Loops and arrays

As a result of this course being time-constrained, we do not have the luxury of deep-diving into Rust possibilities like a full Rust course would. Instead, we will be focusing on the minimal set of building blocks that you need in order to do numerical computing in Rust.

We’ve covered variables and basic debugging tools in the first chapter, and we’ve covered integer and floating-point arithmetic in the second chapter. Now it’s time for the last major language-level component of numerical computations: loops, arrays, and other iterable constructs.

Range-based loop

The basic syntax for looping over a range of integers is simple enough:

#![allow(unused)]
fn main() {
for i in 0..10 {
    println!("i = {i}");
}
}

Following an old tradition, ranges based on the .. syntax are left inclusive and right inclusive, i.e. the left element is included, but the right element is not included. The reasons why this is a good default have been explained at length elsewhere, so we will not bother with repeating them here.

However, Rust acknowledges that ranges that are inclusive on both sides also have their uses, and therefore they are available through a slightly more verbose syntax:

#![allow(unused)]
fn main() {
println!("Fortran and Julia fans, rejoice!");
for i in 1..=10 {
    println!("i = {i}");
}
}

The Rust range types are actually used for more than iteration. They accept non-integer bounds, and they provide a contains() method to check that a value is contained within a range. And all combinations of inclusive, exclusive, and infinite bounds are supported by the language, even though not all of them can be used for iteration:

• The .. infinite range contains all elements in some ordered set
• x.. ranges start at a certain value and contain all subsequent values in the set
• ..y and ..=y ranges start at the smallest value of the set and contain all values up to an exclusive or inclusive upper bound
• The Bound standard library type can be used to cover all other combinations of inclusive, exclusive, and infinite bounds, via (Bound, Bound) tuples

Iterators

Under the hood, the Rust for loop has no special support for ranges of integers. Instead, it operates over a pair of lower-level standard library primitives called Iterator and IntoIterator. These can be described as follows:

• A type that implements the Iterator trait provides a next() method, which produces a value and internally modifies the iterator object so that a different value will be produced when the next() method is called again. After a while, a special None value is produced, indicating that all available values have been produced, and the iterator should not be used again.
• A type that implements the IntoIterator trait “contains” one or more values, and provides an into_iter() method which can be used to create an Iterator that yields those inner values.

The for loop uses these mechanisms as follows:

#![allow(unused)]
fn main() {
fn do_something(i: i32) {}

// A for loop like this...
for i in 0..3 {
    do_something(i);
}

// ...is effectively translated into this during compilation:
let mut iterator = (0..3).into_iter();
while let Some(i) = iterator.next() {
    do_something(i);
}
}

Readers familiar with C++ will notice that this is somewhat similar to STL iterators and C++11 range-base for loops, but with a major difference: unlike Rust iterators, C++ iterators have no knowledge of the end of the underlying data stream. That information must be queried separately, carried around throughout the code, and if you fail to handle it correctly, undefined behavior will ensue.

This difference comes at a major usability cost, to the point where after much debate, 5 years after the release of the first stable Rust version, the C++20 standard revision has finally decided to soft-deprecate standard C++ iterators in favor of a Rust-like iterator abstraction, confusingly calling it a “range” since the “iterator” name was already taken.¹

Another advantage of the Rust iterator model is that because Rust iterator objects are self-sufficient, they can implement methods that transform an iterator object in various ways. The Rust Iterator trait heavily leverages this possibility, providing dozens of methods that are automatically implemented for every standard and user-defined iterator type, even though the default implementations can be overriden for performance.

Most of these methods consume the input iterator and produce a different iterator as an output. These methods are commonly called “adapters”. Here is an example of one of them in action:

#![allow(unused)]
fn main() {
// Turn an integer range into an iterator, then transform the iterator to only
// yield one element every 10 elements.
for i in (0..100).into_iter().step_by(10) {
    println!("i = {i}");
}
}

One major property of these iterator adapters is that they operate lazily: transformations are performed on the fly as new iterator elements are generated, without needing to collect transformed data in intermediary collections. Because compilers are bad at optimizing out memory allocations and data movement, this way of operating is a lot better than generating temporary collections from a performance point of view, to the point where code that uses iterator adapters usually compiles down to the same assembly as an optimal hand-written while loop.

For reasons that will be explained over the next parts of this course, usage of iterator adapters is very common in idiomatic Rust code, and generally preferred over equivalent imperative programming constructs unless the latter provide a significant improvement in code readability.

Arrays and Vecs

It is not just integer ranges that can be iterated over. Two other iterable Rust objects of major interest to numerical computing are arrays and Vecs.

They are very similar to std::array and std::vector in C++:

• The storage for array variables is fully allocated on the stack.² In contrast, the storage for a Vec’s data is allocated on the heap, using the Rust equivalent of malloc() and free().
• The size of an array must be known at compile time and cannot change during runtime. In contrast, it is possible to add and remove elements to a Vec, and the underlying backing store will be automatically resized through memory reallocations and copies to accomodate this.
• It is often a bad idea to create and manipulate large arrays because they can overflow the program’s stack (resulting in a crash) and are expensive to move around. In contrast, Vecs will easily scale as far as available RAM can take you, but they are more expensive to create and destroy, and accessing their contents may require an extra pointer indirection.
• Because of the compile-time size constraint, arrays are generally less ergonomic to manipulate than Vecs. Therefore Vec should be your first choice unless you have a good motivation for using arrays (typically heap allocation avoidance).

There are three basic ways to create a Rust array…

• Directly provide the value of each element: [1, 2, 3, 4, 5].
• State that all elements have the same value, and how many elements there are: [42; 6] is the same as [42, 42, 42, 42, 42, 42].
• Use the std::array::from_fn standard library function to initialize each element based on its position within the array.

…and Vecs supports the first two initialization method via the vec! macro, which uses the same syntax as array literals:

#![allow(unused)]
fn main() {
let v = vec![987; 12];
}

However, there is no equivalent of std::array::from_fn for Vec, as it is replaced by the superior ability to construct Vecs from either iterators or C++-style imperative code:

#![allow(unused)]
fn main() {
// The following three declarations are rigorously equivalent, and choosing
// between them is just a matter of personal preference.

// Here, we need to tell the compiler that we're building a Vec, but we can let
// it infer the inner data type.
let v1: Vec<_> = (123..456).into_iter().collect();
let v2 = (123..456).into_iter().collect::<Vec<_>>();

let mut v3 = Vec::with_capacity(456 - 123 + 1);
for i in 123..456 {
    v3.push(i);
}

assert_eq!(v1, v2);
assert_eq!(v1, v3);
}

In the code above, the Vec::with_capacity constructor plays the same role as the reserve() method of C++’s std::vector: it lets you tell the Vec implementation how many elements you expect to push() upfront, so that said implementation can allocate a buffer of the right length from the beginning and thus avoid later reallocations and memory movement on push().

And as hinted during the beginning of this section, both arrays and Vecs implement IntoIterator, so you can iterate over their elements:

#![allow(unused)]
fn main() {
for elem in [1, 3, 5, 7] {
    println!("{elem}");
}
}

Indexing

Following the design of most modern programming languages, Rust lets you access array elements by passing a zero-based integer index in square brackets:

#![allow(unused)]
fn main() {
let arr = [9, 8, 5, 4];
assert_eq!(arr[2], 5);
}

However, unlike in C/++, accessing arrays at an invalid index does not result in undefined behavior that gives the compiler license to arbitrarily trash your program. Instead, the thread will just deterministically panic, which by default will result in a well-controlled program crash.

Unfortunately, this memory safety does not come for free. The compiler has to insert bounds-checking code, which may or may not later be removed by its optimizer. When they are not optimized out, these bound checks tend to make array indexing a fair bit more expensive from a performance point of view in Rust than in C/++.

And this is actually one of the many reasons to prefer iteration over manual array and Vec indexing in Rust. Because iterators access array elements using a predictable and known-valid pattern, they can work without bound checks. Therefore, they can be used to achieve C/++-like performance, without relying on faillible compiler optimizations or unsafe code in your program.³ And another major benefit is obviously that you cannot crash your program by using iterators wrong.

But for those cases where you do need some manual indexing, you will likely enjoy the enumerate() iterator adapter, which gives each iterator element an integer index that starts at 0 and keeps growing. It is a very convenient tool for bridging the iterator world with the manual indexing world:

#![allow(unused)]
fn main() {
// Later in the course, you will learn a better way of doing this
let v1 = vec![1, 2, 3, 4];
let v2 = vec![5, 6, 7, 8];
for (idx, elem) in v1.into_iter().enumerate() {
    println!("v1[{idx}] is {elem}");
    println!("v2[{idx}] is {}", v2[idx]);
}
}

Slicing

Sometimes, you need to extract not just one array element, but a subset of array elements. For example, in the Gray-Scott computation that we will be working on later on in the course, you will need to work on sets of 3 consecutive elements from an input array.

The simplest tool that Rust provides you to deal with this situation is slices, which can be built using the following syntax:

#![allow(unused)]
fn main() {
let a = [1, 2, 3, 4, 5];
let s = &a[1..4];
assert_eq!(s, [2, 3, 4]);
}

Notice the leading &, which means that we take a reference to the original data (we’ll get back to what this means in a later chapter), and the use of integer ranges to represent the set of array indices that we want to extract.

If this reminds you of C++20’s std::span, this is no coincidence. Spans are another of many instances of C++20 trying to catch up with Rust features from 5 years ago.

Manual slice extraction comes with the same pitfalls as manual indexing (costly bound checks, crash on error…), so Rust obviously also provides iterators of slices that don’t have this problem. The most popular ones are…

• chunks() and chunk_exact(), which cut up your array/vec into a set of consecutive slices of a certain length and provide an iterator over these slices.
  • For example, chunks(2) would yield elements at indices 0..2, 2..4, 4..6, etc.
  • They differ in how they handle trailing elements of the array. chunks_exact() compiles down to more efficient code, but is a bit more cumbersome to use because you need to handle trailing elements using a separate code path.
• windows(), where the iterator yields overlapping slices, each shifted one array/vec element away from the previous one.
  • For example, windows(2) would yield elements at indices 0..2, 1..3, 2..4, etc.
  • This is exactly the iteration pattern that we need for discrete convolution, which the school’s flagship Gray-Scott reaction computation is an instance of.

All these methodes are not just restricted to arrays and Vecs, you can just as well apply them to slices, because they are actually methods of the slice type to begin with. It just happens that Rust, through some compiler magic,⁴ allows you to call slice type methods on arrays and Vecs, as if they were the equivalent all-encompassing &v[..] slice.

Therefore, whenever you are using arrays and Vecs, the documentation of the slice type is also worth keeping around. Which is why the official documentation helps you at this by copying it into the documentation of the array and Vec types.

Exercise

Now, go to your code editor, open the examples/03-looping.rs source file, and address the TODOs in it. The code should compile and runs successfully at the end.

To attempt to compile and run the file after making corrections, you may use the following command in the VSCode terminal:

cargo run --example 03-looping