ium_487184/Jenkinsfile

pipeline {
   agent any
   parameters {
     string(
            defaultValue: 'bartekmalanka',
            description: 'Kaggle username',
            name: 'KAGGLE_USERNAME',
            trim: false
         )
      password(
         defaultValue: '',
         description: 'Kaggle token taken from kaggle.json file, as described in https://github.com/Kaggle/kaggle-api#api-credentials',
         name: 'KAGGLE_KEY'
      )
      string(
            defaultValue: '30',
            description: 'dataset cutoff',
            name: 'CUTOFF',
            trim: false
         )
   }
   stages {
      stage('Download dataset') {
         steps {
            checkout scm
            sh 'ls -l'
            withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
                "KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
                sh 'kaggle datasets download -d elakiricoder/gender-classification-dataset'
                sh 'unzip -o gender-classification-dataset.zip'
            }
         }
      }
      stage('Docker') {
        steps {
               script {
                  def dockerImage = docker.build("docker-image", "./")
                  dockerImage.inside {
                        sh 'ls -l'
                        sh 'ls -l'
                        sh 'python3 createDataset.py'
                        archiveArtifacts 'gender_classification_train.csv'
                        archiveArtifacts 'gender_classification_test.csv'
                        archiveArtifacts 'gender_classification_val.csv'
                     sh 'ls -l'
                  }  
            }
        }
      }           
   }
   post {
        success {
            build job: 'z-s487184-training/main', wait: false
        }
    }
}