.

Jenkinsfile

@@ -37,7 +37,7 @@ pipeline {
 				sh 'chmod u+x download.sh'
 				withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}","KAGGLE_KEY=${params.KAGGLE_KEY}", "CUTOFF=${params.CUTOFF}"]) {
 					sh 'echo KAGGLE_USERNAME: $KAGGLE_USERNAME'
-					sh './download.sh'
+					//sh './download.sh'
 				    sh "python ium-data.py"
 				}
 				archiveArtifacts artifacts: 'd_test.csv, d_dev.csv, d_train.csv'

ium-data.py

@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-#from kaggle.api.kaggle_api_extended import KaggleApi
+from kaggle.api.kaggle_api_extended import KaggleApi
 import pandas as pd
 import matplotlib.pyplot as plt
 from sklearn.model_selection import train_test_split
@@ -28,9 +28,9 @@ def column_stat(analyzed_set, column_name):
 
 
 # Pobieranie danych
-#api = KaggleApi()
-#api.authenticate()
-#api.dataset_download_files('arushchillar/disneyland-reviews', unzip=True)
+api = KaggleApi()
+api.authenticate()
+api.dataset_download_files('arushchillar/disneyland-reviews', unzip=True)
 disney = pd.read_csv('DisneylandReviews.csv', encoding='latin-1')
 
 # Nie zauważyłem w pliku żadnych artefaktów, które trzeba wyczyścić