pipeline { agent any parameters{ string( defaultValue: 'mattkrawl', description: 'Kaggle username', name: 'KAGGLE_USERNAME', trim: false ) password( defaultValue: '8e6132e627c5c176f7e19d880270d22e', description: 'Kaggle token taken from kaggle.json file, as described in https://github.com/Kaggle/kaggle-api#api-credentials', name: 'KAGGLE_KEY' ) string( defaultValue: '100', description: 'CUTOFF', name: 'CUTOFF', trim: false ) } stages { stage('clear_all') { steps { sh 'rm -rf *' } } stage('Build'){ steps{ //cloning github sh 'git clone https://git.wmi.amu.edu.pl/s458023/ium_458023' //running Build withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}" ]) { // downloading and unzipping kaggle dataset sh 'kaggle datasets download -d arnabchaki/data-science-salaries-2023' sh 'unzip data-science-salaries-2023.zip -d ./ium_458023' // removing zip file sh 'rm data-science-salaries-2023.zip' sh 'ls -a' sh 'ls -a ./ium_458023' } } } stage('Docker'){ agent{ dockerfile{ filename 'Dockerfile' dir 'ium_458023' reuseNode true } } steps{ sh 'ls -a' sh 'python ium_458023/create-dataset.py' archiveArtifacts 'salary_test.csv' archiveArtifacts 'salary_dev.csv' archiveArtifacts 'salary_train.csv' } } } }