IUM_04 - back to old Jenkinsfile, old download_dataset script
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42
Jenkinsfile
vendored
42
Jenkinsfile
vendored
@ -1,15 +1,5 @@
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pipeline {
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agent {
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dockerfile {
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filename 'Dockerfile'
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reuseNode true
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}
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}
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environment {
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KAGGLE_USERNAME = credentials('KAGGLE_USERNAME')
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KAGGLE_KEY = credentials('KAGGLE_KEY')
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}
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agent any
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parameters {
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password (
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@ -36,18 +26,30 @@ pipeline {
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}
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}
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stage('Download dataset and preprocess data') {
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stage('Download dataset') {
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steps {
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script {
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sh "echo ${env.KAGGLE_USERNAME}"
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sh "echo ${KAGGLE_USERNAME}"
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sh "echo ${CUTOFF}"
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sh "echo ${params.CUTOFF}"
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sh "chmod +x ./download_dataset.py"
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sh "python3 ./download_dataset.py ${params.CUTOFF}"
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archiveArtifacts artifacts: 'datasets/*', onlyIfSuccessful: true
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withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}"]) {
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sh "kaggle datasets download -d uciml/breast-cancer-wisconsin-data"
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sh "unzip -o breast-cancer-wisconsin-data.zip"
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sh "mkdir -p datasets"
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sh "mv data.csv datasets/data.csv"
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}
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}
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}
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stage('Preprocess data') {
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agent {
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dockerfile {
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filename 'Dockerfile'
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reuseNode true
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}
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}
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steps {
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sh "chmod +x ./download_dataset.py"
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sh "python3 ./download_dataset.py ${params.CUTOFF}"
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archiveArtifacts artifacts: 'datasets/*', onlyIfSuccessful: true
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}
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}
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}
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}
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@ -1,13 +1,13 @@
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# Necessary imports
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import pandas as pd
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import kaggle
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# import kaggle
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import sys
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from sklearn.model_selection import train_test_split
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from sklearn.preprocessing import MinMaxScaler
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# Download the dataset
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kaggle.api.authenticate()
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kaggle.api.dataset_download_files('uciml/breast-cancer-wisconsin-data', path='./datasets', unzip=True)
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# kaggle.api.authenticate()
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# kaggle.api.dataset_download_files('uciml/breast-cancer-wisconsin-data', path='./datasets', unzip=True)
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# Load the dataset
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df = pd.read_csv('./datasets/data.csv', index_col='id')
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