Dockerfile

FROM python:2.7

# Configure the working directory
RUN mkdir -p /opt/project
WORKDIR /opt/project

# Pin the version because pip>=10.0 does not support the --download flag  which is required for dataflow
RUN pip install -U --ignore-installed pip==9.0.3

# Download and install google cloud. See the dockerfile at
# https://hub.docker.com/r/google/cloud-sdk/~/dockerfile/
RUN  \
  export CLOUD_SDK_APT_DEPS="curl gcc python-dev python-setuptools apt-transport-https lsb-release openssh-client git" && \
  export CLOUD_SDK_PIP_DEPS="crcmod" && \
  apt-get -qqy update && \
  apt-get install -qqy $CLOUD_SDK_APT_DEPS && \
  pip install -U $CLOUD_SDK_PIP_DEPS && \
  export CLOUD_SDK_VERSION="184.0.0" && \
  export CLOUD_SDK_REPO="cloud-sdk-$(lsb_release -c -s)" && \
  echo "deb https://packages.cloud.google.com/apt $CLOUD_SDK_REPO main" > /etc/apt/sources.list.d/google-cloud-sdk.list && \
  curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | apt-key add - && \
  apt-get update && \
  apt-get install -y google-cloud-sdk=${CLOUD_SDK_VERSION}-0 && \
  gcloud config set core/disable_usage_reporting true && \
  gcloud config set component_manager/disable_update_check true && \
  gcloud config set metrics/environment github_docker_image

# Setup a volume for configuration and auth data
VOLUME ["/root/.config"]

# Setup local application dependencies
COPY . /opt/project
RUN pip install --process-dependency-links -e .
RUN pip install sklearn scipy

# Setup the entrypoint for quickly executing the sandviklines
#ENTRYPOINT ["scripts/run.sh"]