Workflow Description Language local runner & developer toolkit for Python 3.8+
Installation requires Python 3.8+, pip3 (or conda) and Docker (or Podman/Singularity/udocker). Linux preferred; macOS (Intel) compatible with extra steps. More detail in full documentation.
- Install with pip
: run
pip3 install miniwdl - Install with conda
: run
conda install -c conda-forge miniwdl - Verify your miniwdl installation:
miniwdl run_self_test - Install from source code: see the Dockerfile for dependencies to run
setup.py
Run an example bioinformatics WDL pipeline using miniwdl, or learn more abut miniwdl via a short course (screencast examples). If you are new to the WDL language, see the open source learn-wdl course.
- Run an example using a viral genome assembly workflow
- Learn miniwdl course w/screencasts - shown below
- Learn WDL course w/screencasts
The online documentation includes a user tutorial, reference manual, and Python development codelabs:
See the Releases for change logs. The Project board shows the current prioritization of issues.
The miniwdl runner schedules WDL tasks in parallel up to the CPUs & memory available on the local host; so a more-powerful host enables larger workloads. Separately-maintained projects can distribute tasks to cloud & HPC backends with a shared filesystem:
- AWS:
- miniwdl-omics-run tool for the Amazon Omics workflow service
- AWS Batch plugin (DIY)
- SLURM
- Open an issue
- OpenWDL Slack (#miniwdl channel)
- Bioinformatics Stack Exchange
Feedback and contributions to miniwdl are welcome, via issues and pull requests on this repository. See CONTRIBUTING.md for guidelines and instructions to set up your development environment.
Please disclose security issues responsibly by contacting [email protected].