Nature: IPython interactive demo
nature.com
nature.com
I love the reproducible science movement and iPython is perfect for that. Glad to see Nature talking about it.
Don't be surprised if your lecturers use other languages on their own work. At my university, everybody in the math department uses Matlab and Mathematica. However I know that a lot of the guys who do smooth particle hydrodynamics use Python and Fortran, and my honours supervisor said he once programmed in PostScript (which isn't so much practical, but it's impressive and shows he knows how to program in languages other than Matlab).
It's a pretty amazing story about brining full instant on scientific notebooks to everyone.
It's running on the High Memory OnMetal instances here at Rackspace. Each container gets 512mb of ram.
As much as I hope things like this will be a tipping point for python in the scientific community (from a major player to the dominant player), monoculture hurts everyone. Fortunately, one of the great things about ipython/jupyter is that it's designed to be language independent.
I'm sure a lot of folks here are already aware of this, but just in case you're not: There are Julia, R, Haskell, Ruby, and who-knows-what-else kernels for ipython/jupyter.
I know the basic idea has been around for a long time (e.g. Mathematica), but ipython really is an incredibly well-done and flexible execution of the idea.
Love that there are so many "good" open source options in the ecco-system and people will not only show the work BUT also include the cleaning and tidying up of the data which is equally important in my opinion.
I like IPython NOT for the reproduction but I like interacting with my script with cells. If I was working with a team I would prefer IPython's approach.
With computational thinking I mean any subject matter where the way of arriving at the results is at least as important as the results themselves.
With IPython Notebook, you can perform live demos (e.g. live_reveal extension), communicate with your future self or collaborators and even peer reviewers.
Can someone tell me something about the notebook? I want to decide if this is something I should bookmark, and visit at a later date.
print(open('/proc/cpuinfo').read())
Seems to have network access... I git cloned a small repo from git hub. It already has gcc installed. Looks like they should lock it down a bit more.
The 24 core Xeons are our (rackspace) OnMetal high memory boxes, you don't actually have 24 cores, docker just pulled that from the host, each container is limited.