pipeline {
    agent { 
        dockerfile {
            args '-v /mlruns:/mlruns'
        }
    }
    parameters{
        string(
            defaultValue: '5', 
            description: 'Epoch number', 
            name: 'EPOCH_NUMBER'
        )
    }
    stages {
        stage('conda') {
            sh 'conda env create -f environment.yml'
            sh 'conda activate myenv'
        }
        stage('Copy') {
            steps {
                copyArtifacts projectName: 's444417-create-dataset'
                sh 'ls -la'
                sh 'echo $EPOCH_NUMBER'
                sh 'python3 ./lab8/trainScript.py'
            }
        }
        stage('Archive') {
            steps {
                dir('saved_model') {
                    archiveArtifacts artifacts: '**/**'
                }
                dir('my_runs') {
                    archiveArtifacts artifacts: '**/**'
                }
            }
        }
        stage('Starting eval job') {
            steps {
                build job: 's444417-evaluation/master', wait: false
            }
        }
        stage('Archive mlflow') {
            steps {
                sh 'cd ./lab8'
                sh 'tar -czf mlruns.tar.gz mlruns/'
                archiveArtifacts 'mlruns.tar.gz'
            }
        }
    }
    options {
        copyArtifactPermission('s444417-evaluation');
    }
    post {
        always {
            emailext body: "${currentBuild.currentResult}", subject: 's444417-testing build status', to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
        }
    }
}