Snakemake sets itself apart from existing text-based workflow systems in the following way. Hooking into the Python interpreter, Snakemake offers a definition language that is an extension of Python with syntax to define rules and workflow specific properties. This allows to combine the flexibility of a plain scripting language with a pythonic workflow definition. The Python language is known to be concise yet readable and can appear almost like pseudo-code. The syntactic extensions provided by Snakemake maintain this property for the definition of the workflow. Further, Snakemake’s scheduling algorithm can be constrained by priorities, provided cores and customizable resources and it provides a generic support for distributed computing (e.g., cluster or batch systems). Hence, a Snakemake workflow scales without modification from single core workstations and multi-core servers to cluster or batch systems.