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Memorandums
on windows

もくじ †

参考url
https://kino-code.com/docker_python/

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installing Python Env on Windows11 by Docker †

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Dockerfileの準備 †

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C:\Users\ryu\Desktop\MyDockerに以下の内容のファイルを作成する †

FROM --platform=linux/amd64 ubuntu:22.04

RUN apt-get update && apt-get install -y sudo wget vim curl gawk make gcc
RUN sudo apt-get install bzip2

RUN wget https://repo.continuum.io/archive/Anaconda3-2019.03-Linux-x86_64.sh && \
    sh Anaconda3-2019.03-Linux-x86_64.sh -b  && \
    rm -f Anaconda3-2019.03-Linux-x86_64.sh && \
    sudo curl -sL https://deb.nodesource.com/setup_16.x | sudo bash -  && \
    sudo apt-get install -y nodejs

ENV PATH $PATH:/root/anaconda3/bin

RUN pip install --upgrade pip
RUN pip install pandas_datareader
RUN pip install mplfinance

RUN wget --quiet http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz -O ta-lib-0.4.0-src.tar.gz && \
    tar xvf ta-lib-0.4.0-src.tar.gz && \
    cd ta-lib/ && \
    ./configure --prefix=/usr && \
    make && \
    sudo make install && \
    cd .. && \
    pip install TA-Lib && \
    rm -R ta-lib ta-lib-0.4.0-src.tar.gz

RUN mkdir /workspace

CMD ["jupyter-lab", "--ip=0.0.0.0","--port=8888" ,"--no-browser", "--allow-root", "--LabApp.token=''"]
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Dockerfileからイメージを作成 †

docker build -t jlab:latest C:¥¥Users¥¥ryu¥¥Desktop¥¥MyDocker
PS C:\Users\ryu\Desktop\MyDocker> docker build -t jlab:latest C:\Users\ryu\Desktop\MyDocker\
2023/05/27 20:50:55 http2: server: error reading preface from client //./pipe/docker_engine: file has already been closed
[+] Building 521.9s (13/13) FINISHED
 => [internal] load build definition from Dockerfile                                                               0.1s
 => => transferring dockerfile: 1.07kB                                                                             0.0s
 => [internal] load .dockerignore                                                                                  0.1s
 => => transferring context: 2B                                                                                    0.0s
 => [internal] load metadata for docker.io/library/ubuntu:22.04                                                    3.4s
 => [1/9] FROM docker.io/library/ubuntu:22.04@sha256:dfd64a3b4296d8c9b62aa3309984f8620b98d87e47492599ee20739e8eb5  4.6s
 => => resolve docker.io/library/ubuntu:22.04@sha256:dfd64a3b4296d8c9b62aa3309984f8620b98d87e47492599ee20739e8eb5  0.0s
 => => sha256:dfd64a3b4296d8c9b62aa3309984f8620b98d87e47492599ee20739e8eb54fbf 1.13kB / 1.13kB                     0.0s
 => => sha256:ca5534a51dd04bbcebe9b23ba05f389466cf0c190f1f8f182d7eea92a9671d00 424B / 424B                         0.0s
 => => sha256:3b418d7b466ac6275a6bfcb0c86fbe4422ff6ea0af444a294f82d3bf5173ce74 2.30kB / 2.30kB                     0.0s
 => => sha256:dbf6a9befcdeecbb8813406afbd62ce81394e3869d84599f19f941aa5c74f3d1 29.53MB / 29.53MB                   3.6s
 => => extracting sha256:dbf6a9befcdeecbb8813406afbd62ce81394e3869d84599f19f941aa5c74f3d1                          0.7s
 => [2/9] RUN apt-get update && apt-get install -y sudo wget vim curl gawk make gcc                              147.7s
 => [3/9] RUN sudo apt-get install bzip2                                                                           2.3s
 => [4/9] RUN wget https://repo.continuum.io/archive/Anaconda3-2019.03-Linux-x86_64.sh &&     sh Anaconda3-2019  231.6s
 => [5/9] RUN pip install --upgrade pip                                                                            3.4s
 => [6/9] RUN pip install pandas_datareader                                                                        2.0s
 => [7/9] RUN pip install mplfinance                                                                               1.8s
 => [8/9] RUN wget --quiet http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz -O ta-lib-0.4.0-src  99.5s
 => [9/9] RUN mkdir /workspace                                                                                     0.6s
 => exporting to image                                                                                            24.9s
 => => exporting layers                                                                                           24.9s
 => => writing image sha256:6259009c19b1cb65a6025a23efc2e78e753b7b707afbd0cdebb1fe1ac7e95685                       0.0s
 => => naming to docker.io/library/jlab:latest                                                                     0.0s
PS C:\Users\ryu\Desktop\MyDocker>
PS C:\Users\ryu\Desktop\MyDocker> docker images
REPOSITORY   TAG       IMAGE ID       CREATED         SIZE
jlab         latest    6259009c19b1   8 minutes ago   3.9GB

REPOSITORYという項目に「jlab」という名前のイメージがあれば問題ありません。
このとき作成したイメージのIMAGE IDをメモしておいてください。

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コンテナの作成、実行 †

続いて作成したイメージからコンテナを作成しましょう。

docker run -p 8888:8888 --name jlab IMAGE ID
docker run -p 8888:8888 --name jlab 6259009c19b1

on windows

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