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Comment by julienchastang | Hacker News Reader

I work with scientists that love the IPython Notebook technology. Some claim the IP[y]: Notebook to be the best thing since the Mosaic web browser and the most important development in scientific computing in a decade. They are replacing a variety of tools (Perl, Matlab, R, etc.) with the notebook technology. I tend to agree, it is a revolutionary technology and the idea of executable papers is tantalizing. But I also see some limitations. Setting up a Python environment with all the necessary libraries can be a real pain in the neck even with technologies like pip. Also taking advantage of multicore parallelism is not trivial because of the Python Global Interpreter Lock. I have also worked in JVM environments where parallel computing is becoming significantly easier and I don't see that happening in Python anytime soon. I would love to be proven wrong, of course.

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It should be noted that the IPython Notebook is being developed to support multiple backends. People are working on backends for Haskell[1], Scala [2], and Julia[3]. I'd love to see a Clojure backend.

All of this does not obviate the challenges of setting up IPython, but that could also be (somewhat)resolved via cloud services[4][5][6].

[1] http://gibiansky.github.io/IHaskell/

[2] https://github.com/mattpap/IScala

[3] https://github.com/JuliaLang/IJulia.jl

[4] http://www.windowsazure.com/en-us/develop/python/tutorials/i...

[5] https://www.wakari.io/

[6] http://blog.picloud.com/2012/12/23/introducing-the-picloud-n...

I would totally agree on the first point about how much of a burden it can be to get any moderately complex Python environment up and running (whether IPython Notebook is part of the install or not.) Unfortunately, it's just not as easy as it should be yet.

IMHO, this is what makes a duo like Vagrant + IPython Notebook so appropriate for creating a minimum barrier to entry. In other words, what you really need is a VM that has IPython Notebook and all of the necessary dependencies installed that you just start up as a guest machine. Then, on your host, you point your browser to http://localhost:8888 and get to work with the the ipynb UI.

The approach I described is exactly what I did with Mining the Social Web 2E, and I elaborated on it a bit here: http://miningthesocialweb.com/2013/08/24/reflections-on-auth...

The cool thing about the way Vagrant works is that you can run a VM locally or you can run it in the cloud just as easily with the appropriate plugin.

There's a video that demonstrates how easy it can be to use Vagrant and IPython Notebook to get started here - https://vimeo.com/72383764

By the way, I really like the metaphor of describing IPython Notebook as "executable paper" - that's clever and concise.

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