At a meeting last night with some collaborators at the Vélobstacles project, I was excitedly told about the magic of IPython and it’s notebook functionality for reproducible research. This sounds familiar, I thought to myself. Using a literate programming approach to integrate computation with the communication of methodology and results has been at the core of the development of the RStudio IDE and associated tools such as knitr.
Here is Fernando Pérez speaking at PyCon Canada 2012 in Toronto about IPython for reproducible scientific computing.
This looks like convergent evolution in the R and Python communities, and I’m sure these projects can (and have already) learn a lot from each other.
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