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