fix jenkinsfile-create-dataset

lab2/Jenkinsfile_create_dataset

@@ -1,23 +1,51 @@
 pipeline {
-    agent any
+    agent none
-    parameters {
+/*    parameters {
         string(defaultValue: '6000',
             description: 'numbers of data entries to keep in train.csv',
             name: 'CUTOFF',
             trim: true)
     }
+*/
     stages {
-        stage('sh: Shell Script') {
+        stage('copy files') {
+            agent any
+                steps {
+                    sh '''
+                        cp ./lab1/script.sh .
+                        cp ./lab1/python_script.py .
+                        cp ./lab3/Dockerfile .
+                        cp ./lab3/requirements.txt .
+                        '''
+                }
+        }
+/*        stage('sh: Shell Script') {
             steps {
                 withEnv(["KAGGLE_USERNAME=${params.KAGGLE_USERNAME}",
                 "KAGGLE_KEY=${params.KAGGLE_KEY}" ]) {
-                    sh 'chmod +x ./lab2/script-zadanie-2-4.sh'
+                    sh ''' chmod +x ./lab2/script-zadanie-2-4.sh
-                    sh './lab2/script-zadanie-2-4.sh'
+                            ./lab2/script-zadanie-2-4.sh
-                    sh 'chmod +x ./lab2/script-zadanie-2-4-cutoff.sh'
+                            chmod +x ./lab2/script-zadanie-2-4-cutoff.sh'''
                     sh "./lab2/script-zadanie-2-4-cutoff.sh ${params.CUTOFF}"
                 }
             }
         }
+*/
+        stage('docker') {
+            agent {
+                dockerfile true
+            }
+            stages {
+                stage('test') {
+                    steps {
+                    sh 'cat /etc/issue'
+                    }
+                }
+                stage('actual') {
+                    steps {
+                    sh './script.sh'
+                    }
+                }
                 stage('archive artifacts') {
                     steps {
                         archiveArtifacts 'train.csv'
@@ -27,3 +55,5 @@ pipeline {
                 }
             }
         }
+    }
+}

lab3/Dockerfile

@@ -0,0 +1,19 @@
+FROM ubuntu:latest
+
+RUN apt update >>/dev/null
+RUN apt install -y apt-utils >>/dev/null
+RUN apt install -y python3.8 >>/dev/null
+RUN apt install -y python3-pip >>/dev/null
+RUN apt install -y unzip >>/dev/null
+
+WORKDIR /app
+
+COPY ./python_script.py ./
+COPY ./script.sh ./
+RUN chmod +x script.sh
+
+COPY ./requirements.txt ./
+
+RUN pip3 install -r requirements.txt >>/dev/null
+
+CMD ./script.sh

lab3/python_script.py

@@ -0,0 +1,37 @@
+import pandas as pd
+
+from sklearn import preprocessing
+from sklearn.model_selection import train_test_split
+
+
+df = pd.read_csv('smart_grid_stability_augmented.csv')
+scaler = preprocessing.StandardScaler().fit(df.iloc[:, 0:-1])
+df_norm_array = scaler.transform(df.iloc[:, 0:-1])
+df_norm = pd.DataFrame(data=df_norm_array,
+                       columns=df.columns[:-1])
+df_norm['stabf'] = df['stabf']
+
+train, testAndValid = train_test_split(
+    df_norm,
+    test_size=0.2,
+    random_state=42,
+    stratify=df_norm['stabf'])
+
+test, valid = train_test_split(
+    testAndValid,
+    test_size=0.5,
+    random_state=42,
+    stratify=testAndValid['stabf'])
+
+
+def namestr(obj, namespace):
+    return [name for name in namespace if namespace[name] is obj]
+
+
+dataset = df_norm
+for x in [dataset, train, test, valid]:
+    print([q for q in namestr(x, globals()) if len(q) == max([len(w) for w in namestr(x, globals())])][-1])
+    print("size:", len(x))
+    print(x.describe(include='all'))
+    print("class distribution", x.value_counts('stabf'))
+    print('===============================================================')

lab3/requirements.txt

@@ -0,0 +1,3 @@
+kaggle==1.5.12
+pandas==1.1.2
+sklearn==0.0

lab3/script.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+
+kaggle datasets download -d 'pcbreviglieri/smart-grid-stability' >>/dev/null 2>&1
+unzip smart-grid-stability.zip >>/dev/null 2>&1
+
+python3 python_script.py