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# Using Generator Functions (genfuncs) in Rust

By David Li on 2023-04-20T14:45:32.928Z

# Using Generator Functions (genfuncs) in Rust

In this article, we will explore the use of generator functions, also known as genfuncs, in Rust programming language. Generator functions are a powerful tool that allows you to create iterators with minimal boilerplate code. They are particularly useful when you want to create a custom iterator that yields values on-the-fly.

## What are Generator Functions?

Generator functions are a type of function that, instead of returning a single value, can yield multiple values over time. In Rust, genfuncs are implemented using coroutines, which are a generalization of subroutines that can be paused and resumed multiple times during their execution.

A generator function can be thought of as a state machine that encapsulates the state of an iterator. Once a generator is paused, it can be resumed from the same state it was paused in, allowing it to continue producing values from where it left off.

## Prerequisites

Before we dive into using genfuncs in Rust, you need to have Rust installed on your system. You can download and install Rust from the official website.

## Creating a Simple Generator Function

Let’s start by creating a simple generator function that yields the Fibonacci sequence. First, we need to declare the generator function. In Rust, we use the `async` keyword to indicate that a function is a generator function. Here’s a basic example:

``````async fn fibonacci() -> impl Iterator<Item = u64> {
// Generator function implementation
}``````

In this example, `fibonacci` is a generator function that returns an iterator of `u64` values.

Now let’s implement the generator function. We will use the `yield` keyword to produce values from the generator function:

``````async fn fibonacci() -> impl Iterator<Item = u64> {
let mut a = 0;
let mut b = 1;

loop {
let next = a + b;
a = b;
b = next;
yield a;
}
}``````

Unfortunately, this code will not compile in Rust as of today. This is because Rust’s `async` keyword is designed for asynchronous programming with `Future`s, and the `yield` keyword is not natively available. However, we can achieve similar functionality with the `futures` crate and using `async-stream` crate for creating generator functions.

## Using the `async-stream` Crate

First, add the following dependencies to your `Cargo.toml`:

``````[dependencies]
async-stream = "0.3"
futures = "0.3"``````

Now, modify the `fibonacci` function to use the `async_stream::stream!` macro:

``````use async_stream::stream;
use futures::Stream;

fn fibonacci() -> impl Stream<Item = u64> {
stream! {
let mut a = 0;
let mut b = 1;

loop {
let next = a + b;
a = b;
b = next;
yield a;
}
}
}``````

As you can see, we have replaced the `async` keyword with the `stream!` macro and changed the return type to `impl Stream<Item = u64>`. We also imported the `futures::Stream` trait, which provides useful methods for working with streams.

Now we can use the `fibonacci` generator function like this:

``````use futures::StreamExt;

async fn main() {
let mut fib_stream = fibonacci().take(10);

while let Some(value) = fib_stream.next().await {
println!("{}", value);
}
}``````

In this example, we use the `StreamExt` trait from the `futures` crate to work with the generator function. We limit the output to the first 10 Fibonacci numbers using the `take()` method and print them using an asynchronous `main` function.

## Conclusion

In this article, we explored the concept of generator functions and how to create them in Rust using the `async-stream` crate. Generator functions can be a powerful tool when dealing with complex iterators or when you want to create custom iterators with minimal boilerplate code. Although Rust does not natively support generator functions with the `async` keyword and the `yield` statement, the `async-stream` crate offers a convenient and expressive way to create generator functions.

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