[naasking]

Not true due to parallelism. Also, SQL demonstrates that you can describe the desired result declaratively without being concerned about iteration order. I see SQL's CTEs as a good example of the kind of primitive the article is talking about.

[alterom]

Sure, and perhaps that's the reason why we don't have a built-in for_tree: for some people, order matters; for others, it doesn't.

Then, for some cases, depth-first traversal is needed; for others, breadth-first.

Then, there's parallelism, and even the plain old for loops aren't parallel by default.

By the time you specify exactly what you need from a tree traversal, you've written code to do it.

And if you're fine with some default choice — you already can use the default iterator with the for_each loop.

I don't see what need there is for adding an extra for_tree syntax to do that.

[bloppe]

Also a lot of trees have fixed arity, like binary trees. But to model a general tree, you'd need a dynamically allocated list of children for each node, adding a layer of indirection that can noticeably worsen performance.

Trees are often considered too diverse to include even in the standard library, let alone as a primitive. Even Python doesn't have trees in the standard library. I'm sure it's been proposed and rejected at some point

[naasking]

> But to model a general tree, you'd need a dynamically allocated list of children for each node, adding a layer of indirection that can noticeably worsen performance.

I hate to be a broken record, but this again goes back to the assumption of a specific sequential computation model. Modelling relations as in SQL automatically supports for N-ary child relations. There are other computation models! eg. logic, relational, etc.

[bloppe]

I'm talking about cache optimization. Fundamentally, you simply cannot guarantee data locality while also allowing resizing. Growing the child list may necessitate moving it in memory. This is true no matter what your computation model is.

[smallnamespace]

Those other models lack native mechanical sympathy with the hardware.

Let's be practical about it: the reason you might want to say map_tree is so it could potentially be optimized to run more quickly, e.g. via automatic parallelization.

But to even parallelize a tree read operation we'd have to pull in other threads, split work, we'd want metadata on each node (child counts), and at the end of the day within each worker you'd still have a serial execution order.

For map_tree to have practical benefit your language would need to make a ton of opinionated choices about trees and parallel programming. Feasible? Yes. Worth making it a basic primitive? Well, even LISPs don't offer map_tree, despite building the whole language on top of car/cdr.