Former Scientific Computing Cluster Dashboard
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README.rst Dashboard

The Dashboard allows users to launch scientific computing clusters in EC2 with ease.

I will be updating these instructions in the near future as well as publicly announcing the opensource release of the core dashboard component.


Steps for running dash on Ubuntu 10.04:

mkvirtualenv --no-site-packages crunchio
git clone git:// dash
cd dash
# Install the system dependencies
sudo apt-get install -y python-dev libgmp3-dev libgmp3c2 build-essential
# Install the python dependencies
pip install -r requirements.txt
# Run the following commands and follow the instructions
fab setup
fab bootstrap


After you have completed the setup steps you can run the app with the following command:

python ./ runserver

And then in another terminal, run the django-task daemon:

python ./ taskd


If you want to deploy this app into production, you can use apache and mod_wsgi and manage the taskd with supervisor. The scripts/ directory contains a django.wsgi file and supervisor configuration file to get you started.

Testing Guidelines

I am trying to establish which testing frameworks I intend to use for this application. At the moment, I have the following two expectations:

  • Use doctests to provide functional usage examples is encouraged. But it is not suitible for general testing.
  • I may make use of django.test TestCases
  • Lettuce tests are the current focus, though that may change.

I have been hoping to use pyccuracy, but I haven't managed to get its basic example working correctly even. I have had no response on their mailing list. I would prefer a BDD style testing framework that actually drives a browser like pycurracy but lettuce is BDD and runs quickly, so perhaps it is suitable for some things.

The following two commands can be used to run tests:

# running the doctests and TestCases
./ test cluster
# running the lettuce tests
./ harvest


The dashboard is dependant on a number of open source components and libraries, most notably StarCluster.