What to cache when building Rust using Gitlab CI or similar

Andy Balaam from Andy Balaam's Blog

When building your project with Gitlab CI or a similar build tool, you can end up spending a lot of time watching your build repeat the same steps over and over. This is especially frustrating when it mostly consists of downloading and compiling the same things we downloaded and compiled last time.

To mitigate this, we can ask Gitlab CI to cache things that will be the same next time.

For a Rust project, the most important thing to cache is target in the local directory.

But, if you are installing tools using rustup or cargo, it will really help if you cache those too. Fortunately, Rust knows where those are by using environment variables, and these are defined in the standard Rust Docker image.

We can make sure we’re caching as much as possible by adding a section like this to .gitlab-ci.yml:

    cache:
        key: shared-cache
        paths:
            - target/
            - $CARGO_HOME/
            - $RUSTUP_HOME/

If you add this to all your jobs, they will share a single cache between them, and cache the local target directory as well as any tools installed with rustup or cargo.

Here is a full example from my Evolve SVGs project:

image: rust:latest

before_script:
    - rustup component add rustfmt
    - rustup target add wasm32-unknown-unknown
    - cargo install trunk wasm-bindgen-cli

pages:
    stage: deploy
    script:
        - echo "Publishing pages to" $CI_PAGES_URL
        - make deploy
        - mv dist public
    artifacts:
      paths:
        - public
    only:
        - main
    cache:
        key: shared-cache
        paths:
            - target/
            - $CARGO_HOME/
            - $RUSTUP_HOME/

test:
    stage: test
    script:
        - make test
    cache:
        key: shared-cache
        paths:
            - target/
            - $CARGO_HOME/
            - $RUSTUP_HOME/

Announcing I-DUNNO 1.0 and web-i-dunno

Andy Balaam from Andy Balaam's Blog

It’s hard to believe it’s already a year since the release of RFC 8771 (The Internationalized Deliberately Unreadable Network NOtation), which for me at least made me think about IP addresses in a whole new way.

So, it seems fitting for the anniversary to be able to release proper support for this standard in the Rust universe, with Rust I-DUNNO version 1.0 released. You can find it on Rust’s crates.io at crates.io/crates/i-dunno and the API documentation is at docs.rs/i-dunno.

Also, because for a standard like this to receive the wide adoption it deserves, it’s important that young people have a chance to interact with it, playing with encodings to get a real feel for what it’s like to use in practice, I’m proud to announce the I-DUNNO Creator. On that page you can enter an IP address (IPv4 or IPv6) and see it transformed immediately into a candidate I-DUNNO, with live information about the Confusion Level of the I-DUNNO, as specified in the standard. You can find the source code for the I-DUNNO Creator in the web-i-dunno repo.

The I-DUNNO Creator is built on the Rust package, making use of Rust’s highly-developed WASM support to compile the code into a form that works naturally in a web browser.

I hope that by offering both systems programmers and the young people of today and their new-fangled web sites the opportunity to create I-DUNNOs, I can contribute a little to spreading the word about deliberately unreadable notations to new audiences.

Note: the current implementation is limited to generate only I-DUNNOs with no padding bits. As specified in the standard, I-DUNNOs may end with arbitrary padding, and adding this functionality to rust-i-dunno is left as an exercise for the reader: merge requests welcome!

Announcing Rust I-DUNNO

Andy Balaam from Andy Balaam's Blog

At the ACCU Conference last week I learned about RFC 8771 The Internationalized Deliberately Unreadable Network NOtation (I-DUNNO) from Jim Hague, and thought it would be fun to knock up a Rust implementation.

The project is here: gitlab.com/andybalaam/rust-i-dunno and the docs are published at https://docs.rs/i-dunno.

It’s not done yet, but encoding an IP address as I-DUNNO appears to be working:

$ i-dunno 216.58.205.46
lYÔ®

$ i-dunno 216.58.205.46 | hexdump -C
00000000  db 81 6b 1a 2e 0a                                 |..k...|

Decoding is still to be done.

The implementation is seriously slow at the moment, so I am looking forward to improving it.

I am hoping it is reasonably correct – I based it on the existing Python I-DUNNO implementation and in the process found several potential bugs in that, and created some merge requests to fix bugs and help with testability.

Speaking of testability, I am building up a collection of test cases that could be a potential resource for other implementors, and would welcome suggestions of how this could be shared between projects. The examples so far were generated using the Python implementation, and then manually corrected where I found bugs in that, so I do not have 100% confidence that they are correct.

Anyway, have a play, and send patches and feedback!

Widely used programming languages: past, present, and future

Derek Jones from The Shape of Code

Programming languages are like pop groups in that they have followers, fans and supporters; new ones are constantly being created and some eventually become widely popular, while those that were once popular slowly fade away or mutate into something else.

Creating a language is a relatively popular activity. Science fiction and fantasy authors have been doing it since before computers existed, e.g., the Elf language Quenya devised by Tolkien, and in the computer age Star Trek’s Klingon. Some very good how-to books have been written on the subject.

As soon as computers became available, people started inventing programming languages.

What have been the major factors influencing the growth to widespread use of a new programming languages (I’m ignoring languages that become widespread within application niches)?

Cobol and Fortran became widely used because there was widespread implementation support for them across computer manufacturers, and they did not have to compete with any existing widely used languages. Various niches had one or more languages that were widely used in that niche, e.g., Algol 60 in academia.

To become widely used during the mainframe/minicomputer age, a new language first had to be ported to the major computers of the day, whose products sometimes supported multiple, incompatible operating systems. No new languages became widely used, in the sense of across computer vendors. Some new languages were widely used by developers, because they were available on IBM computers; for several decades a large percentage of developers used IBM computers. Based on job adverts, RPG was widely used, but PL/1 not so. The use of RPG declined with the decline of IBM.

The introduction of microcomputers (originally 8-bit, then 16, then 32, and finally 64-bit) opened up an opportunity for new languages to become widely used in that niche (which would eventually grow to be the primary computing platform of its day). This opportunity occurred because compiler vendors for the major languages of the day did not want to cannibalize their existing market (i.e., selling compilers for a lot more than the price of a microcomputer) by selling a much lower priced product on microcomputers.

BASIC became available on practically all microcomputers, or rather some dialect of BASIC that was incompatible with all the other dialects. The availability of BASIC on a vendor’s computer promoted sales of the hardware, and it was not worthwhile for the major vendors to create a version of BASIC that reduced portability costs; the profit was in games.

The dominance of the Microsoft/Intel partnership removed the high cost of porting to lots of platforms (by driving them out of business), but created a major new obstacle to the wide adoption of new languages: Developer choice. There had always been lots of new languages floating around, but people only got to see the subset that were available on the particular hardware they targeted. Once the cpu/OS (essentially) became a monoculture most new languages had to compete for developer attention in one ecosystem.

Pascal was in widespread use for a few years on micros (in the form of Turbo Pascal) and university computers (the source of Wirth’s ETH compiler was freely available for porting), but eventually C won developer mindshare and became the most widely used language. In the early 1990s C++ compiler sales took off, but many developers were writing C with a few C++ constructs scattered about the code (e.g., use of new, rather than malloc/free).

Next, the Internet took off, and opened up an opportunity for new languages to become dominant. This opportunity occurred because Internet related software was being made freely available, and established compiler vendors were not interested in making their products freely available.

There were people willing to invest in creating a good-enough implementation of the language they had invented, and giving it away for free. Luck, plus being in the right place at the right time resulted in PHP and Javascript becoming widely used. Network effects prevent any other language becoming widely used. Compatible dialects of PHP and Javascript may migrate widespread usage to quite different languages over time, e.g., Facebook’s Hack.

Java rode to popularity on the coat-tails of the Internet, and when it looked like security issues would reduce it to niche status, it became the vendor supported language for one of the major smart-phone OSs.

Next, smart-phones took off, but the availability of Open Source compilers closed the opportunity window for new languages to become dominant through lack of interest from existing compiler vendors. Smart-phone vendors wanted to quickly attract developers, which meant throwing their weight behind a language that many developers were already familiar with; Apple went with Objective-C (which evolved to Swift), Google with Java (which evolved to Kotlin, because of the Oracle lawsuit).

Where does Python fit in this grand scheme? I don’t yet have an answer, or is my world-view wrong to treat Python usage as being as widespread as C/C++/Java?

New programming languages continue to be implemented; I don’t see this ever stopping. Most don’t attract more users than their implementer, but a few become fashionable amongst the young, who are always looking to attach themselves to something new and shiny.

Will a new programming language ever again become widely used?

Like human languages, programming languages experience strong networking effects. Widely used languages continue to be widely used because many companies depend on code written in it, and many developers who can use it can obtain jobs; what company wants to risk using a new language only to find they cannot hire staff who know it, and there are not many people willing to invest in becoming fluent in a language with no immediate job prospects.

Today’s widely used programmings languages succeeded in a niche that eventually grew larger than all the other computing ecosystems. The Internet and smart-phones are used by everybody on the planet, there are no bigger ecosystems to provide new languages with a possible route to widespread use. To be widely used a language first has to become fashionable, but from now on, new programming languages that don’t evolve from (i.e., be compatible with) current widely used languages are very unlikely to migrate from fashionable to widely used.

It has always been possible for a proficient developer to dedicate a year+ of effort to create a new language implementation. Adding the polish need to make it production ready used to take much longer, but these days tool chains such as LLVM supply a lot of the heavy lifting. The problem for almost all language creators/implementers is community building; they are terrible at dealing with other developers.

It’s no surprise that nearly all the new languages that become fashionable originate with language creators who work for a company that happens to feel a need for a new language. Examples include:

  • Go created by Google for internal use, and attracted an outside fan base. Company languages are not new, with IBM’s PL/1 being the poster child (or is there a more modern poster child). At the moment Go is a trendy language, and this feeds a supply of young developers willing to invest in learning it. Once the trendiness wears off, Google will start to have problems recruiting developers, the reason: Being labelled as a Go developer limits job prospects when few other companies use the language. Talk to a manager who has tried to recruit developers to work on applications written in Fortran, Pascal and other once-widely used languages (and even wannabe widely used languages, such as Ada),
  • Rust a vanity project from Mozilla, which they have now abandoned. Did Rust become fashionable because it arrived at the right time to become the not-Google language? I await a PhD thesis on the topic of the rise and fall of Rust,
  • Microsoft’s C# ceased being trendy some years ago. These days I don’t have much contact with developers working in the Microsoft ecosystem, so I don’t know anything about the state of the C# job market.

Every now and again a language creator has the social skills needed to start an active community. Zig caught my attention when I read that its creator, Andrew Kelley, had quit his job to work full-time on Zig. Two and a-half years later Zig has its own track at FOSEM’21.

Will Zig become the next fashionable language, as Rust/Go popularity fades? I’m rooting for Zig because of its name, there are relatively few languages whose name starts with Z; the start of the alphabet is over-represented with language names. It would be foolish to root for a language because of a belief that it has magical properties (e.g., powerful, readable, maintainable), but the young are foolish.

Limiting the number of open sockets in a tokio-based TCP listener

Andy Balaam from Andy Balaam's Blog

I learned quite a bit today about how to think about concurrency in Rust. I was trying to use a Semaphore to limit how many open sockets my TCP listener allowed, and I had real trouble making it work. It either didn’t actually work, allowing any number of clients to connect, or the compiler told me I couldn’t do what I wanted to do, because the lifetime of my Semaphore was not 'static. Here’s the journey I took towards working code that I think is correct (feedback welcome).

Motivation

In the tokio tutorial there is a short section entitled “Backpressure and bounded channels” (partway down the Channels page). It contains this statement:

…take care to ensure total amount of concurrency is bounded. For example, when writing a TCP accept loop, ensure that the total number of open sockets is bounded.

Obviously, when I started work on a TCP accept loop, I wanted to follow this advice.

Like many things in my journey with Rust, it was harder than I expected, and eventually enlightening.

The code

Here is a short Rust program that listens on a TCP port and accepts incoming connections.

Cargo.toml:

[package]
name = "tcp-listener-example"
version = "1.0.0"
edition = "2018"
include = ["src/"]

[dependencies]
tokio = { version = ">=1.0.1", features = ["full"] }

src/main.rs:

use tokio::io::AsyncReadExt;
use tokio::net::TcpListener;

#[tokio::main]
async fn main() {
    let listener = TcpListener::bind("0.0.0.0:8080").await.unwrap();

    loop {
        let (mut tcp_stream, _) = listener.accept().await.unwrap();
        tokio::spawn(async move {
            let mut buf: [u8; 1024] = [0; 1024];
            loop {
                let n = tcp_stream.read(&mut buf).await.unwrap();
                if n == 0 {
                    return;
                }
                print!("{}", String::from_utf8_lossy(&buf[0..n]));
            }
        });
    }
}

This program listens on port 8080, and every time a client connects, it spawns an asynchronous task to deal with it.

If I run it with:

cargo run

It starts, and I can connect to it from multiple other processes like this:

telnet 0.0.0.0 8080

Anything I type into the telnet terminal window gets printed out in the terminal where I ran cargo run. The program works: it listens on TCP port 8080 and prints out all the messages it receives.

So what’s the problem?

The problem is that this program can be overwhelmed: if lots of processes connect to it, it will accept all the connections, and eventually run out of sockets. This might prevent other things working right on the computer, or it might crash our program, or something else. We need some kind of sensible limit, as the tokio tutorial mentions.

So how do we limit the number of people allowed to connect at the same time?

Just use a semaphore, dummy

A semaphore does exactly what we need here – it keeps a count of how many people are doing something, and prevents that number getting too big. So all we need to do is restrict the number of clients that we allow to connect using a semaphore.

Here was my first attempt:

use tokio::io::AsyncReadExt;
use tokio::net::TcpListener;
use tokio::sync::Semaphore;

#[tokio::main]
async fn main() {
    let listener = TcpListener::bind("0.0.0.0:8080").await.unwrap();
    let sem = Semaphore::new(2);

    loop {
        let (mut tcp_stream, _) = listener.accept().await.unwrap();
        // Don't copy this code: it doesn't work
        let aq = sem.try_acquire();
        if let Ok(_guard) = aq {
            tokio::spawn(async move {
                let mut buf: [u8; 1024] = [0; 1024];
                loop {
                    let n = tcp_stream.read(&mut buf).await.unwrap();
                    if n == 0 {
                        return;
                    }
                    print!("{}", String::from_utf8_lossy(&buf[0..n]));
                }
            });
        } else {
            println!("Rejecting client: too many open sockets");
        }
    }
}

This compiles fine, but it doesn’t do anything! Even though we called Semaphore::new with an argument of 2, intending to allow only 2 clients to connect, in fact I can still connect more times than that. It looks like our code changes had no effect at all.

What we were hoping to happen was that every time a client connected, we created _guard, which is a SemaphoreGuard, that occupies one of the slots in the semaphore. We were expecting that guard to live until the client disconnects, at which point the slot will be released.

Why doesn’t it work? It’s easy to understand when you think about what tokio::spawn does. It creates a task and asks for it to be executed in the future, but it doesn’t actually run it. So tokio::spawn returns immediately, and _guard is dropped, before the code that handles the request is executed. So, obviously, our change doesn’t actually restrict how many requests are being handled because the semaphore slot is freed up before the request is processed.

Just hold the guard for longer, dummy

So, let’s hold on to the SemaphoreGuard for longer:

use tokio::io::AsyncReadExt;
use tokio::net::TcpListener;
use tokio::sync::Semaphore;

#[tokio::main]
async fn main() {
    let listener = TcpListener::bind("0.0.0.0:8080").await.unwrap();
    let sem = Semaphore::new(2);

    loop {
        let (mut tcp_stream, _) = listener.accept().await.unwrap();
        let aq = sem.try_acquire();
        if let Ok(guard) = aq {
            tokio::spawn(async move {
                let mut buf: [u8; 1024] = [0; 1024];
                loop {
                    let n = tcp_stream.read(&mut buf).await.unwrap();
                    if n == 0 {
                        drop(guard);
                        return;
                    }
                    print!("{}", String::from_utf8_lossy(&buf[0..n]));
                }
            });
        } else {
            println!("Rejecting client: too many open sockets");
        }
    }
}

The idea is to pass the SemaphoreGuard object into the code that actually deals with the client request. The way I’ve attempted that is by referring to guard somewhere within the async move closure. What I’ve actually done is tell it to drop guard when we are finished with the request, but actually any mention of that variable within the closure would have been enough to tell the compiler we want to move it in, and only drop it when we are done.

It all sounds reasonable, but actually this code doesn’t compile. Here’s the error I get:

error[E0597]: `sem` does not live long enough
  --> src/main.rs:12:18
   |
12 |         let aq = sem.try_acquire();
   |                  ^^^--------------
   |                  |
   |                  borrowed value does not live long enough
   |                  argument requires that `sem` is borrowed for `'static`
...
29 | }
   | - `sem` dropped here while still borrowed

What the compiler is saying is that our SemaphoreGuard is referring to sem (the Semaphore object), but that the guard might live longer than the semaphore.

Why? Surely sem is held within a scope that includes the whole of the client-handling code, so it should live long enough?

No. Actually, the async move closure that we are passing to tokio::spawn is being added to a list of tasks to run in the future, so it could live much longer. The fact that we are inside an infinite loop confused me further here, but the principle still remains: whenever we make a closure like this and pass something into it, the closure must own it, or if we are borrowing it, it must live forever (which is what a 'static lifetime means).

The code above passes ownership of guard to the closure, but guard itself is referring to (borrowing) sem. This is why the compiler says that “sem is borrowed for 'static“.

Wrong things I tried

Because I didn’t understand what I was doing, I tried various other things like making sem an Arc, making guard an Arc, creating guard inside the closure, and even trying to make sem actually have 'static storage by making it a constant. (That last one didn’t work because only very simple types like numbers and strings can be constants.)

Solution: Share the Semaphore in an Arc

After what felt like too much thrashing around, I found what I think is the right answer:

use std::sync::Arc;
use tokio::io::AsyncReadExt;
use tokio::net::TcpListener;
use tokio::sync::Semaphore;

#[tokio::main]
async fn main() {
    let listener = TcpListener::bind("0.0.0.0:8080").await.unwrap();
    let sem = Arc::new(Semaphore::new(2));

    loop {
        let (mut tcp_stream, _) = listener.accept().await.unwrap();
        let sem_clone = Arc::clone(&sem);
        tokio::spawn(async move {
            let aq = sem_clone.try_acquire();
            if let Ok(_guard) = aq {
                let mut buf: [u8; 1024] = [0; 1024];
                loop {
                    let n = tcp_stream.read(&mut buf).await.unwrap();
                    if n == 0 {
                        return;
                    }
                    print!("{}", String::from_utf8_lossy(&buf[0..n]));
                }
            } else {
                println!("Rejecting client: too many open sockets");
            }
        });
    }
}

This code:

  • Creates a Semaphore and stores it inside an Arc, which is a reference-counting pointer that can be shared between tasks. This means it will live as long as someone holds a reference to it.
  • Clones the Arc so we have a copy that can be safely moved into the async move closure. We can’t move sem in to the closure because it’s going to get used again the next time around the loop. We can move sem_clone in to the closure because it’s not used anywhere else. sem and sem_clone both refer to the same Semaphore object, so they agree on the count of clients that are connected, but they are different Arc instances, so one can be moved into the closure.
  • Only aquires the SemaphoreGuard once we’re inside the closure. This way we’re not doing something difficult like borrowing a reference to something that lives outside the closure. Instead, we’re borrowing a reference via sem_clone, which is owned by the closure which we are inside, so we know it will live long enough.

It actually works! After two clients are connected, listener.accept actually opens a socket to any new client, but because we return almost immediately from the closure, we only hold it open very briefly before dropping it. This seemed preferable to refusing to open it at all, which I thought would probably leave clients hanging, waiting for a connection that might never come.

Lifetimes are cool, and tricky

Once again, I have learned a lot about what my code is really doing from the Rust compiler. I find this stuff really confusing, but hopefully by writing down my understanding in this post I have helped my current and future selves, and maybe even you, be clearer about how to share a semaphore between multiple asynchronous tasks.

It’s really fun and empowering to write code that I am reasonably confident is correct, and also works. The sense that “the compiler has my back” is strong, and I like it.

Shutdown order consistency: how Rust helps

Andy Balaam from Andy Balaam's Blog

Some Java code with bugs

Here’s my main method (in Java). Can you guess the bug?

Db db = new Db();
Monitoring monitoring = new Monitoring();
Monitoring mon2 = new Monitoring();
Billing billing = new Billing(db, monitoring);
monitoring.setDb(db);

runMainLoop(billing, mon2);

db.stop();
billing.stop();
monitoring.stop();

If you would like to hunt down the 2 bugs manually, try reading the full code here: ShutdownOrder.java

But maybe you have an idea already? Maybe you’ve seen code like this before? If you have, you probably have an instinct that there’s some kind of bug, even if you can’t say for sure what it is. Code like this almost always has bugs!

This code compiles fine, but it contains two bugs.

First, we forgot to setDb() on mon2. This causes a NullPointerException, because Monitoring expects always to have a working Db.

Second, and in general harder to spot, we shut down our services in the wrong order. It turns out that Monitoring uses its Db during shutdown, so we get an exception. Even worse, if some other code needed to run after monitoring.stop(), it won’t, because the exception prevents us getting any further.

Of course, this is toy code, but this kind of problem is common (and much harder to spot) in real-life code. In fact, my team dealt with a similar bug this week.

It’s fundamentally hard to figure out your shutdown order. It’s complicated further if classes have start() methods too, which I have seen in lots of Java code.

Given that this is just a hard problem, maybe there’s no point looking for tools to make it easier?

Some Rust code without those bugs

Let’s try writing this code in Rust. Here’s the main method:

let db = Db::new();
let monitoring = Monitoring::new(&db);
let mon2 = Monitoring::new(&db);
let billing = Billing::new(&db, &monitoring);

run_main_loop(&billing, &mon2);

// drop() is called automatically on all objects here

Here’s the full code: shutdown_order.rs

This code shuts down all the services automatically at the end, and any mistakes we make in the order are compile errors, not things we find later when our code is running.

The code to shut down each service looks like this:

impl Drop for Monitoring<'_> {
    fn drop(&mut self) {
        // [Disconnect from monitoring API]
        self.db.add_record("MonitorShutDown");
    }
}

This is us implementing the Drop trait for the struct Monitoring (traits are a bit like Java Interfaces). The Drop trait is special: it indicates what to do when an instance of this struct is dropped. In Rust, this is guaranteed to happen when the instance goes out of scope, which is why our comment at the end of the main method sounds so confident.

Furthermore, Rust’s compiler shuts down everything in the reverse order in which it was created, and guarantees that nothing gets used after it has been dropped.

Rust’s lovely world gives us two relevant treats: no unexpected nulls, and lifetimes.

Treat number 1: no unexpected nulls

First, in Rust, like in other modern languages like Kotlin, we have to be explicit about items that could be missing. In our example, we were able to re-arrange the code so that db can never be missing (or null), and the compiler encouraged us to do so. If we really needed it to be missing some of the time, we could have used the Option type, and the compiler would have forced us to handle the case when it was missing, instead of unexpectedly getting a NullPointerException like we did in Java. (In fact, if we’d structured our code to use final in as many places as possible, we could have been encouraged towards basically the same solution in Java too.)

Treat number 2: lifetimes

Second, if you look a bit more closely at the full code of shutdown_order.rs you’ll see lots of confusing-looking annotations like <'a> and &'a:

struct Monitoring<'a> {
    db: &'a Db,
}

The approximate meaning of those annotations is: a Monitoring holds a reference to a Db, and that Db must last longer than the Monitoring.

This “lasts longer than” wording is what Rust Lifetimes are for. Lifetimes are a way of saying how long something lasts.

Lifetimes are really confusing when you start with Rust, and have caused me a lot of pain. Code like this is where they are both most painful and most helpful. As I mentioned earlier, the problem of shutdown order is fundamentally hard. Rust gives you that pain at the beginning, and until you understand what’s going on, the pain is very confusing and acute. But, once your code compiles, it is correct, at least as far as problems like this are concerned.

I love the sense of security it gives me to write Rust code and know the compiler has checked my code for this kind of problem, meaning it can’t crop up at 3am on Christmas Day…

Final note/caveat

This Rust code is probably over-simplified, because all the references are immutable (you can’t change the objects they point to). In practice, we may well have mutable references, and if we do we’re going have to deal with the further difficulty that Rust won’t allow two different objects to hold references to an object if any of those references are mutable. So it would object to Billing and Monitoring using the Db object at the same time. We’d need to make it immutable (as we have here), or find a different way of structuring the code: for example, we could hold the Db instance only within the run_main_loop code, and pass it in temporarily to the Billing and Monitoring objects when we called their methods. A large part of the art, fun and pain of learning Rust is finding new patterns for your code that do what you need to do and also keep the compiler happy. When you manage it, you get amazing benefits!

Edge computing providers

Andy Balaam from Andy Balaam&#039;s Blog

I’m looking into Edge computing at work. By Edge computing I mean running WASM programs in lots and lots of smallish computers in places near to actual people (rather than in huge cloud data centres). I think it’s cool because I love Rust, and Rust is the leading language to compile to WASM.

Here are some companies providing Edge computing services:

  • Fastly – good links with WASM community (hired Mozilla devs), and early adopters – custom WASM engine wasmtime.
  • Cloudflare – huge, and early adopters – WASM engine is Google V8.
  • AWS Lambda@Edge – docs are light on detail, but it looks like a real offering, probably.

Also-rans:

Who did I miss?

short – command line tool to truncate lines to fit in the terminal

Andy Balaam from Andy Balaam&#039;s Blog

Sometimes I run grep commands that search files with hugely-long lines. If those lines match, they are printed out and spam my terminal with huge amounts of information, that I probably don’t need.

I couldn’t find a tool that limits the line-length of its output, so I wrote a tiny one.

It’s called short.

You use it like this (my typical usage):

grep foo myfile.txt | short

Or specify the column width like this:

short -w 5 myfile.txt

It’s written in Rust. Feel free to add features, fix bugs and package it for your operating system/distribution!

Creating a tiny Docker image of a Rust project

Andy Balaam from Andy Balaam&#039;s Blog

I am building a toy project in Rust to help me learn how to deploy things in AWS. I’m considering using Elastic Beanstalk (AWS’s platform-as-a-service) and also Kubernetes. Both of these support deploying via Docker containers, so I am learning how to package a Rust executable as a Docker image.

My program is a small web site that uses Redis as a back end database. It consists of some Rust code and a couple of static files.

Because Rust has good support for building executables with very few dependencies, we can actually build a Docker image with almost nothing in it, except my program and the static files.

Thanks to Alexander Brand’s blog post How to Package Rust Applications Into Minimal Docker Containers I was able to build a Docker image that:

  1. Is very small
  2. Does not take too long to build

The main concern for making the build faster is that we don’t download and build all the dependencies every time. To achieve that we make sure there is a layer in the Docker build process that includes all the dependencies being built, and is not re-built when we only change our source code.

Here is the Dockerfile I ended up with:

# 1: Build the exe
FROM rust:1.42 as builder
WORKDIR /usr/src
Creating a tiny Docker image of a Rust project
# 1a: Prepare for static linking
RUN apt-get update && \
    apt-get dist-upgrade -y && \
    apt-get install -y musl-tools && \
    rustup target add x86_64-unknown-linux-musl

# 1b: Download and compile Rust dependencies (and store as a separate Docker layer)
RUN USER=root cargo new myprogram
WORKDIR /usr/src/myprogram
COPY Cargo.toml Cargo.lock ./
RUN cargo install --target x86_64-unknown-linux-musl --path .

# 1c: Build the exe using the actual source code
COPY src ./src
RUN cargo install --target x86_64-unknown-linux-musl --path .

# 2: Copy the exe and extra files ("static") to an empty Docker image
FROM scratch
COPY --from=builder /usr/local/cargo/bin/myprogram .
COPY static .
USER 1000
CMD ["./myprogram"]

The FROM rust:1.42 as build line uses the newish Docker feature multi-stage builds – we create one Docker image (“builder”) just to build the code, and then copy the resulting executable into the final Docker image.

In order to allow us to build a stand-alone executable that does not depend on the standard libraries in the operating system, we use the “musl” target, which is designed to statically linked.

The final Docker image produced is pretty much the same size as the release build of myprogram, and the build is fast, so long as I don’t change the dependencies in Cargo.toml.

A couple more tips to make the build faster:

1. Use a .dockerignore file. Here is mine:

/target/
/.git/

2. Use Docker BuildKit, by running the build like this:

DOCKER_BUILDKIT=1 docker build  .

Struggling with Rust to figure out the right types for a function signature

Andy Balaam from Andy Balaam&#039;s Blog

I am loving writing code in Rust. So many things about the language and its ecosystem feel so right*.

* For example: ownership of objects, expressive type system, compile to native, offline API docs, immutability, high quality libraries.

One of the things I like about it is that I don’t feel like I need to use an IDE, so I can happily code in Vim with no clever plugins.

One thing an IDE might give me would be an “extract function” refactoring. In most languages I am happy to do that manually, because I can let the compile errors guide me on what my function should look like.

However, in Rust I sometimes find it’s hard to find the right signature for a function I want to extract, and I am struggling to persuade the compiler to help me.

Here is an example from my new listsync project, in listsync-client-rust.rs:

use actix_web::{middleware, App, HttpServer};
use listsync_client_rust;
// ...
#[actix_rt::main]
async fn main() -> std::io::Result<()> {
//...
    HttpServer::new(|| {
        App::new()
            .wrap(listsync_client_rust::cookie_session::new_session())
            .wrap(middleware::Logger::default())
            .configure(listsync_client_rust::config)
    })
//...

I would like to extract the code highlighted above, the creation of an App, into a separate function, like this:

fn new_app() -> ??? {
    App::new()
        .wrap(listsync_client_rust::cookie_session::new_session())
        .wrap(middleware::Logger::default())
        .configure(listsync_client_rust::config)
}
//...
    HttpServer::new(|| {
        new_app()
    })

Simple, right? To find out what the return type of the function should be, I can just make a bad guess, and get the compiler to tell me what I did wrong. In this case, I will guess by changing the question marks above into i32, and run cargo test. I get quite a few errors, one of which is:

error[E0277]: the trait bound `i32: actix_service::IntoServiceFactory<_>` is not satisfied
  --> src/bin/listsync-client-rust.rs:27:5
   |
27 | /     HttpServer::new(|| {
28 | |         new_app()
29 | |     })
   | |______^ the trait `actix_service::IntoServiceFactory<_>` is not implemented for `i32`
   |
   = note: required by `actix_web::server::HttpServer`

So the first problem I see is that the error message I am seeing is about the later code, and there are no errors about my new function.

I obviously went a little too fast. Let’s change the HttpServer::new code back to how it was before, and only make a new function new_app. Now I get an error that should help me:

error[E0308]: mismatched types
  --> src/bin/listsync-client-rust.rs:12:5
   |
11 |   fn new_app() -> i32 {
   |                   --- expected `i32` because of return type
12 | /     App::new()
13 | |         .wrap(listsync_client_rust::cookie_session::new_session())
14 | |         .wrap(middleware::Logger::default())
15 | |         .configure(listsync_client_rust::config)
   | |________________________________________________^ expected i32, found struct `actix_web::app::App`
   |
   = note: expected type `i32`
              found type `actix_web::app::App<impl actix_service::ServiceFactory, actix_web::middleware::logger::StreamLog<actix_http::body::Body>>`

So the compiler has told us what type we are returning! Let’s copy that into the type signature of the function:

use actix_service::ServiceFactory;
use actix_http::body::Body;
// ...
fn new_app() -> App<impl ServiceFactory, middleware::logger::StreamLog<Body>> {
// ...

The first error I get from the compiler is a distraction:

error[E0432]: unresolved import `actix_service`
 --> src/bin/listsync-client-rust.rs:1:5
  |
1 | use actix_service::ServiceFactory;
  |     ^^^^^^^^^^^^^ use of undeclared type or module `actix_service`

I can fix it by adding actix-service = "1.0.5" to Cargo.toml. (I found the version by looking in Cargo.lock, since this dependency was already implicitly used – I just need to make it explicit if I am going to use it directly.)

Once I do that I get the next error:

error[E0603]: module `logger` is private
  --> src/bin/listsync-client-rust.rs:13:54
   |
13 | fn new_app() -> App<impl ServiceFactory, middleware::logger::StreamLog<Body>> {
   |                                                      ^^^^^^

This leaves me a bit stuck: I can’t use StreamLog because it’s in a private module.

More importantly, it makes the point that I don’t actually want to be as specific as I am being: I don’t care what the exact type parameters for App are – I just want to return an App of some kind and have the compiler fill in the blanks. Ideally, if I change the body of new_app later, for example to add another wrap call that changes the type of App we are returning, I’d like to leave the return type the same and have it just work.

With that in mind, I took at look at the type that HttpServer::new takes in. Here is HttpServer:

impl<F, I, S, B> HttpServer<F, I, S, B> where
    F: Fn() -> I + Send + Clone + 'static,
    I: IntoServiceFactory<S>,
    S: ServiceFactory<Config = AppConfig, Request = Request>,
    S::Error: Into<Error> + 'static,
    S::InitError: Debug,
    S::Response: Into<Response<B>> + 'static,
    <S::Service as Service>::Future: 'static,
    B: MessageBody + 'static, 

and HttpServer::new looks like:

pub fn new(factory: F) -> Self

So it takes in a function which actually makes the App, and the type of that function is F, which is a Fn which returns a I + Send + Clone + 'static. From the declaration of HttpServer we can see that the type of I depends on S and B, which have quite complex types. Let’s paste the whole thing in:

use actix_http::{Error, Request, Response};
use actix_service::IntoServiceFactory;
use actix_web::body::MessageBody;
use actix_web::dev::{AppConfig, Service};
use core::fmt::Debug;
// ...
fn new_app<I, S, B>() -> I
where
    I: IntoServiceFactory<S> + Send + Clone + 'static,
    S: ServiceFactory<Config = AppConfig, Request = Request>,
    S::Error: Into<Error> + 'static,
    S::InitError: Debug,
    S::Response: Into<Response<B>> + 'static,
    <S::Service as Service>::Future: 'static,
    B: MessageBody + 'static,
{
    App::new()
        .wrap(listsync_client_rust::cookie_session::new_session())
        .wrap(middleware::Logger::default())
        .configure(listsync_client_rust::config)
}

Note that I had to modify I to include the extra requirements on the return type of F from the definition of HttpServer. (I think I did the right thing, but I’m not sure. If I just remove the + Send + Clone + 'static it seems to behave similarly.)

Now I get this error from the compiler:

error[E0308]: mismatched types
  --> src/bin/listsync-client-rust.rs:27:5
   |
17 |   fn new_app<I, S, B>() -> I
   |                            - expected `I` because of return type
...
27 | /     App::new()
28 | |         .wrap(listsync_client_rust::cookie_session::new_session())
29 | |         .wrap(middleware::Logger::default())
30 | |         .configure(listsync_client_rust::config)
   | |________________________________________________^ expected type parameter, found struct `actix_web::app::App`
   |
   = note: expected type `I`
              found type `actix_web::app::App<impl actix_service::ServiceFactory, actix_web::middleware::logger::StreamLog<actix_http::body::Body>>`
   = help: type parameters must be constrained to match other types
   = note: for more information, visit https://doc.rust-lang.org/book/ch10-02-traits.html#traits-as-parameters

The compiler really tries to help here, suggesting I read a chapter of the Rust Book, but even after reading it I could not figure out how to do what I am trying to do.

Can anyone help me?

Wouldn’t it be amazing if there were some way the compiler could give me easier-to-understand help to figure this out?