See http://devilry.org for documentation. The rest of this readme is intended for developers.

If you plan to develop devilry, you should fork the devilry-django repo, changes to your own repo and request inclusion to the master repo using github pull requests. If you are just trying out devilry, use:

$ git clone https://github.com/devilry/devilry-django.git

The master branch, which git checks out by default, is usually the latest semi-stable development version. The latest stable version is in the latest-stable branch.

1. Install XCode (from app store)

2. Install other dependencies/requirements:

    $ sudo easy_install fabric virtualenv
   

$ sudo apt-get install fabric build-essential python-dev python-virtualenv

You should setup your buildout cache if you plan to do any development. This will make any up re-run of buildout (the dependency/build system we use).

$ fab setup_demo

Note: Creating the testdata takes a lot of time, but you can start using the server as soon as the users have been created (one of the first things the script does).

$ fab reset syncdb

Creating the demo database takes a lot of time (12mins on a macbook air with SSD disk). You may ask a developer to send you a dump, and use it instead of setup_demo:

$ fab reset
$ fab restore_db:/path/to/dbdump.sql

Create a clean development environment with an empty database:

$ cd devenv/
$ virtualenv virtualenv
$ virtualenv/bin/python ../bootstrap.py
$ bin/buildout
$ bin/django_dev.py dev_autogen_extjsmodels
$ bin/django_dev.py syncdb

Autocreate the demo-db:

$ bin/django_dev.py dev_autodb -v2

$ bin/django_dev.py runserver

Go to http://localhost:8000/ and log in as a superuser using:

user: grandma
password: test

Or as a user which is student, examiner and admin using:

user: thor
password: test

Note: All users have password==test, and you can see all users in the superadmin interface. See the demo page on the wiki for more info about the demo database, including recommended test users for each role.

We use Fabric to simplify common tasks. Fabric simply runs the requested @task decorated functions in fabfile.py.

fabfile.py is very straigt forward to read if you wonder what the tasks actually do. The fabric.api.local(...) function runs an executable on the local machine.