Generators and Pin

So the second difficult part that there seems to be a lot of questions about is Generators and the Pin type.

Generators

**Relevant for:**

- Understanding how the async/await syntax works
- Why we need `Pin`
- Why Rusts async model is extremely efficient

The motivation for Generators can be found in RFC#2033. It's very well written and I can recommend reading through it (it talks as much about async/await as it does about generators).

Basically, there were three main options that were discussed when Rust was desiging how the language would handle concurrency:

Stackful coroutines, better known as green threads.
Using combinators.
Stackless coroutines, better known as generators.

Stackful coroutines/green threads

I've written about green threads before. Go check out Green Threads Explained in 200 lines of Rust if you're interested.

Green threads uses the same mechanisms as an OS does by creating a thread for each task, setting up a stack and forcing the CPU to save it's state and jump from one task(thread) to another. We yield control to the scheduler which then continues running a different task.

Rust had green threads once, but they were removed before it hit 1.0. The state of execution is stored in each stack so in such a solution there would be no need for async, await, Futures or Pin. All this would be implementation details for the library.

Combinators

Futures 1.0 used combinators. If you've worked with Promises in JavaScript, you already know combinators. In Rust they look like this:


# #![allow(unused_variables)]
#fn main() {
let future = Connection::connect(conn_str).and_then(|conn| {
    conn.query("somerequest").map(|row|{
        SomeStruct::from(row)
    }).collect::<Vec<SomeStruct>>()
});

let rows: Result<Vec<SomeStruct>, SomeLibraryError> = block_on(future).unwrap();

#}

While an effective solution there are mainly two downsides I'll focus on:

The error messages produced could be extremely long and arcane
Not optimal memory usage

The reason for the higher than optimal memory usage is that this is basically a callback-based approach, where each closure stores all the data it needs for computation. This means that as we chain these, the memory required to store the needed state increases with each added step.

Stackless coroutines/generators

This is the model used in Async/Await today. It has two advantages:

It's easy to convert normal Rust code to a stackless corotuine using using async/await as keywords (it can even be done using a macro).
It uses memory very efficiently

The second point is in contrast to Futures 1.0 (well, both are efficient in practice but thats beside the point). Generators are implemented as state machines. The memory footprint of a chain of computations is only defined by the largest footprint any single step requires. That means that adding steps to a chain of computations might not require any added memory at all.

How generators work

In Nightly Rust today you can use the yield keyword. Basically using this keyword in a closure, converts it to a generator. A closure looking like this (I'm going to use the terminology that's currently in Rust):


# #![allow(unused_variables)]
#fn main() {
let a = 4;
let b = move || {
        println!("Hello");
        yield a * 2;
        println!("world!");
    };

if let GeneratorState::Yielded(n) = gen.resume() {
        println!("Got value {}", n);
    }

if let GeneratorState::Complete(()) = gen.resume() {
        ()
};
#}

Early on, before there was a consensus about the design of Pin, this compiled to something looking similar to this:

fn main() {
    let mut gen = GeneratorA::start(4);

    if let GeneratorState::Yielded(n) = gen.resume() {
        println!("Got value {}", n);
    }

    if let GeneratorState::Complete(()) = gen.resume() {
        ()
    };
}

// If you've ever wondered why the parameters are called Y and R the naming from
// the original rfc most likely holds the answer
enum GeneratorState<Y, R> {
    // originally called `CoResult`
    Yielded(Y),  // originally called `Yield(Y)`
    Complete(R), // originally called `Return(R)`
}

trait Generator {
    type Yield;
    type Return;
    fn resume(&mut self) -> GeneratorState<Self::Yield, Self::Return>;
}

enum GeneratorA {
    Enter(i32),
    Yield1(i32),
    Exit,
}

impl GeneratorA {
    fn start(a1: i32) -> Self {
        GeneratorA::Enter(a1)
    }
}

impl Generator for GeneratorA {
    type Yield = i32;
    type Return = ();
    fn resume(&mut self) -> GeneratorState<Self::Yield, Self::Return> {
        // lets us get ownership over current state
        match std::mem::replace(&mut *self, GeneratorA::Exit) {
            GeneratorA::Enter(a1) => {

          /*|---code before yield1---|*/
          /*|*/ println!("Hello"); /*|*/ 
          /*|*/ let a = a1 * 2;    /*|*/
          /*|------------------------|*/

                *self = GeneratorA::Yield1(a);
                GeneratorState::Yielded(a)
            }
            GeneratorA::Yield1(_) => {

          /*|----code after yield1----|*/
          /*|*/ println!("world!"); /*|*/ 
          /*|-------------------------|*/

                *self = GeneratorA::Exit;
                GeneratorState::Complete(())
            }
            GeneratorA::Exit => panic!("Can't advance an exited generator!"),
        }
    }
}

The yield keyword was discussed first in RFC#1823 and in RFC#1832.

|| {
    let arr: Vec<i32> = (0..a).enumerate().map((i,_) i).collect();
    for n in arr {
        yield n;
    }
    println!("The sum is: {}", arr.iter().sum());
}
|| {
    yield a * 2;
    println!("Hello!");
}

Futures Explained in 200 Lines of Rust