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Workflow Description Language local runner & developer toolkit for Python 3.8+

Project Status MIT license CI Coverage Status Docs Status

Install miniwdl

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 PyPI version : run pip3 install miniwdl
  • Install with conda Anaconda-Server Badge : 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

Use miniwdl

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.

The online documentation includes a user tutorial, reference manual, and Python development codelabs: Docs Status

See the Releases for change logs. The Project board shows the current prioritization of issues.

Scaling up

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:

Getting Help

Feedback and contributions to miniwdl are welcome, via issues and pull requests on this repository. See for guidelines and instructions to set up your development environment.


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