From Go to Rust: The Two Types of Readable Code

23 minute read     Updated:

Adam Gordon Bell %
Adam Gordon Bell

Ever looked at some code and thought, “Wow, that’s an ugly mess!”? Or maybe you picked up a new programming language and felt right at home? It’s funny how our gut feelings about code often come down to what we’re used to.

There’s this joke I heard once:

f(x,y) -> Clear and straightforward - the mark of practical programming.
f x y -> Acceptable in shell scripting, but a bit odd.
(f x y) -> Impossibly puzzling. Approach with caution!

I bet Lisp programmers, who are used to seeing code that looks a bit different, came up with this. It’s a light-hearted way of saying what feels “right” in coding is pretty personal. But there’s some truth to the idea that readability and familiarity go hand in hand.

But is readability more than just familiarity? Last time, I mentioned that expert readability and beginner approachability can sometimes clash, and today, I wanted to explore this.

Many believe that readability is a universal standard, easily recognized, and equally applicable to all. But that’s not the case. Readability varies greatly and is influenced by syntax, library design, and programming concepts. More importantly, it affects beginners and experts differently. In other words, there are two types of readability—Newcomer Readability and Experienced Readability- and they can conflict.

Let’s define readability like this:
Category Description
Newcomers Readability How quickly you can get up to speed reading a new programming language. Related to how familiar you are with the syntax and concepts used, despite having never seen that language before.
Experienced Readability How quickly someone experienced in the language can understand a piece of code.

So, with these definitions, you can’t dismiss the (f x y) style as less readable just because you aren’t familiar with it. What matters is how readable it is for an experienced LISPer.

Some things help both beginner and expert alike, but other things trade one off against the other.

Let’s start with the first group.


Computers don’t need structure—like function calls or modules. They’re happy with an endless jumble of instructions. Remember the last time you tried deciphering someone else’s ‘spaghetti code’? How did that make you feel?

In 2004ish, at my first software developer job, I got introduced to a large dBASE program with no structure below the file level. Each file just started executing at the top, and well, that’s about it. 100s of files that looked like this.

    @ 0,0 CLEAR TO 0,79
    @ 0,0 SAY "Main Menu"
    @ 1,0 SAY "1. View Records"
    @ 2,0 SAY "2. Add Record"
    @ 3,0 SAY "3. Exit"
    @ 5,0 SAY "Select an option: "
    ACCEPT "> " TO nChoice

    IF nChoice = 1
        DO viewrec.prg
    ELSE IF nChoice = 2
        DO address.prg
    ELSE IF nChoice = 3
        @ 8,0 SAY "Invalid option, please try again."

Because of that experience, it’s pretty clear to me that being able to break things down into functions or procedures or whatever is super valuable. If some init function is 150 lines long and does three distinct things, grouping those three things into separate functions that init calls is a big win. I think this is generally agreed by most - although, like any good idea, it can be taken three steps too far.

There are other types of structure, though.

ASCII Art and You

If structure helps scanning and improves readability for all, then code comments and whitespace are another obvious way we can highlight structure. Here are two versions of some code:

x = 6 // picked by random dice roll
stop-word = "salad" // see pre-training data 
exponents = 10**6 // max solution space
x = 6                   // picked by random dice roll
stop-word = "salad"     // see pre-training data 
exponents = 10**6       // max solution space

Have you ever lined up your comments up neatly like this? For me, it makes a list of declarations more readable. They show that we are in some sort of setup section and that the lines are related.

Simple line breaks are another obvious but sometimes missed way to provide structure.

package main

import (

func main() {
    strs := []string{"c", "a", "b"}
    fmt.Println("Strings:", strs)

    ints := []int{7, 2, 4}
    fmt.Println("Ints:   ", ints)

The blank line, much like a paragraph break in writing, helps group related things and break up unrelated ones.

Jimmy Koppel makes a pretty good argument that structure should be taken further. We should use code comments and whitespace to structure large files, which aids readability by reducing mental effort.

You see this often in CSS:



/* Horizontal */
.ui.animated.button .visible.content,
.ui.animated.button .hidden.content {
  transition: right @animationDuration @animationEasing 0s;

/* Vertical */
.ui.vertical.animated.button .visible.content,
.ui.vertical.animated.button .hidden.content {
  transition: top @animationDuration @animationEasing, transform @animationDuration @animationEasing;


.ui.inverted.button {
  box-shadow: 0px 0px 0px @invertedBorderSize @white inset !important;
  background: transparent none;
  color: @white;
  text-shadow: none !important;

All of that reminds me of the regions that were common with the C# code, and I found that they aided readability in large files.

#region MyRegion

your code here


C# Regions

All of this, of course, can be overused and abused. ( Your 4000-line C# class file is probably easier to understand with regions, but maybe it shouldn’t be 4000 lines. ) But still, adding structure to code with whitespace and comments helps readability when things get hairy.

Less To Go Wrong

Another way to improve readability is to strictly just have less that can go wrong. A for each can’t have an off-by-one error, so if I replace a for (int i = 0; ... loop with a for each, I no longer worry about my indexes being off.

Even if somewhere that for each has an implementation that may use indexes, I can just assume it works correctly and move my thinking to a higher level. You can only hold so many things in working memory at a time, so cut what you can.

func maximumCount(nums []int) int {
    var pos, neg int = 0, 0
    for _, e := range nums {
        if e > 0 {
        } else if e < 0 {
+    return max(pos,neg)
-    if pos > neg {
-        return pos
-    } else {
-        return neg-    }
Having a max to call is handy. It communicates intent for the reader, improving readability in a small way.

Using functions like max feels straightforward, right? Everyone knows what it means to get the maximum of two numbers. But if we keep building up helpful standard libraries and language features, we quickly leave behind common knowledge and start adding to the number of things a beginner has to learn.

Here is reduce:

let numbers = [1, 2, 3, 4]

// Original 
var sum1 = 0
for number in numbers {
    sum1 += number

// Improved
let sum2 = numbers.reduce(0, +)

Things like reduce are where the readability of an expert can really grow. If you’re going to spend years working in a programming language, learning the conventions is a small cost to pay to improve day-to-day readability.

filter and map also benefit expert readability.

const numbers = [1, 2, 3, 4, 5, 6];

// Original 
let evensSquares1 = [];
for (let i = 0; i < numbers.length; i++) {
    if (numbers[i] % 2 === 0) {
        evensSquares1.push(numbers[i] * numbers[i]);

// Improved
const evensSquares2 = numbers.filter(number => number % 2 === 0)
                             .map(number => number * number);

flatMap is super helpful:

// Assume you have some X⇒M[Y] function to call 
def intToStringOption(x: Int): Option[String] = {
    if (x % 2 == 0) Some(x.toString) else None

// But you have a M[X] not a X
val x = Some(2)

// Original
// So you have some busy work to get your M[Y]
val r1 = if (x.isDefined) {
} else {

// Improved
// Unless it's a monad
val r2 = x.flatMap(intToStringOption)

While simplifications like using reduce or filter and map chains elevate the abstraction level and reduce error-prone boilerplate, they also encapsulate complexity that might not be immediately apparent to beginners. Each of these higher-order functions embodies a concept that, while straightforward for an experienced developer, adds to the list of things a newcomer must learn and understand before fully appreciating the readability improvements these concepts offer.

I guess I’m saying that higher-order functions are valuable for the expert but a barrier for the newcomers. And it’s not just higher-order functions. They are one class of a concept you can learn that can let you write code at a slightly higher level. You can overlook some of the details.

trait Positive {
    fn is_positive(&self) -> bool;

impl Positive for i32 {
    fn is_positive(&self) -> bool {
        *self > 0

fn main() {
    let num = 10_i32;
    println!("Is {} positive? {}", num, num.is_positive());

Other concepts do the same thing, like pattern matching, Sum types, Generics, and polymorphic traits.

If used to more concisely express the concept at hand ( and not for showing off), all these things can improve expert readability at the cost of beginner readability.

Readability Enhancers Definition Effects on Beginners Effects on Experts
Structural Enhancements Use of functions, whitespace, comments, and even comment headings to visually structure code. Makes code easier to navigate and understand; helps group related logic. Aids in quick navigation and understanding of code structure; reduces mental effort.
Simplification Techniques Utilizing constructs that reduce error likelihood and leveraging built-in functions for common tasks. Simplifies understanding of code by reducing complexity; minimizes common errors. It may harm readability depending on specific familiarity. Streamlines code, making it easier to read and maintain; promotes using concise, expressive constructs.
Advanced Language Features Employing higher-order functions, pattern matching, and other expressive language features. Increases complexity and learning curve due to more concepts to grasp. Enhances expressiveness and conciseness; allows for more complex concepts and clearer intent.

Which To Choose?

So, which column do you care the most about? What trade-off to choose?

Earlier I showed refactoring some go code to call max. But Go doesn’t have a way to get the maximum of some ints in the standard library. So I’d have to implement the max function myself, which takes away some of the benefits, and I assume Rob Pike would rather I just use the if x > y ... else ... logic that I started with. That’s because – in my view – go chooses beginner readability over expert readability. If you’ve not programmed in Go yet, there are very few concepts in it that you aren’t already familiar with. And that is a legit choice. Go choose beginner readability and simplicity. Clearly, Go has been wildly successful at gaining adoption in the ‘cloud native’ network services world, and I’m sure that choice is part of the reason.

Rust makes the opposite choice. And not because of the borrow checker vs Go’s GC, but because of the trait system, the sum types, the structural pattern matching, the const generics, the procedural macros, and so on. This is also a totally legit choice. Rust choose to be a more complex, for-knowledgeable-experts type of tool.

Myself, I think expert readability is more important than beginner friendliness. In the future, I hope we are using higher-level concepts. And I hope that will allow us to write better code.

It’s crucial, however, to acknowledge the balance that must be struck. Complex features can make the initial learning curve steeper for beginners. Higher-order functions, pattern matching, and other complex constructs are additional layers to learn, which can be intimidating for those new to programming or to a particular language.

But expert readability matters. Simple languages will always be needed, but we should also optimize for experienced users. We need languages where experts can understand code quickly because it precisely communicates its intent, and to do that, we need to have building blocks larger than ifs and for loops.

Adam Gordon Bell %
Spreading the word about Earthly. Host of CoRecursive podcast. Physical Embodiment of Cunningham's Law.
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