Fully generic recursion in Rust

Previously, we introduced a method for writing performant stack safe recursion in Rust for a single recursive data structure. This post uses the same ideas to implement a single recursion backend that can collapse or expand any recursive data structure.

This generic recursion backend is implemented in my new recursion crate. Docs are here. Source code, along with examples and benchmarks, can be found here.

A Recap

Last time, we implemented collapse_layers and expand_layers1 functions, specialized to ExprTopo.

​We’re going to start by looking at our ExprTopo::collapse_layers function from the last post. Note that it’s specialized for use with ExprLayer. We explored the impl in detail last time, so we’re going to elide that, and just look at the types:

pub struct ExprIdx(usize);

pub struct ExprTopo {
    // nonempty, in topological-sorted order. guaranteed via construction.
    elems: Vec<ExprLayer<ExprIdx>>,

impl ExprTopo {
    fn collapse_layers<F: FnMut(ExprLayer<A>) -> A>(self, mut collapse_layer: F) -> A {
        /* see previous post for full impl */

It’s generic in one way - it can take any function ExprLayer<A> -> A and use it to collapse an ExprTopo down to a single value. But it’s still tied, explicitly, to ExprTopo. It would be better if we only had to write this function once, instead of once per data structure. That way, we can focus on optimizing that function, and can closely analyze it for correctness (instead of having to write it multiple times, at the risk of introducing subtle errors in boilerplate code).

A more Generic collapse

Here’s what we want our generic collapse_layers function to look like:

/// Support for collapsing a data structure into a single value, one layer at a time
pub trait Collapse<A, Wrapped> {
    fn collapse_layers<F: FnMut(Wrapped) -> A>(self, collapse_layer: F) -> A;

This should be read as being parameterized over some type Layer, with Wrapped being Layer<A>2. A is just the type we’re collapsing the data structure down into.

While we’re at it, let’s put together a trait for expanding a recursive data structure from some seed:

/// Support for expanding a data structure from a seed value, one layer at a time
pub trait Expand<A, Wrapped> {
    fn expand_layers<F: Fn(A) -> Wrapped>(a: A, expand_layer: F) -> Self;

Now that we have these traits, we can represent the generic ability to collapse or expand arbitrary recursive data structures, we just need to figure out how to implement them.

But how?

In the last post, we saw how ExprLayer::map could be used to factor out the core logic of collapse_layers and expand_layers. We’re going to abstract over this, such that we can map over a single layer of any recursive data structure, instead of just ExprLayer<_>. To do this, we’re going to introduce a trait called MapLayer.

/// The ability to map over some a single layer of some structure
/// 'Layer<_>', eg 'ExprLayer<_>'.
pub trait MapLayer<B> { // where Self is Layer<A>
    type Unwrapped;    // which is A
    type To;           // which is Layer<B>
    /// fn map_layer(Self: Layer<A>, f: Fn(A) -> B) -> Layer<B>
    fn map_layer<F: FnMut(Self::Unwrapped) -> B>(self, f: F) -> Self::To;

You should read this as being implemented for some Layer<_> (eg ExprLayer<_>) with the (pseudocode) type signature fn map_layer(self: Layer<A>, f: Fn(A) -> B) -> Layer<B>.

And here it is 3

Here’s what it looks like as implemented for ExprLayer<_>

impl<A, B> MapLayer<B> for ExprLayer<A> {
    type To = ExprLayer<B>;
    type Unwrapped = A;

    fn map_layer<F: FnMut(Self::Unwrapped) -> B>(self, mut f: F) -> Self::To {
        match self {
            Expr::Add(a, b) => Expr::Add(f(a), f(b)),
            Expr::Sub(a, b) => Expr::Sub(f(a), f(b)),
            Expr::Mul(a, b) => Expr::Mul(f(a), f(b)),
            Expr::LiteralInt(x) => Expr::LiteralInt(x),

Some boilerplate, nothing too complex.

Implementing the Collapse and Expand traits

We’ll be implementing Collapse and Expand for this data structure:

/// Index into the vector of elements
struct Index(usize);

/// Recursive tree made up of layers of some type 'Layer<_>', eg `ExprLayer<_>`
pub struct RecursiveTree<Wrapped> {
    /// nonempty, in topological-sorted order
    elems: Vec<Wrapped>, // Layer<Index> (eg `ExprLayer<Index>`)

Index is a generic version of the ExprIndex used in the previous post - it’s an internal index used to track links between different layers of the RecursiveTree.

Here’s what ExprTopo would look like using RecursiveTree:

type ExprTopo = RecursiveTree<ExprLayer<Index>>


Here’s what the implementation of Collapse looks like. I’ve elided the internal machinery so we can focus on the types - the full source code is here, but since it’s fully generic you can just use the crate, there’s no need to ever implement it yourself.

impl<A, Wrapped, Underlying> Collapse<A, Wrapped>
    for RecursiveTree<Underlying>
            Underlying: MapLayer<A, To = Wrapped, Unwrapped = Index>
    fn collapse_layers<F: FnMut(Wrapped) -> A>(self, mut collapse_layer: F) -> A {
        /* elided */

This is very similar to the ExprTopo::collapse_layers function in the previous post, and all we need is a MapLayer!

Here’s what it looks like in use:

pub fn eval(expr: ExprTopo) -> i64 {
    self.collapse_layers(|expr| match expr {
        ExprLayer::Add { a, b } => a + b,
        ExprLayer::Sub { a, b } => a - b,
        ExprLayer::Mul { a, b } => a * b,
        ExprLayer::LiteralInt { literal } => literal,


Here’s what expanding this data structure from a seed value looks like. As before, I’ve elided the implementation. If you’re curious, the full source code is here.

impl<A, Underlying, Wrapped> Expand<A, Wrapped> for RecursiveTree<Underlying>
    Wrapped: MapLayer<Index, Unwrapped = A, To = Underlying>,
    fn expand_layers<F: Fn(A) -> Wrapped>(a: A, expand_layer: F) -> Self {
        /* elided */

Very similar to the ExprTopo::expand_layers function in the previous post, but over some generic structure. Just to verify, let’s write a function to expand out an ExprTopo from a boxed expression, just as we did in the last post. But this time, it’s generic:

pub fn from_boxed(ast: &ExprBoxed) -> ExprTopo {
    ExprTopo::expand(ast, |seed| match seed {
        ExprBoxed::Add { a, b } => ExprLayer::Add { a, b },
        ExprBoxed::Sub { a, b } => ExprLayer::Sub { a, b },
        ExprBoxed::Mul { a, b } => ExprLayer::Mul { a, b },
        ExprBoxed::LiteralInt { literal } => ExprLayer::LiteralInt { literal: *literal },


These pass all the same tests as the Expr-specialized collapse_layers/expand_layers functions, but we only have to write the machinery of recursion once! Not once per recursive data structure, just once! 4

Just as before, I want to emphasize that this is fully generic over any recursive data structure:

A minimal example

For the last section of this blog post, we’re going to use the machinery we’ve built up to implement another data structure: an N-tree. An N-tree is a tree where each node can have any number of child nodes, and where some value V is stored at each node of the tree. Nodes with no child nodes are leaf nodes.

pub struct NTreeLayer<Val, A> {
    val: Val,
    children: Vec<A>,

pub type RecursiveNTree<V> = RecursiveTree<NTreeLayer<V, Index>>;

impl<A, B, V> MapLayer<B> for NTreeLayer<V, A> {
    type To = NTreeLayer<V, B>;
    type Unwrapped = A;

    fn map_layer<F: FnMut(Self::Unwrapped) -> B>(self, f: F) -> Self::To {
        Self::To {
            val: self.val,
            children: self.children.into_iter().map(f).collect(),

This is pretty good, not much boilerplate!

Here’s some simple functions over our N-tree:

pub fn depth<V>(r: RecursiveNTree<V>) -> usize {
    r.collapse_layers(|layer| layer.children.iter().max().map_or(1, |n| n + 1))

pub fn max<V: Ord>(r: RecursiveNTree<V>) -> Option<V> {
    r.collapse_layers(|layer| layer.children.into_iter().filter_map(|x| x).max())

Cool, right?

Async IO

I’ve also used my crate to implement a small but fully functional filetree reader/file contents search tool example. It’s fully async, with all the bells and whistles one might expect. 5. You can find the source code here..

To be continued

My next post will show how to implement different recursion backends (yes, this is where we finally get to see stack machines in action), along with some cool stuff with fused expand_layers and collapse_layers operations such that we can construct a recursive data structure and consume it at the same time, without having to allocate a RecursiveTree.

Thank you

Thank you to Fiona, Rain, Eliza, among others, for reviewing drafts of this post.

  1. If you’re a recursion schemes nerd like me, you might notice that these correspond to catamorphism (a collapsing change) and anamorphism (an expanding change), but with less greek. They don’t sound as cool, but I think they’re a more readable representation of the same concept. ↩︎

  2. In a perfect world, we could parameterize this over the Layer type (such as ExprLayer), but in Rust all types need to be fully applied, so we need to use Wrapped instead, to represent the fully applied Layer<A> type. ↩︎

  3. If you’re a functional programming nerd like me, you might recognize this as ‘Functor’ ↩︎

  4. a bolt of lightning strikes behind me. I am momentarily shown silhouetted by the actinic blue light. It is very dramatic ↩︎

  5. ok, so it just uses tokio::fs (which just calls std lib blocking functions to work with the file system) instead of something hand crafted with manual file handle management, but there’s a good reason I didn’t implement that: I didn’t want to ↩︎

See also