Snakemake is a powerful workflow management system that allows you to define and execute complex computational workflows in a reproducible and scalable manner. In this tutorial, we'll walk through the basics of Snakemake and demonstrate how to create and execute a simple workflow.
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Snakemake works very well on local machines and on computational clusters, however it does not have a server handler, which means having multiple people running the same workflow on a server can cause complications. This can for example happen on modelling-as-a service servers. In that case you are advised to use a more involved worfklow manager, such as Argo. |
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See also the example project on Github: https://github.com/Deltares/FAIR-data-example-project |
Prerequisites
Before we begin, make sure you have the following prerequisites installed on your system:
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- Snakemake: Install Snakemake using pipconda, the a Python package manager. Open a terminal or command prompt and run the following command:
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conda install -c bioconda snakemake |
Alternatively, Deltaforge is a Deltares python distribution which comes with snakemake. See its documentation for installation instructions.
Introduction to Snakemake
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