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Enable bursting of user jobs to remote compute resources for the Galaxy application.
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GalaxyCloudRunner enables bursting of user jobs to remote compute resources for the Galaxy application. It provides a dynamic job runner that can be plugged into Galaxy.


GalaxyCloudRunner enables bursting of user jobs to remote compute resources for the Galaxy application. It provides several dynamic job rules that can be plugged into Galaxy, enabling Galaxy to submit jobs to remote cloud nodes.

How it works

The GalaxyCloudRunner provides a library of rules that can be plugged into Galaxy through job_conf.xml. Once configured, you can get your jobs to be automatically routed to remote Pulsar nodes running on the cloud. The GalaxyCloudRunner will discover what Pulsar nodes are available by querying the CloudLaunch API. Adding a new node is a simple matter of visiting the CloudLaunch site and launching a new Pulsar node on your desired cloud.

Getting Started

Getting started with the GalaxyCloudRunner is a simple process.

  1. First, install galaxycloudrunner into your Galaxy's virtual environment via pip install galaxycloudrunner.
  2. Add a job rule to Galaxy which will determine the Pulsar node to route to.
  3. Configure your job_conf.xml to use this rule.
  4. Launch as many Pulsar nodes as you need through CloudLaunch.
  5. Submit jobs as usual.

For detailed instructions, see:

Developer installation

Clone the source code repository and install the library with the dev dependencies.

git clone
cd galaxycloudrunner
pip install --upgrade .[dev]

To build the HTML docs locally, run the following commands. The built site will be available in docs/_build/html.

cd docs
make html


Community contributions for any part of the project are welcome. If you have a completely new idea or would like to bounce your idea before moving forward with the implementation, feel free to create an issue to start a discussion.

Contributions should come in the form of a pull request. The code needs to be well documented and all methods have docstrings. We are largely adhering to the PEP8 style guide with 80 character lines, 4-space indentation (spaces instead of tabs), explicit, one-per-line imports among others. Please keep the style consistent with the rest of the project.

Release process

  1. Update any dependencies in and commit the changes.
  2. Increment the library version number in galaxycloudrunner/ as per semver rules.
  3. Add release notes to CHANGELOG.rst, adding the most recent commit hash to the changelog, and make a commit. List of commits can be obtained using git shortlog <last release hash>..HEAD
  4. Test the release with PyPI staging server, as described in You will need to pip install -U wheel twine for this step.
  5. Release to PyPI
    # Remove stale files or wheel might package them
    rm -r build dist
    python sdist bdist_wheel
    twine upload -r pypi dist/galaxycloudrunner-*
  6. Tag release and make a GitHub release. Alternatively, push the current commits and make a release directly on GitHub to include the release changelog in the tag body.
    git tag -a v0.3.0 -m "Release 0.3.0"
    git push
    git push --tags
  7. Increment version number in galaxycloudrunner/ to <current-version>+dev to indicate the development cycle; commit, and push the changes.
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