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3.8 KiB
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99 lines
3.8 KiB
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==============================================================================
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Datatracker Development in a Docker Container (beta)
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==============================================================================
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Intro
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=====
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Docker_ is a toolkit which lets you package software together with its
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dependencies in lightweight containers, and run it in isolated virtual
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environments.
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During and just after IETF-94 I've spent quite a bit of time setting up a
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docker image which provides the dependencies needed to run the datatracker,
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and it's now available for beta testing. Hopefully this should make it
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substantially easier to get started with datatracker development.
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Steps
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=====
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1. Set up Docker on your preferred platform. Official installers exist for
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many Linux flavours, OS X, Windows and Cloud services. Here's the full `List
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of Installation Instructions`_.
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Docker containers require the services of an underlying Linux API, which
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means that on OS X and Windows, these have to be provided by a virtual
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machine which runs a minimal Linux image. The virtual machine used on
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non-Linux platforms is commonly VirtualBox. On Linux kernels with version
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3.8 or later, no virtual machine is needed, as the docker images can be
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fully supported with the native kernel services.
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Please follow the Docker installations all the way through to successfully
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running the ``hello-world`` example in a terminal window ( ``$ docker run
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hello-world``).
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2. Check out your datatracker branch as usual, in a suitable directory.
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We'll assume ``~/src/dt/`` here, and assume you are ``'coder'``::
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~/src/dt/ $ svn co https://svn.tools.ietf.org/svn/tools/ietfdb/personal/coder/6.8.2.dev0
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3. In the checked-out working copy, you'll find a ``docker/`` directory and a
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``data/`` directory at the top level. We're first going to set up a copy of
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the MySQL database files under the ``data/`` directory.
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There is a command in the ``docker/`` directory, ``setupdb`` which will do
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this for you, or you can do it manually.
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Either run::
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~/src/dt/6.8.2.dev0/ $ docker/setupdb
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or do this step-by-step: fetch down a pre-built copy of the datatracker
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database, place it in the ``data`` directory, unpack it, and fix
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permissions::
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~/src/dt/6.8.2.dev0/ $ cd data
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~/src/dt/6.8.2.dev0/data/ $ wget https://www.ietf.org/lib/dt/sprint/ietf_utf8.bin.tar.bz2
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~/src/dt/6.8.2.dev0/data/ $ tar xjf ietf_utf8.bin.tar.bz2
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~/src/dt/6.8.2.dev0/data/ $ chmod -R go+rwX mysql
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4. In the ``docker/`` directory you'll also find a wrapper script named
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``'run'``. We will be using the wrapper to run a pre-built docker image
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fetched from the docker hub::
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~/src/dt/6.8.2.dev0/ $ docker/run
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This will pull down the latest docker ietf/datatracker-environment image,
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start it up with appropriate settings, map the internal ``/var/lib/mysql/``
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directory to the external ``data/mysql/`` directory where we placed the
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database, set up a python virtualenv for you, install some dependencies,
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and drop you in a bash shell where you can run the datatracker.
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6. You are now ready to run the tests::
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(virtual) $ ietf/manage.py test --settings=settings_sqlitetest
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and then start the dev server::
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(virtual) $ ietf/manage.py runserver 0.0.0.0:8000
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Note the IP address ``0.0.0.0`` used to make the dev server bind to all
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addresses. The internal port 8000 has been mapped to port 8000 externally,
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too. In order to find the IP address of the VirtualBox, run ``'$
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docker-machine ip'`` *outside* the virtual environment::
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~/src/dt/6.8.2.dev0/ $ docker-machine ip
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192.168.59.103
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~/src/dt/6.8.2.dev0/ $ open http://192.168.59.103:8000/
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.. _Docker: https://www.docker.com/
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.. _`List of Installation Instructions`: https://docs.docker.com/v1.8/installation/
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.. _VirtualBox: https://www.virtualbox.org/
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