Tag: rust

Jan 06 2025

Rosetta Stone – Rust

In an earlier blog post I explained the motivation for a series of “Rosetta Stone” posts which described the ecosystem for different programming languages. This post covers Rust, the associated GitHub repository with some minimal code is here. This blog post aims to provide some discussion around technology choices whilst the GitHub repository provides details of what commands to execute and a minimal example project.

I became interested in Rust because a number of new tools such as uv and ruff for the Python ecosystem are written in Rust. It’s fair to say there has been a buzz around the language in programming circles for some years.

About Rust

Rust started out as a personal project by Graydon Hoare, an employee of Mozilla, in 2006. It was adopted by Mozilla in 2009 and in 2012 the first public release was made. It was originally designed with a focus on memory management and memory safety. It stands with C and assembly as the only languages supported in the development of the Linux kernel. I read the The Rust Programming Language book recently, the distinguishing feature of Rust is the borrow checker and ownership model which is what gives it strong memory safety credentials.

Rust is named for the rust fungi, not the corrosion of iron but it seems few people realise this!

Rust currently ranks 13th on the TIOBE index but has been regularly voted the most admired language on the Stackoverflow rankings.

How is the language defined?

The home for the Rust language is here. Rust evolves through an RFC (request for comments) process, which can be found in the Rust RFC Book. Currently there is no formal specification for the language but there is an exercise to write one.

New versions of the language are released every 6 week (see here). Breaking changes can be introduced in editions (once every 3 years with the next edition, 2024, due in February 2025) but upgrading between editions is optional and there are tools to support version migrations. For more about the edition process see here.

There is a roadmap for the 2024 edition (see here) and presumably once that is released the next roadmap will be developed.

Rust Compilers

The Rust compiler is rustc, there are some alternatives but they are experiments rather than production systems. Typically rustc is invoked with the cargo package manager, see below. My first impression was that the compiler provided really good error messages.

Details of installation can be found here in the accompanying GitHub repository. Installing the whole Rust toolchain is ridiculously simple.

Package management

cargo is the Rust package manager, it is also typically used to compile code to produce a “crate” which may be a binary or library.

Rather neatly invoking cargo to produce a new package also creates a new Git repository with the appropriate layout:

cargo new hello_world --bin

This generates a cargo.toml file which defines the project and dependencies, and on compile a cargo.lock file is produced which specifies exactly the versions of all the dependences. This parallels the NPM system for JavaScript/TypeScript. There is also a --lib flag which generates a layout for a library package. In practice this is just a starting point, your code may include both binaries and libraries for which you will need to edit the cargo.toml file. However, this cargo new process reflects how I would start a project in Python.

The standard library is here, there are no built-in CSV or JSON libraries – regular readers will recall I use this as a measure of a language’s completeness since my favoured language, Python, has them! Others may have different opinions.

Third party Rust crates can be found on the crate registry.

Virtual environments

Rust does not require virtual environments since cargo fetches the appropriate packages on compile, it uses a local cache of packages but this is a true cache – if the version of a package is not in the cache then it is fetched.

Project layout for package publication

cargo new generates a minimal project layout. More generally the conventional project layout is shown below (see here) when code is compiled a target directory is created for the compiled code.

It is rather nice having a mandated project layout!

Testing

A testing framework is built-in and a skeleton test is included when a --lib project is created by cargo The tests look like this:

This is essentially a unit test and the intention in Rust is that the unit tests sit next to the functions which they test, in Python unit tests tend to be separated into tests directory. In a Rust project the tests directory holds integration tests. There is a third type of test, doctests which are embedded in the comments intended for documentation.

All three types of test can be run with cargo test.

The built-in test functionality does not include features such as mocks or parameterized tests but there are third party crates to provide this functionality.

Static analysis and formatting tools

Clippy is the built-in linter, used in addition to rustfmt, the formatter. The are invoked using cargo with cargo fmt and cargo clippy. As a compiled language the compiler provides static analysis too. I would not expect alternatives to clippy or rustfmt to gain much traction since these appear to be the “official” tools.

Documentation Generation

rustdoc is the standard documentation generator tool (see here), working from comments in code and invoked using cargo doc. It feels to me that there is scope for alternatives to rustdoc although perhaps I am mixing up the documentation generation engine with the standards for code comments for documentation which have arisen in Python.

Wrapping up

I was struck by how everything is pretty much built-in for Rust; compiling, packaging, testing, formatting, and linting. All of these tools can be driven from the package management tool, cargo. It is almost like the design team was trying to make the job of writing this post as easy as possible! In writing Rust code in associated with this post I found the built-in test framework missing features (like mocks and parameterization which I’m used to in Python), similarly the documentation system is quite simple so perhaps in time alternatives will start to predominate.

My “home” language of Python has acquired these features over a long period of time, utilizing third party libraries and tools that eventually became de facto standards.

It would be nice to make a comparison with Go which occupies a similar space in programming as a relatively recent arrival with what I believe is a similarly full tool suite.

I welcome comments, probably best on Mastodon where you can find me here.

Dec 12 2024

Book review: The Rust Programming Language by Steve Klabnik and Carol Nichols

My next review is a small departure, it is for The Rust Programming Language by Steve Klabnik and Carol Nichols but rather than buy the physical book I read this interactive version, which has quizzes and embedded, runnable code.

The Rust programming language is the target for my next Rosetta Stone blog post which identifies all the tooling for a language. For Rust these tools (the compiler, formatter, linter, package management and automated documentation) are pretty much all “built-in” so my job will be easy. The challenge in this case has been learning the language since I try to write a little code for the Rosetta Stone posts to demonstrate what I’ve learned.

Rust is a relatively new language, very highly regarded amongst developers and one of only two approved for developing Linux. Its focus is on “safety” and speed. It has been used to make new, highly performant tools for the Python ecosystem, like ruff and uv, which is how I came to know of it.

For a Python programmer Rust does not look alien in the way that Haskell and Lisp do; admittedly it uses curly braces for scoping, is strongly-typed and supports pointers and references which are not features of Python but are common in other languages.

To me it feels like C but with some object-oriented features; the authors talk explicitly about it having features of functional languages including use of the Option value which contains something or nothing, the compiler enforces the handling of nothing. I think I might start using this more explicitly in Python which allows type-hinting to indicate an Option-like value. The other explicitly referenced functional feature is the use of closures, in Python closures are functions defined within functions or anonymous / lambda functions whilst in Rust they seem to be closer to functions passed as arguments to other functions.

Rust makes what seems an odd distinction between functions and macros in its standard library. Macros are identified with an exclamation mark, for example println! As I understand this is because a macro is implemented using code generation at runtime which allows the developer to supply, for example, a variable number of arguments to println! which would not be possible for a function println. Python doesn’t make this distinction and is very permissive in the arguments that a function can take, allowing both position and keyword arguments of variable number.

I was struck by the way that different languages use the same word for different things. For example in Rust a struct is both a data container but can also carry methods in the way that “classes” in other languages do. In Python an enum is a closed list of values but in Rust those values can have user-defined associated values so that an enum for IP address protocols can contain V4 and V6 (as it would in Python) but in addition it can hold an actual IP address associated with each entry in the enumeration.

My understanding is that Rust is considered an object-oriented language by some but not all. In practical terms the only object-oriented feature missing is inheritance although this can be approximated by the use of generics and traits.

Since I have scarcely used pointers and references in 40 years of programming I found these concepts a bit challenging but I have made progress in my understanding through reading this book. Excited by this new found understanding I was then confused by Rust’s ownership model! Ownership and borrowing are the big, unique conceptual features of Rust. The aim of ownership is to rigorously ensure that code is safe – no writing past the end of arrays, or dereferencing null points. It also means that the performance hit of a garbage collector is not required, this task is pretty much entirely handled at compile time by the borrow checker. The strong ownership model makes concurrent programming easier too.

In trying to understand ownership and borrowing I found some useful tools, the best entry point was the BORIS tool by Christian Schott which lists other visualization tools including the Aquascope tool used in this book. I found the first such tool in RustViz which is used in teaching, it needs the user to put annotations into the code rather than working out the annotations itself. I also read this article by Chris Morgan.

As language books go, this one is pretty readable, and I found the built-in quizzes handy, if only to illustrate my ignorance particularly of the ownership and borrowing model. I think for my next technical book I might read Category Theory for Programmers by Bartosz Milewski. I have felt when applying type-hints to Python, and learning Rust and Haskell that I was missing out by not understanding at least the basics of category theory.

I enjoyed this book and the format worked pretty well for me, although I need to find a way of reading online content like this in more comfort. I’m keen to give Rust a go now!