pipeline {
   agent any
   //Definijuemy parametry, które będzie można podać podczas wywoływania zadania
   parameters {
      string(
         defaultValue: '1000',
         description: 'Amount of values to be used from dataset',
         name: 'CUTOFF',
         trim: false
      )
      string(
         defaultValue: 'wleczny',
         description: 'Kaggle username',
         name: 'KAGGLE_USERNAME',
         trim: false
      )
      password(
         defaultValue: '2e89e20ceb0a48d9df01a01bad744776',
         description: 'Kaggle token',
         name: 'KAGGLE_KEY'
      )
   }
   stages {
      stage('Checkout') {
         steps {
            sh 'rm -rf ium_z487183'
            sh 'git clone https://git.wmi.amu.edu.pl/s487183/ium_z487183.git'
         }
      }
      stage('Prepare data') {
         steps {
            withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}"]) {
               sh 'ium_z487183/get-data.sh'
               sh 'python3 ium_z487183/prepare_dataset.py'
            }
         }
      }
      stage('Archive artifacts') {
         agent { 
            dockerfile {
               filename 'CreateDataset.dockerfile'
               dir      'ium_z487183'
               reuseNode true
            }
         }
         steps {
            withEnv(["CUTOFF=${params.CUTOFF}"]) {
               archiveArtifacts 'X_test.csv'
               archiveArtifacts 'X_val.csv'
               archiveArtifacts 'X_train.csv'
               archiveArtifacts 'Y_test.csv'
               archiveArtifacts 'Y_val.csv'
               archiveArtifacts 'Y_train.csv'
            }
         }
      }
   }
}