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@ -23,9 +23,9 @@ pipeline {
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stages {
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stage('Run create-dataset script') {
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steps {
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withEnv (["KAGGLE_USERNAME=${env.KAGGLE_USERNAME}", "KAGGLE_KEY=${env.KAGGLE_KEY}"]) {
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withEnv (["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}"]) {
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sh 'chmod +x create-dataset.py'
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sh 'python3 ./create-dataset.py $KAGGLE_KEY'
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sh 'python3 ./create-dataset.py $KAGGLE_USERNAME'
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}
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}
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}
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@ -11,8 +11,8 @@ from sklearn.model_selection import train_test_split
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def download_kaggle_dataset():
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print(sys.argv)
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os.environ["KAGGLE_USERNAME"] = sys.argv[1]
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os.environ["KAGGLE_KEY"] = sys.argv[2]
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os.environ["KAGGLE_USERNAME"] = "vskyper"
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os.environ["KAGGLE_KEY"] = sys.argv[1]
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kaggle = KaggleApi()
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kaggle.authenticate()
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kaggle.dataset_download_files("mlg-ulb/creditcardfraud", path="./", unzip=True)
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