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