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What is looper?

Looper is a job submitting engine. Looper deploys arbitrary shell commands for each sample in a standard PEP project. You can think of looper as providing a single user interface to running, monitoring, and managing all of your sample-intensive research projects the same way, regardless of data type or pipeline used.

What makes looper better?

Looper decouples job handling from the pipeline process. In a typical pipeline, job handling (managing how individual jobs are submitted to a cluster) is delicately intertwined with actual pipeline commands (running the actual code for a single compute job). In contrast, the looper approach is modular: looper only manages job submission. This approach leads to several advantages compared with the traditional integrated approach:

  1. pipelines do not need to independently re-implement job handling code, which is shared.
  2. every project uses a universal structure, so datasets can move from one pipeline to another.
  3. users must learn only a single interface that works with any project for any pipeline.
  4. running just one or two samples/jobs is simpler, and does not require a distributed compute environment.


Releases are posted as GitHub releases, or you can install using pip:

pip install --user looper

Update with:

pip install --user --upgrade looper

If the looper executable in not automatically in your $PATH, add the following line to your .bashrc or .profile:

export PATH=~/.local/bin:$PATH

Quick start

To test looper, follow the Hello Looper example repository to run your first looper project:

# download and unzip the hello_looper repository

# Run looper:
cd hello_looper-master
looper run project/project_config.yaml

Detailed explanation of results is in the Hello world tutorial.