2023-04-14 18:51:14 +02:00
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pipeline {
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agent any
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parameters {
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string(
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defaultValue: 'wojciechbatruszewicz',
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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: '50',
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description: 'dataset 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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2023-04-20 19:37:30 +02:00
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stage('Download dataset') {
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2023-04-14 18:51:14 +02:00
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steps {
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checkout scm
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2023-04-14 19:24:34 +02:00
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dir ('./createDataset') {
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sh 'ls -l'
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withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
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"KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
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2023-04-20 19:37:30 +02:00
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// sh 'chmod +x ./datasetScript.sh'
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// sh './datasetScript.sh'
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sh 'kaggle datasets download -d rishikeshkonapure/home-loan-approval'
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sh 'unzip -o home-loan-approval.zip'
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2023-04-14 19:24:34 +02:00
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}
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2023-04-14 18:51:14 +02:00
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}
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}
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}
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2023-04-20 19:37:30 +02:00
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stage('Docker') {
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steps {
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2023-04-20 19:41:12 +02:00
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script {
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2023-06-11 10:54:35 +02:00
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def dockerImage = docker.build("docker-image", "./docker")
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2023-04-20 19:41:12 +02:00
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dockerImage.inside {
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sh 'ls -l'
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2023-04-20 19:46:26 +02:00
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dir ('./createDataset') {
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sh 'ls -l'
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2023-04-20 19:53:26 +02:00
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sh 'python3 ./createDataset.py'
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2023-04-20 19:50:15 +02:00
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archiveArtifacts 'home_loan_train.csv'
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archiveArtifacts 'home_loan_test.csv'
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archiveArtifacts 'home_loan_val.csv'
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2023-04-20 19:46:26 +02:00
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}
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2023-04-20 19:41:12 +02:00
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}
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}
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2023-04-20 19:37:30 +02:00
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}
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}
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2023-06-11 11:38:25 +02:00
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stage('triggerTrain') {
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steps {
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2023-06-11 11:40:58 +02:00
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build job: "z-s487179-training", wait: true
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2023-06-11 11:38:25 +02:00
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}
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}
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2023-04-20 19:37:30 +02:00
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// stage('Archive file') {
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// steps {
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// dir ('./createDataset') {
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// archiveArtifacts artifacts: 'loan_sanction_shuffled.csv', fingerprint: true\
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// }
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// }
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// }
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2023-04-14 18:51:14 +02:00
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}
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}
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