Dockerfile

# Use the official lightweight Python image.
# https://hub.docker.com/_/python
FROM python:3.8-slim as base

# Setup env
ENV LANG C.UTF-8
ENV LC_ALL C.UTF-8
ENV PYTHONDONTWRITEBYTECODE 1
ENV PYTHONFAULTHANDLER 1

#######################################################

FROM base AS python-deps

# Install pipenv and compilation dependencies
RUN pip install pipenv
RUN apt-get update && apt-get install -y --no-install-recommends gcc

# Install python dependencies in /.venv
COPY Pipfile .
COPY Pipfile.lock .
RUN PIPENV_VENV_IN_PROJECT=1 pipenv install --deploy

#######################################################

FROM base AS runtime

ENV PYTHONPATH /app

# Allow statements and log messages to immediately appear in the Knative logs
ENV PYTHONUNBUFFERED True

# Copy virtual env from python-deps stage
COPY --from=python-deps /.venv /.venv
ENV PATH="/.venv/bin:$PATH"

# Install additional dependencies
RUN pip install --no-cache-dir gunicorn==20.1.0

# Create and switch to a new user
RUN useradd --create-home appuser
WORKDIR /app
USER appuser

# Copy application into container
COPY . .

ENV PYTHONPATH /app

# Run the web service on container startup. Here we use the gunicorn
# webserver, with one worker process and 8 threads.
# For environments with multiple CPU cores, increase the number of workers
# to be equal to the cores available.
# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
CMD exec gunicorn --bind :$PORT --workers 1 --threads 8 --timeout 0 src.main:app