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OIOIOI

SIO2 is a free platform for carrying out algorithmic contests and OIOIOI is its main component --- the web interface.

Installation

It should be easier to begin with a separate folder at first:

mkdir sio2
cd sio2

and to install OIOIOI inside a virtualenv:

pip install virtualenv
virtualenv venv
. venv/bin/activate

Then OIOIOI and its dependencies can be installed by simply running:

pip install -e git://github.com/sio2project/oioioi.git#egg=oioioi

This will also store the source code in src/. There is no official release yet, so a simple pip install oioioi wouldn't work.

OIOIOI is a set of Django Applications, so you need to create a folder with Django settings and other deployment configuration:

oioioi-create-config deployment
cd deployment

The created deployment directory looks like a new Django project, but already configured to serve the OIOIOI portal. You need to at least set the database configuration in settings.py and initialize it:

./manage.py syncdb
./manage.py migrate

Simple configuration

In the simple configuration, OIOIOI will use the system-installed compilers, and will not use the safe execution environment. User's programs will be run with the normal user privileges. This is not a safe configuration and the judging will run quite slowly. It is to easily make OIOIOI up and running for testing purposes.

Ensure that required dependencies are installed:

  • gcc/g++ (Ubuntu package: build-essential)
  • fpc (Ubuntu package: fp-compiler)
  • latex with support for Polish (Ubuntu packages: texlive-latex, texlive-lang-polish)
  • lessc (LESS compiler; Ubuntu package: node-less)

and in one terminal run the Django web server:

./manage.py runserver 0.0.0.0:8000

and in the other the evaluation daemons:

./manage.py supervisor

The supervisor process monitor all processes needed by OIOIOI, except the web server. It has many nice features.

Finally you need an adminstrator account:

./manage.py createsuperuser

Now you're ready to access the site at http://localhost:8000.

Production configuration

  1. Begin with the simple configuration described above.

  2. Make sure you are in the deployment folder and the virtualenv is activated.

  3. Install RabbitMQ. We tested version 2.8.6 from RabbitMQ Debian/Ubuntu Repos. Anything newer should work as well.

  4. Uncomment and set BROKER_URL in settings.py to point to the configured RabbitMQ vhost. The default setting corresponds to the default RabbitMQ installation.

  5. Enable Filetracker server by uncommenting corresponding lines in settings.py and restart the daemons.

  6. Download sandboxes:

    ./manage.py download_sandboxes
    
  7. Disable system compilers and unsafe code execution by commenting out USE_UNSAFE_EXEC = True and USE_LOCAL_COMPILERS = True in settings.py.

  8. (optionally) Disable starting the judging process on the server, especially if you want to configure judging machines (see below) for judging, what is strongly recommended. Comment out the RUN_LOCAL_WORKERS = True setting.

  9. Configure Apache with mod_wsgi. An example configuration is automatically created as apache-site.conf. Have a look there. Once this is done, you do not need to run manage.py runserver.

  10. Comment out DEBUG = True in settings.py. This is crucial for security and efficiency.

  11. Set admin email in settings. Error reports and teacher account requests will be sent there.

  12. You probably want to run manage.py supervisor automatically when the system starts. We do not have a ready-made solution for this yet. Sorry!

Setting up judging machines

  1. Create a new user account for the judging processes and switch to it.

  2. Set up virtualenv:

    virtualenv venv
    . venv/bin/activate
    
  3. Install the sioworkers package:

    pip install sioworkers
    
  4. Start the worker process:

    sio-celery-worker BROKER_URL
    

    The passed argument must point to the RabbitMQ server configured on the server machine.

  5. That's all. You probably want to have the worker started automatically when system starts. We do not have a ready-made solution for this yet. Sorry!

The worker assumes that the Filetracker server is running on the same server as RabbitMQ, on the default port 9999. If this is not the case, you should pass the Filetracker server URL in the FILETRACKER_URL environment variable.

Final notes

It is strongly recommended to install the librabbitmq Python module (on the server and the worker machines). We observed some not dispatched evaluation requests when running celery with its default AMQP binding library:

pip install librabbitmq

Celery will pick up the new library automatically, once you restart the daemons.

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