Ditching Excel for Python in a legacy industry
I'm a research actuary working in reinsurance.  Here is why I think Python creates more problems than it solves from the standpoint of most insurance business users:<p>1.) Environment management.  There are many solutions for managing python dependencies, my favorite is Docker + pip.  Good luck getting actuaries and underwriters to write Dockerfiles etc, and good luck getting I.T. to support Docker on Windows desktops.  Like it or not, the best "feature" of Excel is that it is mostly the same on every corporate Windows machine.<p>2.) Unless you are using numpy / numba, Python isn't that much faster than VBA (if at all).  Both are "compiled" to interpreter bytecode.<p>3.) Speed of development and traceability.  Excel takes a lot of getting used to, but if you know the purpose of the spreadsheet (e.g. a reserve calculation), it's relatively easy to figure out what a mangled and convoluted formula is doing (Excel has a "debugger" that allows you to evaluate formulas by highlighting pieces).<p>4.) LAST BUT NOT LEAST.  Many financial and actuarial (insurance) calculations are inherently recursive.  Excel has built-in memoization (in the dynamic programming sense).  It also has a reactive programming model.  Good luck implementing that in Python without tripping up on the huge amount of function call overhead, even if you use a memoization decorator.