <= e._Engine__variations, e._Engine__validate_and_assign_code(subarr_s))67'''68Test that the random numbers for code follow the restrictions69'''70def test_valid_random_code():71 e = Engine()72 e._Engine__variations = 5073 for i in range(0, 100):74 e._Engine__validate_and_assign_code("")75 res = True76 for c in e._Engine__code:77 if c >= e._Engine__variations:78 res = False79 if len(e._Engine__code) < e._Engine__code_len_min:80 res = False81 if len(e._Engine__code) > e._Engine__code_len_max:82 res = False83 code_s = " ".join([str(x) for x in e._Engine__code])84 test_validate("Testing validate code with no input (" + code_s + ")", True, res)85'''86Test that the pegs input is validated properly87'''88def test_valid_pegs():89 e = Engine()90 e._Engine__variations = 5091 e._Engine__code = [0, 1, 2, 3]92 test_validate("Testing validate pegs with an array too short", True, e._Engine__validate_and_return_pegs("0 1 2") is None)93 test_validate("Testing validate pegs with an array too long", True, e._Engine__validate_and_return_pegs("0 1 2 3 4") is None)94 test_validate("Testing validate pegs with an invalid char", True, e._Engine__validate_and_return_pegs("0 1 2 a") is None)95 test_validate("Testing validate pegs with a negative number", True, e._Engine__validate_and_return_pegs("0 1 2 -1") is None)96 test_validate("Testing validate pegs with a number too large", True, e._Engine__validate_and_return_pegs("0 1 2 50") is None)97 test_validate("Testing validate pegs with a valid input", True, e._Engine__validate_and_return_pegs("0 1 2 49") is not None)98'''99Test the full matches function100'''101def test_full_matches():102 e = Engine()103 e._Engine__code = [1, 2, 3, 4]104 test_validate("Testing full matches with 1 match", 1, e._Engine__get_full_matches([1, 3, 2, 5]))105 test_validate("Testing full matches with 2 matches", 2, e._Engine__get_full_matches([1, 3, 3, 5]))106 test_validate("Testing full matches with 3 matches", 3, e._Engine__get_full_matches([1, 3, 3, 4]))107 test_validate("Testing full matches with 4 matches", 4, e._Engine__get_full_matches([1, 2, 3, 4]))108'''109Test the partial matches function110'''111def test_partial_matches():112 e = Engine()113 e._Engine__code = [1, 2, 3, 4]114 test_validate("Testing partial matches with 1 match", 1, e._Engine__get_partial_matches([1, 4, 3, 3]))115 test_validate("Testing partial matches with 2 matches", 2, e._Engine__get_partial_matches([1, 4, 3, 2]))116 test_validate("Testing partial matches with 3 matches", 3, e._Engine__get_partial_matches([3, 4, 0, 2]))117 test_validate("Testing partial matches with 4 matches", 4, e._Engine__get_partial_matches([3, 4, 1, 2]))118'''119Test the game iterate function when winning120'''121def test_game_iterate_win():122 e = Engine()123 e._Engine__code = [1, 2, 3, 4]124 e._Engine__rows = 4125 res = e._Engine__game_iterate([0, 1, 2, 3])126 test_validate("Testing full matches at 1st win iteration", 0, res["full_matches"])127 test_validate("Testing partial matches at 1st win iteration", 3, res["partial_matches"])128 test_validate("Testing game over at 1st win iteration", False, e._Engine__game_over)129 test_validate("Testing win at 1st win iteration", False, e._Engine__win)130 test_validate("Testing game row at 1st win iteration", 1, e._Engine__crt_row)131 res = e._Engine__game_iterate([1, 1, 2, 3])132 test_validate("Testing full matches at 2nd win iteration", 1, res["full_matches"])133 test_validate("Testing partial matches at 2nd win iteration", 2, res["partial_matches"])134 test_validate("Testing game over at 2nd win iteration", False, e._Engine__game_over)135 test_validate("Testing win at 2nd win iteration", False, e._Engine__win)136 test_validate("Testing game row at 2nd win iteration", 2, e._Engine__crt_row)137 res = e._Engine__game_iterate([1, 2, 2, 3])138 test_validate("Testing full matches at 3rd win iteration", 2, res["full_matches"])139 test_validate("Testing partial matches at 3rd win iteration", 1, res["partial_matches"])140 test_validate("Testing game over at 3rd win iteration", False, e._Engine__game_over)141 test_validate("Testing win at 3rd win iteration", False, e._Engine__win)142 test_validate("Testing game row at 3rd win iteration", 3, e._Engine__crt_row)143 res = e._Engine__game_iterate([1, 2, 3, 4])144 test_validate("Testing full matches at 4th win iteration", 4, res["full_matches"])145 test_validate("Testing partial matches at 4th win iteration", 0, res["partial_matches"])146 test_validate("Testing game over at 4th win iteration", True, e._Engine__game_over)147 test_validate("Testing win at 4th win iteration", True, e._Engine__win)148 test_validate("Testing game row at 4th win iteration", 4, e._Engine__crt_row)149'''150Test the game iterate function when losing151'''152def test_game_iterate_lose():153 e = Engine()154 e._Engine__code = [1, 2, 3, 4]155 e._Engine__rows = 4156 res = e._Engine__game_iterate([4, 3, 2, 1])157 test_validate("Testing full matches at 1st lose iteration", 0, res["full_matches"])158 test_validate("Testing partial matches at 1st lose iteration", 4, res["partial_matches"])159 test_validate("Testing game over at 1st lose iteration", False, e._Engine__game_over)160 test_validate("Testing win at 1st lose iteration", False, e._Engine__win)161 test_validate("Testing game row at 1st lose iteration", 1, e._Engine__crt_row)162 res = e._Engine__game_iterate([0, 3, 1, 2])163 test_validate("Testing full matches at 2nd lose iteration", 0, res["full_matches"])164 test_validate("Testing partial matches at 2nd lose iteration", 3, res["partial_matches"])165 test_validate("Testing game over at 2nd lose iteration", False, e._Engine__game_over)166 test_validate("Testing win at 2nd lose iteration", False, e._Engine__win)167 test_validate("Testing game row at 2nd lose iteration", 2, e._Engine__crt_row)168 res = e._Engine__game_iterate([1, 2, 2, 3])169 test_validate("Testing full matches at 3rd lose iteration", 2, res["full_matches"])170 test_validate("Testing partial matches at 3rd lose iteration", 1, res["partial_matches"])171 test_validate("Testing game over at 3rd lose iteration", False, e._Engine__game_over)172 test_validate("Testing win at 3rd lose iteration", False, e._Engine__win)173 test_validate("Testing game row at 3rd lose iteration", 3, e._Engine__crt_row)174 res = e._Engine__game_iterate([1, 2, 3, 0])175 test_validate("Testing full matches at 4th lose iteration", 3, res["full_matches"])176 test_validate("Testing partial matches at 4th lose iteration", 0, res["partial_matches"])177 test_validate("Testing game over at 4th lose iteration", True, e._Engine__game_over)178 test_validate("Testing win at 4th lose iteration", False, e._Engine__win)179 test_validate("Testing game row at 4th lose iteration", 4, e._Engine__crt_row)180if __name__ == "__main__":181 test_valid_rows()182 test_valid_variations()183 test_valid_code()184 test_valid_random_code()185 test_valid_pegs()186 test_full_matches()187 test_partial_matches()188 test_game_iterate_win()...
test_config.py
Source:test_config.py
...29 'engine': self.engine_test_conf,30 'kafka': self.kafka_test_conf,31 'spark': self.spark_test_conf32 })33 def test_validate(self):34 pass35class TestBaskervilleConfig(unittest.TestCase):36 def setUp(self):37 pass38 # def test_instance(self):39 # raise NotImplementedError()40 #41 # def test_validate(self):42 # raise NotImplementedError()43class TestEngineConfig(unittest.TestCase):44 def setUp(self):45 pass46 # def test_instance(self):47 # raise NotImplementedError()48 #49 # def test_validate(self):50 # raise NotImplementedError()51class TestAutoConfig(unittest.TestCase):52 def setUp(self):53 pass54 # def test_instance(self):55 # raise NotImplementedError()56 #57 # def test_validate(self):58 # raise NotImplementedError()59class TestManualConfig(unittest.TestCase):60 def setUp(self):61 pass62 # def test_instance(self):63 # raise NotImplementedError()64 #65 # def test_validate(self):66 # raise NotImplementedError()67class TestSimulationConfig(unittest.TestCase):68 def setUp(self):69 pass70 # def test_instance(self):71 # raise NotImplementedError()72 #73 # def test_validate(self):74 # raise NotImplementedError()75class TestElasticConfig(unittest.TestCase):76 def setUp(self):77 pass78 # def test_instance(self):79 # raise NotImplementedError()80 #81 # def test_validate(self):82 # raise NotImplementedError()83class TestDatabaseConfig(unittest.TestCase):84 def setUp(self):85 pass86 # def test_instance(self):87 # raise NotImplementedError()88 #89 # def test_validate(self):90 # raise NotImplementedError()91class TestKafkaConfig(unittest.TestCase):92 def setUp(self):93 pass94 # def test_instance(self):95 # raise NotImplementedError()96 #97 # def test_validate(self):98 # raise NotImplementedError()99class TestSparkConfig(unittest.TestCase):100 def setUp(self):101 pass102 # def test_instance(self):103 # raise NotImplementedError()104 #105 # def test_validate(self):...
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- TestNG Tutorial
- Webdriver Tutorial
- WebDriverIO Tutorial
- Protractor Tutorial
- Selenium 4 Tutorial
- Jenkins Tutorial
- NUnit Tutorial
- Jest Tutorial
- Playwright Tutorial
- Cypress Tutorial
- PyTest Tutorial
YouTube
You could also refer to video tutorials over LambdaTest YouTube channel to get step by step demonstration from industry experts.
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