Dockerfile

# syntax=docker/dockerfile:1

# Comments are provided throughout this file to help you get started.
# If you need more help, visit the Dockerfile reference guide at
# https://docs.docker.com/engine/reference/builder/

ARG PYTHON_VERSION=3.11
FROM python:${PYTHON_VERSION}-slim as base

# Prevents Python from writing pyc files.
ENV PYTHONDONTWRITEBYTECODE=1

# Keeps Python from buffering stdout and stderr to avoid situations where
# the application crashes without emitting any logs due to buffering.
ENV PYTHONUNBUFFERED=1

WORKDIR /app
# todo pass the csv as arcument in the cli and write documentation and add to catalog in moderate platform
# todo static s3 report to s3 http url and dataset to download and run
# todo dataset csv process the report data validation inide the success 200, output path as url
# todo if faul caputure console raise exception place the htmp lo caricano gli altri su s3
# Create a non-privileged user that the app will run under.
# See https://docs.docker.com/go/dockerfile-user-best-practices/
ARG UID=10001
RUN adduser \
    --disabled-password \
    --gecos "" \
    --home "/nonexistent" \
    --shell "/sbin/nologin" \
    --no-create-home \
    --uid "${UID}" \
    appuser

# Download dependencies as a separate step to take advantage of Docker's caching.
# Leverage a cache mount to /root/.cache/pip to speed up subsequent builds.
# Leverage a bind mount to requirements.txt to avoid having to copy them into
# into this layer.
RUN --mount=type=cache,target=/root/.cache/pip \
    --mount=type=bind,source=pyproject.toml,target=pyproject.toml \
    --mount=type=bind,source=poetry.lock,target=poetry.lock \
    python -m pip install poetry && \
    poetry config virtualenvs.create false && \
    poetry install --only main --no-interaction --no-ansi && \
    rm -rf $POETRY_CACHE_DIR

# Switch to the non-privileged user to run the application.
USER appuser

# Copy the source code into the container.
COPY . .

# Run the application.
CMD ["python -m src.cmp.main"]