pipeline{
    agent any

    parameters {
        gitParameter(
            name: 'BRANCH',
            type: 'branch',
            defaultValue: 'master',
            description: 'Select the branch of training'
        )

        buildSelector(
            name: 'BUILD_SELECTOR',
            description: 'Which build to use for copying artifacts',
            defaultSelector: lastSuccessful()
        )
    }

    stages{
         stage('Copy model artifacts with test dataset') {
            steps {
                script {
                    // Biblioteka w Jenkis automatycznie dopisuje origin przed nazwą brancha
                    // dlatego wprowadziłem poniższe przekształcenie
                    def branchName = params.BRANCH ?: 'master'
                    branchName = branchName.replaceFirst('origin/', '')

                    def myProject = "z-s487175-training/${branchName}"
                    copyArtifacts(
                        projectName: myProject,
                        fingerprintArtifacts: true,
                        selector: buildParameter('BUILD_SELECTOR')
                    )
                }
            }
        }

        stage('Prediction on Test Dataset'){
            steps{
                // Nadanie uprawnień
                sh "docker run -v ${env.WORKSPACE}:/app ium chmod 777 /app/model_with_data.pickle"
                // Pobranie numeru builda
                script {
                    // Pobranie numeru builda
                    def buildNumber = currentBuild.number
                    // Uruchomienie skryptu
                    sh "docker run -v ${env.WORKSPACE}:/app ium python3 /app/DL-prediction.py --build-number=${buildNumber}"
                }
            }
        }

        stage('Archive prediction results'){
            steps{
                sh "docker cp \$(docker ps -l -q):/app/results_prediction.csv ${env.WORKSPACE}"
                sh "docker cp \$(docker ps -l -q):/app/metrics.csv ${env.WORKSPACE}"
                archiveArtifacts artifacts: 'results_prediction.csv, metrics.csv', fingerprint: true
            }
        }
    }
}