Can someone familiar with Matplotlib comment on how Sho's Python plotting utilities[1] compare?
This looks cool; still trying to wrap my head around what's fundamentally new vs. what is packaging together existing Python libraries and letting it all talk to .Net code (not that that isn't neat and useful in itself).
IPython, with Matplotlib and Numpy, has a ton of numerical libraries, especially LAPACK, which aren't in SHO. Matplotlib is also much more extensive in its capabilities. Some coder cried when they were told to write another Matrix class.
SHO has all the advantages of .NET's ecosystem, so that it can call anything .NET and be called by anything .NET. Making an environment like this should not be about using a Python REPL. You could work on the hard parts - models for asynchronous interactive calculations, or provenance tracking, or helping translate data formats from one API to another - and let the user choose a REPL.
Sho probably needs to sell its differences a bit more (if it has them). I didn't see any promises that would make it worth my while branching out from python's scipy + matplotlib + rpy packages. Maybe they're aiming for .Net users more...
My immediate thought was 'why wouldn't I just use R?' R has the advantage that almost everything you need to do statistically already has at least one package built for it.
The examples in the video section; a sticky sorter prototype? What is sho? I don't get it.
This looks cool; still trying to wrap my head around what's fundamentally new vs. what is packaging together existing Python libraries and letting it all talk to .Net code (not that that isn't neat and useful in itself).
[1] http://research.microsoft.com/en-us/um/redmond/projects/sho/...