Right, but the difference is whether you will ever have to do more than "just a little glue" and making sure you can easily delegate to a different tool to handle those cases. In my experience, there are precious few cases where you never have to do more than just a little glue. Basically any application in which Python owns the data model (e.g., the data model is a non-trivial tree of Python class objects), this is incompatible.

> Sure, and we agree: you wouldn’t use pure Python for something where every scrap of performance matters.

I don't want to be disagreeable, but this is the sort of thing I would say about Go or Java--you shouldn't use it for cases where every scrap of performance matters. But there's an enormous gap between the things Python can do and the things that Go and Java can do. Moreover, if you do run into problems with Go or Java, there's a lot of optimization available to you (at least not in the general case, although there are niches where you can gain a lot of performance with pandas or similar).

Moreover, there's just not a good reason to choose it these days. There are better options without the traps.