common-workflow-
redun
| common-workflow- | redun | |
|---|---|---|
| 1 | 4 | |
| - | 489 | |
| - | 1.6% | |
| - | 7.5 | |
| - | 3 months ago | |
| Python | ||
| - | Apache License 2.0 |
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common-workflow-
-
Nextflow: Data-Driven Computational Pipelines
https://www.commonwl.org/
https://github.com/common-workflow-language/common-workflow-...
redun
- Redun: Yet another redundant workflow engine
-
Nextflow: Data-Driven Computational Pipelines
I'm personally a huge fan of redun¹ for running computational pipelines. It's pure python, it's easy to learn/debug, it has automatic caching, retry, provenance logging, and a great integration with AWS Batch for running large jobs. I've been really impressed with how easy it is to run a job to completion that fans out to thousands of AWS spot instances at once.
I've used nextflow in the past, and I've found it to be much harder to use. Learning another DSL is annoying, documentation was sparse, I constantly ran into bugs, and it was hard to debug in general. I don't know how much it's changed over the past 3 years though.
¹https://github.com/insitro/redun
- Insitro's redun: Yet another redundant workflow engine
- Insitro's new open source software uses DAGs.
What are some alternatives?
common-workflow-language - Repository for the CWL standards. Use https://cwl.discourse.group/ for support 😊
Prefect - The easiest way to build, run, and monitor data pipelines at scale.
cgpipe - cgpipe - minimum viable HPC pipeline
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
huey - a little task queue for python
nextflow - A DSL for data-driven computational pipelines
luigi - Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.