list.count has a special case for if (item == value) count++. I suspect that helps significantly here too, because the value item will usually be an interned integer.

Actually, PyObject_RichCompareBool has that fast path inside as well. I had the fast path before but then I wondered whether it was really needed or not (and I was a bit too lazy for benchmarkings). But I forgot about the interned integer case so it's probably faster.

We could probably make this significantly more efficient by looking at the memory directly without materializing an iterator and all the elements. str.count is a similar example. However, that is going to be a lot more complicated, so it seems fine to skip it; if somebody wants to optimize this method later they can.

Yes, that's what I suspected so I went for the simplest approach (at least to have the code around).