I've had a chance to use Python several times in various projects. The language really excelled at small projects, where the expressiveness of the language and

I've had a chance to use Python several times in various projects. The language really excelled at small projects, where the expressiveness of the language and the excellent libraries available really let us get a lot done with little code and time. Avoiding the recompile/redeploy steps also helped. But using the language for larger projects was quite a different thing. Suddenly you could find yourself in code several layers down, being passed an object of God knows what type from unfamiliar code, and having to find out what you were receiving essentially by trial and error. And once the execution times started to climb, it became increasingly frustrating to see trivial problems that would have been caught during compilation in a statically typed language appear in Python only after 30-60 minutes of execution. There are surely ways to alleviate these specific problems -- I can think of some things to try myself -- but my experience suggests that the sweet spot for dynamic languages like Python is in projects that fit between one pair of ears, and stricter statically typed languages become increasingly useful as things scale up. (Hardly a radical position, I know.)