Dockerfile.custom_deployment

# syntax=docker/dockerfile:1.4
FROM python:3.12-slim@sha256:bae1a061b657f403aaacb1069a7f67d91f7ef5725ab17ca36abc5f1b2797ff92 AS base

WORKDIR /app
ENV PYTHONUNBUFFERED=1
ENV DEBIAN_FRONTEND=noninteractive

RUN --mount=type=cache,target=/var/cache/apt \
    apt-get update -qq && \
    apt-get install -yq --no-install-recommends \
    git \
    openssh-client \
    wget \
    gpg \
    software-properties-common \
    build-essential && \
    apt-get clean && rm -rf /var/lib/apt/lists/*

RUN wget https://repo.anaconda.com/miniconda/Miniconda3-py312_25.3.1-1-Linux-x86_64.sh -O ~/miniconda.sh && \
    chmod +x ~/miniconda.sh && \
    bash ~/miniconda.sh -b -p /app/miniconda && \
    rm ~/miniconda.sh && \
    /app/miniconda/bin/conda init bash

# Set environment variables to point to conda environment
ENV VIRTUAL_ENV="/app/miniconda/bin"
ENV PATH="/app/miniconda/bin:$PATH"
ENV PYTHONPATH="/app/miniconda/lib/python3.12/site-packages:${PYTHONPATH:-}"

# Install uv & mamba
RUN --mount=type=cache,target=/root/.cache/pip \
    pip3 install --no-cache-dir uv==0.5.21
RUN --mount=type=cache,target=/app/miniconda/pkgs \
    conda install -c conda-forge mamba -y

# Install R and kernels in the crow_env environment
RUN --mount=type=cache,target=/app/miniconda/pkgs \
    mamba install -c conda-forge -y \
    r-base=4.3.3 \
    r-recommended=4.3 \
    r-irkernel=1.3.2 \
    r-factominer=2.11 \
    r-rcolorbrewer=1.1_3 \
    r-devtools=2.4.5 \
    r-broom=1.0.7 \
    r-data.table=1.15.4 \
    r-enrichr=3.2 \
    r-factoextra=1.0.7 \
    r-ggnewscale=0.5.0 \
    r-ggrepel=0.9.6 \
    r-ggpubr=0.6.0 \
    r-ggvenn=0.1.10 \
    r-janitor=2.2.1 \
    r-multcomp=1.4_26 \
    r-matrix=1.6_5 \
    r-pheatmap=1.0.12 \
    r-tidyverse=2.0.0 \
    r-readxl=1.4.3 \
    r-reshape=0.8.9 \
    r-rstatix=0.7.2 \
    r-viridis=0.6.5 \
    udocker=1.3.17 \
    imbalanced-learn=0.13.0 \
    ipykernel=6.29.5 \
    sqlite=3.47.2 \
    anndata=0.11.1 \
    biopython=1.84 \
    datasets \
    ete3=3.1.3 \
    fcsparser=0.2.8 \
    keras=3.7.0 \
    jupyter=1.0.0 \
    matplotlib=3.10.0 \
    matplotlib-venn=1.1.1 \
    nbconvert=7.16.4 \
    numpy=1.26.4 \
    optuna=4.1.0 \
    openpyxl=3.1.5 \
    pandas=2.2.3 \
    plotly=5.24.1 \
    rpy2=3.5.11 \
    scipy=1.14.1 \
    scanpy=1.10.4 \
    seaborn=0.13.2 \
    scikit-learn=1.6.0 \
    statsmodels=0.14.4 \
    umap-learn=0.5.7

RUN --mount=type=cache,target=/app/miniconda/pkgs \
    python -m ipykernel install --user --name python3 --display-name "Python 3 (ipykernel)"
RUN --mount=type=cache,target=/app/miniconda/pkgs \
    R -e 'IRkernel::installspec(name = "R", displayname = "R (4.3.3)")'

RUN --mount=type=cache,target=/app/miniconda/pkgs \
    mamba install -c conda-forge -c bioconda -y \
    biokit=0.5.0 \
    gseapy=1.1.4 \
    blast=2.16.0 \
    clipkit=2.3.0 \
    clustalo=1.2.4 \
    fastqc=0.12.1 \
    iqtree=2.3.6 \
    mafft=7.526 \
    metaeuk=7.bba0d80 \
    mygene=3.2.2 \
    perl=5.32.1 \
    phykit=2.0.1 \
    pydeseq2=0.4.12 \
    spades=4.0.0 \
    trim-galore=0.6.10 \
    bioconductor-enhancedvolcano=1.20.0 \
    bioconductor-deseq2=1.42.0 \
    bioconductor-clusterprofiler=4.10.0 \
    bioconductor-org.hs.eg.db=3.18.0 \
    bioconductor-genomicranges=1.54.1 \
    bioconductor-summarizedexperiment=1.32.0 \
    bioconductor-apeglm=1.24.0 \
    bioconductor-flowcore=2.14.0 \
    bioconductor-flowmeans=1.62.0

ENV UV_COMPILE_BYTECODE=1
ENV UV_LINK_MODE=copy
RUN mamba clean -all -y && \
    rm -rf /app/miniconda/pkgs/* && \
    find /app/miniconda \( -type d -name __pycache__ -o -type d -name tests -o -type d -name '*.tests' -o -type d -name 'test' \) -exec rm -rf {} + && \
    find /app/miniconda -type f -name '*.a' -delete && \
    find /app/miniconda -type f -name '*.js.map' -delete


FROM base AS builder

ARG MODULE_NAME

RUN --mount=type=cache,target=/var/cache/apt \
    apt-get update -qq && \
    apt-get install -yq --no-install-recommends \
    build-essential && \
    apt-get clean && rm -rf /var/lib/apt/lists/*

ENV VIRTUAL_ENV="/app/miniconda/bin"
ENV PATH="/app/miniconda/bin:$PATH"

# Now copy application code (this will change frequently)
COPY ./${MODULE_NAME} /app/${MODULE_NAME}
RUN mkdir -p /app/scripts
COPY ./scripts/run_crow_job.py /app/scripts/

# Install application dependencies (this will only rerun when code changes)
WORKDIR /app/${MODULE_NAME}
RUN --mount=type=cache,target=/root/.cache/uv \
    --mount=type=cache,target=/app/miniconda/pkgs \
    if [ -f "pyproject.toml" ]; then \
        uv pip install --system -e .; \
    elif [ -f "requirements.txt" ]; then \
        uv pip install --system -r requirements.txt; \
    else \
        echo "No pyproject.toml or requirements.txt found" && exit 1; \
    fi

RUN find /app -type l -delete && \
    rm -rf /app/.git

FROM base AS runtime

COPY --from=builder /app/ /app/

ENV VIRTUAL_ENV="/app/miniconda/bin"
ENV PATH="/app/miniconda/bin:$PATH"
ENV PYTHONPATH="/app/miniconda/lib/python3.12/site-packages:${PYTHONPATH:-}"
CMD ["python", "scripts/run_crow_job.py"]