Add 'Jenkinsfile_create_dataset'
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Jenkinsfile_create_dataset
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78
Jenkinsfile_create_dataset
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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: 'kaggletests',
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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: '',
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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: '0',
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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_all') {
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steps {
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//Wypisz wartość parametru w konsoli (To nie jest polecenie bash, tylko groovy!)
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sh 'rm -rf *'
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}
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}
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stage('checkout') {
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steps {
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//Wypisz wartość parametru w konsoli (To nie jest polecenie bash, tylko groovy!)
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sh 'git clone https://git.wmi.amu.edu.pl/s487174/ium_z487174'
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}
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}
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stage('Build') {
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steps {
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// Run the maven build
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withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
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"KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
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print 'DEBUG: parameter isFoo = ' + params.KAGGLE_KEY
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sh "export KAGGLE_USERNAME=${params.KAGGLE_USERNAME}"
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sh "export KAGGLE_KEY=${params.KAGGLE_KEY}"
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// sh 'kaggle datasets download -d bartoszpieniak/poland-cars-for-sale-dataset'
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// sh 'unzip archive.zip -d ./ium_z487174'
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}
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}
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}
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stage('BuildDocker') {
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steps {
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//Wypisz wartość parametru w konsoli (To nie jest polecenie bash, tylko groovy!)
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sh 'mkdir ./results'
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sh 'echo $KAGGLE_KEY'
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sh 'docker build -t datasets:1.0 ./ium_z487174'
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// sh 'pip3 install -r ./ium_z487174/requirements.txt'
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// sh 'python3 ./ium_z487174/dataset.py'
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}
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}
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stage('RunDocker') {
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steps {
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sh "docker run -e KAGGLE_USERNAME=$KAGGLE_USERNAME -e KAGGLE_KEY=$KAGGLE_KEY -v /var/lib/jenkins/workspace/z-s487174-create-dataset/results:/app/results datasets:1.0"
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}
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}
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stage('Goodbye!') {
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steps {
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echo 'Goodbye!'
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//Zarchiwizuj wynik
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//archiveArtifacts 'output.txt'
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archiveArtifacts 'results/train_data.csv, results/dev_data.csv, results/test_data.csv'
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}
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}
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}
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}
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