I have three personal reasons to prefer static compiled over dynamic interpreted 1. Refactoring. In, say, c++, you change a signature, or a member name, and yo

I have three personal reasons to prefer static compiled over dynamic interpreted 1. Refactoring. In, say, c++, you change a signature, or a member name, and your IDE provides you with a neat, comprehensive list of errors to fix, if you're even performing the change manually. Contrast that with python, for instance, and I have to rely on what appear to be heuristics if I use an IDE to propagate a change, or otherwise repeatedly hit run to change everything that I've broken, and pray I didn't miss any code paths that'll bite me later. Maybe I'm just not writing pythonic code, but I find it rather difficult to maintain large codebases in python for this reason. 2. Focus. I realized that having a constant stream from a trusted linter makes it really easy to stay on task. I can throw out a bunch of scaffolding and then fill in the blanks based on the constant stream of errors, pre compilation. Sure, in pycharm I can run code analysis to get a list of probable errors, but given the nature of dynamic languages, there'll be plenty that's missed and plenty that isn't necessarily right, and not having a project wide linter in real time isn't the same. 3. Understanding APIs and library internals. There is a TON of use information that comes for free with explicit static typing, especially for scientific/numerical code. In python I frequently find myself having to look up simple function use because arguments, names, and returns can be ambiguous. In a typed language, I know exactly what goes in, what goes out, and how to structure my data appropriately. The difference in coding speed is huge, and I don't have to run the code nearly as often to make sure I'm doing things right. Why anyone would choose python for large projects eludes me!