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<ol class="chapter"><li><a href="0_0_introduction.html"><strong aria-hidden="true">1.</strong> Introduction</a></li><li><a href="0_1_background_information.html"><strong aria-hidden="true">2.</strong> Some background information</a></li><li><ol class="section"><li><a href="0_1_1_trait_objects.html"><strong aria-hidden="true">2.1.</strong> Trait objects and fat pointers</a></li><li><a href="0_1_2_generators_pin.html" class="active"><strong aria-hidden="true">2.2.</strong> Generators and Pin</a></li></ol></li><li><a href="0_2_naive_implementation.html"><strong aria-hidden="true">3.</strong> Naive example</a></li><li><a href="0_3_proper_waker.html"><strong aria-hidden="true">4.</strong> Proper Waker</a></li><li><a href="0_4_proper_future.html"><strong aria-hidden="true">5.</strong> Proper Future</a></li><li><a href="0_5_async_wait.html"><strong aria-hidden="true">6.</strong> Supporting async/await</a></li><li><a href="0_6_concurrent_futures.html"><strong aria-hidden="true">7.</strong> Bonus: concurrent futures</a></li></ol>
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<h1 class="menu-title">Futures Explained in 200 Lines of Rust</h1>
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<main>
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<h1><a class="header" href="#generators-and-pin" id="generators-and-pin">Generators and Pin</a></h1>
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<p>So the second difficult part that there seems to be a lot of questions about
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is Generators and the <code>Pin</code> type.</p>
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<h2><a class="header" href="#generators" id="generators">Generators</a></h2>
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<pre><code>**Relevant for:**
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- Understanding how the async/await syntax works
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- Why we need `Pin`
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- Why Rusts async model is extremely efficient
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</code></pre>
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<p>The motivation for <code>Generators</code> can be found in <a href="https://github.com/rust-lang/rfcs/blob/master/text/2033-experimental-coroutines.md">RFC#2033</a>. It's very
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well written and I can recommend reading through it (it talks as much about
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async/await as it does about generators).</p>
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<p>Basically, there were three main options that were discussed when Rust was
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desiging how the language would handle concurrency:</p>
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<ol>
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<li>Stackful coroutines, better known as green threads.</li>
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<li>Using combinators.</li>
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<li>Stackless coroutines, better known as generators.</li>
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</ol>
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<h3><a class="header" href="#stackful-coroutinesgreen-threads" id="stackful-coroutinesgreen-threads">Stackful coroutines/green threads</a></h3>
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<p>I've written about green threads before. Go check out
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<a href="https://cfsamson.gitbook.io/green-threads-explained-in-200-lines-of-rust/">Green Threads Explained in 200 lines of Rust</a> if you're interested.</p>
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<p>Green threads uses the same mechanisms as an OS does by creating a thread for
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each task, setting up a stack and forcing the CPU to save it's state and jump
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from one task(thread) to another. We yield control to the scheduler which then
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continues running a different task.</p>
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<p>Rust had green threads once, but they were removed before it hit 1.0. The state
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of execution is stored in each stack so in such a solution there would be no need
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for <code>async</code>, <code>await</code>, <code>Futures</code> or <code>Pin</code>. All this would be implementation
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details for the library.</p>
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<h3><a class="header" href="#combinators" id="combinators">Combinators</a></h3>
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<p><code>Futures 1.0</code> used combinators. If you've worked with <code>Promises</code> in JavaScript,
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you already know combinators. In Rust they look like this:</p>
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<pre><pre class="playpen"><code class="language-rust">
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# #![allow(unused_variables)]
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#fn main() {
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let future = Connection::connect(conn_str).and_then(|conn| {
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conn.query("somerequest").map(|row|{
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SomeStruct::from(row)
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}).collect::<Vec<SomeStruct>>()
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});
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let rows: Result<Vec<SomeStruct>, SomeLibraryError> = block_on(future).unwrap();
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#}</code></pre></pre>
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<p>While an effective solution there are mainly two downsides I'll focus on:</p>
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<ol>
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<li>The error messages produced could be extremely long and arcane</li>
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<li>Not optimal memory usage</li>
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</ol>
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<p>The reason for the higher than optimal memory usage is that this is basically
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a callback-based approach, where each closure stores all the data it needs
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for computation. This means that as we chain these, the memory required to store
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the needed state increases with each added step.</p>
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<h3><a class="header" href="#stackless-coroutinesgenerators" id="stackless-coroutinesgenerators">Stackless coroutines/generators</a></h3>
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<p>This is the model used in Async/Await today. It has two advantages:</p>
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<ol>
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<li>It's easy to convert normal Rust code to a stackless corotuine using using
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async/await as keywords (it can even be done using a macro).</li>
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<li>It uses memory very efficiently</li>
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</ol>
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<p>The second point is in contrast to <code>Futures 1.0</code> (well, both are efficient in
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practice but thats beside the point). Generators are implemented as state
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machines. The memory footprint of a chain of computations is only defined by
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the largest footprint any single step requires. That means that adding steps to
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a chain of computations might not require any added memory at all.</p>
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<h2><a class="header" href="#how-generators-work" id="how-generators-work">How generators work</a></h2>
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<p>In Nightly Rust today you can use the <code>yield</code> keyword. Basically using this
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keyword in a closure, converts it to a generator. A closure looking like this
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(I'm going to use the terminology that's currently in Rust):</p>
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<pre><pre class="playpen"><code class="language-rust">
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# #![allow(unused_variables)]
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#fn main() {
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let a = 4;
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let b = move || {
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println!("Hello");
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yield a * 2;
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println!("world!");
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};
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if let GeneratorState::Yielded(n) = gen.resume() {
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println!("Got value {}", n);
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}
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if let GeneratorState::Complete(()) = gen.resume() {
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()
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};
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#}</code></pre></pre>
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<p>Early on, before there was a consensus about the design of <code>Pin</code>, this
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compiled to something looking similar to this:</p>
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<pre><pre class="playpen"><code class="language-rust">fn main() {
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let mut gen = GeneratorA::start(4);
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if let GeneratorState::Yielded(n) = gen.resume() {
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println!("Got value {}", n);
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}
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if let GeneratorState::Complete(()) = gen.resume() {
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()
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};
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}
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// If you've ever wondered why the parameters are called Y and R the naming from
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// the original rfc most likely holds the answer
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enum GeneratorState<Y, R> {
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// originally called `CoResult`
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Yielded(Y), // originally called `Yield(Y)`
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Complete(R), // originally called `Return(R)`
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}
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trait Generator {
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type Yield;
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type Return;
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fn resume(&mut self) -> GeneratorState<Self::Yield, Self::Return>;
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}
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enum GeneratorA {
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Enter(i32),
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Yield1(i32),
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Exit,
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}
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impl GeneratorA {
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fn start(a1: i32) -> Self {
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GeneratorA::Enter(a1)
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}
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}
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impl Generator for GeneratorA {
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type Yield = i32;
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type Return = ();
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fn resume(&mut self) -> GeneratorState<Self::Yield, Self::Return> {
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// lets us get ownership over current state
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match std::mem::replace(&mut *self, GeneratorA::Exit) {
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GeneratorA::Enter(a1) => {
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/*|---code before yield1---|*/
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/*|*/ println!("Hello"); /*|*/
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/*|*/ let a = a1 * 2; /*|*/
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/*|------------------------|*/
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*self = GeneratorA::Yield1(a);
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GeneratorState::Yielded(a)
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}
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GeneratorA::Yield1(_) => {
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/*|----code after yield1----|*/
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/*|*/ println!("world!"); /*|*/
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/*|-------------------------|*/
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*self = GeneratorA::Exit;
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GeneratorState::Complete(())
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}
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GeneratorA::Exit => panic!("Can't advance an exited generator!"),
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}
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}
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}
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</code></pre></pre>
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<blockquote>
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<p>The <code>yield</code> keyword was discussed first in <a href="https://github.com/rust-lang/rfcs/pull/1823">RFC#1823</a> and in <a href="https://github.com/rust-lang/rfcs/pull/1832">RFC#1832</a>.</p>
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</blockquote>
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<pre><code>|| {
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let arr: Vec<i32> = (0..a).enumerate().map((i,_) i).collect();
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for n in arr {
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yield n;
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}
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println!("The sum is: {}", arr.iter().sum());
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}
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|| {
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yield a * 2;
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println!("Hello!");
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}
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</code></pre>
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