Dockerfile

# The build-stage image:
FROM continuumio/miniconda3 AS build
MAINTAINER Matheus Woeffel <matheuswoeffel@gmail.com>

# Install the package as normal:
COPY environment.yml .
RUN conda env create -f environment.yml

# Install conda-pack:
RUN conda install -c conda-forge conda-pack

# Use conda-pack to create a standalone enviornment
# in /venv:
RUN conda-pack -n env -o /tmp/env.tar && \
  mkdir /venv && cd /venv && tar xf /tmp/env.tar && \
  rm /tmp/env.tar

# We've put venv in same path it'll be in final image,
# so now fix up paths:
RUN /venv/bin/conda-unpack

# The runtime-stage image; we can use Debian as the
# base image since the Conda env also includes Python
# for us.
FROM debian:buster AS runtime

# Copy /venv from the previous stage:
COPY --from=build /venv /venv

RUN apt-get -y update && apt-get install -y --no-install-recommends \
         wget \
         nginx \
         ca-certificates \
    && rm -rf /var/lib/apt/lists/*

# Set some environment variables. PYTHONUNBUFFERED keeps Python from buffering our standard
# output stream, which means that logs can be delivered to the user quickly. PYTHONDONTWRITEBYTECODE
# keeps Python from writing the .pyc files which are unnecessary in this case. We also update
# PATH so that the train and serve programs are found when the container is invoked.

ENV PYTHONUNBUFFERED=TRUE
ENV PYTHONDONTWRITEBYTECODE=TRUE
ENV PATH="/opt/program:${PATH}"

# Copy project files into the container workdir
COPY src /opt/program
WORKDIR /opt/program

# When image is run, run the code with the environment
# activated:
SHELL ["/bin/bash", "-c"]
RUN ["chmod", "+x", "/venv/bin/activate"]
ENTRYPOINT source /venv/bin/activate && python serve