I am learning how to write Quantlib code with Python in order to create a project of mine called Vol Kills. What better way to learn than writing down what I have figured out? And perhaps I can help others out along the way.
First question, why Quantlib? why Python?
Firstly Python is easier to learn than C++ (I admit I never tried, always sounded too daunting). You can code quick with no need to worry about the cruft that comes with Java and C.
Secondly, we're really just using Python to send messages to Quantlib which is written in C++ compiled down to super fast 1s and 0s.
Best of both worlds!
Third Python does a lot. You get the stats libraries; web frameworks; heavy lifting"extract transform load" libraries and more right there in the one place (their motto is "batteries included" after all). No need to mess around with multiple languages and run times.
A quick word about QuantLib. It's a collection of code which helps people like me model financial investments; understand how investor's portfolios tick and perhaps point out some opportunities and pitfalls ahead.
Quantlib has been developed for over a decade. It is widely used and battle hardened. Best of all it is free and open source, which means you can use it without worrying about licensing fees and nasty bugs (the more eyeballs on the code the less chance of errors).