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Ruffus - a lightweight python module to run computational pipelines
This is perfect for computational biology work. Good documentation too.
I write all my code into this framework now.
ruffus.org.uk
You're welcome!
I write all my code into this framework now.
ruffus.org.uk
You're welcome!
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Ruffus is nice, but I never could figure out how to parameterize the generated jobs (for different objects etc...).
I have my own pipeline now based on function-wrapping job objects that I probably should pour into the net one of these days if anyone was interested. It supports multiprocessing, code change detection (on the level of the wrapped functions), resume (d'oh) and of course the usually file time checking, as well as partial fault tolerance (a broken job will only affect itself and the jobs depended on it, no the other jobs). -
Hi. Just found this by Google.
I am the primary developer of Ruffus.
Ruffus is designed to be light-weight, flexible and easy to use but the fundamental approach is different enough to normal scripting that some of my users have to work through the whole of the tutorial before "getting it".
We are always looking for new ways to present the documentation or even adjust the semantics to make things clearer / easier. Feedback so far has been tremendously useful and driven most of the development of Ruffus.
I am here to help people figure things out / hand-hold if necessary. So if anyone wants to send me (on- or off-line) a quick conceptual sketch of what you want to do / what the pipeline is supposed to do, I am happy to write some quick code or point you in the right direction.
Of course, if you have rolled your own pipeline code already, you probably have quite different ideas about how things should be done!
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.07-01-2026, 11:43 AM
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