[kristjansson]

I think that complaint applies to the (vast, essential) ecosystem, not to the language and standard library. AFAIK, there aren't serious performance potholes to hit in the language and standard library any more. You're not paying a huge performance penalty for writing things the simple way, but things are uniformly pretty slow.

It's when you pull in fast libraries that composition breaks down e.g. the many-fold difference between numpy's sum method and summing a numpy array with a python for-loop and an accumulator.

[qsort]

I agree, the standard library doesn't have those problems. As you said though, the ecosystem is kind of the point of using Python in the first place.

Again, I'm not really a fan of Python as a general purpose language for large projects, but it really, really excels at being a kind of "universal glue", and it's why I use it again and again.

In that role, "uniformly slow" is better than "performance rollercoaster".