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Add Flowdapt #148

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Expand Up @@ -35,6 +35,7 @@ A curated list of awesome open source workflow engines
* [FireWorks](https://materialsproject.github.io/fireworks/) [![Stars](https://img.shields.io/github/stars/materialsproject/fireworks.svg)](https://github.com/materialsproject/fireworks) - FireWorks stores, executes, and manages calculation workflows.
* [Fission Workflows](https://github.com/fission/fission-workflows) [![Stars](https://img.shields.io/github/stars/fission/fission-workflows.svg)](https://github.com/fission/fission-workflows) - A high-perfomant workflow engine for serverless functions on Kubernetes.
* [Flor](https://github.com/floraison/flor) [![Stars](https://img.shields.io/github/stars/floraison/flor.svg)](https://github.com/floraison/flor) - A workflow engine written in Ruby.
* [Flowdapt](https://flowdapt.ai) [![Stars](https://img.shields.io/github/stars/emergentmethods/flowdapt.svg)](https://github.com/emergentmethods/flowdapt) - Easy orchestration of heterogeneous workflows on distributed clusters, run vanilla Python, swap effortlessly between Ray, Dask, or Local executors.
* [Flyte](https://github.com/lyft/flyte) [![Stars](https://img.shields.io/github/stars/lyft/flyte.svg)](https://github.com/lyft/flyte) - A container-native, type-safe workflow and pipelines platform optimized for large scale processing and machine learning written in Golang. Workflows can be written in any language, with out of the box support for Python.
* [ForML](https://github.com/formlio/forml) [![Stars](https://img.shields.io/github/stars/formlio/forml.svg)](https://github.com/formlio/forml) - A development framework and MLOps platform for the lifecycle management of data science projects.
* [Galaxy Project](https://github.com/galaxyproject/galaxy) [![Stars](https://img.shields.io/github/stars/galaxyproject/galaxy.svg)](https://github.com/galaxyproject/galaxy) - Galaxy is a scientific tool and workflow system that facilitates reproducibility and transparency by providing a graphical user interface (GUI), a multitude of computational dataset tools, a rich API, and a robust scientific community.
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