Part of the reason we built Beaker was that the IPython devs explicitly stated they didn't believe in multiple languages within one notebook. It's possible that this opinion has changed with the Jupyter migration, but I haven't heard anything to that effect.
The Jupyter web page is a fine example of reverse information distribution. I went from" I think I know what this is" to "I have no idea what this is" within seconds of the page loading.
Same here! all of the buzz around iPython, and there is no succinct explanation of wtf it is or why I would want it. Jupyter seems to be a more generalize version of iPython with pluggable engines, but again, what does that mean?
So far, I am coming to the conclusion that iPython is a tool for data scientists, but I am not really sure.
IPython itself is a REPL with many, many convenience and magic functions, auto-completion, etc... If you write any amount of python, it's hugely useful!
Then, there are IPython Notebooks, which give you the HTML, cell-based frontend for executing code.
Jupyter is the v2/generalization for both of these things - there is the Jupyter shell, which is a plugin-friendly REPL, and Jupyter notebooks, which allow you to run code across a variety of langauges. AFAIK so far, you can only run one language per Jupyter notebook (though having dug around the source code, the possibility for multiple languages on a per-cell basis is very much there).
I still find myself using IPython and Jupyter interchangably, which probably doesn't help the confusion.
The project is currently (this month) moving from it's previous incantation called 'IPython'* to 'Jupyter'. The website apparently hasn't catched up yet.
FYI, the latest Jupyter + matplotlib have interactive plotting inline with "%matplotlib notebook". The server must be running for this to work (so you can't interact with static ipynb files in nbviewer, for example), but a static version of the plot is generated for static notebooks. There are also some changes coming down the line to expose the traits of matplotlib plots so that libraries like mpld3 can be integrated more seamlessly.
Yeah, most of our curriculum uses regular old matplotlib. We only use this technique specifically in our D3 curriculum. In general I can't think of many use cases where this is actually better than just having a couple of files, aside from instructional ones.
Yeah, I've been using Jupyter with inline plotting and it's really quite nice. A notebook that's not tied to proprietary software (i.e. Mathematica) and which can run a full-fledged programming language is a marvelous tool.
IPython feels like an important new way to do computing, particularly for exploring and teaching. I love the idea of bringing more powerful HTML tools into it.
learn more at http://BeakerNotebook.com/