Hacker News Reader

IPython is pretty unusual. When I was first introduced to it, I thought of it as mostly an upgrade for the default python shell. But as I find more and more features like IPy Notebooks and IPCluster, I'm realizing that it's a completely new sort of thing. It's not just better command history in your shell or whatever - it's a whole new approach to computing emphasizing reproducibility and distributed workflows.

View on HN

I honestly thought the same thing until I was introduced to the scientific computing world last summer. I will have a blog post soon about how the differences of developing in a datacentric / ipython enabled python environment. The biggest difference is that the IPython notebook makes it reasonable to edit multi line functions at a repl.

Indeed, and communicating that clearly and effectively is something that we don't always succeed at. This is the reason why, on many occasions I had to resist fairly vociferous requests that we split up the parallel computing code from the shell, and also all the clients.

In the future that may make sense, once our internal protocols and APIs are so stable that we can do so without breaking functionality just as a way to help decouple development. But as a way to think about computational workflow, these pieces are all part of a coherent vision. It's just one that we don't always communicate clearly :)

Reply on news.ycombinator.com