ium_z434686/Jenkinsfile_create_dataset

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pipeline {
agent any
//Definijuemy parametry, które będzie można podać podczas wywoływania zadania
parameters{
string(
defaultValue: 'patrykgaka',
description: 'Kaggle username',
name: 'KAGGLE_USERNAME',
trim: false
)
password(
defaultValue: 'd14370cec1714b0cd1ef2875038b5950',
description: 'Kaggle token taken from kaggle.json file, as described in https://github.com/Kaggle/kaggle-api#api-credentials',
name: 'KAGGLE_KEY'
)
string(
defaultValue: '500',
description: 'CUTOFF',
name: 'CUTOFF',
trim: false
)
}
stages {
stage('clear_before') {
steps {
sh 'rm -rf *'
}
}
stage('Clone Git') {
steps {
sh 'git clone https://git.wmi.amu.edu.pl/s434686/ium_z434686'
}
}
stage('Build') {
steps {
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
"KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
sh 'kaggle datasets download -d rush4ratio/video-game-sales-with-ratings'
sh 'unzip video-game-sales-with-ratings.zip -d ./ium_z434686'
}
}
}
stage('Docker') {
agent {
dockerfile {
filename 'Dockerfile'
dir 'ium_z434686'
reuseNode true
}
}
steps {
sh 'python ./ium_z434686/create-dataset.py'
sh 'python ./ium_z434686/train.py'
sh 'python ./ium_z434686/predict.py'
archiveArtifacts 'X_test.csv'
archiveArtifacts 'X_dev.csv'
archiveArtifacts 'X_train.csv'
archiveArtifacts 'Y_test.csv'
archiveArtifacts 'Y_dev.csv'
archiveArtifacts 'Y_train.csv'
archiveArtifacts 'prediction.csv'
}
}
stage('clear_after') {
steps {
sh 'rm -rf *'
}
}
post {
always {
build job: 'z-s434686-training'
}
}
}