« Home

Rust: First Impressions

I recently decided to give the Rust programming language a try. Although Rust had crossed my radar a few times before, I’d never gotten much further than Hello World!. The language has undergone a lot of change over the last few years, but things appear to finally be slowing down for its upcoming 1.0 release.

The Project

My latest encounter with Rust began when I set out to write a ray tracer to get some experience with graphics programming. I initially considered a few different languages.

As a GitHub search for “raytracer” shows, the typical language for the job is C++. And I think it makes sense. You have to recursively trace about a million rays of light through the scene, so you need something fast (or a book to read while you wait for your Ruby ray tracer to finish executing). It’s also a problem that maps well to the OOP paradigm. The “scene” will naturally have different sorts of shapes (e.g., planes, spheres, cubes), each with a mix of shared and unique behavior that can be modeled well with inheritance. Finally, bindings to a decent graphics library are a must, which C++ also accommodates.

It turns out that Rust also nicely meets these requirements. It’s fast, more or less supports OOP via its trait system, and has at least one nice graphics library. So I gave it a try. What follows are my impressions of the language as a Rust novice (so take my praises and criticisms with a grain of salt).

The Good

I had a pretty great experience with Rust, so there was a lot to like.


Ownership is probably the most unique of Rust’s features. It’s also what I struggled the most with when it came to getting my code to compile.

The idea is that since Rust code isn’t garbage collected, and the programmer isn’t managing memory, the compiler needs some way to keep track of the lifetime of your data so that it can allocate and deallocate memory for you. In theory, this is awesome. You get the performance benefits of managing your own memory with all the safety of a garbage collected language.

In order for that to work, the compiler enforces a set of rules for ownership and borrowing of pointers and other resources. Resources are said to be owned by their variables. They can be borrowed by another variable, but just like a bike you lend out, the owner can’t use it while it’s being borrowed.

It does get a bit complicated and I’m not yet experienced enough to describe it in more detail, but I’m really liking the ownership system so far. I’ll qualify that by saying, given the choice between manually managing my memory or letting Rust do it, I’d choose Rust. Comparing Rust to a GC-ed language isn’t quite fair, as Rust is presumably being used because GC isn’t an option.

While the “borrow checker” has been the biggest hindrance in getting my Rust code to compile, it (theoretically) protects you from a whole class of memory issues (like leaks and dangling pointers). Based on my experience so far, I do think fighting the borrow checker is vastly preferable to hunting down the cause of a segfault in a large C/C++ codebase.


Cargo, Rust’s package manager, has been a pleasure to work with. The best kind of package managers are the ones that just work, and so far that’s been for me with Cargo. The tool is reminiscent in many ways of Ruby’s Bundler, and it turned out that wasn’t a coincidence as both were created by the same people.

Cargo is similar to Bundler in that it provides a simple way to list out your build dependencies—each from either crates.io (the rubygems.org equivalent), a GitHub repo, or from the local filesystem. It then retrieves and builds your dependencies, saving the version numbers or git commit SHAs in the Cargo.lock file. With that file checked in to source control, it’s easy to get repeatable builds using exactly those same dependencies, so you don’t suffer from issues with others trying to build your project with slightly different versions of the dependencies. Pretty neat.


git = "https://github.com/PistonDevelopers/image"


name = "image"
version = "0.2.0-alpha.10"
source = "git+https://github.com/PistonDevelopers/image#5b589d98e53da920a28dbed8b3ea83452280cdd2"
dependencies = [
 "num 0.1.12 (git+https://github.com/rust-lang/num)",

Support for Testing

Rust has some really cool built-in support for unit testing. This is great because every roadblock to writing tests makes them that much less likely to get written. In Rust, tests can be tagged with a #[test] attribute and added directly to the source file:

Once you’ve set up your project with Cargo, tests are easy to run:

Safety vs. Flexibility

Every language seems to make its own trade-offs between safety (protecting the programmer from him or herself) and flexibility (which allows you to do useful things). The protections that prevent you from unsafe memory access or type errors always come at the cost of some flexibility.

With C, you’re free to do whatever you want to your bits. If GCC doesn’t like the types you’ve assigned, you can always cast your way out of it—future segmentation faults notwithstanding. Haskell is on the other end of the spectrum. Its rigid type system protects you from all sorts of silly mistakes, but its functional purity makes normally simple things like printing to stdout or getting a random number considerably more difficult.

Rust seems to aim for somewhere in the middle of the two extremes. I think one of the clear goals of Rust is to provide a safer choice for the sort of systems programming that C or C++ is typically used for. One way to achieve safety is to prevent the programmer from doing anything useful, but I don’t think that’s the case here.

Rust encourages safety by providing reasonable defaults, but there’s usually an escape hatch if you need to do something not-so-safe (which can happen every now and then in the real world). By default, variable bindings are immutable, which means any mutation must be made explicit.

Rust also forgoes null pointers and encourages an Option type (similar to Swift’s optional and Haskell’s Maybe monad) to represent a value that may be absent. In languages like Java, null pointers often mean null pointer exceptions. With an optional type, the compiler can enforce that you handle both scenarios (i.e., value presence and absence). In my project, one example of this was checking for an intersection when tracing a ray. An intersection only occurs if there’s an object in the ray’s traced path, so it may be absent:

The Bad

There were a few things I didn’t like about Rust. I’m sure most of these are just due to my inexperience with the language or Rust being a relatively new language.

Unstable APIs

Rust is still in alpha and much of the standard API is currently marked as unstable. This means that—for now at least—every time you upgrade to the latest nightly, there’s a pretty good chance that your code will no longer compile. I’ve gone through this a few times with my ray tracer and spent a few hours moving to new APIs each time (for example, serialize to rustc-serialize). The other issue this presents is that a lot of the 3rd-party tutorials and example code out there won’t compile with the latest compiler.

The good news is that this is supposed to change soon with the 1.0 release.

Steep Learning Curve

One of the trade-offs made in exchange for all the nice things about Rust is that it takes a while to get off the ground. For me at least, it’s not a language like Python or Ruby that you can start making useful things with on your first day. Using Rust effectively is predicated on having a good understanding of the language. As a beginner, I struggled with compiler error messages that seemed cryptic taken out of context (mostly due to borrowing or ownership problems), but once I’d read more of the official book, they did start to make more sense. Moreover, like Haskell, Rust has a powerful type system and gives you a lot of rope to hang yourself with. I got stuck a few times when trying to define and deserialize a polymorphic “shape” type.

Lifetime Syntax

I think Rust generally has pretty nice syntax. I like its Ruby-style closures (|x| x * x). While I like the ownership paradigm, I’m not sold on the syntax for defining lifetimes. The terse a, b, c identifiers combined with the borrowed and mutable symbols can start to feel like reading and writing hieroglyphics:

Sure, I imagine this will get easier to read with time, but I wouldn’t mind some Java-style verbosity here.

Wrapping Up

I was going to add a “The Ugly” section to complete the trifecta, but my experience with Rust has actually been a really pleasant one. I’m sure the API stability and documentation will only improve with time.

With that said, I don’t think Rust is a good general purpose programming language. I don’t plan to use Rust for web programming any time soon. When it comes to rapid development, I think the extra cognitive overhead in dealing with ownership and complexities like String vs. &str make it hard sell against something like Ruby. But for problems in Rust’s wheelhouse—like system tools or operating systems or media decoders—where you need speed and safety, it’s a really great tool to have.