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e357e763d7
Docker stack now includes a studio, smtp server, rabbitmq container and an LMS worker. There are still a couple things to do, though. (see TODOs)
61 lines
2.1 KiB
Docker
61 lines
2.1 KiB
Docker
FROM ubuntu:16.04
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############ common to lms & cms
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# Install system requirements
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RUN apt update
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RUN apt upgrade -y
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# Global requirements
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RUN apt install -y language-pack-en git python-virtualenv build-essential software-properties-common curl git-core libxml2-dev libxslt1-dev python-pip libmysqlclient-dev python-apt python-dev libxmlsec1-dev libfreetype6-dev swig gcc g++
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# edxapp requirements
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RUN apt install -y gettext gfortran graphviz graphviz-dev libffi-dev libfreetype6-dev libgeos-dev libjpeg8-dev liblapack-dev libpng12-dev libxml2-dev libxmlsec1-dev libxslt1-dev nodejs npm ntp pkg-config
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# Install symlink so that we have access to 'node' binary without virtualenv.
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# This replaces the "nodeenv" install.
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RUN apt install -y nodejs-legacy
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# Static assets will reside in /openedx/data and edx-platform will be
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# checked-out in /openedx
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VOLUME /openedx/data
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WORKDIR /openedx
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# Checkout edx-platform code
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RUN git clone https://github.com/edx/edx-platform.git
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WORKDIR /openedx/edx-platform
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RUN git fetch && \
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git checkout open-release/ginkgo.master
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# Install python requirements
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RUN pip install pip==8.1.2
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RUN pip install setuptools==24.0.3
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RUN pip install -r requirements/edx/pre.txt
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RUN pip install -r requirements/edx/github.txt
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RUN pip install -r requirements/edx/local.txt
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RUN pip install -r requirements/edx/base.txt
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RUN pip install -r requirements/edx/post.txt
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RUN pip install -r requirements/edx/paver.txt
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# Finish requirements install
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RUN paver install_prereqs
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# Copy configuration files
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COPY ./config/lms.env.json /openedx/
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COPY ./config/cms.env.json /openedx/
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COPY ./config/lms.auth.json /openedx/
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COPY ./config/cms.auth.json /openedx/
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COPY ./config/production_lms.py /openedx/edx-platform/lms/envs/production.py
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COPY ./config/production_cms.py /openedx/edx-platform/cms/envs/production.py
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############ End of code common to lms & cms
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# service variang is "lms" or "cms"
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ARG service_variant
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# Configure environment
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ENV DJANGO_SETTINGS_MODULE ${service_variant}.envs.production
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ENV SERVICE_VARIANT ${service_variant}
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# Run server
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EXPOSE 8000
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CMD gunicorn --name ${SERVICE_VARIANT} --bind=0.0.0.0:8000 --max-requests=1000 ${SERVICE_VARIANT}.wsgi:application
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