resolve conflict
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commit
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32
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# Nasz obraz będzie dzidziczył z obrazu Ubuntu w wersji latest
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# Latest Ubuntu as starter
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FROM ubuntu:latest
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FROM ubuntu:latest
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# Instalujemy niezbędne zależności. Zwróć uwagę na flagę "-y" (assume yes)
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# Install required dependencies
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RUN pip install --user kaggle
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RUN apt update
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RUN pip install --user pandas
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RUN export PATH=”$PATH:/usr/local/bin/python”
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RUN pip install --user scikit-learn
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RUN apt install python3-pip -y
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RUN pip install --user matplotlib
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RUN apt install unzip -y
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RUN pip install kaggle
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RUN pip install pandas
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RUN pip install scikit-learn
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RUN pip install matplotlib
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RUN mkdir ~/.kaggle/
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RUN echo '{"username":"wirus006","key":"c3323e37d3f91a0914d0172ef3c7c30c"}' > ~/.kaggle/kaggle.json
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# Stwórzmy w kontenerze (jeśli nie istnieje) katalog /app i przejdźmy do niego (wszystkie kolejne polecenia RUN, CMD, ENTRYPOINT, COPY i ADD będą w nim wykonywane)
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# Create app directory in image
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WORKDIR /app
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WORKDIR /app
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# Skopiujmy nasz skrypt do katalogu /app w kontenerze
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# Copy init dataset script to /app directory in image
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COPY ./init.py ./app
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COPY ./init.py ./
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# Domyślne polecenie, które zostanie uruchomione w kontenerze po jego starcie
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# Download kaggle dataset
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CMD python3 init.py
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RUN kaggle datasets download -d hakeem/atp-and-wta-tennis-data
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RUN unzip -o atp-and-wta-tennis-data.zip
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# Script executed after docker run
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CMD python3 ./init.py
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54909
result.csv
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54909
result.csv
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