The problem with:

    ret = ""
    for s in strings:
        ret += s

is that it re-allocates O(n) times, even if ret is referenced only once.

If the s are small the usual geometric buffer growth mitigates that. Of course you can compute the final buffer size in this case, but often you have a bunch of dynamically-generated strings of different sizes.

  def reduce(acc, f): 
    for v in self:
      acc = f(acc, v)
    return acc

The current acc goes out of scope each time you call f. There's no shared reference (assuming f doesn't sneak store it elsewhere, which for string combining, f should just be `return a+b`?).

The binding for acc in the reduce call is still active during the f call, which means there are at least two references to acc.

Why is it still active? Even an interpreter with no lookahead could see that it goes out of scope immediately when f returns (it gets shadowed on that line), so as long as there's no guarantee about when finalizers get called, it should be able to mark it dead inside of reduce as soon as it's passed to f. Like move semantics here should be a general pattern for optimization, no?

Does Python actually do that? If the f call throws, you can still observe the (unchanged) binding of acc in reduce.

Fair, I suppose there's no end to the level of insanity that a programmer can do in a dynamic language. I'd think it could perhaps still look to see there's no catch, but maybe eval makes even that impossible.

It might - let's assume it does. My point is that it's better to use the explicit optimized method for joining strings in a performance-sensitive context than to try to meet the conditions for an implicit optimization.