The Power of Generics in Rust Library APIs
When designing Rust library crate APIs, generics can be a powerful tool to increase flexibility and usability. By being more lenient with input types, you can offer callers the opportunity to avoid allocations and find alternative representations of input data that suit their needs better.
The Dark Side of Generics
However, there are some downsides to consider. Generic functions provide less information to the type system, making it harder for the compiler to infer types and potentially leading to more type annotations. Additionally, generics can result in code bloat or dynamic dispatch runtime costs.
A Slice of Traits
One way to make your API more lenient is to take a slice (&[T]) instead of a &Vec<T>. This allows callers to use different data structures, such as VecDeque, arrays, or even iterators. You can also use traits like Deref, AsRef, and Borrow to further increase flexibility.
Into the Woods
Implicit conversions using Into<_> can also make your API feel more magical, but beware of potential performance costs. Taking an Into<Option<T>> instead of an Option<T> can simplify the API, but may have hidden costs.
Keeping Code Bloat in Check
Rust’s monomorphization of generic code can lead to code bloat, which can negatively impact performance. To avoid this, you can factor out generic traits and use unsized types to iterate over slices instead of arrays. Dynamic dispatch can also be a viable option, especially when measurement shows it to be beneficial.
The Consequences of Code Bloat
Code bloat can have far-reaching consequences, including nonlinear effects on cache usage and performance. It’s essential to consider the impact of code bloat on your users’ code and to measure performance in a real-world application rather than relying on microbenchmarks.
The Path Forward
When designing Rust library APIs, it’s crucial to weigh the benefits of generics against the potential downsides. By being mindful of code bloat and performance costs, you can create APIs that are both flexible and efficient. Remember to measure twice, code once, and consider the impact of your design on your users’ code.