99 lines
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 set of tools which lets you package software together with its
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dependencies in lightweight containers, and run it in isolated virtual environments.
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During and just after IETF-94 I've spent quite a bit of time setting up a docker
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image which provides the dependencies needed to run the datatracker, and it's now
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available for beta testing. Hopefully this should make it substantially easier to
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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
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exist for many Linux flavours, OS X, Windows and Cloud services.
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Docker containers require the services of an underlying Linux API,
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which means that on OS X and Windows, these have to be provided
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by a virtual machine which runs a minimal Linux image. The virtual
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machine used is commonly VirtualBox, although at least one
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unofficial VM image and controller (boot2docker_) also supports
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Parallels, XenServer and VMWare.
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The primary installers available is the unofficial boot2docker_ and
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the official `Docker Engine`_. I've tried both, and at this time,
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November 2015, boot2docker has worked much better for me than
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Docker Engine. YMMV.
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Boot2docker can self-upgrade and provides up-to-date docker server
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and clients. Run update after you install::
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~ $ boot2docker upgrade
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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 ``data/`` directory
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at the top level. Fetch down a pre-built copy of the datatracker
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database, place it in this directory, unpack it, and fix permissions::
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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 checked-out working copy, you'll also find a ``docker/``
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directory at the top level. It contains a Dockerfile which can
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be used to build a docker image, but that doesn't concern us at
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the moment. We will be using a wrapper script, ``'run'``, to
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run a pre-built docker image 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 datatracker image, start it
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up with appropriate settings, map the internal ``/var/lib/mysql/``
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directory to the external ``data/mysql/`` directory where we placed
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the database, set up a python virtualenv for you, install some
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dependencies, and drop you in a bash shell where you can run the
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datatracker.
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5. Make sure that all requirements are installed::
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(virtual) $ cd ~/src/dt/6.8.2.dev0
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(virtual) $ pip install -r requirements.txt
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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
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to all addresses. The internal port 8000 has been mapped to port
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8000 externally, too. In order to find the IP address of the
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VirtualBox, run ``'$ boot2docker ip'`` or equivalent *outside* the
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virtual environment::
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~/src/dt/6.8.2.dev0/ $ boot2docker 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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.. _`Docker Engine`: https://docs.docker.com/engine/installation/
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.. _boot2docker: http://boot2docker.io/
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.. _VirtualBox: https://www.virtualbox.org/
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