# ---------------------------------------------------------------------------
# APtool Docker image
# ---------------------------------------------------------------------------
# Uses the official Python 3.11 slim image as the base. "slim" is a minimal
# Debian-based image (~45MB) that includes just enough to run Python -- no
# compilers, man pages, or other extras. This keeps the image small.
FROM python:3.11-slim

# Set the working directory inside the container. All subsequent COPY, RUN,
# and CMD instructions will execute relative to /app.
WORKDIR /app

# Copy requirements.txt first, BEFORE the app code. Docker caches each
# layer, so if requirements.txt hasn't changed, "pip install" won't re-run
# even if app.py changes. This speeds up rebuilds significantly.
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Now copy the application code and templates into the image.
# sites.conf is baked in as a default but gets overridden at runtime
# by the docker-compose volume mount (see docker-compose.yml).
COPY app.py .
COPY templates/ templates/
COPY sites.conf .

# Create the uploads directory inside the container. At runtime this
# gets overlaid by a bind mount from the host (./uploads:/app/uploads)
# so that uploaded photos persist across container restarts.
RUN mkdir -p uploads

# Document that the app listens on port 5000. This is informational --
# the actual port mapping is configured in docker-compose.yml.
EXPOSE 5000

# Run the app with gunicorn (production WSGI server) instead of Flask's
# built-in dev server. Flags:
#   -w 2             -- 2 worker processes (handles concurrent requests)
#   -b 0.0.0.0:5000  -- bind to all interfaces on port 5000
#   --access-logfile - -- print access logs to stdout (visible in docker logs)
#   app:app          -- module:variable -- import "app" from app.py, use the
#                       Flask instance named "app"
CMD ["gunicorn", "-w", "2", "-b", "0.0.0.0:5000", "--access-logfile", "-", "app:app"]