Unit 1.1 - Introduction

This is the open-source Rust training material we use for our professional multi-day (embedded) Rust training programs.

It comprises several modules based on the material of the teach-rs project (now part of Trifecta Tech Foundation) that we previously co-developed and that we contribute back to when improvements are made.

Published under the CC-BY-SA 4.0 license, you are free to use and share this material as long as you give us appropriate credit and share any modifications you make under that same license.

If you spot any mistakes or have a suggestion, please open an issue or pull request on the GitHub repository.

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For testimonials, an introduction of our expert trainers, and more information about the programs we offer, please refer to our professional training page.

Unit 1.2 - Introduction

Exercise 1.2.1: Setup Your Installation

In this file you'll find instructions on how to install the tools we'll use during the course.

All of these tools are available for Linux, macOS and Windows users. We'll need the tools to write and compile our Rust code, and allow for remote mentoring. Important: these instructions are to be followed at home, before the start of the first tutorial. If you have any problems with installation, contact the lecturers! We won't be addressing installation problems during the first tutorial.

Rust and Cargo

First we'll need rustc, the standard Rust compiler. rustc is generally not invoked directly, but through cargo, the Rust package manager. rustup takes care of installing rustc and cargo.

This part is easy: go to https://rustup.rs and follow the instructions. Please make sure you're installing the latest default toolchain. Once done, run

rustc -V && cargo -V

The output should be something like this:

rustc 1.79.0 (129f3b996 2024-06-10)
cargo 1.79.0 (ffa9cf99a 2024-06-03)

Using Rustup, you can install Rust toolchains and components. More info:

Rustfmt and Clippy

To avoid discussions, Rust provides its own formatting tool, Rustfmt. We'll also be using Clippy, a collection of lints to analyze your code, that catches common mistakes for you. You'll find that Rusts Clippy can be a very helpful companion. Both Rustfmt and Clippy are installed by Rustup by default.

To run Rustfmt on your project, execute:

cargo fmt

To run clippy:

cargo clippy

More info:

Rustfmt: https://github.com/rust-lang/rustfmt
Clippy: https://github.com/rust-lang/rust-clippy

Visual Studio Code

During the course, we will use Visual Studio Code (vscode) to write code in. Of course, you're free to use your favorite editor, but if you encounter problems, you can't rely on support from us. Also, we'll use VSCode to allow for remote collaboration and mentoring during remote training sessions.

You can find the installation instructions here: https://code.visualstudio.com/.

We will install some plugins as well. The first one is Rust-Analyzer. Installation instructions can be found here https://marketplace.visualstudio.com/items?itemName=rust-lang.rust-analyzer. Rust-Analyzer provides a lot of help during development and in indispensable when getting started with Rust.

Another plugin we'll use is CodeLLDB. This plugin enables debugging Rust code from within vscode. You can find instructions here: https://marketplace.visualstudio.com/items?itemName=vadimcn.vscode-lldb.

If you're following the training remotely, install the Live Share plugin as well. We will use the plugin to share code and provide help during remote tutorial sessions. Installation instructions can be found here: https://marketplace.visualstudio.com/items?itemName=MS-vsliveshare.vsliveshare

More info:

Tip

This repo contains quite a lot of rust projects and due to the complicated setup of the repo Rust Analyzer can't autodiscover them well.

To fix this we've specified the projects manually in the .vscode/settings.json file. To reduce the burden on your computer, you can comment out any of the projects that we're not using in our training.

Git

During the trainings, you'll need the Git version control tool. If you haven't installed Git already, you can find instructions here: https://git-scm.com/book/en/v2/Getting-Started-Installing-Git. If you're new to Git, you'll also appreciate GitHubs intro to Git https://docs.github.com/en/get-started/using-git/about-git and the Git intro with vscode, which you can find here: https://www.youtube.com/watch?v=i_23KUAEtUM.

More info: https://www.youtube.com/playlist?list=PLg7s6cbtAD15G8lNyoaYDuKZSKyJrgwB-

Course code

Now that everything is installed, you can clone the source code repository using Git. The repository can be found here: https://github.com/tweedegolf/rust-training.

Instructions on cloning the repository can be found here: https://docs.github.com/en/get-started/getting-started-with-git/about-remote-repositories#cloning-with-https-urls

Trying it out

Now that you've got the code on your machine, navigate to it using your favorite terminal and run:

cd exercises/1-course-introduction/1-introduction/1-setup-your-installation
cargo run

This command may take a while to run the first time, as Cargo will first fetch the crate index from the registry. It will compile and run the intro package, which you can find in exercises/1-course-introduction/1-introduction/1-setup-your-installation. If everything goes well, you should see some output:

   Compiling intro v0.1.0 ([/path/to/rust-workshop]/exercises/1-course-introduction/1-introduction/1-setup-your-installation)
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.15s
     Running `target/debug/intro`
🦀 Hello, world! 🦀
You've successfully compiled and run your first Rust project!
X: 2; Y: 2

If Rust-Analyzer is set up correctly, you can also click the '▶️ Run'-button that is shown in exercises/1-course-introduction/1-introduction/1-setup-your-installation/src/main.rs. With CodeLLDB installed correctly, you can also start a debug session by clicking 'Debug', right next to the '▶️ Run'-button. Play a little with setting breakpoints by clicking on a line number, making a red circle appear and stepping over/into/out of functions using the controls. You can view variable values by hovering over them while execution is paused, or by expanding the 'Local' view under 'Variables' in the left panel during a debug session.

Instructions for FFI module

This part is relevant only if you're partaking in one of the modules on Rust FFI.

For doing FFI we will need to compile some C code and for that we need a C compiler installed. We've chosen to use clang in our excercises.

The prerequisite is that calling clang in your terminal should work. If it doesn't, follow the instructions for your platform below.

Linux

For the bookworms using a Debian-like:

sudo apt update
sudo apt install clang

If you're on Arch, btw:

sudo pacman -S clang

For those tipping their Fedora's:

sudo dnf install clang

Windows

Always make sure to select the option to add the install to path.

Using winget:

winget install -i -e --id LLVM.LLVM

For the sweethearts using chocolatey:

choco install llvm

For the handsome people preferring manual installation:

Go to the releases page: https://github.com/llvm/llvm-project/releases
Go to a recent release
Search for LLVM-[VERSION]-win64.exe and download it
Run the exe

MacOS

Using brew:

brew install llvm

Then also add to path, e.g.:

echo 'export PATH="$(brew --prefix llvm)/bin:$PATH"' >> ~/.zshrc
source ~/.zshrc

Instructions for embedded

This part is relevant only if you're partaking in one of the modules on embedded Rust.

Hardware

We will use the BBC micro:bit V2 and either you've already got it or we will bring it with us.

You'll also need a Micro-USB cable, but we're sure you've got one to spare.

Please check that everything is complete. If not, please contact us.

Software

Then, we'll install some tools needed to flash the mcu and inspect the code.

Install the thumbv7em-none-eabihf toolchain with the following command:

rustup target add thumbv7em-none-eabihf

We'll also install a couple of tools that let us inspect our binaries:

rustup component add llvm-tools
cargo install cargo-binutils

Now, let's install probe-rs. Follow the installation instructions. Probe-rs talks with the debug interface on the micro:bit, to flash your application, log messages, or even set breakpoints and read out device memory.

If you're on linux, you'll need to update your udev rules. On ubuntu or fedora, run the following inside the workshop folder you just cloned;

sudo cp 99-microbit-v2.rules /etc/udev/rules.d
sudo udevadm control --reload-rules
sudo udevadm trigger

It's possible that probe-rs detects two debugging interfaces. This is known to happen on Windows. In that case, go to the .cargo/config.toml and change the runner to the one that specifies the exact probe it needs to use. Make sure the values are the same as what probe-rs reports is one of the interfaces. Unsure? You can run probe-rs list to get a list of all connected probes.

Trying it out

Before we begin, we need to test our hardware. We'll be testing the nRF52833 microcontroller and the LSM303AGR motion sensor, that are present on the micro:bit V2. Make sure you have checked out the latest version of the workshop source.

Running the test

To test the hardware, please connect the micro:bit V2 to your pc, switch it on, and run

cd ./exercises/1-course-introduction/1-introduction/2-embedded
cargo run --release

If everything works correctly, you should now see the accelerometer samples being printed on the display. If not, don't worry and contact us.

Docs

Datasheets, manuals, and schematics of the parts we are using in the embedded workshops.

BBC micro:bit V2

nRF52833

nRF52833 product specification

LSM303AGR

Datsheet

Unit 2.1 - Basic Syntax

Slides

Exercise 2.1.1: Basic Syntax

Open exercises/2-foundations-of-rust/1-basic-syntax/1-basic-syntax in your editor. This folder contains a number of exercises with which you can practise basic Rust syntax.

While inside the exercises/2-foundations-of-rust/1-basic-syntax/1-basic-syntax folder, to get started, run:

cargo run --bin 01

This will try to compile exercise 1. Try and get the example to run, and continue on with the next exercise by replacing the number of the exercise in the cargo run command.

Some exercises contain unit tests. To run the test in src/bin/01.rs, run

cargo test --bin 01

Make sure all tests pass!

Unit 2.2 - Ownership and References

Slides

Exercise 2.2.1: Move Semantics

This exercise is adapted from the move semantics exercise from Rustlings

While inside the exercises/2-foundations-of-rust/2-ownership-and-references/1-move-semantics folder, to get started, run:

cargo run --bin 01

This will try to compile exercise 1. Try and get the example to run, and continue on with the next exercise by replacing the number of the exercise in the cargo run command.

Some exercises contain unit tests. To run the test in src/bin/01.rs, run

cargo test --bin 01

Make sure all tests pass!

01.rs should compile as is, but you'll have to make sure the others compile as well. For some exercises, instructions are included as doc comments at the top of the file. Make sure to adhere to them.

Exercise 2.2.2: Borrowing

Fix the two examples in the exercises/2-foundations-of-rust/2-ownership-and-references/2-borrowing crate! Don't forget you can run individual binaries by using cargo run --bin 01 in that directory! Make sure to follow the instructions that are in the comments!

Unit 2.3 - Advanced Syntax

Slides

Exercise 2.3.1: Error propagation

Follow the instructions in the comments of exercises/2-foundations-of-rust/3-advanced-syntax/1-error-propagation/src/main.rs!

Exercise 2.3.2: Error handling

Follow the instructions in the comments of exercises/2-foundations-of-rust/3-advanced-syntax/2-error-handling/src/main.rs!

Exercise 2.3.3: Slices

Follow the instructions in the comments of exercises/2-foundations-of-rust/3-advanced-syntax/3-slices/src/main.rs! Don't take too much time on the extra assignment, instead come back later once you've done the rest of the exercises.

Exercise 2.3.4: Ring Buffer

This is a bonus exercise! Follow the instructions in the comments of exercises/2-foundations-of-rust/3-advanced-syntax/4-ring-buffer/src/main.rs!

Exercise 2.3.5: Boxed Data

Follow the instructions in the comments of exercises/2-foundations-of-rust/3-advanced-syntax/5-boxed-data/src/main.rs!

Unit 2.4 - Traits and Generics

Slides

Exercise 2.4.1: Local Storage Vec

In this exercise, we'll create a type called LocalStorageVec, which is generic list of items that resides either on the stack or the heap, depending on its size. If its size is small enough for items to be put on the stack, the LocalStorageVec buffer is backed by an array. LocalStorageVec is not only generic over the type (T) of items in the list, but also by the size (N) of this stack-located array using a relatively new feature called "const generics". Once the LocalStorageVec contains more items than fit in the array, a heap based Vec is allocated as space for the items to reside in.

Within this exercise, the objectives are annotated with a number of stars (⭐), indicating the difficulty. You are likely not to be able to finish all exercises during the tutorial session

Questions

When is such a data structure more efficient than a standard Vec?
What are the downsides, compared to just using a Vec?

Open the exercises/2-foundations-of-rust/4-traits-and-generics/1-local-storage-vec crate. It contains a src/lib.rs file, meaning this crate is a library. lib.rs contains a number of tests, which can be run by calling cargo test. Don't worry if they don't pass or even compile right now: it's your job to fix that in this exercise. Most of the tests are commented out right now, to enable a step-by-step approach. Before you begin, have a look at the code and the comments in there, they contain various helpful clues.

2.4.1.A Defining the type ⭐

Currently, the LocalStorageVec enum is incomplete. Give it two variants: Stack and Heap. Stack contains two named fields, buf and len. buf will be the array with a capacity to hold N items of type T; len is a field of type usize that will denote the amount of items actually stored. The Heap variant has an unnamed field containing a Vec<T>. If you've defined the LocalStorageVec variants correctly, running cargo test should output something like

running 1 test
test test::it_compiles ... ignored, This test is just to validate the definition of `LocalStorageVec`. If it compiles, all is OK

test result: ok. 0 passed; 0 failed; 1 ignored; 0 measured; 0 filtered out; finished in 0.00s

This test does (and should) not run, but is just there for checking your variant definition.

Hint 1

You may be able to reverse-engineer the `LocalStorageVec` definition using the code of the `it_compiles` test case.

Hint 2 (If you got stuck, but try to resist me for a while)

Below definition works. Read the code comments and make sure you understand what's going on.

#![allow(unused)]
fn main() {
// Define an enum `LocalStorageVec` that is generic over
// type `T` and a constant `N` of type `usize`
pub enum LocalStorageVec<T, const N: usize> {
    // Define a struct-like variant called `Stack` containing two named fields:
    // - `buf` is an array with elements of `T` of size `N`
    // - `len` is a field of type `usize`
    Stack { buf: [T; N], len: usize },
    // Define a tuple-like variant called `Heap`, containing a single field
    // of type `Vec<T>`, which is a heap-based growable, contiguous list of `T`
    Heap(Vec<T>),
}
}

2.4.1.B `impl`-ing `From<Vec<T>>` ⭐

Uncomment the test it_from_vecs, and add an implementation for From<Vec<T>> to LocalStorageVec<T>. To do so, copy the following code in your lib.rs file and replace the todo! macro invocation with your code that creates a heap-based LocalStorageVec containing the passed Vec<T>.

#![allow(unused)]
fn main() {
impl<T, const N: usize> From<Vec<T>> for LocalStorageVec<T, N> {
    fn from(v: Vec<T>) -> Self {
        todo!("Implement me");
    }
}
}

Question

How would you pronounce the first line of the code you just copied in English?*

Run cargo test to validate your implementation.

2.4.1.C `impl LocalStorageVec` ⭐⭐

To make the LocalStorageVec more useful, we'll add more methods to it. Create an impl-block for LocalStorageVec. Don't forget to declare and provide the generic parameters. For now, to make implementations easier, we will add a bound T, requiring that it implements Copy and Default. First off, uncomment the test called it_constructs. Make it compile and pass by creating a associated function called new on LocalStorageVec that creates a new, empty LocalStorageVec instance without heap allocation.

The next methods we'll implement are len, push, pop, insert, remove and clear:

len returns the length of the LocalStorageVec
push appends an item to the end of the LocalStorageVec and increments its length. Possibly moves the contents to the heap if they no longer fit on the stack.
pop removes an item from the end of the LocalStorageVec, optionally returns it and decrements its length. If the length is 0, pop returns None
insert inserts an item at the given index and increments the length of the LocalStorageVec
remove removes an item at the given index and returns it.
clear resets the length of the LocalStorageVec to 0.

Uncomment the corresponding test cases and make them compile and pass. Be sure to have a look at the methods provided for slices [T] and Vec<T> Specifically, [T]::copy_within and Vec::extend_from_slice can be of use.

2.4.1.E `Iterator` and `IntoIterator` ⭐⭐

Our LocalStorageVec can be used in the real world now, but we still shouldn't be satisfied. There are various traits in the standard library that we can implement for our LocalStorageVec that would make users of our crate happy.

First off, we will implement the IntoIterator and Iterator traits. Go ahead and uncomment the it_iters test case. Let's define a new type:

#![allow(unused)]
fn main() {
pub struct LocalStorageVecIter<T, const N: usize> {
    vec: LocalStorageVec<T, N>,
    counter: usize,
}
}

This is the type we'll implement the Iterator trait on. You'll need to specify the item this Iterator implementation yields, as well as an implementation for Iterator::next, which yields the next item. You'll be able to make this easier by bounding T to Default when implementing the Iterator trait, as then you can use the std::mem::take function to take an item from the LocalStorageVec and replace it with the default value for T.

Take a look at the list of methods under the 'provided methods' section. In there, lots of useful methods that come free with the implementation of the Iterator trait are defined, and implemented in terms of the next method. Knowing in the back of your head what methods there are, greatly helps in improving your efficiency in programming with Rust. Which of the provided methods can you override in order to make the implementation of LocalStorageVecIter more efficient, given that we can access the fields and methods of LocalStorageVec?

Now to instantiate a LocalStorageVecIter, implement the [IntoIter] trait for it, in such a way that calling into_iter yields a LocalStorageVecIter.

2.4.1.F `Index` ⭐⭐

To allow users of the LocalStorageVec to read items or slices from its buffer, we can implement the Index trait. This trait is generic over the type of the item used for indexing. In order to make our LocalStorageVec versatile, we should implement:

Index<usize>, allowing us to get a single item by calling vec[1];
Index<RangeTo<usize>>, allowing us to get the first n items (excluding item n) by calling vec[..n];
Index<RangeFrom<usize>>, allowing us to get the last n items by calling vec[n..];
Index<Range<usize>>, allowing us to get the items between n and m items (excluding item m) by calling vec[n..m];

Each of these implementations can be implemented in terms of the as_ref implementation, as slices [T] all support indexing by the previous types. That is, [T] also implements Index for those types. Uncomment the it_indexes test case and run cargo test in order to validate your implementation.

2.4.1.G Removing bounds ⭐⭐

When we implemented the borrowing Iterator, we saw that it's possible to define methods in separate impl blocks with different type bounds. Some of the functionality you wrote used the assumption that T is both Copy and Default. However, this means that each of those methods are only defined for LocalStorageVecs containing items of type T that in fact do implement Copy and Default, which is not ideal. How many methods can you rewrite having one or both of these bounds removed?

2.4.1.H Borrowing `Iterator` ⭐⭐⭐

We've already got an iterator for LocalStorageVec, though it has the limitation that in order to construct it, the LocalStorageVec needs to be consumed. What if we only want to iterate over the items, and not consume them? We will need another iterator type, one that contains an immutable reference to the LocalStorageVec and that will thus need a lifetime annotation. Add a method called iter to LocalStorageVec that takes a shared &self reference, and instantiates the borrowing iterator. Implement the Iterator trait with the appropriate Item reference type for your borrowing iterator. To validate your code, uncomment and run the it_borrowing_iters test case.

Note that this time, the test won't compile if you require the items of LocalStorageVec be Copy! That means you'll have to define LocalStorageVec::iter in a new impl block that does not put this bound on T:

#![allow(unused)]
fn main() {
impl<T: Default + Copy, const N: usize> LocalStorageVec<T, N> {
    // Methods you've implemented so far
}

impl<T: const N: usize> LocalStorageVec<T, N> {
    pub fn iter(&self) -> /* TODO */
}
}

Defining methods in separate impl blocks means some methods are not available for certain instances of the generic type. In our case, the new method is only available for LocalStorageVecs containing items of type T that implement both Copy and Default, but iter is available for all LocalStorageVecs.

2.4.1.I Generic `Index` ⭐⭐⭐⭐

You've probably duplicated a lot of code in exercise 2.4.1.F. We can reduce the boilerplate by defining an empty trait:

#![allow(unused)]
fn main() {
trait LocalStorageVecIndex {}
}

First, implement this trait for usize, RangeTo<usize>, RangeFrom<usize>, and Range<usize>.

Next, replace the multiple implementations of Index with a single implementation. In English:

"For each type T, I and constant N of type usize, implement Index<I> for LocalStorageVec<T, N>, where I implements LocalStorageVecIndex and [T] implements Index<I>"

If you've done this correctly, it_indexes should again compile and pass.

2.4.1.J `Deref` and `DerefMut` ⭐⭐⭐⭐

The next trait that makes our LocalStorageVec more flexible in use are Deref and DerefMut that utilize the 'deref coercion' feature of Rust to allow types to be treated as if they were some type they look like. That would allow us to use any method that is defined on [T] by calling them on a LocalStorageVec. Before continuing, read the section 'Treating a Type Like a Reference by Implementing the Deref Trait' from The Rust Programming Language (TRPL). Don't confuse deref coercion with any kind of inheritance! Using Deref and DerefMut for inheritance is frowned upon in Rust.

Below, an implementation of Deref and DerefMut is provided in terms of the AsRef and AsMut implementations. Notice the specific way in which as_ref and as_mut are called.

#![allow(unused)]
fn main() {
impl<T, const N: usize> Deref for LocalStorageVec<T, N> {
    type Target = [T];

    fn deref(&self) -> &Self::Target {
        <Self as AsRef<[T]>>::as_ref(self)
    }
}

impl<T, const N: usize> DerefMut for LocalStorageVec<T, N> {
    fn deref_mut(&mut self) -> &mut Self::Target {
        <Self as AsMut<[T]>>::as_mut(self)
    }
}
}

Question

Replacing the implementation of deref with self.as_ref() results in a stack overflow when running an unoptimized version. Why? (Hint: deref coercion)

Unit 2.5 - Closures and Dynamic dispatch

Slides

Exercise 2.5.1: Config Reader

In this exercise, you'll work with dynamic dispatch to deserialize with serde_json or serde_yaml, depending on the file extension. The starter code is in exercises/2-foundations-of-rust/5-closures-and-dynamic-dispatch/1-config-reader. Fix the todo's in there.

To run the program, you'll need to pass the file to deserialize to the binary, not to Cargo. To do this, run

cargo run -- <FILE_PATH>

Deserializing both config.json and config.yml should result in the Config being printed correctly.

Unit 3.1 - Crate Engineering

Slides

Exercise 3.1.1: My Serde App

This exercise is adapted from the serde_lifetimes exercise by Ferrous Systems

Open exercises/3-crate-engineering/1-crate-engineering/1-my-serde-app/src/main.rs. In there, you'll find some Rust code we will do this exercise with.

We used todo!() macros to mark places where you should put code to make the program run. Look at the serde_json api for help.

Hint

Serde comes with two traits: `Serializable` and `Deserializable`. These traits can be `derive` d for your `struct` or `enum` types. Other `serde-*` crates use these traits to convert our data type from and to corresponding representation (`serde-json` to JSON, `serde-yaml` to YAML, etc.).

How come main returns an anyhow::Result<()>? By having main return a result, we can bubble errors up all the way to runtime. You can find more information about it in Rust By Example. The anyhow::Result is a more flexible type of Result, which allows for easy conversion of error types.

What is that r#"... thing?
r in front of a string literal means it's a "raw" string. Escape sequences (\n, \", etc.) don't work, and thus they are very convenient for things like regular expressions, JSON literals, etc.

Optionally r can be followed by one or more symbols (like # in our case), and then your string ends when there's a closing double quote followed by the same number of the same symbols. This is great for cases when you want to have double quotes inside your string literal. For our example r#" ... "# works great for JSON. In rare cases you'd want to put two or more pound signs. Like, when you store CSS color values in your JSON strings:

#![allow(unused)]
fn main() {
// here `"#` would not terminate the string
r##"
    {
        "color": "#ff00ff"
    }
"##
}

Exercise 3.1.2: Quizzer

In this exercise, you will create a Rust crate that adheres to the guidelines that were pointed out during the lecture. Additionally, you will add and use dependencies, create unit tests, and create some documentation. You can view this exercise as a stepping stone to the final project.

This exercise should be done in groups of 2 people

3.1.2.A Setting up ⭐

Create a new project using cargo new --name quizzer. Make sure it acts as both a binary and a library. That means there will be both a src/lib.rs and a src/bin/quizzer/main.rs file in your crate, where quizzer is the name of the binary:

$ tree
.
├── Cargo.toml
├── quiz.json
└── src
    ├── bin
    │   └── quizzer
    │       └── main.rs
    └── lib.rs

Add the following dependencies to your Cargo.toml file. Below items contain links to their page on lib.rs. Make sure you get a general idea of what these crates are for and how they can be used. Don't dive too deep just yet.

anyhow 1.0
clap 4.0 Also, skim over https://docs.rs/clap/latest/clap/_derive/_tutorial/index.html
serde-json 1.0
serde 1.0

Your Cargo.toml should look like this:

[package]
name = "quizzer"
version = "0.1.0"
edition = "2021"

### See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html

[dependencies]
anyhow = "1.0.66"
clap = { version = "4.0.18", features = ["derive"] }
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0.87"

For clap and serde, the non-standard derive feature of each these crates is enabled. For clap, it allows us to derive the Parser trait, which greatly simplifies creating a CLI. The derive feaure from serde allows us to derive the Serialize and Deserialize traits on any struct we wish to serialize or deserialize using serde and its backends, in our case serde_json.

3.1.2.B Quizzer ⭐⭐⭐

This exercise is about both design and finding information. You'll have to figure out a model to represent your quiz questions, as well as a means to store them into a JSON file, and load them yourself. Also, you will have to find out how to parse the program arguments.

We will use the project we just set up to write a quiz game creator and player. You may add other dependencies as needed. It has the following functional requirements:

It runs as a command-line tool in your terminal.
It has two modes: question-entering mode and quiz mode. The mode is selected with a subcommand, passed as the first argument to the program.
- Question-entering mode: Allows for entering multiple-choice quiz questions, with 4 possible answers each, exactly 1 of them being correct. The questions are stored on disk as a JSON file.
- Quiz mode: Loads stored questions from the JSON file, presents the questions one-by-one to the player, reads and verifies the player input, and presents the score at the end of the game.
Errors are correctly handled, i.e. your application does not panic if it encounters any unexpected situation. Use anywhow and the question-mark (?) operator to make error-bubbling concise. You can read about the ?-operator here: https://doc.rust-lang.org/reference/expressions/operator-expr.html#the-question-mark-operator
Logic concerning creating, storing, and loading quiz questions is defined in the library part of your crate.
Functionality regarding user input (arg parsing, reading from stdin) is defined in the application code, not in your library.
Logical units of your crate are divided up into modules.

Before you start coding, make sure you've listed all open questions and found answers to them. You're also encouraged to draw a simple diagram of the module structure of your application, annotating each module with its responsibilities.

Exercise 3.1.3: BSN

The BSN (Burgerservicennummer) is a Dutch personal identification number that somewhat resembles the US Social Security Number in its use. The BSN is a number that adheres to some rules. In this exercise, we will create a Rust type that guarantees that it represents a valid BSN.

3.1.3.A Newtype ⭐⭐

In this part we will implement the BSN number validation, as well as a fallible constructor.

A BSN is valid if and only if it matches the following criteria:

It consists of 8 or 9 digits
It passes a variant of the 11 check (elfproef (Dutch)):

For 8-digit BSNs, we concatenate a 0 to the end. The digits of the number are labeled as ABCDEFGHI. For example: for BSN 123456789, A = 1, B = 2, C = 3, and so forth until I.

Then, (9 × A) + (8 × B) + (7 × C) + (6 × D) + (5 × E) + (4 × F) + (3 × G) + (2 × H) + (-1 × I) must be a multiple of 11

Open exercises/3-crate-engineering/1-crate-engineering/3-bsn in your editor. You'll find the scaffolding code there, along with two files:

valid_bsns.in containing a list of valid BSNs
invalid_bsns.in containing a list of invalid BSNs.

In src/lib.rs, implement Bsn::validate to make the test_validation test case pass. Implement Bsn::try_from_string as well. To try just the test_validation test case, run:

cargo test -- test_validation

3.1.3.B Visitor with Serde ⭐⭐⭐

Next up is implementing the serde::Serialize and serde::Deserialize traits, to support serialization and deserialization of Bsns. In this case, simply deriving those traits won't suffice, as we want to represent the BSN as a string after serialization. We also want to deserialize strings directly into Bsns, while still upholding the guarantee that an instantiated Bsn represents a valid BSN. Therefore, you have to incorporate Bsn::validate into the implementation of the deserialization visitor.

More information on implementing the traits:

serde::Serialize: https://serde.rs/impl-serialize.html
serde::Deserialize: https://serde.rs/impl-deserialize.html

If everything works out, all tests should pass.

Exercise 3.1.4: 3D Printer

An imaginary 3D printer uses filament to create all kinds of things. Its states can be represented with the following state diagram:

                   ┌─────────────────┐
                   │                 │
                   │                 │   Reset
                   │      Idle       │◄────────────────────────────┐
         ┌────────►│                 │                             │
         │         │                 │                             │
         │         │                 │                             │
         │         └────────┬────────┘                             │
         │                  │                                      │
         │                  │                                      │
         │                  │ Start                                │
         │                  │                                      │
         │                  ▼                                      │
         │         ┌─────────────────┐                    ┌────────┴────────┐
         │         │                 │                    │                 │
         │         │                 │   Out of filament  │                 │
Product  │         │    Printing     ├──────────────────► │      Error      │
retrieved│         │                 │                    │                 │
         │         │                 │                    │                 │
         │         │                 │                    │                 │
         │         └────────┬────────┘                    └─────────────────┘
         │                  │
         │                  │ Product ready
         │                  │
         │                  ▼
         │         ┌─────────────────┐
         │         │                 │
         │         │                 │
         │         │  Product Ready  │
         └─────────┤                 │
                   │                 │
                   │                 │
                   └─────────────────┘

The printer boots in Idle state. Once a job is started, the printer enters the Printing state. In printing state, it keeps on printing the product until either it is ready or the printer is out of filament. If the printer is out of filament, the printer goes into Error state, which it can only come out of upon device reset. If the product is ready, the printer goes to Product Ready state, and once the user retrieves the product, the printer goes back to Idle.

The printer can be represented in Rust using the typestate pattern as described during the lecture. This allows you to write a simple 3D printer driver. In exercises/3-crate-engineering/1-crate-engineering/4-3d-printer, a Printer3D struct is instantiated. Add methods corresponding to each of the traits, that simulate the state transitions by printing the state. A method simulating checking if the printer is out of filament is provided.

Of course, to make the printer more realistic, you can add more states and transitions.

Exercise 3.1.5: FizzBuzz

In this exercise, you will practise writing a unit test, and use Rusts benchmarking functionality to help you optimize a FizzBuzz app. You will need cargo-criterion, a tool that runs benchmarks and creates nice reports. You can install it by running

cargo install cargo-criterion --version=1.1.0

3.1.5.A Testing Fizz Buzz ⭐

Open exercises/3-crate-engineering/1-crate-engineering/5-fizzbuzz/src/lib.rs. Create a unit test that verifies the correctness of the fizz_buzz function. You can use the include_str macro to include exercises/3-crate-engineering/1-crate-engineering/5-fizzbuzz/fizzbuzz.out as a &str into your binary. Each line of fizzbuzz.out contains the expected output of the fizz_buzz function given the line number as input. You can run the test with

cargo test

By default, Rusts test harness captures all output and discards it, If you like to debug your test code using print statements, you can run

cargo test -- --nocapture

to prevent the harness from capturing output.

3.1.5.B Benchmarking Fizz Buzz ⭐⭐

You'll probably have noticed the fizz_buzz implementation is not very optimized. We will use criterion to help us benchmark fizz_buzz. To run a benchmark, run the following command when in the exercises/3-crate-engineering/1-crate-engineering/5-fizzbuzz/ directory:

cargo criterion

This command will run the benchmarks, and report some statistics to your terminal. It also generates HTML reports including graphs that you can find under target/criterion/reports. For instance, target/criterion/reports/index.html is a summary of all benchmark. Open it with your browser and have a look.

Your job is to do some optimization of the fizz_buzz function, and use cargo-criterion to measure the impact of your changes. Don't be afraid to change the signature of fizz_buzz, if, for instance, you want to minimize the number of allocations done by this function. However, make sure that the function is able to correctly produce the output. How fast can you FizzBuzz?

Unit 4.1 - Introduction to Multitasking

Slides

There are no exercises for this unit

Unit 4.2 - Parallel Multitasking

Slides

Exercise 4.2.1: TF-IDF

Follow the instructions in the comments of exercises/4-multitasking/2-parallel-multitasking/1-tf-idf/src/main.rs!

Exercise 4.2.2: Mutex

The basic mutex performs a spin-loop while waiting to take the lock. That is terribly inefficient. Luckily, your operating system is able to wait until the lock becomes available, and will just put the thread to sleep in the meantime.

This functionality is exposed in the atomic_wait crate. The section on implementing a mutex from "Rust Atomics and Locks" explains how to use it.

change the AtomicBool for a AtomicU32
implement lock. Be careful about spurious wakes: after wait returns, you must stil check the condition
implement unlocking (Drop for MutexGuard<T> using wake_one.

The linked chapter goes on to further optimize the mutex. This is technically out of scope for this course, but we won't stop you if you try (and will still try to help if you get stuck)!

Unit 4.3 - Asynchronous Multitasking

Slides

Exercise 4.3.1: Async Channels

Channels are a very useful way to communicate between threads and async tasks. They allow for decoupling your application into many tasks. You'll see how that can come in nicely in exercise E.2. In this exercise, you'll implement two variants: a oneshot channel and a multi-producer-single-consumer (MPSC) channel. If you're up for a challenge, you can write a broadcast channel as well.

4.3.1.A MPSC channel ⭐⭐

A multi-producer-single-consumer (MPSC) channel is a channel that allows for multiple Senders to send many messages to a single Receiver.

Open exercises/4-multitasking/3-asynchronous-multitasking/1-async-channels in your editor. You'll find the scaffolding code there. For part A, you'll work in src/mpsc.rs. Fix the todo!s in that file in order to make the test pass. To test, run:

cargo test -- mpsc

If your tests are stuck, probably either your implementation does not use the Waker correctly, or it returns Poll::Pending where it shouldn't.

4.3.1.B Oneshot channel ⭐⭐⭐

A oneshot is a channel that allows for one Sender to send exactly one message to a single Receiver.

For part B, you'll work in src/broadcast.rs. This time, you'll have to do more yourself. Intended behavior:

Receiver implements Future. It returns Poll::Ready(Ok(T)) if inner.data is Some(T), Poll::Pending if inner.data is None, and Poll::Ready(Err(Error::SenderDropped)) if the Sender was dropped.
Receiver::poll replaces inner.waker with the one from the Context.
Sender consumes self on send, allowing the it to be used no more than once. Sending sets inner.data to Some(T). It returns Err(Error::ReceiverDropped(T)) if the Receiver was dropped before sending.
Sender::send wakes inner.waker after putting the data in inner.data
Once the Sender is dropped, it marks itself dropped with inner
Once the Receiver is dropped, it marks itself dropped with inner
Upon succesfully sending the message, the consumed Sender is not marked as dropped. Instead std::mem::forget is used to avoid running the destructor.

To test, run:

cargo test -- broadcast

4.3.1.C Broadcast channel (bonus) ⭐⭐⭐⭐

A Broadcast channel is a channel that supports multiple senders and receivers. Each message that is sent by any of the senders, is received by every receiver. Therefore, the implemenentation has to hold on to messages until they have been sent to every receiver that has not yet been dropped. This furthermore implies that the message shoud be cloned upon broadcasting.

For this bonus exercise, we provide no scaffolding. Take your inspiration from the mpsc and oneshot modules, and implement a broadcast module yourself.

Exercise 4.3.2: Async Chat

In this exercise, you'll write a simple chat server and client based on Tokio. Open exercises/4-multitasking/3-asynchronous-multitasking/2-async-chat in your editor. The project contains a lib.rs file, in which a type Message resides. This Message defines the data the chat server and clients use to communicate.

4.3.2.A Server ⭐⭐⭐

The chat server, which resides in src/bin/server.rs listens for incoming TCP connections on port 8000, and spawns two tasks (futures):

handle_incoming: reads lines coming in from the TCP connection. It reads the username the client provides, and broadcasts incoming Messages, possibly after some modification.
handle_outgoing: sends messages that were broadcasted by the handle_incoming tasks to the client over TCP.

Both handle_incoming and handle_outgoing contain a number to todos. Fix them.

To start the server, run

cargo run --bin server

4.3.2.B Client ⭐⭐

The chat client, residing in src/bin/client.rs contains some todo's as well. Fix them to allow for registration and sending Messages to the server.

To start the client, run

cargo run --bin client

If everything works well, you should be able to run multiple clients and see messages sent from each client in every other.

Unit 5.1 - Rust for Web

Slides

Exercise 5.1.1: Pastebin

This exercise is about writing a simple pastebin web server. Like the quizzer app, you will need to set up the project yourself. This webserver will be powered by axum.

Data is kept in memory. Bonus if you use a database or sqlite, but first make the app function properly without.
Expose a route to which a POST request can be sent, that accepts some plain text, and stores it along with a freshly generated UUID. The UUID is sent in the response. You can use the uuid crate to generate UUIDs.
Expose a route to which a GET request can be sent, that accepts a UUID and returns the plain text corresponding to the UUID, or a 404 error if it doesn't exist.
Expose a route to which a DELETE request can be sent, that accepts a UUID and deletes the plain text corresonding to that UUID.

Unit 6.1 - Foreign Function Interface

Slides

Exercise 6.1.1: CRC in C

In this exercise, we will call a CRC checksum function written in C from a Rust program.

Instructions

Prerequisites:

A C compiler

Steps:

Add the cc build dependency, by adding to Cargo.toml the lines:
```
[build-dependencies]
cc = "1.0"
```

Create build.rs (in the same directory as Cargo.toml) with contents

extern crate cc;

fn main() {
    println!("cargo:rerun-if-changed=crc32.h");
    println!("cargo:rerun-if-changed=crc32.c");
    cc::Build::new().file("crc32.c").compile("crc32.a");
}

build.rs is a build script that cargo runs before it compiles your crate. This will find your c code, compile it, and link it into the executable rust produces.

In main.rs, define an extern (fill in the argument and return types)

#![allow(unused)]
fn main() {
extern "C" {
    fn CRC32( ... ) -> ...; // hint: https://doc.rust-lang.org/std/os/raw
}
}

Now, create a rust wrapper that calls the extern function

#![allow(unused)]
fn main() {
fn crc32( ... ) -> ... { 
    ... // (hints: `unsafe`, `.as_ptr()`, `.len()`)
}
}

Call our wrapper on some example input

fn main() {
    println!("{:#x}", crc32(b"12345678"));
}

In the above example, the correct output is 0x9ae0daaf

Exercise 6.1.2: CRC in Rust

Now, let's do it the other way around: we can use a CRC checksum function written in Rust in a C program.

Instructions

Prerequisites:

A C compiler

Steps:

Change Cargo.toml to

[package]
name = "crc-in-rust"
version = "0.1.0"
edition = "2021"

[lib]
name = "crc_in_rust"
crate-type = ["dylib"]

# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html

[dependencies]

Expose an extern rust function in the lib.rs

#![allow(unused)]
fn main() {
#[no_mangle]
pub extern "C" fn crc32(...) -> ... {

    ...

    crc32_rust(...)
}
}

Create a C header file crc_in_rust.h

#include <stdint.h> // uint32_t, uint8_t
#include <stddef.h> // size_t

uint32_t crc32(const uint8_t data[], size_t data_length);

Create main.c and use the rust crc32 function

#include <stdint.h> // uint32_t, uint8_t
#include <stddef.h> // size_t
#include <stdio.h> // printf
#include "crc_in_rust.h"

int main() { 
    uint8_t data[] = { 0,1,2,3,4,5,6 };
    size_t data_length = 7;

    uint32_t hash = crc32(data, data_length);

    printf("Hash: %d\n", hash);

    return 0;
}

Give the rust function the same signature as the one defined in the header file

Compile the rust crate and then run

Linux & MacOS:

# Build main.c, link it to the dynamic library and output the executable called main
$ clang main.c target/debug/libcrc_in_rust.so -omain
# Run the executable
$ ./main
Hash: -1386739207

Windows:

# Build main.c, link it to the import library of the DLL and output the executable called main.exe
❯ clang main.c .\target\debug\crc_in_rust.dll.lib -o "main.exe"
# Move the dll to the same folder as the exe so it can find it
❯ cp .\target\debug\crc_in_rust.dll crc_in_rust.dll
# Run the executable
❯ .\main.exe
Hash: -1386739207

Exercise 6.1.3: QOI Bindgen

In this exercise, we will use cargo bindgen to generate the FFI bindings for a C library. Bindgen will look at a C header file, and generate Rust functions, types and constants based on the C definitions.

However, the generated code will likely be ugly and non-idiomatic. To wrap a C library properly, good API design and documentation is needed.

Background

The image crate provides functionality for encoding, decoding and editing images in Rust. It supports many image formats, like JPEG, PNG and GIF, but also QOI. QOI is a "Quite OK Image format", which aims for fast encoding and decoding of images, while providing a file size similar to PNGs. In this exercise, we test if the image crate produces the same results when decoding QOI images as the QOI reference C library.

The QOI C library is a header-only library, which means the function implementations are included within the header file instead of in a separate C file. We've added a separate C file which includes the header to make it easier to compile and include the library in our Rust program.

Generating bindings

Prerequisites:

A C compiler is installed on the system
Bindgen, which can be installed with cargo install bindgen-cli

Steps:

Create the Rust bindings: bindgen qoi.h -o src/bindings.rs

Use a build.rs script to compile and link qoi.h. Create build.rs and insert

fn main() {
    cc::Build::new().file("qoi.c").compile("qoi"); // outputs `qoi.a`
}

And add this section to your Cargo.toml

[build-dependencies]
cc = "1"

Create src/lib.rs with the contents pub mod bindings;. This will make the bindings module available in main.rs.
Run cargo check to verify everything is compiling correctly.

Inspecting our bindings

In the generated bindings.rs file we find this signature for the qoi_read C function from QOI:

#![allow(unused)]
fn main() {
extern "C" {
    pub fn qoi_read(
        filename: *const ::std::os::raw::c_char,
        desc: *mut qoi_desc,
        channels: ::std::os::raw::c_int,
    ) -> *mut ::std::os::raw::c_void;
}
}

Some observations:

The definition is inside an extern "C" block, and has no body. Therefore, this function is marked as an extern, and Rust expects it to be linked in.
The function is marked pub, meaning we can import and use it in other modules (like main.rs in our case)

We can deduce the behavior somewhat from the type signature:

filename is a C string with the name of the QOI file we want to read

desc describes some metadata about the image, the function will write to this qoi_desc struct. This struct was also generated by bindgen:

#![allow(unused)]
fn main() {
#[repr(C)]
#[derive(Debug, Copy, Clone)]
pub struct qoi_desc {
    pub width: ::std::os::raw::c_uint,
    pub height: ::std::os::raw::c_uint,
    pub channels: ::std::os::raw::c_uchar,
    pub colorspace: ::std::os::raw::c_uchar,
}
}

channels is the number of channels the image has: either 3 for RGB images, or 4 for RGBA images (which also have an alpha channel for transparency). For this exercise, we will assume the images have an alpha channel.
The return value is a void pointer. If the function has successfully read the pixel data from a QOI image, then this pointer should point towards the pixel data.

As the types are raw C types, it can be a hassle to call it directly from Rust.

We will deal with the last point by writing a nice Rust wrapper around the generated bindings.

Writing our wrapper

To make the qoi_read function easier to use, we would like to write a wrapper that takes a path and returns an image buffer:

#![allow(unused)]
fn main() {
fn read_qoi_image(filename: &Path) -> ImageBuffer<Rgba<u8>, &[u8]> {
    todo!()
}
}

To implement this wrapper, there are a couple of challenges that need to be solved:

We need to turn the path into a C string. Hint: we can use std::ffi::CString::new to create a C string from a sequence of bytes, and the most convenient way to turn the path into bytes is to first get the OsStr from it. We can then pass the C string as a pointer.
We need to provide a qoi_desc, this struct can be imported from the bindings. Pass a mutable reference to an instance of this struct to the function.
After calling qoi_read, we need to turn the returned void pointer into an image buffer.
- First, we should check if the returned void pointer is_null(). If it is null, something has gone wrong with reading the image.
- Next, we need to determine the length of the returned pixel data. Assuming the image has an alpha channel, we have 4 bytes for every pixel in the image. The number of pixels in the image can be determined from the qoi_desc struct.
- Now we can turn our void pointer into a &[u8]. We can cast our void pointer as *const u8 first. Next, we use std::slice::from_raw_parts with the previously calculated length.
- Finally, we can use ImageBuffer::from_raw to construct our image buffer.

To try out our wrapper, we can try to read a QOI image and export it as a PNG:

fn main() {
    let image = read_qoi_image(Path::new("image.qoi"));
    image.save("image.png").unwrap();
}

If implemented correctly, this should produce a nice picture!

Now that we can decode images using the QOI reference C library, we can test if the image crate produces the same results with the following unit test:

#![allow(unused)]
fn main() {
#[cfg(test)]
mod tests {
    use crate::read_qoi_image;
    use std::path::Path;

    #[test]
    fn test_qoi_read() {
        let filename = "image.qoi";
        let image = image::open(filename).unwrap().into_rgba8();
        let my_image = read_qoi_image(Path::new(filename));

        assert_eq!(image.width(), my_image.width());
        assert_eq!(image.height(), my_image.height());

        assert!(image.pixels().eq(my_image.pixels()));
    }
}
}

If you add this test to main.rs and run it with cargo test we should see:

running 1 test
test tests::test_qoi_read ... ok

Freeing the pixel data

When working with data from C, we are responsible for deallocating the memory once we are done using it. Some C libraries might provide a separate function to clean up data structures. For QOI, we instead have to call libc::free to free the memory, as indicated by the documentation of the qoi_read function:

The returned pixel data should be free()d after use.

To make sure someone using our wrapper does not forget to free the memory, we can implement the Drop trait to automatically call libc::free when the variable goes out of scope.

First, create a wrapper struct MyImage<'a>(ImageBuffer<Rgba<u8>, &'a [u8]>);, which holds the image buffer.

Next, implement the Drop trait for MyImage to free the memory (we should retrieve the pointer from the image buffer and cast it back to a void pointer):

#![allow(unused)]
fn main() {
impl Drop for MyImage<'_> {
    fn drop(&mut self) {
        todo!(); // call libc::free here using a pointer to the image buffer
    }
}
}

To make this MyImage wrapper more convenient to use, we can also implement the Deref trait to allow us to directly call the methods from the internal image buffer on it:

#![allow(unused)]
fn main() {
impl<'a> Deref for MyImage<'a> {
    type Target = ImageBuffer<Rgba<u8>, &'a [u8]>;

    fn deref(&self) -> &Self::Target {
        &self.0
    }
}
}

Now update the read_qoi_image function to return an instance of MyImage.

Uninitialized memory

There is one more trick: our current function initializes the qoi_desc struct with zeros (or whatever values you put there while creating an instance of the struct). This is wasteful because the extern function will overwrite these values. Because the extern function is linked in, the compiler likely does not have enough information to optimize this.

For a relatively small struct such as qoi_desc, this is not much of a problem. However, for larger structures or big arrays, this can make a serious impact on performance.

If we look at the LLVM IR, the intermediate representation which is generated and optimized before it gets turned into assembly code, we can see that it did not optimize away the initialization of the struct with values. Here we see it uses memset to initialize the desc with zeros before calling qoi_read:

call void @llvm.memset.p0.i64(ptr noundef nonnull align 4 dereferenceable(10) %desc.i, i8 0, i64 10, i1 false), !noalias !142
%pointer.i = call noundef ptr @qoi_read(ptr noundef nonnull %t.0.i.i, ptr noundef nonnull %desc.i, i32 noundef 4) #17, !noalias !142

(The LLVM IR can be generated using cargo rustc --bin qoi-bindgen --release -- --emit=llvm-ir)

The solution is to use std::mem::MaybeUninit:

#![allow(unused)]
fn main() {
let mut desc = MaybeUninit::uninit();
let pointer = unsafe { qoi_read(filename.as_ptr(), desc.as_mut_ptr(), 4) };
let desc = unsafe { desc.assume_init() };
}

The MaybeUninit type is an abstraction for uninitialized memory. The .uninit() method gives a chunk of uninitialized memory big enough to store a value of the desired type (in our case qoi_desc will be inferred).

Conclusion

In this exercise we saw how we can generate bindings to a C library with bindgen. The generated bindings are a bit difficult to work with, as they are unsafe and rely on C types. We've discussed how we can create nice wrappers around the generated bindings to deal with all these C types and to make them safer to work with.

Unit 7.1 - Rust from Python

Slides

Exercise 7.1.1: Test your environment

7.1.1.A: Set up the tools ⭐

Follow the instructions to instal the Maturin build tool: https://pyo3.rs/v0.21.2/getting-started. We recommend using pyenv: https://github.com/pyenv/pyenv, but pyenv only supports UNIX and WSL. Of course, you can use your favourite venv manager, too.

Navigate to the exercises/7-rust-for-data-science/1-rust-from-python/1-hello-world/ folder in your terminal. Setup and activate your virtual environment, and install the things we need. If you're using pyenv, that means running the following commands:

$ pyenv activate pyo3
$ pip install maturin
$ pip install asyncio
$ pip install aiofiles

7.1.1.B: Trying it out ⭐

If everything went well, you should now be able to build this project into a Python extension:

$ maturin develop
$ python test.py

The test.py script ends in a call to a function that unconditionally raises, so your script is expected to result in an uncaught exception.

Now, try running test_async.py as well and observe its behavior.

7.1.1.C: Running futures concurrently ⭐⭐

You can use asyncio.gather in your python script to execute multiple awaitables. Spawn a number of print_sleep futures, each with different sleep durations using asyncio.gather and observe the behavior.

Exercise 7.1.2: Streaming JSON

Here's a cool crate: Struson. It's a crate that allows for (de)serialization of JSON objects in a streaming fashion, meaning that you don't need to hold all of the data in memory. This contrasts a bit with the great library serde_json, which is very, very ergonomic, but does not allow for easy streaming (de)serialization of data. We're going build something around Struson, that we can use from Python.

Now, let's say we have a stream of JSON. Could be from someone on the internet or some other process running on the machine. Or, you know, a file. The stream consists of data that looks like this:

[
    {
        "lhs": {
            "d":[
                1, 2, 3, 4,
                5, 6, 7, 8,
                9, 10, 11, 12
            ],
            "n": 3
        },
        
        "op": [
            {
                "code": "dot",
                "rhs": {
                    "d": [
                        13, 14, 15, 16,
                        17, 18, 19, 20,
                        21, 22, 23, 24
                    ],
                    "n": 3
                }
            }
        ]
    }
]

This JSON is an array of objects that each represent the following:

lhs: a matrix with m rows and n columns. m can be derived from n and the length of d. In this case m = len / n = 12 / 3 = 4.
op: a sequence of operations that need to take place given lhs and, if the operation takes two operands, its rhs field. x corresponds to the operation that should be executed, and should more or less correspond to the methods provided on nalgebra's Matrix type. In this case, the Matrix::dot method should be run, which, for probably good reason, is describead as 'the dot product between two vectors or matrices (seen as vectors)'.

Our library should streamingly deserialize each incoming object from an asyncio stream of bytes, apply the given operation, and pass on the result.

Exercise 7.1.2.A: Give it a go ⭐

The scaffolding code in exercises/7-rust-for-data-science/1-rust-from-python/2-strompy/ implements what we want in Rust, and also provides a synchronous implementation. Have a look around in the code, and try to make sense of it. https://docs.rs is your friend if you want to know more about the dependencies that are being used. Note that for struson, we import a fork that supports deserializing asynchronously.

You can run cargo test to build and run the tests in src/lib.rs.

Exercise 7.1.2.B: The sync way ⭐⭐

During the next exercises, it's good to keep the PyO3 User Guide and the PyO3 API docs at hand.

This exercise is about making strompy_test.py run. Therefore, fix the todo!() in the exec function in src/lib.rs. Don't forget to add the function to the exposed module!

If you've done it correctly, you should be able to run it with the following commands:

$ maturin develop
$ python strompy_test.py

7.1.2.B: The `async` way ⭐⭐⭐

This time, we'll make strompy_test_async.py work. Implement feed_bytes and add an async method to the StrompyJsonReader type that yields a PyResult<Option<Vec<Vec<f64>>>> and is exposed with the name 'next'.

If you've done it correctly, you should be able to run it with the following commands:

$ maturin develop
$ python strompy_test_async.py

7.1.2.C: More features (Bonus) ⭐⭐⭐

Can you make strompy support more operations from Nalgebra?

7.1.2.D: Tidying up (Bonus) ⭐⭐⭐⭐

Representing the vectors as Vec<Vec<f64>> works, but it's not great. Make the StrompyJsonReader produce PyResult<Option<Py<PyList>>>s that constists of PyLists instead.

This is quite a hard exercise, as it involves working with PyO3s smart pointers: Py<T>, Bound<'py, T>, and GIL tokens: Python

Unit 8.1 - The Rust embedded ecosystem

Slides

Exercise 8.1.1: LSM303AGR ID

Use our newly gained knowledge to get our first application running and read out the ID of the LSM303AGR accelerometer. We can communicate with the LSM303AGR using the I2C that is present on the micro:bit board. Note that the nRF52833 supports I2C with its TWIM (Two-Wire Interface Master) peripheral.

To get started we'll setup the i2c peripheral on our development kit and read out the ID register of the LSM303AGR accelerometer. The starting point can be found in the file at exercises/8-embedded/1-embedded-ecosystem/src/main.rs in the repository.

Try to run the existing project and then fill in the functionality as instructed by the comments.

To use that project, you can use the following commands from inside that folder using the terminal:

cargo build: Builds the project
cargo run: Builds the project, flashes it to the device and listens for any logs which it will display in the terminal. (This uses the probe-rs run tool)

In both cases you can add the --release flag to turn on optimizations.

Some pointers to help you get started

You can find the documentation on the HAL here on docs.embassy.dev. This website houses the docs for embassy for every available chip. Normally you'd search at docs.rs, but that only shows one possible configuration of the HAL.
To find out how to configure I2C for the nRF52833: embassy-nrf TWIM demo example.
You can find the LSM303AGR data sheet here: https://www.st.com/resource/en/datasheet/lsm303agr.pdf. You can find the accelerometer device ID in the WHO_AM_I_A register, at register address 0x0F. You'll need 0x19 to address the accelerometer itself.
Use the Twim::blocking_write_read method to first write the device address, then write the register address, and then read its contents into a buffer.

Unit 8.2 - Portable Rust drivers

Slides

Exercise 8.2.1: LSM303AGR Driver

When you really want to use a device, you want to have a driver. Let's write an actual portable device driver for the accelerometer we've got.

Go to the assignment in exercises/8-embedded/2-portable-drivers/1-lsm303agr-driver and implement the lsm303agr module. The goal is to use embedded-hal for our hardware definitions, so try not to use any nRF-specific types in that module.

Use the driver to read data from the sensor in src/main.rs

As a bonus exercise, support reading the magnetometer as well

Unit 8.3 - Async on Embedded

Slides

Exercise 8.3.1: Compass

In this exercise, we'll use the lsm303agr driver. Although the documentation doesn't show it, it supports async if you enable its async feature

Have a look at the examples in the lsm303agr-rs repository to get an idea of how to use this driver.

Using the lsm303agr driver, implement a compass. You can use the dial module to indicate the north pole's direction. You'll find a couple of todo!()'s with instructions.

Compiling the starter code yields a bunch of warnings. They'll be gone once your done.

Exercise 8.3.2: Blinky compass

The channel sender - receiver example in the embassy repository shows how to spawn separate tasks, and how to use channels to communicate between tasks. Using that knowledge, make the indicator LED in the dial module blink while magnetometer measurements are taken at the same time.

As we're not using defmt in this exercise, replace the unwrap!(<expr>) macro invocations with <expr>.unwrap() calls.

Unit 8.4 - The Embassy Framework

Slides

Exercise 8.4.1: Embassy project

This exercise is a bit bigger than you're used to: we're going to do a custom project using Embassy and the micro:bit V2. Work together in teams of 2 to 3 people during this exercise.

We have set up a crate for you to work on, with a simpl blinky application. You're free to adapt anything about it, it's just meant as a starting point. The crate resides in exercises/8-embedded/4-embassy-framework/1-embassy-project. Try it out to ensure the intial setup works.

You can choose from any of below projects:

Build a snake game that uses the LED matrix as game display. You can use the buttons as input, or use the accelerometer or magnetometer. Or a combination.
Create a light banner that reads text from UART, using the virtual COM port that is exposed by the interface MCU and shows it on the LED matrix.
Create an audio recorder that reads samples from the on-board microphone and replays it using the on-board speaker. Additionally, you can show and FFT chart or a volume meter on the display
Write a driver for the capacative touch sensor
Build a button masher multiplayer game. Who is the fastest button presser? Either have it work with the two on-board buttons, or connect multiple boards together somehow. Show the score on the LED matrix.

Wrap-up

Slides

Evaluation form

Thank you for taking the time to help us improve the training!

You can find the evaluation from here