I think this kind of control mechanism is not a great idea and could lead to easy bugs.
I think it's a better idea to write a function that applies a function to the elements of a tree. Ideally you'd make a function for each traversal order. This makes it obvious what is happening.
I bet you could do something generic like this in languages that have deferred execution like C#'s IEnumerable. Something like
foreach (Node node in EnumerateNodes(root, x => x != null, x => [x.Left, x.Right]))
where EnumerateNodes uses `yield return` (i.e. is a generator) and calls itself recursively. Though it'd probably be easier / better performance to write an implementation specific to each node type.
Once you have algebraic data-types in a language, writing a recursive visitor pattern is pretty simple.
Encoding the semantics of a tree traversal operator likewise is difficult in the general case. What exactly would the order be, what if I want to traverse in a non-standard ordering, what about skipping branches; all would be difficult to cleanly represent.
I have seen it done where you return actions with key ones being recurse, stop, replace, and replace & then carry out some function, but again, this is pretty simple to implement.
No, that seems like language bloat. Better to make your language have internal iterators, as then data structures can add their own logic that matches their need for iteration. Then special cases don't need additional syntax.
Trees aren't really a "special case". Sequences, trees and graphs are core abstractions to most programming, why try to flatten all trees and graphs to sequences?
Because your code is actual running serially so no matter what there is an iteration order, and the order matters for performance even if your code does not care.
For example if you literally don’t care about the order then your code can map over a default iterator that is efficient (DFS).
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.
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
> 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.
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.
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.
The point wasn't that it should be treated as a sequence of not, but that with good base abstractions you can move the decision of what to do, and how, into the data structure itself, rather than having to have the language decide for it.
> Sequences, trees and graphs are core abstractions to most programming, why try to flatten all trees and graphs to sequences?
Because "trees" and "graphs" aren't actually single concepts, they're families of concepts that can vary along many dimensions. Most programming languages offer one or a small handful of sequence types, because most sequence use patterns are the same. Most languages don't offer a tree or graph type, and as soon as you try to implement one you see why: there are multiple different kinds of trees and graphs, and multiple different representations that are appropriate for different use cases, and any one you might pick would be unsuitable for most programs people want to write.
> Most languages don't offer a tree or graph type, and as soon as you try to implement one you see why: there are multiple different kinds of trees and graphs, and multiple different representations that are appropriate for different use cases
I think it's more because the abstract interfaces for trees and graphs that can support multiple representations aren't as well known [1]. An iterator/sequence interface has a simple abstract structure that everyone immediately understands, but the structure needed to abstract over graphs and trees are trickier.
I agree with the author, we need better primitives, if you need functionality now:
Major tools that exist today for partial structure traversal and focused manipulation:
- Optics (Lenses, Prisms, Traversals)
Elegant, composable ways to zoom into, modify, and rebuild structures.
Examples: Haskell's `lens`, Scala's Monocle, Clojure's Specter.
Think of these as programmable accessors and updaters.
- Zippers
Data structures with a "focused cursor" that allow local edits without manually traversing the whole structure.
Examples: Huet’s original Zipper (1997), Haskell’s `Data.Tree.Zipper`, Clojure’s built-in zippers.
- Query Languages (for semantic traversal and deep search)
When paths aren't enough and you need semantic conditionals:
- SPARQL (semantic web graph querying)
- Datalog (logic programming and query over facts)
- Cypher (graph traversal in Neo4j)
- Prolog (pure logic exploration)
These approaches let you declaratively state what you want instead of manually specifying traversal steps.
These are what I think the author is looking for. But it shouldn't be a "primitive" in terms of code automatically generated by the compiler, but an interface or typeclass like your examples (in a language advanced enough to have them.)
The problem is that 'lens', 'monocle', etc. are famously abstract and difficult for people to apply to their actual problems. IMO, the solution would be for standard libraries to specify interfaces called 'BreadthFirstTraverse', 'DepthFirstTraverse', etc.
> These are what I think the author is looking for. But it shouldn't be a "primitive" in terms of code automatically generated by the compiler
I think people are often too enamored by general purpose languages that can express such abstractions natively. I don't see an issue with a language that provides this as a primitive without being able to express it itself, constraints can be useful for other properties. Once you can traverse trees, most programming problems can be tackled even in such constrained languages, eg. SQL with CTE.
I definitely agree for traversals, but Lenses need some sort of primitive support - even in Haskell they're mostly generated with TemplateHaskell, and the language developers have spent a long time trying to make the `record.field` accessor syntax overloadable enough to work with lenses[1][2]. Hopefully someday we'll be free from having to memorize all the lens operators.
Optics are famously abstract in implementation, but I don't think people have trouble applying them - people seem to like JQuery/CSS selectors, and insist on `object.field` syntax; it's kind of wild that no mainstream language has a first-class way to pass around the description of a location in an arbitrary data structure.
Optics let you concisely describe the location, but defer the dereferencing, so you could definitely approximate optics, not by passing around pointers you compute with `offsetof`, but passing around functions that use `offsetof` to return memory locations to reference (read/write to). You could certainly write a composition operator for `*(*T) => List<*R>`... Some people have done something like it[1][2]:
Account acc = getAccount();
QVERIFY(acc.person.address.house == 20);
auto houseLens = personL() to addressL() to houseL();
std::function<int(int)> modifier = [](int old) { return old + 6; };
Account newAcc2 = over(houseLens, newAcc1, modifier);
These also use templating to get something that still feels maybe a little less ergonomic than it could be, though.
Traversable and lenses are very closely linked. If you go to the original paper leading to Traversable [1] and read through it, it feels basically identical to reading through the parts of the lens library that lay down the core abstractions and the laws implementations must follow if you want to be able to blindly manipulate them. In fact, the traverse function is a Traversal, and so fits trivially into the lens ecosystem.
Arent haskell traversables different in that they preserve the structure if you were to map over them, as compared to the solution posted in the article, where they get flattened to what amounts to a list?
Indeed they call for new names, as they encompass far more than iterators.
If you read a bit more about them, I think you will be surprised to see the breadth of what these abstractions can be used for. To start, they've been used to build a new compositional foundation for game theory[1], and they can be used to model gradient-based learning in machine learning[2].
As for their simpler applications as getters and setters, they are programmable in the sense that you can think of lens/prism types as interfaces that can be implemented arbitrarily. So you can create your own lenses and combine them like legos to construct new, "bigger" getters and setters from the smaller components.
This thread is about traversing a tree. At what point do we take a step back and think that iterating through a data structure and "building new compositional foundations for game theory" shouldn't be conflated together?
When does someone give up on the pagentry of programming and just get something done by looping through data instead of "constructing getters and setters to model gradient based machine learning".
It really seems like the straight forward way of doing things is to make simple iteration and worry about the game theory after that is all figured out.
I do get, and to some extent sympathize with, your position. But the comments to the article are, in large part, fundamentally addressing a higher level of abstraction than the more narrow scope of the article’s premise. As several commenters have referenced, traversing a tree in a ‘simple’ and narrow manner is addressed at the appropriate level of abstraction using already established mechanisms, particularly in Haskell using Traversable (a typeclass with a standardized implementation for trees). The discussion of Optics and Lenses are more of a side discussion about the syntax and implementations of a more broad set of data structures than merely trees.
I think your comment is valuable in spirit because it could bring a more thorough discussion of the creation or popularization of a syntactically clean and a shift of the idiomatic-ness of such a solution to traversing trees. Leaving the more abstract and general Optics discussion to be a side dish for commenters to discuss as well.
Also, just a nitpick, but traversing a tree is a broader topic than iteration. Iteration implies, both colloquially and formally, performing a computation on each element of a data structure, while traversal is a more general algorithm that could be the basis of iteration, but may also be more akin to a search through the data structure without expectation of performing computation until the searched for ‘member’ is returned from the traversal. So it’s not an apples-to-oranges comparison with your conflation of iteration and traversal, but does seem a little like Canis Familiaris-to-Mammal comparison.
I read your whole comment but I'm still not getting where the actual rubber meets the road. If I have a tree data structure what am I missing? What is it that I can't do that makes this extreme iteration complexity worthwhile? To me, having simple access to the data structure is enough because that's what I want a data structure for.
how about we also get regex-parsable streams (IO::Async in perl has something like it, suboptimal perhaps) and regex-parsable treestructures (totally possible)? seems like just having the ~= work on structures (or whatever the API is called in other languages, this being Perl5)?
To point out a prolog thing which is also applicable to other languages with good patter matching: the break/return/prune examples are all ergonomic to implement as recursion in a way that fails in C++ style type based dispatch.
In Rust, you can extend the syntax a bit within the language itself.
For C++, you could define yourself a template that expands to the two functions you listed.
For any language, you could write yourself a pre-processor that adds for_tree notation and expands it,
either with pre-processor semantics or working on the abstract syntax tree (which is more "proper" but also more work"). I would recommend the former to test notations, and then you can live with them for a while to experiment with them and see if and how often you really need the construct (recall that is how C++ evolved from C via "C with classes" - it was first a pre-processor).
Once you and others are 100% convinced of the new syntax, go to your prefered language's working group/ISO committee and propose inclusion.
My own feeling is that this is not something for which I need more than recursion; calling inside traverse() traverse(left) and traverse(right) for binary trees or using a normal for loop to iterate over all this->children() from 0 to this->children.size() is something that occurs in graph libraries and parsers/compilers once in a while but not often enough to warrant its own notation. Rather, when I look at languages like C++, I'd have a language that is simpler, cleaner, more homogeneous and more orthogonal; C++ is complicated, convoluted, too large to implement it correctly by a single person in reasonable time (compared to beauties like C, Pascal, Scheme), so I stand on the side of minimalism.
The "syntax extension" thing is precisely the reason I have an interest in (and advocacy for) Common Lisp.
Be that as it may, for C++, Eric Neibler's [Boost.Proto](https://www.boost.org/doc/libs/1_84_0/doc/html/proto.html) could likely help conveniently connect syntax to implementation to achieve something similar to what the author is taking about.
That's "just" a particular kind of fancy iterator that you should be able to implement in any language with iterator support. Here's one in Python:
# Expects:
# Tuple of iterateOn where iterateOn can be None
def fancyIt(init, *options):
if init != None:
yield(init)
for f in options:
newVal = f(init)
yield from fancyIt(newVal, *options)
class Tree:
def __init__(self, val, left = None, right = None):
self.val = val
self.left = left
self.right = right
def left(self):
return self.left
def right(self):
return self.right
myTree = Tree(
1,
Tree(2,
Tree(3),
Tree(4, None, Tree(5))),
Tree(6, None, Tree(7)))
for node in fancyIt(myTree, Tree.left, Tree.right):
print(node.val)
which prints the numbers 1 through 7 in order.
Breadth-first is slightly trickier, but only slightly trickier one time.
Yeah, tree traversal is really easy and implementing it as an iterator is natural. Maybe don't use a recursive technique if you plan on working with non-toy datasets, Python's default stack limit is pretty small (1000), but this is otherwise a very flexible API.
While easy, I think bisect would be a good addition to every stdlib too.
I did the tree just to match the author's example. I would agree that a bespoke iterator for breadth- and depth-first iteration for any given tree is probably a better way to go. As long as we're in a language like Python, build in something that allows you to examine a branch and decline to descend into it while you're at it.
I don't think this is a large problem in practice because you shouldn't be using dozens of tree types in a given code base, so adding iterators to a tree is no big deal. In general there aren't enough types of iteration available to a given data structure that you need to describe how to iterate on it from the "outside". (Generally when you are doing that, it's too non-trivial to fit into this pattern anyhow; see the Visitor pattern in general.) This strikes me as maybe the sort of default tool you might slap in a library somewhere, but it should be a niche tool. If you're using it all the time you're probably doing something wrong. By default your data structures should be providing iteration packaged with them and it should generally be what you need. And your language should support aborting iteration, in whatever that looks like normally. I'm not sure I know a language that doesn't, it's a fairly basic element of iterator support when you get into implementation.
There are also many cases where a tree iterator will perform significantly better, including CPython. I don't have enough experience with PyPy to know if it could inline the Tree.left and Tree.right calls down to zero penalty at JIT time. Rust and C++ and the other static languages with sophisticated compilers might be able to get that down to fully inlined and zero-cost, but even if they can it's probably better not to push that on to the optimizer as the optimizers will eventually give up if this is composed with enough other stuff. Better to just have an efficient implementation in the first place.
Yes, students should absolutely implement the classic algorithms to learn.
Yes, there are some occasions when you need to home grow one at $work.
BUT, in my opinion, most of the time, professional code should use a battle tested, vuln hardened library or builtin version. These things are VERY HARD to get exactly right. Jon Bently's Programming Pearls famously had a latent bug in its binary search for 20 years before someone caught it.
Sure but all pre-made, battle-tested tree datastructures you'd use in production in all languages already come with some form of iterator that you can just for-loop over, so the original articles point is still moot.
Your reply is not relevant to my reply. The original poster is asking for this functionality and appears to believe it is something other than an iterator and requires some sort of special language support. However, it is completely implementable as an iterator, in a reasonably usable manner, with no additional language support. My specific code is written only to show that fact off.
Anyone who copies and pastes it is welcome to both pieces when it breaks. Others have already alluded to possible improvements that could be made, and I already have my own analysis in a grandchild reply as to why I don't think this is a terribly pressing need or necessarily even a good idea.
The reason I provide code is that it gets past the "oh, you say it's just an iterator, but I still don't believe you, since you haven't spelled it out to the n'th degree". When code is provided, belief ceases to be an issue. It is clearly something an iterator can implement, in existing languages, with existing iterator support.
Unless you're going to claim it is somehow impossible to provide this functionality in a tested manner, you're completely changing the topic in an uninteresting direction, since it is always true that functionality generally needs testing and bits of code slammed into an HN conversation just to make a particular point probably shouldn't be copied wholesale into your production code.
Whoops, my edit window closed, but that first comment derives from a previous version that had a different signature for the functions in the "options" list. Ignore it.
Well, the whole point of the blog post is to argue for a new kind of syntactic sugar and the author explicitly mentions iterators.
> Well a range based for loop requires that your tree exist in memory AND that you have an iterator defined for your tree. With for_tree you could operate on an entirely imperative tree, without needing to define any iterators or generator functions. Here's an example where I'm checking every single string composed of "a", "b", and "c" of length 8 or less.
for_tree(string x = ""; x.size() <= 8; x : {x+"a", x+"b", x+"c"}){
print(x);
}
You could definitely find every string composed of "a", "b", and "c" of length 8 or less by defining a custom iterator but it would be a verbose and unpleasant way of writing it:
class StringIterator {
public:
using iterator_category = std::forward_iterator_tag;
using value_type = std::string;
using difference_type = std::ptrdiff_t;
using pointer = const std::string*;
using reference = const std::string&;
StringIterator(bool begin = false) : is_end_(!begin) { if (begin) s_ = ""; }
const std::string& operator*() const {
if (is_end_) throw std::out_of_range("End iterator");
return s_;
}
StringIterator& operator++() {
if (is_end_) return *this;
if (s_.size() < 8) return s_.push_back('a'), *this;
while (!s_.empty() && s_.back() == 'c') s_.pop_back();
if (s_.empty()) is_end_ = true;
else s_.back() = s_.back() == 'a' ? 'b' : 'c';
return *this;
}
StringIterator operator++(int) { auto tmp = *this; ++(*this); return tmp; }
bool operator==(const StringIterator& other) const {
return is_end_ == other.is_end_ && (is_end_ || s_ == other.s_);
}
bool operator!=(const StringIterator& other) const { return !(*this == other); }
private:
std::string s_;
bool is_end_;
};
int main() {
StringIterator begin(true), end;
int count = 0;
for (auto it = begin; it != end; ++it) ++count;
std::cout << (count == 9841 ? "Pass" : "Fail") << std::endl;
return 0;
}
def itWithStop(init, stop, *options):
if init is not None and not stop(init):
yield(init)
for f in options:
newVal = f(init)
yield from itWithStop(newVal, stop, *options)
for s in itWithStop("",
lambda x: len(x) > 2,
lambda x: x + "a",
lambda x: x + "b",
lambda x: x + "c"):
print(s)
yields the combinations of 0 - 2 length strings with a, b, and c.
Python has a number of ways to achieve this depending on exactly how you want to pass the arguments; multiple functions, optional arguments, etc. How nice the final call looks is more about your local language's closures look.
The main point here is that this will happily iterate on things that don't "exist".
module Tmp where
iter :: forall a. (a -> Bool) -> [a -> a] -> a -> [a]
iter p opts x = if p x then x:concatMap (iter p opts) (opts <*> [x]) else []
ghci> :l tmp.hs
[1 of 1] Compiling Tmp ( tmp.hs, interpreted )
Ok, one module loaded.
ghci> iter (\x -> length x < 3) [(++ "a"), (++ "b"), (++ "c")] ""
["","a","aa","ab","ac","b","ba","bb","bc",
"c","ca","cb","cc"]
(Since things are lazy in Haskell, functions that return lists effectively are iterators. There's probably something in the standard library somewhere for (opts <*> [x]) to avoid the wrapping x in an unnecessary list, but my Haskell is rusty.)
The iterator in my example will also happily iterate on things that don't exist. We all agree that it's possible to do in any language. But the main point is that the blog post is talking about syntactic sugar for an easier way to do it.
And yes, Haskell is amazing at this sort of thing.
The syntactic sugar being asked for in this case is awfully thin. I definitely put this in the class of "stop pining for it and just use what's there".
If the poster wants to particularize this to C++ because C++'s syntax can't support it in any reasonable manner, that's fine, but that's a C++ problem, not a "Programming languages..." problem. Which would be perfectly understandable and I'm not really complaining, more clarifying that most of the rest of the world can just rub together three or four existing constructs in a pretty reasonable manner to get this.
Same thing, but the iterator is instead hidden inside the language implementation. `foreach` is already a quite general construct, and iterators are the way to extend them. However, I can see the benefit of designing a library to help implement more intricate iterators.
Ceterum censeo this would be a family of simple macros in LISP.
It seems like it should be possible to factor out most of the iterator boilerplate into a helper class. Then each place where you want to iterate you can construct an instance of that helper class and supply a lambda that specifies how to descend into children. If you're doing the same iteration in several places then you can use a named function instead of a lambda, which means less typing for each `for` loop. Here's a rough sketch: https://godbolt.org/z/x94WY77rv
I mean people do use iterator instead of for loops quite a lot.
IMO the thing that would be really nice is if control flow like `for` was actually the same as using an iterator. This would really help in Rust too where handling errors inside iterator callbacks is a right pain.
I've seen a few languages try this but it seems to not be very popular. I think it can get a bit confusing how control flow keywords like `return` and `break` work if you turn `if` into syntactic sugar for a function call taking a closure etc.
Sean Parent developed ‘forest’ for C++ that automatically maintains the invariant that its structure is always a hierarchy. It includes full-order iteration through its default iterator: https://stlab.cc/2020/12/01/forest-introduction.html
Don't need to go that far, std::map is a tree (the standard does not dictate it, but it is in all ilmplementations), and you could always traverse it. The whole idea of iterators was popularized by C++ and its STL.
std::map uses a tree as an implementation detail to achieve certain performance guarantees. It is not a tree from the user’s perspective, however. That is, there are no parent/child relationships between the elements in a std::map.
I remember that I was using trees quite often last century, when I was writing programs in C. I seldom use tree or comparably complex data structures nowadays, when I almost only write web apps (mostly backend in Ruby or Python but some frontend in JS.) I'm bet that both Ruby and Python have plenty of trees written in C inside their interpreters. I do everything with arrays (lists) and hash tables (dicts) in Ruby and Python. Maybe a language construct for trees would be nice for lower level languages and almost out of scope for higher level ones.
The same from another angle: there are a lot of trees in the indices of SQL databases (example [1]) but we don't zoom in to that level of detail very often when defining our tables.
Usually yes. Web apps are simple. There isn't much to do inside a request params to db to response call. But sometimes, not every year, there is something to really reason about. I still remember some project from 10 or 20 years ago.
User interface widgets form a forest - windows contain layouts that contain widgets which also can be layouts, etc, etc.
To implement Brown's algorithm to optimize class-based language models I had to implement a complex forest (DAG, actually) in Python using lists of fixed length. That was not especially nice to work with.
Couldn't you just do this with a regular for loop and a few datatypes/functions? (This pseudocode is an Elm/Haskell/Rust/TypeScript-inspired abomination, but pretty portable to any language...)
type Node = { value: Any, left: Node, right: Node }
type Direction = Left | Right
type TreePosition = { root: Node, currentNode: Node = root, position: Direction[] = [] }
# Implementation left as an exercise but should be obvious and run in O(1), I believe. Returns Nothing when we're out of nodes.
function nextPosition(position: TreePosition): Option<TreePosition>
# The tree you want to iterate through
const myTree: Node = ...
# The loop
for(let position: TreePosition? = TreePosition(root: myTree); position != Nothing; position = nextPosition(position) {
node = position!.currentNode
# Your loop code
}
I'd argue this doesn't belong as a language-level feature, but maybe an API/stdlib-level feature.
Indeed, I don't see any need to have a tree as a language primitive along with a traversal function (iterator). Tree traversal is not really different than iterating over a vector/list. E.g. even java has stuff like: TreeSet.forEach(consumerRef) or for(Type val : tree) doStuffWith(val)
Trees are an insignificant middle ground between lists (which, by the way, are degenerate trees) and general iterators (on general object graphs, or not even materialized).
For perspective, I'm a novice with algorithm design, I've been grinding leetcode for the past 6 months or so, almost exclusively in Rust. I was bewildered by the same concern since I had initially set out to, not only focus on Rust, but to primarily maximize use of the Iterator construct, since I was not intricately familiar with it. A few months in I discovered that there was an appropriate Iterator construct which accomplishes the same thing.
// Comments for the non-Rust native reader, regarding this Function declaration:
// successors is a function that accepts an `Option` container for some Value of type T, called `first`
// and a Closure called `succ`, constrained below:
pub fn successors<T, F>(first: Option<T>, succ: F) -> Successors<T, F> ⓘ
where
// `succ` must receive the iterated state, and return the next iterated state
F: FnMut(&T) -> Option<T>,
// Each time the `next()` function is called on the returned Iterator (a Successors-flavored iterator),
// the state of `first` is yielded, and then
// `succ` is called to progress
// until a `None` type is reported by `succ`
I'm not sure where the concept came from, but it's not dissimilar to the author's implementation, but instead of the ControlFlow enum, it relies simply on the Option enum. I know though, that it was initially built in the Itertools crate as unfold and then upstreamed some time later.
Essentially you use `first` to contain a Queue, Stack, or Level for the different traversals, and define traversal or activities from there.
It's fairly ergonomic in practice, ergonomic enough for Leetcode.
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Also I’m slightly confused by this example.
for_tree(string x = ""; x.size() <= 8; x : {x+"a", x+"b", x+"c"}){
print(x);
}
So, our “next node” operation is to concatenate to x. Won’t we either have to have a method for modifying x to go “up” a node, or we’ll have to keep a record of what x was upon entering each node? Like in this example we’ll end up with x=“aaaaaaaa” and then go up a node, over to a “b” node, and get x=“aaaaaaaab”, right?
I think the intention is that you keep a record of what x is in the current node, and at every node above the current node. In the recursive implementation which the author describes as equivalent, these values are kept in the stack.
Well, it doesn't need to be any worse than the stack-based implementation of a recursive tree traversal, and it can't be significantly better. You have to store that state somewhere.
Perhaps it can be optimized to be a little better than the recursive version, depending on how much overhead your language uses for a stack frame that it won't need for this special case.
The author said it could be implemented recursively, so a call with x="aaaaaaa" would call three more functions with x="aaaaaaaa", "aaaaaaab" and "aaaaaaac". you never need to go up a node
The article's thesis relies on the idea that a genuinely primitive traversal action exists, in the way that a for-loop is primitive and widely applicable, or adding two floats is common enough to justify building it into the language (or processor).
But tree traversal doesn't have this universal property. There are too many methods and purposes for traversing a tree, sufficient that IMHO no single primitive embodiment could materially improve a language. Also, modern compilers efficiently break down high-level traversal code so well that expressing the idea at a high level incurs no serious penalty compared to having a primitive for that purpose, or a series of them.
Though Haskell's Traversable is similar in name, then depending on what the developer intends, both Functor, Foldable or Monad could also help with the traversal. I.e, Haskell already has what the blog post asks for.
One great reason not to use recursive functions for traversing trees is that you can allocate your own stack data structure rather than relying on the call stack itself. In most languages/runtimes, the call stack has a maximum depth which limits the depth of trees you can process, usually on the order of thousands of stack frames.
Managing your own stack usually produces weirder looking code (personally I find "naive" recursive approaches more readable) - but having it as a first-class language feature could solve that!
The language doesn't get much of a say, stack limits are usually inherited from the OS itself. It's fixable by not using the OS-provided stack but that's a much more invasive change than a new syntax/stdlib feature.
Tail call elimination is an optimisation that is only possible for certain code patterns. How would you write a tail-recursive tree walk, without using a separate stack or queue data structure to store state?
In addition, clojure.core has the handy tree-seq function:
(defn tree-seq
"Returns a lazy sequence of the nodes in a tree, via a depth-first walk.
branch? must be a fn of one arg that returns true if passed a node
that can have children (but may not). children must be a fn of one
arg that returns a sequence of the children. Will only be called on
nodes for which branch? returns true. Root is the root node of the
tree."
{:added "1.0"
:static true}
[branch? children root]
(let [walk (fn walk [node]
(lazy-seq
(cons node
(when (branch? node)
(mapcat walk (children node))))))]
(walk root)))
Didn't Wirth(may be it was someone else) say that it is better to have a complex data structure and simple algorithm/code that works on them than having simple data structures and complex code.
Complex data structures absorb lot of the complexity of the problem and reduce the complexity of the rest of the code.
It is even better to have 100 functions work on 100 data structures. Powerful programming languages like Lisp and Haskell give you that. Generics gives you most of that.
If every ounce of performance matters, e.g. in a database, you want 10000 functions, 100 for each data structure.
Lisp gives you an infinite amount of functions that operate on one data structure: the cons cell. :P
I guess all you really need are dynamically allocated arrays. A cons cell is an array of two. A struct with N fields is an array of N. Everything else is built on that.
This is heavy biased to C++, which is a language that already has too many features that people just want to use. This is a very specific case to be placed as a language feature, and could be just a lib.
If this becomes a C++ feature, imagine how many data structures we would need to support?
Many other languages, specially the FP languages, allow to do that as a library. Even the languages that are only inspired by FP. Example, Ruby:
class BinTree
include Enumerable
def initialize v, l, r
@v, @l, @r = v, l, r
end
def each &block
@l.each(&block) unless @l.nil?
yield @v
@r.each(&block) unless @r.nil?
end
end
Using the Enumerable mixin includes many FP-based methods, such as map, filter and reduce by only defining each, which in this case is DFS.
You know, if Haskellers already have that functionality, maybe it's less that they're smug and more that they have already solved the problem. Do you call someone smug when you complain about being freezing and they invite you in out of the cold?
This is solved by iterators in C++. The idea of an iterators is to generalize the concept of a pointer —- something which refers to a location in your data structure.
For example the most basic operations of a pointer are to advance and dereference.
std::map is actually implemented as a tree. To iterator its members you can do
for (cost auto &pair : map)
The only requirement for your custom data structure to work is to implement begin() and end() which return iterators - “pointer like” objects.
I'm surprised nobody's brought up C++ generators yet (which avoid potential problems with recursion stack depth).
for (const auto&node: await depth_first_tree(node))
And generators have the added advantage that walking trees is just a special case of the more general case of traversing a directed graph of elements, which is equally easy.
I didn't even know C++ had generators, but you're right, generators make functions that walking trees much more obviously correct and convenient to write.
The site cppreference has an example of walking trees in C++ using them.
But I have a question: why is it that in your example, you write `await` before the generator function, but it's not in the example given on cppreference? Also, did you mean `co_await`?
To answer your question: I have used them, but I was too lazy to look up the correct syntax. Yes. It should be co_await. The library I used was layered on top of the C++20 co-routine implementation, not c++23, and used co_await there (but probably should not have).
Do NOT use the c++20 co-routine APIs (a half-implemented nightmare of an API, although what is there does miraculously work, contrary to expectations). Probably better to wait for c++23 generators, which are so far available as an experimental feature on GCC 14.0 (which makes the feature unusable in any of my projects).
All of which, I guess, answers my question about why nobody has brought up c++ generators yet. C# has nice generators.
Not as ergonomic as a direct tree-iterator, but I can't see of an elegant way to introduce that in an imperative language while keeping the forking/recursion aspect clear
Sure you can do it any way but the OP was about adding language features for iteration of a specific data structure. Iteration in C++ is state machine based and coroutines give you a neat way to implicitly model them without having to manage the boiler plate yourself.
Yeah, but what I do not get is why you need all this. What problem does this solve? The C function that advances to the next tree node does exactly the same. And what is neat about it? It just seems a lot more complicated. Or in other words: A new language feature should make things simpler and not more complicated to express. But maybe I am just missing a realistic examples where it actually makes things simpler?
210 comments
[ 4.2 ms ] story [ 307 ms ] threadI think it's a better idea to write a function that applies a function to the elements of a tree. Ideally you'd make a function for each traversal order. This makes it obvious what is happening.
map_tree_pre(my_tree, my_func);
map_tree_in(my_tree, my_func);
map_tree_post(my_tree, my_func);
map_tree_bfs(my_tree, my_func);
https://cs3110.github.io/textbook/chapters/data/trees.html
Encoding the semantics of a tree traversal operator likewise is difficult in the general case. What exactly would the order be, what if I want to traverse in a non-standard ordering, what about skipping branches; all would be difficult to cleanly represent.
I have seen it done where you return actions with key ones being recurse, stop, replace, and replace & then carry out some function, but again, this is pretty simple to implement.
Candidates: Racket, Scheme, Rust.
Defining your own iterator would be enough for most cases.
For example if you literally don’t care about the order then your code can map over a default iterator that is efficient (DFS).
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.
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
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.
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.
Because "trees" and "graphs" aren't actually single concepts, they're families of concepts that can vary along many dimensions. Most programming languages offer one or a small handful of sequence types, because most sequence use patterns are the same. Most languages don't offer a tree or graph type, and as soon as you try to implement one you see why: there are multiple different kinds of trees and graphs, and multiple different representations that are appropriate for different use cases, and any one you might pick would be unsuitable for most programs people want to write.
I think it's more because the abstract interfaces for trees and graphs that can support multiple representations aren't as well known [1]. An iterator/sequence interface has a simple abstract structure that everyone immediately understands, but the structure needed to abstract over graphs and trees are trickier.
[1] https://www.cs.tufts.edu/~nr/cs257/archive/andrey-mokhov/alg...
Major tools that exist today for partial structure traversal and focused manipulation:
- Optics (Lenses, Prisms, Traversals)
- Zippers - Query Languages (for semantic traversal and deep search)The problem is that 'lens', 'monocle', etc. are famously abstract and difficult for people to apply to their actual problems. IMO, the solution would be for standard libraries to specify interfaces called 'BreadthFirstTraverse', 'DepthFirstTraverse', etc.
I think people are often too enamored by general purpose languages that can express such abstractions natively. I don't see an issue with a language that provides this as a primitive without being able to express it itself, constraints can be useful for other properties. Once you can traverse trees, most programming problems can be tackled even in such constrained languages, eg. SQL with CTE.
Optics are famously abstract in implementation, but I don't think people have trouble applying them - people seem to like JQuery/CSS selectors, and insist on `object.field` syntax; it's kind of wild that no mainstream language has a first-class way to pass around the description of a location in an arbitrary data structure.
[1] https://ghc-proposals.readthedocs.io/en/latest/proposals/002...
[2] https://ghc-proposals.readthedocs.io/en/latest/proposals/015...
[1] https://en.cppreference.com/w/cpp/types/offsetof
[1] https://github.com/graninas/cpp_lenses [2] https://github.com/jonsterling/Lens.hpp
[1] https://www.cs.ox.ac.uk/jeremy.gibbons/publications/iterator...
Think of these as programmable accessors and updaters.
How is iterating through something already not 'programmable' ?
If you read a bit more about them, I think you will be surprised to see the breadth of what these abstractions can be used for. To start, they've been used to build a new compositional foundation for game theory[1], and they can be used to model gradient-based learning in machine learning[2].
As for their simpler applications as getters and setters, they are programmable in the sense that you can think of lens/prism types as interfaces that can be implemented arbitrarily. So you can create your own lenses and combine them like legos to construct new, "bigger" getters and setters from the smaller components.
[1] https://arxiv.org/pdf/1603.04641 [2] https://arxiv.org/abs/2103.01931
EDIT: fixed typo
When does someone give up on the pagentry of programming and just get something done by looping through data instead of "constructing getters and setters to model gradient based machine learning".
It really seems like the straight forward way of doing things is to make simple iteration and worry about the game theory after that is all figured out.
I think your comment is valuable in spirit because it could bring a more thorough discussion of the creation or popularization of a syntactically clean and a shift of the idiomatic-ness of such a solution to traversing trees. Leaving the more abstract and general Optics discussion to be a side dish for commenters to discuss as well.
Also, just a nitpick, but traversing a tree is a broader topic than iteration. Iteration implies, both colloquially and formally, performing a computation on each element of a data structure, while traversal is a more general algorithm that could be the basis of iteration, but may also be more akin to a search through the data structure without expectation of performing computation until the searched for ‘member’ is returned from the traversal. So it’s not an apples-to-oranges comparison with your conflation of iteration and traversal, but does seem a little like Canis Familiaris-to-Mammal comparison.
Definitely can be done to streaming data… protobufs in a way is this, given it’s a sort of BNF from a bird’s eye.
https://wiki.haskell.org/index.php?title=Research_papers/Gen...
For C++, you could define yourself a template that expands to the two functions you listed.
For any language, you could write yourself a pre-processor that adds for_tree notation and expands it, either with pre-processor semantics or working on the abstract syntax tree (which is more "proper" but also more work"). I would recommend the former to test notations, and then you can live with them for a while to experiment with them and see if and how often you really need the construct (recall that is how C++ evolved from C via "C with classes" - it was first a pre-processor). Once you and others are 100% convinced of the new syntax, go to your prefered language's working group/ISO committee and propose inclusion.
My own feeling is that this is not something for which I need more than recursion; calling inside traverse() traverse(left) and traverse(right) for binary trees or using a normal for loop to iterate over all this->children() from 0 to this->children.size() is something that occurs in graph libraries and parsers/compilers once in a while but not often enough to warrant its own notation. Rather, when I look at languages like C++, I'd have a language that is simpler, cleaner, more homogeneous and more orthogonal; C++ is complicated, convoluted, too large to implement it correctly by a single person in reasonable time (compared to beauties like C, Pascal, Scheme), so I stand on the side of minimalism.
Be that as it may, for C++, Eric Neibler's [Boost.Proto](https://www.boost.org/doc/libs/1_84_0/doc/html/proto.html) could likely help conveniently connect syntax to implementation to achieve something similar to what the author is taking about.
Breadth-first is slightly trickier, but only slightly trickier one time.
While easy, I think bisect would be a good addition to every stdlib too.
I don't think this is a large problem in practice because you shouldn't be using dozens of tree types in a given code base, so adding iterators to a tree is no big deal. In general there aren't enough types of iteration available to a given data structure that you need to describe how to iterate on it from the "outside". (Generally when you are doing that, it's too non-trivial to fit into this pattern anyhow; see the Visitor pattern in general.) This strikes me as maybe the sort of default tool you might slap in a library somewhere, but it should be a niche tool. If you're using it all the time you're probably doing something wrong. By default your data structures should be providing iteration packaged with them and it should generally be what you need. And your language should support aborting iteration, in whatever that looks like normally. I'm not sure I know a language that doesn't, it's a fairly basic element of iterator support when you get into implementation.
There are also many cases where a tree iterator will perform significantly better, including CPython. I don't have enough experience with PyPy to know if it could inline the Tree.left and Tree.right calls down to zero penalty at JIT time. Rust and C++ and the other static languages with sophisticated compilers might be able to get that down to fully inlined and zero-cost, but even if they can it's probably better not to push that on to the optimizer as the optimizers will eventually give up if this is composed with enough other stuff. Better to just have an efficient implementation in the first place.
(this is for iterating over nested JSON-like objects, which are just weird trees)
There are a lot of ways you could avoid the recursion, but that's a particularly nice way!
[1] https://doc.rust-lang.org/std/vec/struct.Vec.html#method.bin...
Yes, students should absolutely implement the classic algorithms to learn.
Yes, there are some occasions when you need to home grow one at $work.
BUT, in my opinion, most of the time, professional code should use a battle tested, vuln hardened library or builtin version. These things are VERY HARD to get exactly right. Jon Bently's Programming Pearls famously had a latent bug in its binary search for 20 years before someone caught it.
https://research.google/blog/extra-extra-read-all-about-it-n...
So yeah, it looks easy but don't do it. Stand on some giant's shoulders instead.
Anyone who copies and pastes it is welcome to both pieces when it breaks. Others have already alluded to possible improvements that could be made, and I already have my own analysis in a grandchild reply as to why I don't think this is a terribly pressing need or necessarily even a good idea.
The reason I provide code is that it gets past the "oh, you say it's just an iterator, but I still don't believe you, since you haven't spelled it out to the n'th degree". When code is provided, belief ceases to be an issue. It is clearly something an iterator can implement, in existing languages, with existing iterator support.
Unless you're going to claim it is somehow impossible to provide this functionality in a tested manner, you're completely changing the topic in an uninteresting direction, since it is always true that functionality generally needs testing and bits of code slammed into an HN conversation just to make a particular point probably shouldn't be copied wholesale into your production code.
> Well a range based for loop requires that your tree exist in memory AND that you have an iterator defined for your tree. With for_tree you could operate on an entirely imperative tree, without needing to define any iterators or generator functions. Here's an example where I'm checking every single string composed of "a", "b", and "c" of length 8 or less.
You could definitely find every string composed of "a", "b", and "c" of length 8 or less by defining a custom iterator but it would be a verbose and unpleasant way of writing it:Python has a number of ways to achieve this depending on exactly how you want to pass the arguments; multiple functions, optional arguments, etc. How nice the final call looks is more about your local language's closures look.
The main point here is that this will happily iterate on things that don't "exist".
(Since things are lazy in Haskell, functions that return lists effectively are iterators. There's probably something in the standard library somewhere for (opts <*> [x]) to avoid the wrapping x in an unnecessary list, but my Haskell is rusty.)And yes, Haskell is amazing at this sort of thing.
If the poster wants to particularize this to C++ because C++'s syntax can't support it in any reasonable manner, that's fine, but that's a C++ problem, not a "Programming languages..." problem. Which would be perfectly understandable and I'm not really complaining, more clarifying that most of the rest of the world can just rub together three or four existing constructs in a pretty reasonable manner to get this.
Ceterum censeo this would be a family of simple macros in LISP.
IMO the thing that would be really nice is if control flow like `for` was actually the same as using an iterator. This would really help in Rust too where handling errors inside iterator callbacks is a right pain.
I've seen a few languages try this but it seems to not be very popular. I think it can get a bit confusing how control flow keywords like `return` and `break` work if you turn `if` into syntactic sugar for a function call taking a closure etc.
In PHP you loop through an iterator with the foreach control structure.
In JavaScript you use for of.
In rust it’s for in.
What am I missing?
The same from another angle: there are a lot of trees in the indices of SQL databases (example [1]) but we don't zoom in to that level of detail very often when defining our tables.
[1] https://www.postgresql.org/docs/current/btree.html
To implement Brown's algorithm to optimize class-based language models I had to implement a complex forest (DAG, actually) in Python using lists of fixed length. That was not especially nice to work with.
Essentially you use `first` to contain a Queue, Stack, or Level for the different traversals, and define traversal or activities from there.
It's fairly ergonomic in practice, ergonomic enough for Leetcode.
Here's a BFS: https://leetcode.com/problems/course-schedule-iv/solutions/6...
[0] https://doc.rust-lang.org/std/iter/fn.successors.html
[1] https://docs.rs/itertools/latest/itertools/fn.unfold.html
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Also I’m slightly confused by this example.
}So, our “next node” operation is to concatenate to x. Won’t we either have to have a method for modifying x to go “up” a node, or we’ll have to keep a record of what x was upon entering each node? Like in this example we’ll end up with x=“aaaaaaaa” and then go up a node, over to a “b” node, and get x=“aaaaaaaab”, right?
I guess we can delete the a node’s copy of x after all of a node’s child nodes are visited, at least.
Perhaps it can be optimized to be a little better than the recursive version, depending on how much overhead your language uses for a stack frame that it won't need for this special case.
But tree traversal doesn't have this universal property. There are too many methods and purposes for traversing a tree, sufficient that IMHO no single primitive embodiment could materially improve a language. Also, modern compilers efficiently break down high-level traversal code so well that expressing the idea at a high level incurs no serious penalty compared to having a primitive for that purpose, or a series of them.
[0] https://www.hillelwayne.com/post/graph-types/ and https://news.ycombinator.com/item?id=39592444
One great reason not to use recursive functions for traversing trees is that you can allocate your own stack data structure rather than relying on the call stack itself. In most languages/runtimes, the call stack has a maximum depth which limits the depth of trees you can process, usually on the order of thousands of stack frames.
Managing your own stack usually produces weirder looking code (personally I find "naive" recursive approaches more readable) - but having it as a first-class language feature could solve that!
https://clojuredocs.org/clojure.zip/zipper
Complex data structures absorb lot of the complexity of the problem and reduce the complexity of the rest of the code.
If every ounce of performance matters, e.g. in a database, you want 10000 functions, 100 for each data structure.
I guess all you really need are dynamically allocated arrays. A cons cell is an array of two. A struct with N fields is an array of N. Everything else is built on that.
If this becomes a C++ feature, imagine how many data structures we would need to support?
Many other languages, specially the FP languages, allow to do that as a library. Even the languages that are only inspired by FP. Example, Ruby:
Using the Enumerable mixin includes many FP-based methods, such as map, filter and reduce by only defining each, which in this case is DFS.Then we can proceed to define a binary tree:
Iterate over all the elements: Iterate over the even elements: Stop iteration when finding a value: And so on. The same can be done in Python, Kotlin and many others.C++ already solved that problem. Iterator are designed so that an algorithm can be written once and used with multiple data structures.
I really don't see your point
1. BFS is not supported.
2. Traversal type (inorder, preorer, postorder, or even mixed order!) is also not handled.
3. The syntax doesn't make it apparent that stack overflow can occur, e.g. by doing DFS on a linked list.
Thank you... I'll see myself out... lol =3
For example the most basic operations of a pointer are to advance and dereference.
std::map is actually implemented as a tree. To iterator its members you can do
The only requirement for your custom data structure to work is to implement begin() and end() which return iterators - “pointer like” objects.Are generators not a thing in other languages?
The site cppreference has an example of walking trees in C++ using them.
https://en.cppreference.com/w/cpp/coroutine/generator
But I have a question: why is it that in your example, you write `await` before the generator function, but it's not in the example given on cppreference? Also, did you mean `co_await`?
Do NOT use the c++20 co-routine APIs (a half-implemented nightmare of an API, although what is there does miraculously work, contrary to expectations). Probably better to wait for c++23 generators, which are so far available as an experimental feature on GCC 14.0 (which makes the feature unusable in any of my projects).
All of which, I guess, answers my question about why nobody has brought up c++ generators yet. C# has nice generators.
Sorry I brought it up. :-(
Iterators for trees are not implemented with call stack recursion.
> I'm surprised nobody's brought up C++ generators yet
You cannot modify, insert, or use standard algorithms with a generator.
Not as ergonomic as a direct tree-iterator, but I can't see of an elegant way to introduce that in an imperative language while keeping the forking/recursion aspect clear
https://godbolt.org/z/fnGzszf3j
Here is how I one could write in C: https://godbolt.org/z/P3ErP4T4d or possibly with the setup code moved into the helper function for convenience: https://godbolt.org/z/soz7W5z1G