# Implementing flat_map in Rust

Not too long ago I happened to watch @jonhoo's Crust of Rust stream on iterators. He implemented the standard library function flatten and along the way explained bits and pieces of Rust's trait system. In the stream, he recommends implementing flat_map as a way to better understand traits. So, here we are!

First let's try to understand what flat_map is and why it's useful. Then I'll show you how I implemented it, explaining my thought process along the way. I'm assuming that you've coded in Rust before and are familiar with iterators and traits.

## What in the world is flat_map?

Most of us are familiar with the concept of mapping. For every element in a collection, apply a function that transforms the element, collect the transformed values, and return the transformed collection.

To put it more formally, given a collection $[a]$ and a function $f: a \rightarrow b$, $map([a]) = [b]$, where $a$ and $b$ are types.

Alright, now what's the deal with flat? Let's try to understand it through an example.

Let's say I have a list of elements $A = [[1,2], [3, 4, 5]]$. Flattening $A$ will give me the list $[1, 2, 3, 4, 5]$. To put it simply, flat removes nesting from collections. The level of nesting removed depends on the implementation of the function. In Javascript's Array.prototype.flat, you can specify how deep a nested structure should be flattened by passing in a depth parameter. In Rust, the standard library function flatten will remove only one level of nesting.

Now that we've understood what flat and map mean separately, understanding flat_map is a piece of cake.

To compute a flat_map, first map the collection, and then flatten it. It's that simple.

## Why have a flat_map function?

The concept of flat_map gets used very often when attempting to explain the mystical concept of monads. Monads themselves are a very interesting concept and are very heavily used by the functional programming community to handle "impurity". If you've ever fiddled with lists, streams, or optional values, you've interacted with monads (yay 🎉).

Monads are known for being notoriously difficult to explain so much so that there exists the curse of the monads:

Not that this curse is shying me away from attempting to explain it, but understanding monads is fortunately not necessary to implement flat_map. There are a ton of resources available to embark on the journey of understanding monads, so I'll save the task of venturing on that journey to the reader.

With these conceptuals out of the way, let's get to implementing flat_map in Rust.

## Getting started

Let's create a new lib called flat_map

cargo new --lib flat_map

This should generate the following file structure

flat_map/├── Cargo.toml└── src    └── lib.rs

Before we start coding the function, let's write some tests.

#[cfg(test)]mod tests {    use super::*;    #[test]    fn empty() {        assert_eq!(flat_map(std::iter::empty(), |x: Vec<()>| {x}).count(), 0);    }    #[test]    fn simple() {        assert_eq!(flat_map(vec!["a", "b"].into_iter(), |x| {x.chars()}).count(), 2);    }    #[test]    fn simple_wide() {        assert_eq!(flat_map(vec!["al", "bet"].into_iter(), |x| x.chars()).count(), 5);    }    #[test]    fn from_std_lib_test() {        let words = ["alpha", "beta", "gamma"];                // chars() returns an iterator        let merged: String = flat_map(words.iter(), |s| s.chars())                                  .collect();        assert_eq!(merged, "alphabetagamma");    }    #[test]    fn empty_middle() {        let words = ["alpha", "", "beta", "", "", "gamma"];        let merged: String = flat_map(words.iter(), |s| s.chars()).collect();        assert_eq!(merged, "alphabetagamma");    }}

A couple of things to note:

• The api for the flat_map implementation is implicit from the tests. It takes in an iterator and a closure, and returns something that can be turned into an iterator. The specific types of these parameters will be discussed later
• I'm using the #[cfg(test)] annotation. This ensures that tests don't get compiled along with non-test code when running cargo build.

The first three tests are pretty basic. Each one executes flat_map and checks if it returns the current number of elements.

The last two tests are the most interesting ones. The first one is straight from the standard library documentation, but adapted to our api. The expected behavior of running flat_map using the specified closure is that it should run chars() on each input element, resulting in a list of iterators over the characters in eachstr. Then it should flatten each iterator in the list resulting in an iterator yielding chars. Using collect() and type coercion, this iterator is collected into a String and asserted with the expected output. The second one augments it by add empty strings in between. The function should continue to iterate over the rest of the list of chars, even if it encounters an empty string.

## A first pass

To begin with, let's write down the function definition for flat_map.

pub fn flat_map<I, F, B>(iter: I, f: F) -> FlatMap<I, F, B>where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    FlatMap::new(iter, f)}

There's a lot going on in this function. Let's break it down a bit.

Here we're defining a function called flat_map. It takes in two parameters iter and f, and returns something that is of types FlatMap. We haven't defined the FlatMap type just yet, but we'll get to it soon. The function body is fairly simple. We simply invoke the new associated method on FlatMap and return it.

Cool, but what on earth are those generics? It'll make a lot of sense if we take a look at the trait bounds. Here we are saying that the type of the generic parameter I is bounded by the trait Iterator. This means that the type I must implement the Iterator trait. Ergo, the parameter iter must implemented Iterator. This trait bound makes sense: we must only be able to call flat_map on an iterator. It doesn't make sense to call flat_map on non-iterable values.

Let's take a look at the second generic parameter, F. This one is very interesting, at least syntax wise. F is bounded by the trait FnMut(I::Item) -> B. What does that mean? At a high level, you can think of F as the type of a closure that takes in I::Item and returns something of type B. Since I is an iterator, it has an associated type Item. Therefore, the parameter f is a closure that takes in an element of the same type that iter yields, and returns something of type B. This is the closure that will handle the map part of flat_map.

The observant reader will note that the syntax for specifying the FnMut trait bound is different. It almost looks like a function definition itself. As with most beautiful things in Rust, this is sugar syntax for the real unstable Fn trait. This syntax is needed to make using Higher-Rank Trait Bounds ergonomic in Rust. They don't really show up in too many contexts outside of the Fn family of traits. You can read more about the technical details in the nomicon.

Finally, let's tackle the generic parameter B. We are saying that it must be bounded by the trait bound IntoIterator. Hmmm, but why? Let's zoom out a little bit and review what flat_map does. flat_map first maps the collection, and then flattens it. As we've seen before, the closure f does the map part. Now, to flatten it, we need a collection of nested collections, i.e, each element of the mapped collection must itself another collection. In other words, each element of the mapped collection can be iterated over, which basically means that it can be turned into an iterator. Hence, the trait bound IntoIterator.

Phew, that function did have a lot going on. Let's move on to writing out the FlatMap struct. That's where all of the action happens.

pub struct Flatmap<I, F, B> where    I: Iterator,    f: FnMut(I::Item) -> B,    B: IntoInterator{    iter: I,    f: F,    inner: Option<B::IntoIter>}impl<I, F, B> for FlatMap<I, F, B> where    I: Iterator,    f: FnMut(I::Item) -> B,    B: IntoInterator{    fn new(iter: I, f: f) -> Self {        iter,        f,        inner: None,    }}

This one should be fairly straightforward. We define a struct FlatMap with the same trait bounds as the function flat_map. iter stores the thing we are iterating over, f stores the closure that gets invoked on every element. But what is inner doing?

Iterators in Rust are lazy. Funnily enough, in the context of iterators, lazyiness is actually a great thing. It means that the iterator invokes next() only when it needs to. Calling iter or map or any method that returns an iterator doesn't actually iterate over the collection. You have to write some code that will actually consume the iterator.

let a = vec![1, 2, 3];a.iter().map(|x| x + 1);

This code looks like it performs the map. However, it doesn't. The compiler will give you a warning saying

   Compiling playground v0.0.1 (/playground)warning: unused std::iter::Map that must be used --> src/main.rs:3:1  |3 | a.iter().map(|x| x + 1);  | ^^^^^^^^^^^^^^^^^^^^^^^^  |  = note: #[warn(unused_must_use)] on by default  = note: iterators are lazy and do nothing unless consumedwarning: 1 warning emitted    Finished dev [unoptimized + debuginfo] target(s) in 0.58s     Running target/debug/playground

As the message says, iterators are lazy. They need to be consumed. One way to consume it is by simply calling collect on the iterator.

let a = vec![1, 2, 3];let b: Vec<usize> = a.iter().map(|x| x + 1).collect();

The type of the collection to be returned was inferred from the type of b.

To implement Iterator for a struct, at a minimum, we need to implement the next method specified by the trait. Any consumer of an iterator will have to invoke next to actually advance through it.

Remember I said that flat_map first maps the collection, and then flattens it. This gives the illusion that we must first iterate over the entire collection, map each element, and then flatten the resulting collection. A very naive implementation of this idea would mean that the first call to next will iterate over the entire collection, but subsequent calls would just spit out the processed values. That's definitely not lazy in nature, and it's not efficient. We can do better!

Let's try to figure out what should happen on the first call to next() for the FlatMap iterator. We first need to map, and then flatten. Invoking f on the first element of iter will do the mapping. This will return an iterator. Invoking next on this iterator will begin the process of flattening it. It will return the first element of the flat_maped collection. Lazy? check. Will doing this for every call to next work? Let's find out!

impl<I, F, B> Iterator for FlatMap<I, F, B> where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    type Item = B::Item;     fn next(&mut self) -> Option<Self::Item> {        let mut iterator = Some((self.f)(self.iter.next()?).into_iter());        iterator.as_mut()?.next()    }}

One iteresting thing here is the assignment for Item. B implements IntoIterator. The value of the associated type B::Item is the type that an iterator over B will return. That's exactly the type that we want flat_map to return.

Let's see if it compiles.

> cargo build   Compiling flat_map v0.1.0 (/Users/eltonpinto/dev/learn/rust_iterators/flat_map)warning: field is never read: inner  --> src/lib.rs:25:5   |25 |     inner: Option<B::IntoIter>,   |     ^^^^^^^^^^^^^^^^^^^^^^^^^^   |   = note: #[warn(dead_code)] on by default    Finished dev [unoptimized + debuginfo] target(s) in 0.09s

We can safely ignore the warning. Woo hoo! It compiles. That means it should work right? Let's run our tests.

> cargo test  Compiling flat_map v0.1.0 (/Users/eltonpinto/dev/learn/rust_iterators/flat_map)    Finished test [unoptimized + debuginfo] target(s) in 0.55s     Running target/debug/deps/flat_map-1bcf67ed8ede3985  running 4 teststest tests::empty ... oktest tests::simple ... oktest tests::from_std_lib_test ... FAILEDtest tests::simple_wide ... FAILEDfailures:---- tests::from_std_lib_test stdout ----thread 'tests::from_std_lib_test' panicked at 'assertion failed: (left == right)  left: "abg", right: "alphabetagamma"', src/lib.rs:104:9note: run with RUST_BACKTRACE=1 environment variable to display a backtrace---- tests::simple_wide stdout ----thread 'tests::simple_wide' panicked at 'assertion failed: (left == right)  left: 2, right: 5', src/lib.rs:93:9failures:    tests::from_std_lib_test    tests::simple_widetest result: FAILED. 2 passed; 2 failed; 0 ignored; 0 measured; 0 filtered outerror: test failed, to rerun pass '--lib'

Hmm, that didn't work.

Taking a closer look at the results, it seems like our implementation is collecting only the first element of each nested collection. The reason is that every call to next for FlatMap invokes map on the next element of iter. We invoke f, get the new iterator, and then call next on this iterator only once. This new iterator gets dropped as it goes out of scope. We are basically ignoring the rest of the values in the iterator, and return only the first one.

## Fixing the error

To solve this problem, we need some way of persisting that inner iterator returned by f so that subsequent calls to next on FlatMap will first consume the inner iterator, and only then advance to the next element in iter. Hmmm, how do we do that? Well, we'll use the inner field of FlatMap!

Whenever we call next on iter, we will persist the iterator we get in inner. Then, on subsequent calls to next on FlatMap, we will first consume inner. Once inner is consumed, we will call next on iter and repeat the process.

There is one issue that we still need to fix. What should we do if the inner iterator itself has nothing to iterate over, i.e., it returns None on the first call to next()? The expected behavior is to continue to iterate over the outer list until you find an inner iterator that returns something. To handle this case, we can simple wrap our logic in a loop and return as soon as the inner iterator returns something, or we've completely iterated over the outer iterator.

Let's code this out!

impl<I, F, B> Iterator for FlatMap<I, F, B> where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    type Item = B::Item;     fn next(&mut self) -> Option<Self::Item> {        loop {            if let Some(ref mut inner) = self.inner {                if let Some(val) = inner.next() {                    return Some(val);                }            self.inner = Some((self.f)(self.iter.next()?).into_iter());        }    }}

Awesome, now let's run the tests...

> cargo testrunning 5 teststest tests::empty ... oktest tests::empty_middle ... oktest tests::simple ... oktest tests::from_std_lib_test ... oktest tests::simple_wide ... oktest result: ok. 5 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out   Doc-tests flatmaprunning 0 teststest result: ok. 0 passed; 0 failed; 0 ignored; 0 measured; 0 filtered out

Yes!!! All tests passed. We've successfully implemented flat_map!

## Learnings

While implementing flat_map, I was surprisingly able to better understand Higher-Ranked Trait Bounds. When I read about it in the nomicon before, it didn't make any sense and I merely brushed over it. It was when I tried writing out the trait bound for FnMut myself did i realize it's significance. I also developed a more stronger love for the ? operator. Boy does it make code look a lot more cleaner.

## Final code

Here's the final code:

fn flat_map<I, F, B>(iter: I, f: F) -> FlatMap<I, F, B>where    I: Iterator,    F: FnMut(I::Item) -> B,     B: IntoIterator{    FlatMap::new(iter, f)}struct FlatMap<I, F, B> where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    iter: I,    f: F,    inner: Option<B::IntoIter>}impl<I, F, B> FlatMap<I, F, B> where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    pub fn new(iter: I, f: F) -> Self {        Self { iter, f, inner: None}    }}impl<I, F, B> Iterator for FlatMap<I, F, B> where    I: Iterator,    F: FnMut(I::Item) -> B,    B: IntoIterator{    type Item = B::Item;     fn next(&mut self) -> Option<Self::Item> {        if let Some(ref mut inner) = self.inner {            if let Some(val) = inner.next() {                return Some(val);            }        }        self.inner = Some((self.f)(self.iter.next()?).into_iter());        self.inner.as_mut()?.next()    }}#[cfg(test)]mod tests {    use super::*;    #[test]    fn empty() {        assert_eq!(flat_map(std::iter::empty(), |x: Vec<()>| {x}).count(), 0);    }    #[test]    fn simple() {        assert_eq!(flat_map(vec!["a", "b"].into_iter(), |x| {x.chars()}).count(), 2);    }    #[test]    fn simple_wide() {        assert_eq!(flat_map(vec!["al", "bet"].into_iter(), |x| {x.chars()}).count(), 5);    }    #[test]    fn from_std_lib_test() {        let words = ["alpha", "beta", "gamma"];                // chars() returns an iterator        let merged: String = flat_map(words.iter(), |s| s.chars())                                  .collect();        assert_eq!(merged, "alphabetagamma");    }}

P.S: My initial implementation did not handle the empty_middle test case. Huge thanks to Domantas, Rodrigo, and Paul for spotting the bug!