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Short Description
Yabi is a web based workflow environment
Full Description



Yabi is a 3-tier application stack to provide users with an intuitive, easy to use, abstraction of compute and data environments. Developed at the Centre for Comparative Genomics (, Yabi has been deployed across a diverse set of scientific disciplines and high performance computing environments.

Yabi has a few key features:

  • simplified web based access to High Performance Computing
  • easy tool addition and maintenance
  • handling of disparate compute and storage resouces ie. PBSPro, SGE, Torque, Slurm, SSH, SFTP, Amazon S3, Openstack Swift
  • easy and powerful workflow creation environment

More docs at Read the Docs (


Hosted on Bitbucket:

Or if you prefer, GitHub:

Documentation on Read the Docs:

Project Managed on JIRA:




For developers

We do our development using Docker containers. See:
You will have to set up Docker on your development machine.

Other development dependencies are Python 2 and virtualenv (

All the development tasks can be done by using the shell script in this directory.
Please run it without any arguments for help on its usage.

Some typical usages are:

  • ./ start

      To start up all the docker containers needed for dev. 
      You can access the Django Yabi application on http://localhost:8000
      (replace localhost with ``$ boot2docker ip`` if using boot2docker) after this.
      You can login with one of the default users *demo/demo* or *admin/admin*.
  • ./ runtests

      Starts up all the docker containers and runs all our tests against them.
  • ./ pythonlint

      Lint your python code.
  • ./ jslint

      Lint your javascript code.

Note: Our docker containers are coordinated using docker-compose ( but docker-compose will be installed into a virtualenv environment automatically by the ./ script for you.


  1. Fork next_release branch
  2. Make changes on a feature branch
  3. Submit pull request


Hunter AA, Macgregor AB, Szabo TO, Wellington CA and Bellgard MI, Yabi: An online research environment for Grid, High Performance and Cloud computing, Source Code for Biology and Medicine 2012, 7:1 doi:10.1186/1751-0473-7-1 Published: 15 February 2012 Source Code for Biology and Medicine (

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