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Now your readers can \textbf{Launch IPython} directly in their browsers (by clicking on the link in the bottom left of your the  figure block), see your annotated data and code, and test and adjust it. Beyond the obvious advantages this provides for streamlining the scientific process, imagine implementing this to facilitate classroom learning or centralizing repeated analysis in a lab setting. What's more, it gives you a place to be very descriptive with your code, explaining each part. code.  In the predator-prey modeling example below, a detailed walk-through is given in the IPython Notebook. The  hope might be is  thatwith a clear walk-through,  anyone so inclined could modify or fork it, perhaps adding a third organism or some other environmental constraint. constraints.  Or, if they had some ecological data, to test to see how well the modelcould  fit their data. it. Science is a creative and iterative process.