As a disclaimer, I'm a noted advocate of using Python to build production systems for quant finance (old talk but: http://python.mirocommunity.org/video/1531/py

As a disclaimer, I'm a noted advocate of using Python to build production systems for quant finance (old talk but: http://python.mirocommunity.org/video/1531/pycon-2010-python-in-quantitat http://python.mirocommunity.org/video/1531/pycon-2010-python...). I've been very successful at doing it and largely as the result of my example many other quant shops have chosen the Python route to excellent results. The pandas Python library (http://pandas.sourceforge.net http://pandas.sourceforge.net) is an open-source outgrowth of my proprietary work. My question is: why program in C++? I don't think anyone will argue it's an insanely low productivity language relative to Python or R. But Python and R are slow for iterative, procedural code. The near panacea for Pythonistas is to use Cython (http://cython.org http://cython.org) to develop C speed code but take maybe only 1.5-2x longer than writing Python code (to get all the type declarations right etc.). You can also directly call methods in C / C++ libraries using Cython, so it really is the best of both world in my experience. I think in general that hybrid systems are best avoided if at all possible since debugging across "the bridge" is a thorny problem. You typically end up with more code than you planned in the higher-productivity language (e.g. R). I like Python because Python is good at all the things that R is not good at. Yes, Python's statistics libraries are very weak (though we're making progress in http://statsmodels.sourceforge.net http://statsmodels.sourceforge.net) compared with CRAN, but in quant finance it turns out that 90% of the modeling and data analysis that you actually do isn't that statistically sophisticated. It's largely a relational data manipulation and time series processing problem (which pandas takes care of in spades-- has much better integrated data alignment features than just about anything in R, too). I suppose I should post this in stackexchange-- Python is also excellent for building GUIs. I've used wxPython and PyQt and found that I could hack together a GUI in an afternoon that would have taken a week to do in Java or C++.