Dockerfile-quickstart

# >>>>>>>>>>>>>>>>>>>>>>>>>>>
# Auto-generated by agi-pack.
FROM debian:buster-slim AS sklearn-base

# Setup environment variables
ENV PROJECT agi
ENV PYENV agi-py38
ENV PYTHON_VERSION 3.8.10
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONUNBUFFERED 1
ENV PYTHONWARNINGS ignore

# Setup conda paths
ENV CONDA_PATH=/opt/conda/envs/${PYENV}
ENV CONDA_PREFIX=${CONDA_PATH}
ENV CONDA_EXE=${CONDA_PATH}/bin/conda
ENV PATH=${CONDA_PATH}/bin:/opt/conda/bin:$PATH
ENV CONDA_DEFAULT_ENV ${PYENV}

# Install system packages
RUN apt-get -y update \
    && apt-get -y install \
    curl git \
    wget \
    build-essential \
    && apt-get -y autoclean \
    && apt-get -y autoremove \
    && rm -rf /var/lib/apt/lists/*

# Install mambaforge
RUN curl -sLo ~/mambaforge.sh "https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-$(uname)-$(uname -m).sh" \
  && chmod +x ~/mambaforge.sh \
  && ~/mambaforge.sh -b -p /opt/conda \
  && /opt/conda/bin/mamba init bash \
  && /opt/conda/bin/mamba config --set pip_interop_enabled True \
  && /opt/conda/bin/mamba create -n ${PYENV} python=${PYTHON_VERSION} -y \
  && rm ~/mambaforge.sh

# Install pip packages, with cache mounting /opt/conda/pkgs for faster builds
# Note: Cache mounts allow us to re-use the cache for conda packages
# instead of having to re-download them every time we build.
RUN --mount=type=cache,target=/opt/conda/pkgs/ \
    mamba install -yv \
    loguru \
    typer \
    scikit-learn \
    && echo "pip install complete"

# Export conda environment on login
RUN echo "export CONDA_PATH=/opt/conda/envs/${PYENV}" >> ~/.bashrc
RUN echo "export PATH=/opt/conda/envs/${PYENV}/bin:$PATH" >> ~/.bashrc
RUN echo "export CONDA_DEFAULT_ENV=${PYENV}" >> ~/.bashrc
RUN echo "mamba activate ${PYENV}" > ~/.bashrc
ENTRYPOINT ["/bin/bash", "-c"]

# Setup working directory
WORKDIR /app/$PYENV