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pythoninthegrasspythoninthegrass
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Poetry + Docker
Docker FTW <3
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‎.dockerignore‎

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**/.project
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**/.settings
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**/.toolstarget
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**/.venv
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**/.vs
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**/.vscode
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**/*.*proj.user
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**/*.dbmdl
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**/*.example
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**/*.jfm
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**/*.py#
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**/*.py~
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**/*.pyc
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**/*test.*
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**/azds.yaml
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**/bin
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**/charts
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**/django
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**/docker-compose*
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**/Dockerfile*
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**/heroku.yml
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**/img
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**/node_modules
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**/npm-debug.log
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**/obj
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**/pre-commit-config.yaml
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**/Procfile
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**/README.md
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**/runtime.txt
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**/secrets.dev.yaml
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**/terraform
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**/values.dev.yaml

‎.env.example‎

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JUPYTER_TOKEN=docker
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PORT=8888

‎.gitignore‎

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django/data/
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django/manage.py
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*.sqlite
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redis*
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!redis.conf.example
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*.pem
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*.key
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raw/
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gitleaks_report*.json
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# Byte-compiled / optimized / DLL files

‎.pre-commit-config.yaml‎

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repos:
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# checks for secrets via rules (gitleaks.toml)
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- repo: https://github.com/zricethezav/gitleaks
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rev: v8.9.0
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rev: v8.13.0
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hooks:
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- id: gitleaks
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- repo: https://github.com/ambv/black
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rev: 22.6.0
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rev: 22.8.0
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hooks:
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- id: black
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- repo: https://gitlab.com/pycqa/flake8

‎Dockerfile‎

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# using ubuntu LTS version
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FROM ubuntu:22.04 AS builder-image
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# avoid stuck build due to user prompt
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ARG DEBIAN_FRONTEND=noninteractive
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RUN apt-get -qq update \
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&& apt-get -qq install \
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--no-install-recommends -y \
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aptitude \
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autoconf \
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automake \
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build-essential \
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ca-certificates \
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curl \
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git \
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locales \
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libbz2-dev \
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libffi-dev \
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libncurses-dev \
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libreadline-dev \
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libsqlite3-dev \
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libssl-dev \
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libtool \
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libxslt-dev \
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libyaml-dev \
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python3 \
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python3-dev \
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python3-pip \
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sqlite3 \
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unixodbc-dev \
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unzip \
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&& rm -rf /var/lib/apt/lists/*
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# Set locale
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RUN locale-gen en_US.UTF-8
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ENV LANG=en_US.UTF-8
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ENV LANGUAGE=en_US:en
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ENV LC_ALL=en_US.UTF-8
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ARG USERNAME=appuser
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ENV HOME="/home/${USERNAME}"
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ENV PATH="$HOME/.asdf/bin:$HOME/.asdf/shims:$PATH"
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RUN useradd --create-home $USERNAME
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# install asdf then python latest
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RUN bash -c "git clone --depth 1 https://github.com/asdf-vm/asdf.git $HOME/.asdf \
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&& echo '. $HOME/.asdf/asdf.sh' >> $HOME/.bashrc \
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&& echo '. $HOME/.asdf/asdf.sh' >> $HOME/.profile"
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RUN asdf plugin-add python \
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&& asdf install python 3.10.7 \
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&& asdf global python 3.10.7
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# TODO: test poetry via asdf
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ENV POETRY_HOME="$HOME/.poetry"
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RUN curl -sSL https://install.python-poetry.org | python3.10 -
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ENV PATH "${POETRY_HOME}/bin:$PATH"
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WORKDIR $$HOME/app
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COPY pyproject.toml poetry.lock ./
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RUN python3.10 -m venv /opt/venv
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# Install pip requirements
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RUN . /opt/venv/bin/activate && poetry install
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# TODO: dive + docker-slim
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FROM ubuntu:22.04 AS runner-image
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ARG USERNAME=appuser
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ENV HOME="/home/${USERNAME}"
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ENV VIRTUAL_ENV="/opt/venv"
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ENV PATH="${VIRTUAL_ENV}/bin:$HOME/.asdf/bin:$HOME/.asdf/shims:$PATH"
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RUN useradd --create-home $USERNAME \
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&& mkdir -p ${HOME}/app
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COPY --chown=${USERNAME}:${USERNAME} . $HOME/app
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COPY --from=builder-image --chown=${USERNAME}:${USERNAME} /opt/venv /opt/venv
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COPY --from=builder-image --chown=${USERNAME}:${USERNAME} $HOME/.asdf $HOME/.asdf
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# avoid stuck build due to user prompt
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ARG DEBIAN_FRONTEND=noninteractive
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RUN apt-get -qq update \
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&& apt-get -qq install \
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--no-install-recommends -y \
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ca-certificates \
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curl \
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git \
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libsqlite3-dev \
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sqlite3 \
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&& rm -rf /var/lib/apt/lists/*
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FROM jupyter/minimal-notebook:latest
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# Keeps Python from generating .pyc files in the container
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ENV PYTHONDONTWRITEBYTECODE=1
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# Turns off buffering for easier container logging
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ENV PYTHONUNBUFFERED=1
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# activate virtual environment
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RUN python -m venv $VIRTUAL_ENV
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USER jovyan
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COPY . $HOME/work
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USER appuser
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WORKDIR $HOME/work
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WORKDIR $HOME/app
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RUN conda install \
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xarray \
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netCDF4 \
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bottleneck \
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numpy \
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pandas \
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matplotlib \
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jupyterlab
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# ENTRYPOINT ["python", "main.py"]
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# CMD ["gunicorn", "-c", "config/gunicorn.conf.py", "main:app"]
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CMD ["/bin/bash", "startup.sh"]
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# CMD ["/bin/bash"]

‎README.md‎

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# python_template
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# wine_quality
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!["It's dangerous to go alone! Take this."](img/zelda.jpg)
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<!-- <img src="https://user-images.githubusercontent.com/4097471/144654508-823c6e31-5e10-404c-9f9f-0d6b9d6ce617.jpg" width="300"> -->
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![JupyterLab](img/jupyterlab.png)
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## Summary
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Oftentimes the initial setup of a Python repo can take a few minutes to a couple hours.
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By laying the foundation to rapidly implement an idea, can focus on the good bits instead of
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devops drudgery.
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### Caveat Emptor
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Very little of this gets tested on Windows hosts. Windows Subsystem for Linux (WSL) is used where necessary with the default Ubuntu LTS install. Moved bulk of document to the [markdown](markdown/) directory to opt-in vs. opt-out of documentation.
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Be the change et al if Windows is your main and you wanna raise a PR with broad instructions on getting tooling working under Windows (e.g., docker, poetry, playwright.)
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Udacity course on data science.
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**Table of Contents**
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* [python_template](#python_template)
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* [wine_quality](#wine_quality)
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* [Summary](#summary)
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* [Caveat Emptor](#caveat-emptor)
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* [Setup](#setup)
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* [Usage](#usage)
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* [Mac and Linux users](#mac-and-linux-users)
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* [Poetry](#poetry)
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* [Docker](#docker)
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* [Both](#both)
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* [TODO](#todo)
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* [Further Reading](#further-reading)
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## Setup
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* Install
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* [editorconfig](https://editorconfig.org/)
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* [wsl](https://docs.microsoft.com/en-us/windows/wsl/setup/environment)
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* [asdf](https://asdf-vm.com/guide/getting-started.html#_2-download-asdf)
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* [poetry](https://python-poetry.org/docs/)
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* [docker-compose](https://docs.docker.com/compose/install/)
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* [playwright](https://playwright.dev/python/docs/intro#installation)
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* [Kubernetes (k8s)](markdown/kubernetes.md)
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* [docker](https://docs.docker.com/compose/install/)
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* Download CSVs from [here](https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/)
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* Move to `csv` directory
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## Usage
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### Mac and Linux users
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Development environments and tooling are first-class citizens on macOS and *nix. For Windows faithfuls, please setup [WSL](markdown/wsl.md).
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### Poetry
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* Install requirements via Poetry:
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```bash
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poetry install
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poetry run ipython kernel install --name "python3.10.7" --user
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```
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* Run Jupyter Lab
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```bash
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poetry shell
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jupyter lab --ip=0.0.0.0 --port=8888 --no-browser
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```
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* Quit the server via `ctrl-c` in the terminal
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* Enter `deactivate` to exit the Poetry virtual environment
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### Docker
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* Customize the `.env.example` and rename to `.env`
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* General commands
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```bash
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# build image locally
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docker-compose build --pull --no-cache
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# start container
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docker-compose up -d
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# stop container
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docker-compose stop
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# remove container and network
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docker-compose down
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```
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### Both
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* Open a browser and navigate to `http://127.0.0.1:888`
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* Docker uses the token specified in `.env`
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* Select the "python3.10.7" kernel if asked
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* Open `refactor-wine-quality.ipynb` from the left-hand column
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* Run cells by selecting them and pressing `shift-enter`
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## TODO
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* Django
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* Merge with [docker_python](https://github.com/pythoninthegrass/docker_python) and put the latter on an ice float
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* Flask
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* Bonus points for [Svelte](https://svelte.dev/blog/the-easiest-way-to-get-started) front-end ❤️
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* FastAPI
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* MongoDB
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* Switch to `docker-compose`
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* Fix unique index deleting too many keys
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* k8s
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* `~/.kubeconfig`
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* ansible
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* wsl
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* VSCode
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* Remote WSL install and usage
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* Or at least further reading nods
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* Debugging
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* Dependencies
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* script itself via [icecream](https://github.com/gruns/icecream)
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* Get Jupyter working in [VSCode](https://github.com/microsoft/vscode-jupyter)
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* `Makefile`
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## Further Reading
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[Starting JupyterLab](https://jupyterlab.readthedocs.io/en/stable/getting_started/starting.html)
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[Jupyter Docker Stacks — Docker Stacks documentation](https://jupyter-docker-stacks.readthedocs.io/en/latest/index.html)
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[Dockerizing Jupyter Projects](https://towardsdatascience.com/dockerizing-jupyter-projects-39aad547484a)

‎compose.yml‎

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version: "3.9"
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services:
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jupyter:
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image: jupyter/minimal-notebook:latest
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tty: true # false for `entrypoint` in Dockerfile
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stdin_open: true # false for `entrypoint` in Dockerfile
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env_file:
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- ./.env
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volumes:
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- .:/home/jovyan/work
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ports:
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- 8888:${PORT:-8888}
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build:
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context: ./
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dockerfile: ./Dockerfile
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networks:
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default:
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driver: bridge

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