pipeline {
    agent {
	    docker {
	        image 'zadanie'
	        args '-v /mlruns:/mlruns'
	    }
	}
	parameters {
		buildSelector(
			defaultSelector: lastSuccessful(),
			description: 'Which build to use for copying artifacts',
			name: 'BUILD_SELECTOR'
		)
		string(
            defaultValue: '100',
            description: 'number of epochs',
            name: 'EPOCH'
        )
	}
    stages {

		stage('Copy artifacts') {
			steps {
                copyArtifacts fingerprintArtifacts: true, projectName: 's444501-create-dataset', selector: buildParameter('BUILD_SELECTOR')
			}
		}
        stage('Train model') {
            steps {
                withEnv(["EPOCH=${params.EPOCH}"]) {
				    sh 'python biblioteki_ml.py $EPOCH'
				}
			}
		}
		stage('Archive artifacts') {
            steps {
				archiveArtifacts artifacts: 'model.pkl, neural_network_prediction_results.csv'
				archiveArtifacts artifacts: 'mlruns/**'
			}
		}
		stage ('Model - evaluation') {
            steps {
                build job: 's444501-evaluation/master', wait: false
            }
        }
	}
	post {
        always {
            emailext body: "${currentBuild.currentResult}", subject: 's444501-training', to: 'e19191c5.uam.onmicrosoft.com@emea.teams.ms'
        }
    }
}