#worker #tower #amqp #lapin #building #task #up

lapin-tower-worker

Framework for building AMQP workers with lapin and tower

3 releases

0.1.4 Aug 28, 2024
0.1.3 Aug 26, 2024
0.1.2 Aug 26, 2024
0.1.1 Aug 21, 2024

#669 in Network programming

Download history 372/week @ 2024-08-21 210/week @ 2024-08-28

582 downloads per month

MIT license

18KB
284 lines

lapin-tower-worker

When you need a standardized way to build workers for AMQP tasks & data

Usage

The library works on a task and result model, once those are defined the worker can automate the process of pulling tasks, executing your logic and publishing results.

To standardize the way application logic is integrated we use tower and tokio as the main building blocks. The idea for this library came to me as I ended up writing retry & timeout logic & concurrency limits for workers and noticed that I was just re-implementing worse and less reusable tower middleware.

Defining a task

#[derive(Debug)]
struct MyAwesomeTask {
    value: String
}

impl AMQPTask for MyTask {
    type DecodeError = FromUtf8Error;

    type TaskResult = MyAwesomeResult;

    fn decode(data: Vec<u8>) -> Result<Self, Self::DecodeError> {
        String::from_utf8(data).map(|value| MyTask { value })
    }

    fn queue() -> &'static str {
        "awesome-tasks"
    }
}

To define a task you need to define how its decoded from a Vec<u8> and which queue its pulled from.

Also don't forget to add Debug to your task or override the debug function of the trait, these are used to create readable tracing spans to track the execution of your tasks.

Defining a result

#[derive(Debug)]
struct MyAwesomeResult {
    value: String
}

impl AMQPTaskResult for MyAwesomeResult {
    type EncodeError = Infallible;

    fn encode(self) -> Result<Vec<u8>, Self::EncodeError> {
        self.value.into_bytes()
    }

    fn publish_exchange(&self) -> String {
        "" // direct exchange
    }

    fn publish_routing_key(&self) -> String {
        "awesome-results" // through direct exchange this will end up in the queue "awesome-results"
    }
}

My tasks don't produce results...

AmqpTaskResult is implemented for (), and the publish implementation is a no-op. If you specify () as your TaskResult nothing will be published.

Creating the worker

Put your logic into a tower::Service, please refer to the tower documentation for more information. Lets use our good ol friend Pin<Box<dyn Future<Output = Result<Self::Response, Self::Error>> + Send>> to define our service future type and throw in anyhow::Error to keep errors simple.

Remember, your Service needs to be Cloneable, this allows the worker to run tasks concurrently on your service.

poll_ready is used in tower to determine if the service is ready to handle requests, I won't go into the details of storing futures in your service to poll on every invocation. If you wish for your service to for some reason stop accepting tasks and terminate you can return your Error type instead.

I recognize tower is not easy to use, however it is a good and standardized way to apply useful middleware.

#[derive(Clone)]
struct AwesomeService {
    db_conn: DbConnection, // This thing is almost always cloneable
}

impl Service<MyAwesomeTask> for AwesomeService {
    type Response = MyAwesomeResult;
    type Error = anyhow::Error;

    type Future = Pin<Box<dyn Future<Output = Result<Self::Response, Self::Error>> + Send>>;

    fn poll_ready(
        &mut self,
        _cx: &mut std::task::Context<'_>,
    ) -> std::task::Poll<Result<(), Self::Error>> {
        std::task::Poll::Ready(Ok(()))
    }

    fn call(&mut self, task: MyAwesomeTask) -> Self::Future {
        let db_conn = self.db_conn.clone();
        Box::pin(async move {
            let stuff = do_awesome_stuff(&db_conn, task.value).await?;
            Ok(MyAwesomeResult { value: stuff })
        })
    }

Lets put everything together into the worker and run it.

Get a lapin connection and create a channel, thats most of what you will be doing with the crate.

let amqp =
    lapin::Connection::connect("amqp://user:password@localhost:5672", Default::default())
        .await
        .unwrap();
let channel = amqp.create_channel().await.unwrap();

Initialize the service and hand it over to the worker, then spawn the worker onto a tokio::task::JoinSet. The worker needs a name to use for consumer tag and tracing. You can set WorkerConfig to alter some behaviour, like acking the message on a decode error or not, as I don't want to take this decision away.

let service = AwesomeService {
    db_conn: get_db_conn().await.unwrap(),
};
let worker = AMQPWorker::new(
    "awesome-worker",
    service,
    channel.clone(),
    WorkerConfig::default(),
);

Lets add a ConcurrencyLimitLayer to our worker, this will limit the number of concurrent tasks that can be spawned, otherwise the worker will pull as many tasks as are in the queue and just run them concurrently, this might be undesirable in a distributed architecture. add_layer returns a new worker instance everytime.

let worker = worker.add_layer(ConcurrencyLimitLayer::new(8));

Worker can't take too long, lets add a timeout

let worker = worker.add_layer(TimeoutLayer::new(Duration::from_secs(60*5))); // 5 minutes

Now we can spawn the worker onto a joinset.

let mut set = tokio::task::JoinSet::new();
let consume_options = BasicConsumeOptions::default();
let consume_arguments = FieldTable::default();
worker.consume_spawn(consume_options, consume_arguments, &mut set);

Dependencies

~10–22MB
~335K SLoC