Figure 5.

Comparison between Ruffus and Leaf code. Code for pipeline definition and use is highlighted in bold. Both samples implement the same simple pipeline made of three nodes (namely first_task, second_task and third_task), the first passes a text string to the other two, which in turn append some additional text to it. In Ruffus (left) the pipeline structure is defined through the “@follows” decorator, which must be attached to each function definition in order to specify its ascendants. In Leaf (right) the pipeline structure is visually defined as standalone LGL code (first lines in the example). Ruffus keeps track of produced resources by checking files specified through the “@files” decorator, which is the main tool for exchanging data between nodes. Leaf uses common function parameters while seamlessly caching their content on the disk to track the processing status. Leaf also caches the source code that produces each resource, and is thus able to detect changes in the code and invalidate all the resources affected by the change. The Ruffus file-based mechanism is also supported by Leaf through the “F” flag in LGL with the only requirement being that the function producing the files as their resources must return the corresponding file names (see main text).

Napolitano et al. BMC Bioinformatics 2013 14:201   doi:10.1186/1471-2105-14-201
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