ium_458023/JenkinsfileCreateDataset

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pipeline {
agent {
dockerfile {
filename 'lab4.dockerfile'
reuseNode true
}
}
parameters{
string(
defaultValue: 'mattkrawl',
description: 'Kaggle username',
name: 'KAGGLE_USERNAME',
trim: false
)
password(
defaultValue: 'c21878a7463faa44361330ffbcea68a6',
description: 'Kaggle token taken from kaggle.json file, as described in https://github.com/Kaggle/kaggle-api#api-credentials',
name: 'KAGGLE_KEY'
)
string(
defaultValue: '1000',
description: 'CUTOFF',
name: 'CUTOFF',
trim: false
)
}
stages {
stage('Checkout') {
steps {
checkout scmGit(
branches: [[name: '*/master']],
extensions: [cleanBeforeChceckout()],
userRemoteConfigs: [[url: 'https://git.wmi.amu.edu.pl/s458023/ium_458023.git']]
)
}
}
stage('Prepare data'){
steps{
//running Build
withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
"KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
// downloading and unzipping kaggle dataset
sh 'echo "{\"username\":\"$KAGGLE_USERNAME\",\"key\":\"$KAGGLE_KEY\"}" > /.kaggle/kaggle.json'
sh './get-data.sh'
sh 'python3 prepare_dataset.py'
}
}
}
stage('Archive artifacts'){
steps{
withEnv(["CUTOFF=${params.CUTOFF}"]){
archiveArtifacts 'wines_test.csv'
archiveArtifacts 'wines_dev.csv'
archiveArtifacts 'wines_train.csv'
}
}
}
}
}