Welcome to gwf¶
gwf is a flexible, pragmatic workflow tool for building and running large, scientific workflows. It runs on Python 3.5+ and is developed at the Bioinformatics Research Centre (BiRC), Aarhus University.
To get a feeling for what a gwf workflow looks like, have a look at a few examples.
- Getting started
To quickly get started writing workflows in gwf you can read the Tutorial.
We don’t have the backend you need to run your workflow on your cluster? See the Writing Backends section to roll your own.
We aim to make gwf a community developed project. Learn how to contribute.
Easy to adopt, there’s no special syntax to learn if you already know Python
Automatically resolves dependencies between targets based on filenames
Only submits targets when their output files are not up to date
Supports multiple backends like Slurm, SGE and a local backend for testing
Fire-and-forget, does not require you to use screen or tmux to keep your workflow running
Commands for cleaning temporary data from your workflow
Friendly to your system administrator!
- User’s Guide
- A Minimal Workflow
- Running Your First Workflow
- Setting the Default Verbosity
- Debugging a Workflow
- Defining Targets with Dependencies
- Named Inputs and Outputs
- Specifying Target Resources
- Observing Target Execution
- What Happens When a Target Fails?
- Reusable Targets with Templates
- Viewing Logs
- Cleaning Up
- A Note About Reproducibility
- Mapping over Inputs
- Tips and Tricks
- Change Log