I stumbled across a … bug(?) … a limitation(?) … an issue(!) with the Rust compiler. Fortunately, I was able to find out what was going on in the Rust programming language forum. I thought this issue was interesting enough and subtle enough to try to explain to my blog audience.

To be clear, this is an issue. This is a limitation in the Rust trait solver. The maintainers of the Rust compiler didn’t make Rust work this way for a principled reason. There’s no particularly strong theoretical reason Rust has to have this limitation.

Programming language design, like API design, and computer UX design (especially for technical tools like build systems and admin systems) is a difficult form of engineering, bridging computer science and cognitive science. Sometimes, it’s more art than science, because building systems that other technical workers will use comes with nearly infinite trade-offs and judgment calls.

The effort and quality matter too. Different programming languages have different strengths and weaknesses. Some programming languages are hard to use correctly, like C++. Some are easy to write, but hard to then read and maintain, like Perl. Some programming languages are great for one-off scripts where you’re the only user, like Python, and others enforce that you follow reliable engineering principles, like Rust.

Polymorphism is a powerful programming language feature. In polymorphism, we have generic functions that don’t know exactly what type of data they will be operating on. Often, the data types won’t even all have been designed yet when the generic function is written. The generic function provides the general outline of the work, but the details of some parts of the work, some specific operations, must be tailored to the specific types being used. The generic code needs some way of accessing these specific operations, and the users of the generic code need some way of specifying them.

In this next¹ post of my series explaining how Rust is better off without Object-Oriented Programming, I discuss the last and (in my opinion) the weirdest of OOP’s 3 traditional pillars.

It’s not encapsulation, a great idea which exists in some form in every modern programming language, just OOP does it oddly. It’s not polymorphism, also a great idea that OOP puts too many restrictions on, and that Rust borrows a better design for from Haskell (with syntax from C++).

Endianness is a long-standing headache for many a computer science student, and a thorn in the side of practitioners. I have already written some about it in a different context. Today, I’d like to talk more about how to deal with endianness in programming languages and APIs, especially how to deal with it in a principled, type-safe way.

Before we get to that, I want to make some preliminary clarifications about endianness, which will help inform our API design.

Update: Arvid Norlander has gone through the trouble of refactoring this code into a crate and publishing it. Thank you, Arvid!

Rust’s BTreeMap and corresponding BTreeSet are excellent, B-tree-based sorted map and key types. The map implements the ergonomic entry API, more flexible than other map APIs, made possible by the borrow checker. They are implemented with the more performant but more gnarly B-Tree data structure, rather than the more common AVL trees or red-black trees. All in all, they are an excellent piece of engineering, and an excellent standard library feature.

I am no stranger to programming language controversy. I have a whole category on my blog dedicated to explaining why Rust is better than C++, and I’ve taken the extra step of organizing it into an MDBook for everyone’s convenience. Most of them have been argued about on Reddit, and a few even on Hacker News. Every single one of them have been subject to critique, and in the process, I’ve been exposed to every corner, every trope and tone and approach of programming language debate religious war, from the polite and well-considered to the tiresome and repetitive all the way to the rude and non-sensical.

Here it is, the Rust vs C++ mdbook.

I’ve wanted for a while to re-organize some of the content on my blog into gardens. I got the idea from the blog post “The Garden and the Stream: A Technopastoral”. Basically, some content is ill-suited to date-based, time-organized systems like blogs. In fact, most of my content remains valid over a long period of time, rather than participating in conversation (with some exceptions), but rapidly becomes less discoverable after I’ve written it, as it is buried by newer posts.

I know I set the goal for myself of doing less polemics and more education, but here I return for another Rust vs C++ post. I did say I doubted I would be able to get fully away from polemics, however, and I genuinely think this post will help contextualize the general Rust vs. C++ debate and contribute to the conversation. Besides, most of the outlining and thinking for this post – which is the majority of the work of writing – was already done when I set that goal. It also serves as a bit of conceptual glue, structuring and contextualizing many of my existing posts. So please bear with me as I say more on the topic of Rust and C++.

Does the choice of programming language matter?

For years, many programmers would answer “no”. There was an “OOP consensus” across languages as different as C++ and Python. Choice of programming language was just a matter of which syntax to use to express the same OOP patterns, or what libraries were needed for the application. Language features like type checking or closures were seen as incidental, mere curiosities or distractions.

To the extent there was a spectrum of opinions, it was between OOP denizens and those that didn’t really think software architecture mattered at all — an feeble attempt of corporatization against true programmers and their free-spirited ways. The office park versus the squatters. That’s how we got the wave of so-called “scripting languages”.

This is a collection of little Rust thoughts that weren’t complicated enough for a full post. I saved them up until I had a few, and now I’m posting the collection. I plan on continuing to do this again for such little thoughts, thus the #1 in the title.

serde flattening

What if you want to read a JSON file, process some of the fields, and write it back out, without changing the other fields? Can you still use serde? Won’t it only keep fields that you know about in your data structure?

Intro programming classes will nag you to do all sorts of programming chores: make sure your code actually compiles, write unit tests, write comments, split the code into functions (though sometimes the commenting and factoring advice is bad). Today, however, I want to talk about one little chore, one particular little habit, that is just as essential as all of those things, but rarely covered in the CS100 lectures or grading rubrics: logging.

In this post, I continue my series on how Rust differs from the traditional object-oriented programming paradigm by discussing the second of the three traditional pillars of OOP: polymorphism.

Polymorphism is an especially big topic in object-oriented programming, perhaps the most important of its three pillars. Several books could be (and have been) written on what polymorphism is, how various programming languages have implemented it (both within the OOP world and outside of it – yes, polymorphism exists outside of OOP), how to use it effectively, and when not to use it. Books could be written on how to use the Rust version of it alone.

The NSA recently published a Cybersecurity Information Sheet about the importance of memory safety, where they recommended moving from memory-unsafe programming languages (like C and C++) to memory-safe ones (like Rust). Dr. Bjarne Stroustrup, the original creator of C++, has made some waves with his response.

To be honest, I was disappointed. As a current die-hard Rustacean and former die-hard C++ programmer, I have thought (and blogged) quite a bit about the topic of Rust vs C++. Unfortunately, I feel that in spite of the exhortation in his title to “think seriously about safety,” Dr. Stroustrup was not in fact thinking seriously himself. Instead of engaging conceptually with the article, he seems to have reflexively thrown together some talking points – some of them very stale – not realizing that they mostly are not even relevant to the NSA’s Cybersecurity Information Sheet, let alone a thoughtful rebuttal of it.

Rust doesn’t support default parameters in function signatures. And unlike in many languages, there’s no way to simulate them with function overloading. This is frustrating for many new Rustaceans coming from other programming languages, so I want to explain why this is actually a good thing, and how to use the Default trait and struct update syntax to achieve similar results.

Default parameters (and function overloading) are not part of object-oriented programming, but they are a common feature of a lot of the programming languages new Rustaceans are coming from. This post therefore fits in some ways with my on-going series on how Rust is not object-oriented, and so it is tagged with that series. It was also inspired by Reddit responses to my first OOP post.

Rust is not an object oriented programming language.

Rust may look like an object-oriented programming language: Types can be associated with “methods,” either “intrinsic” or through “traits.” Methods can often be invoked with C++ or Java-style OOP syntax: map.insert(key, value) or foo.clone(). Just like in an OOP language, this syntax involves a “receiver” argument placed before a . in the caller, called self in the callee.

But make no mistake: Though it may borrow some of the trappings, some of the terminology and syntax, Rust is not an object-oriented programming language. There are three pillars of object-oriented programming: encapsulation, polymorphism, and inheritance. Of these, Rust nixes inheritance entirely, so it can never be a “true” object-oriented programming language. But even for encapsulation and polymorphism, Rust implements them differently than OOP languages do – which we will go into in more detail later.

I don’t want you to think of me as a hater of C++. In spite of the fact that I’ve been writing a Rust vs C++ blog series in Rust’s favor (in which this post is the latest installment), I am very aware that Rust as it exists would never have been possible without C++. Like all new technology and science, Rust stands on the shoulders of giants, and many of those giants contributed to C++.

I’m a Rust programmer and in general a fan of strong typing over dynamic or duck typing. But a lot of advocacy for strong typing doesn’t actually give examples of the bugs it can prevent, or it gives overly simplistic examples that don’t really ring true to actual experience.

Today, I have a longer-form example of where static typing can help prevent bugs before they happen.

The Problem

Imagine you have a process that receives messages and must respond to them. In fact, imagine you have potentially many such processes, and want to write a framework to handle it.

I came across a programming problem recently where I wanted to use dynamic polymorphism with serde. This turned out to be much easier than I expected, and I thought it was an interesting enough case study to share, especially for people who are learning Rust.

A Brief Discussion of Polymorphism in Rust

As most of you will know, Rust’s system for polymorphism – traits – supports both static and dynamic polymorphism, with a bias towards static polymorphism.

Using async in Rust can lead to bad surprises. I recently came across a particularly gnarly one, and I thought it was interesting enough to share a little discussion. I think that we are too used to the burden of separating async from blocking being on the programmer, and Rust can and should do better, and so can operating system APIs, especially in subtle situations like the one I describe here.

UPDATE 2: I have made the title longer because people seem to be insisting on misunderstanding me, giving examples where the only reasonable thing to do is to escalate an Err into a panic. Indeed, such situations exist. I am not advocating for panic-free code. I am advocating that expect should be used for those functions, and if a function is particularly prone to being called like that (e.g. Mutex::lock or regex compilation), there should be a panicking version.

It took me a long time to admit to myself that the venerable Unix command line interface is stuck in the past and in need of a refresh, but it was a formative moment in my development as a programmer when I finally did. Coming from that perspective, I am very glad that there is a new wave of enthusiasm (coming especially from the Rust community) to build new tools that are fixing some of the problems with this very old and established user-interface.

Preface (by Jimmy Hartzell)

I am a huge fan of Jon Gjengset’s Rust for Rustaceans, an excellent book to bridge the gap between beginner Rust programming skills and becoming a fully-functional member of the Rust community. He’s famous for his YouTube channel as well; I’ve heard good things about it (watching video instruction isn’t really my thing personally). I have also greatly enjoyed his Twitter feed, and especially have enjoyed the thread surrounding this tweet:

I just made a pull request to reqwest. I thought this particular one was interesting enough to be worth blogging about, so I am.

We know that many C++ family languages have a feature known as function overloading, where two functions or methods can exist with the same name but different argument types. It looks something like this:

void use_connector(ConnectorA conn) {
    // IMPL
}

void use_connector(ConnectorB conn) {
    // IMPL
}

The compiler then chooses which method to call, at compile-time, based on the static type of the argument. In C++, this is part of compile-time polymorphism, an easy “if statement” in the template meta-language. In Java and many other languages, it’s merely a convenience, for when an ad-hoc group of types are possible for what an outsider sees as the same operation, but which from the perspective of the library requires different implementations.

There’s more than one way to do it.

• Perl motto

There should be one– and preferably only one –obvious way to do it.

• The Zen of Python (inconsistent formatting is part of the quote)

When it comes to statically-typed systems programming languages, C++ is the Perl, and Rust is the Python. In this post, the next installment of my Rust vs C++ series, I will attempt to explain why C++’s feature-set is problematic, and explain how Rust does better.

For my next entry in my series comparing Rust to C++, I will be discussing a specific data structure API: the Rust map API. Maps are often one of the more awkward parts of a collections library, and the Rust map API is top-notch, especially its entry API – I literally squealed when I first learned about entries.

And as we shall discuss, this isn’t just because Rust made better choices than other standard libraries when designing the maps API. Even more so, it’s because the Rust programming language provides features that better expresses the concepts involved in querying and mutating maps. Therefore, this serves as a window into some deep differences between C++ and Rust that show why Rust is better.

What is “bad” Rust?

When we say that a snippet of code is “bad” Rust, it’s ambiguous.

We might on the one hand mean that it is “invalid” Rust, like the following function (standing on its own in a module):

fn foo(bar: u32) -> u32 {
    bar + baz // but baz is never declared...
}

In this situation, a rule of the programming language has been violated. The compiler stops compiling and does not output a binary. In fact, it has to stop compiling, because this is not a Rust program. It might resemble one, but it in fact does not make any sense, because it is violating one of the extra-syntactic constraints that text has to have to be a Rust program.

For this next iteration in my series comparing Rust to C++, I want to talk about something I’ve been avoiding so far: memory safety. I’ve been avoiding this topic so far because I think it is the most discussed difference between C++ and Rust, and therefore I felt I’d have relatively little to add to the conversation. I’ve also been avoiding it because I wanted to draw attention to all the other little ways in which Rust is a better-designed programming language, to say that even if you concede to the C++ people that Rust isn’t “truly memory safe” or “memory safe enough,” Rust still wins.

Finally in 2019, Rust stabilized the async feature, which supports asynchronous operations in a way that doesn’t require multiple operating system threads. This feature was so anticipated and hyped and in demand that there was a website whose sole purpose was to announce its stabilization.

async was controversial from its inception; it’s still controversial today; and in this post I am throwing my own 2 cents into this controversy, in defense of the feature. I am only going to try to counter one particular line of criticism here, and I don’t anticipate I’ll cover all the nuance of it – this is a multifaceted issue, and I have a day job. I am also going to assume for this post that you have some understanding of how async works, but if you don’t, or just want a refresher I heartily recommend the Tokio tutorial.

I have been working on a serialization project recently that involves endianness (also known as byte order), and it caused me to explore parts of the Rust standard library that deals with endianness, and share my thoughts about how endianness should be represented in a programming language and its standard library, as I think this is also something that Rust does better than C++, and also makes for a good case study to talk about API design and polymorphism in Rust.

This post is part of my series comparing C++ to Rust, which I introduced with a discussion of C++ and Rust syntax. In this post, I discuss move semantics. This post is framed around the way moves are implemented in C++, and the fundamental problem with that implementation, With that context, I shall then explain how Rust implements the same feature. I know that move semantics in Rust are often confusing to new Rustaceans – though not as confusing as move semantics in C++ – and I think an exploration of how move semantics work in C++ can be helpful in understanding why Rust is designed the way it is, and why Rust is a better alternative to C++.

This past May, I started a new job working in Rust. I was somewhat skeptical of Rust for a while, but it turns out, it really is all it’s cracked up to be. As a long-time C++ programmer, and C++ instructor, I am convinced that Rust is better than C++ in all of C++’s application space, that for any new programming project where C++ would make sense as the programming language, Rust would make more sense.