zadanie doker
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22
Dockerfile
22
Dockerfile
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FROM python:3.9
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RUN pip install --user kaggle
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RUN pip install --user pandas
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ADD . .
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ARG KAGGLE_USERNAME
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ARG KAGGLE_KEY
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RUN chmod a+x *.sh
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RUN ./dataset_download.sh
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CMD python kagle.py
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FROM ubuntu:latest
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WORKDIR /ium
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RUN apt update && apt install -y python3-pip
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RUN pip3 install pandas
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RUN pip3 install numpy
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RUN pip3 install sklearn
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COPY ./Steam-200k.csv ./
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COPY ./kagle.py ./
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41
Jenkinsfile
vendored
41
Jenkinsfile
vendored
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pipeline {
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parameters {
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string(
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defaultValue: 'szymonjadczak',
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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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}
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agent {
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dockerfile {
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additionalBuildArgs "--build-arg KAGGLE_USERNAME=${params.KAGGLE_USERNAME} --build-arg KAGGLE_KEY=${params.KAGGLE_KEY} -t s444386-create-dataset"
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agent {
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dockerfile true
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}
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stages {
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stage('Stage 1') {
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steps {
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sh 'chmod u+x ./kagle.py'
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sh 'python3 kagle.py'
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}
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}
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}
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}
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environment {
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KAGGLE_USERNAME="$params.KAGGLE_USERNAME"
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KAGGLE_KEY="$params.KAGGLE_KEY"
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CUTOFF="$params.CUTOFF"
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}
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stages {
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stage('Stage 1') {
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steps {
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echo 'Hello world!!!'
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checkout([$class: 'GitSCM', branches: [[name: '*/master']], extensions: [], userRemoteConfigs: [[url: 'https://git.wmi.amu.edu.pl/s444386/ium_444386']]])
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archiveArtifacts 'Steam-200k.csv'
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}
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}
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}
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}
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4
kagle.py
4
kagle.py
@ -2,8 +2,8 @@ import os
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import pandas as pd
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from sklearn.model_selection import train_test_split
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os.system("kaggle datasets download -d tamber/steam-video-games")
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os.system("unzip -o steam-video-games.zip")
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#os.system("kaggle datasets download -d tamber/steam-video-games")
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#os.system("unzip -o steam-video-games.zip")
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steam=pd.read_csv('Steam-200k.csv',usecols=[0,1,2,3],names=['userId','game','behavior','hoursPlayed'])
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steam.isnull().values.any()
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