It’s easy (and common) to point to Instagram et al as examples of people using Python and even Django at scale. Beyond those big hitters though, Python is obvio

It’s easy (and common) to point to Instagram et al as examples of people using Python and even Django at scale. Beyond those big hitters though, Python is obviously a very popular language, and Django is a very popular web framework. The people making these tooling decisions aren’t just noobs. Python and Django obviously meet the functional and performance characteristics desired by a lot of people. I have Django projects, some of which I am going to assume are more complex than Mailman, using far less than two gigabytes in production. Not through any extreme optimisation efforts. It’s just…what’s happened. In my experience, the resource footprint you experienced with Mailman is not representative. Notwithstanding the fact that we’ve seen amazing performance improvements in Python as recently ad 6(?) months ago, if speed were my primary concern, I am obviously not picking Python. This doesn’t mean that it should be relegated to the frankly at this point outdated bucket of “scripting languages”. The language’s features, performance profile, and package ecosystem all surpass these use cases. The conventional wisdom, which I completely agree with, is that these days things are good enough that speed need not be a primary concern for most people most of the time. Sure, oldschool Mailman was fast, but did anyone want to or know how to actually work on it anymore? Evidently not.