Learning and Loving Rust Combinators (2019-10-15)

Learning and Loving Rust Combinators

I've been working pretty regularly on redis-oxide, a pure rust clone of redis, and the following snippet surprised me:

HashOps::HLen(key) => match read_hashes!(state, &key) {
    Some(hash) => hash.len() as Count,
    None => 0,

By itself, this code isn't extraordinary. It just checks how many elements is in a given redis hash (dictionary), defaulting to zero. The fact it doesn't use combinators is what suprised me. Most of my code recently has taken the following form:

HashOps::HLen(key) => read_hashes!(state, &key)
    .map_or(0, |hash| hash.len() as Count)

So What?

Combinators are nice as they allow for concise, and often more readable, type transformations. Both examples have similar line length, but differ in visual complexity. The first example has the match keyword, a block, and pattern matches on option's variants. Visually this is more text to parse and understand, especially when you're tired after work. The second, "combinated", example is in my opinion easier to read. We're reading our state, transforming the hash type into a Count, and then discarding the None case by defaulting to 0.

We'll see that there's a few more advantages, such as eliminating branches and general purity.

What are Combinators?

Combinators are a realization of a pretty common pattern: "I can't deal with this type. I'll just return it." You've likely used this pattern many, many times. Do you recognize the following snippets?

In python:

def sketchy_legacy_code(n):
    if n is None:
        return None
    return n * 2

Or in javascript:

function sketchyLegacyCode(n) {
  if (n === undefined || n === null) {
    return n;
  return n * 2;

This pattern certainly occurs more frequently in weakly typed or dynamically typed languages. A (sometimes reasonable) solution to this problem is exceptions, but rust doesn't have them. And exceptions can be problematic, as you can forget to catch them or catching them makes the code harder to understand.

Combinators are then a generalization of this concept. If I can operate on this type, I'll do so. Otherwise, I'll pass it along. This is a very powerful pattern. You can focus on the happy path and errors will be propagated automatically if they occur.

Why use Combinators in Rust?

In the same way that monads saved haskell, combinators help save rust. Rust is notorious for it's error handling as you're forced to encode your errors directly in the type system. This usually takes the form of returning Option<T> and Result<T, E>, which your callees consume.

So rust provides a thousand tools to cut through these types. I'll focus on Option<T> this article as I'm working with a forgiving database. An Option<T> in rust is an enum:

enum Option<T> {

So if I receive an Option<T>, it's either got data for me (Some(T)) or nothing for me (None). This type is very common in redis-oxide and most rust projects. Sometimes you don't care if it's None, so you can use if let Some(value) = myoption {...}, or just let value = myoption.unwrap(). But sometimes you end with a pathological case.

A Pathological Case

The redis command ZSCORE zset_name member is such an example. It has the following (observed behaviour):

  1. If the sorted set does not exist, return Nil.
  2. If the sorted exists, and the member isn't found, return Nil.
  3. Otherwise, return the score of the member as Int.

Let's code this using match statements:

// Inputs: zset_key, member
match read_zsets!(state, &zset_key) {
  // The sorted set may not contain `member`, so another option!
  Some(zset) => match zset.score(&member) {
    // Notice that we have to explicitly give the ReturnValue type.
    // We can't wrap it as we need to return Nil!
    Some(score) => ReturnValue::IntRes(score),
    None => ReturnValue::Nil
  None => ReturnValue::Nil

Now this can nest even deeper if we have more options or results to deal with. And we're repeating ourselves with ReturnValue::Nil.

Thankfully, we can use the and_then combinator to un-nest one of our match statements. Let's ignore the None from read_zsets!, as it's not different than the None from zset.score.

match read_zsets!(state, &zset_key).and_then(|zset| zset.score(&member)) {
  Some(score) => ReturnValue::IntRes(score),
  None => ReturnValue::Nil

Ok, it's better. But now the line is long and awkwardly formatted. Using and_then transformed our type into Option<Score>, and we would like Option<ReturnValue::IntRes>. We can get there with a map:

read_zsets!(state, &zset_key)
    .and_then(|zset| zset.score(&member))

Now our only problem is the return type. We've reached Option<ReturnValue::IntRes>, so we can use the unwrap_or method to deal with the missing key case:

read_zsets!(state, &zset_key)
    .and_then(|zset| zset.score(&member))

We did it! We've concisely encoded ZSCORE in rust in a hard-to-fuck-up way. Any sweeping refactors won't forget to change a branch, as there's no branches. You've just transformed the types a few times to achieve the desired result.

A Detour into the Rust Language Source Code

The example above may seem clear to you, but sometimes it's easy to get caught up in a flow.

So what exactly does map do, and how is it different from and_then?

Thanks to modern software engineering practice, we can just check the source code.

Here's how rust implements map on an Option<T>. The signature below says: I take a function with one parameter, T, which returns a type U. I will then give you can an Option<U>.

pub fn map<U, F: FnOnce(T) -> U>(self, f: F) -> Option<U> {
    match self {
        Some(x) => Some(f(x)),
        None => None,

So this seems reasonable. It's similar to the python and javascript examples above. However, that Some(f(x)) can cause issues. What is my function returns an option, like zset.scores? Welp, this expression:

read_zsets!(state, &zset_key)
    .map(|zset| zset.scores(&member))

Has type Option<Option<Score>>. Not good. That's why and_then exists:

pub fn and_then<U, F: FnOnce(T) -> Option<U>>(self, f: F) -> Option<U> {
    match self {
        Some(x) => f(x),
        None => None,

So and_then will not wrap our result in Some, and instead relies on the passed function to return an Option. So that's why we used it in our previous example. zset.score returns an option, so let's just use its option instead!


Overall, combinators are useful for making concise type transformations. You can decompose your problem into a series of handy transformations, and work your way to the solution. This is very common in functional languages, like haskell's do notation or clojures threading macro (nil punning).

For sure, if this ends up on hackernews, someone will point out the issues with combinators. The worst of them is probably the "what type am I working with?" or borrowing issues.

That said, their use in redis-oxide is likely of great benefit, especially for future maintenance.