Jenkinsfile

@@ -1,35 +1,9 @@
 pipeline {
     agent any
-    parameters{
-     string(
-         defaultValue: 'piotrwrzodak',
-         description: 'Kaggle username',
-         name: 'KAGGLE_USERNAME',
-         trim: false
-     )
-     password(
-         defaultValue: '',
-         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('Build') {
+        stage('Stage 1') {
             steps {
-            sh 'git clone https://git.wmi.amu.edu.pl/s444510/ium_z444510.git'
-            withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}", "KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
-               sh 'kaggle datasets download -d thedevastator/airbnb-prices-in-european-cities'
-               sh 'unzip airbnb-prices-in-european-cities.zip -d ./ium_z444510'
-               sh 'rm airbnb-prices-in-european-cities.zip'
-               sh 'ls -a'
-               sh 'ls -a ./ium_z444510'
-            }
+                echo 'Hello world!'
             }
         }
     }

create-dataset.py

@@ -1,17 +0,0 @@
-import pandas as pd
-import os
-import numpy as np
-
-
-cutoff = int(os.environ['CUTOFF'])
-
-data = pd.read_csv('./ium_z444510/barcelona_weekends.csv')
-data = data.sample(cutoff)
-data = data.iloc[:, 1:]
-
-train_set, dev_set, test_set = np.split(data.sample(frac=1, random_state=42),
-                                        [int(.6 * len(data)), int(.8 * len(data))])
-
-train_set.to_csv('train.csv', index=False)
-dev_set.to_csv('dev.csv', index=False)
-test_set.to_csv('test.csv', index=False)