I have tried both, Bokeh (without the server) and plot.js (their python lib offers a JSON encode option so that you can use their Python lib with plotly.js without sending data to plotly).

However, I found both to be very similar and still don't have a clear favorite. Any opinions on which solution is better suited for (internal) interactive dashboards?

One thing I've been waiting for (and if I had the time, I'd love to work on something like this) is scientific javascript. I love es6 and classless oop[0] that javascript provides (and general dynamic-ness) but the lack of operator overloading makes mathy infix operators work with an array-like type not possible in native js. Something that had the "functional", dynamic semantics of javascript with the natural notation that numpy has (with its broadcasting rules) would be fantastic.

Stuff like plotly is great, but as far as I can tell, I'm not going to be able to use it any time soon because I'm not going to write a >10 term expression in javascript when every '+' becomes a 'add(a,b)' or 'a.add(b)'.

[0] https://youtu.be/bo36MrBfTk4?t=33m45s

To do that you first need to have a way of extending JavaScript with C and/or Fortran. No way numpy can be implemented in pure js or python without being excruciatingly slow.

You can do it with the nodejs FFI. It makes me cringe a bit to say that, but you could do it in roughly the same way as how NumPy does it.

Indeed! I think the success of Bokeh (http://bokeh.pydata.org/) from Continuum has influenced their decision...

Thanks for the link! Have you found a way to use the plots offline in your own server (e.g. in Django)? I have just found integration with Jupyter....