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31ffbd656c
...
8eb731b53f
38
Jenkinsfile
vendored
38
Jenkinsfile
vendored
@ -1,36 +1,10 @@
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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: 'piotrwrzodak',
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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: '1000',
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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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agent any
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stages {
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stage('Build') {
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steps {
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sh 'git clone https://git.wmi.amu.edu.pl/s444510/ium_z444510.git'
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withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
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sh 'kaggle datasets download -d thedevastator/airbnb-prices-in-european-cities'
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sh 'unzip airbnb-prices-in-european-cities.zip -d ./ium_z444510'
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sh 'rm airbnb-prices-in-european-cities.zip'
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sh 'ls -a'
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sh 'ls -a ./ium_z444510'
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stage('Stage 1') {
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steps {
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echo 'Hello world!'
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}
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}
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}
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}
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}
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}
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}
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@ -1,17 +0,0 @@
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import pandas as pd
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import os
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import numpy as np
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cutoff = int(os.environ['CUTOFF'])
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data = pd.read_csv('./ium_z444510/barcelona_weekends.csv')
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data = data.sample(cutoff)
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data = data.iloc[:, 1:]
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train_set, dev_set, test_set = np.split(data.sample(frac=1, random_state=42),
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[int(.6 * len(data)), int(.8 * len(data))])
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train_set.to_csv('train.csv', index=False)
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dev_set.to_csv('dev.csv', index=False)
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test_set.to_csv('test.csv', index=False)
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