Explore computational expressions in rust (do notation)

F# includes support for what they call computational expressions which seems to be an extremely useful and powerful abstraction which doesn't require a large number of extra syntax to support it. There is a gentle introduction here, an official documentation page, and a paper discussing the topic.

I'm not an expert and am actually quite new to the idea but I'm going to try to present the idea briefly below. See the links above for more thorough discussion of these topics. I think the idea is very interesting and if the rust developers haven't seen the idea, I should think it would be a useful concept in the future development of rust.

Also, I think it can be understood as an approach to make error handing in the functional style more agreeable and some people find that very appealing. I'm not going to try to explain in detail how it works because the article linked does a much better job that I would.

I view computational expressions somewhat as an inversion of implementing the iterator trait in rust. In rust, if you have a type which you implement the iterator trait for, you immediately gain access to all of the methods iterators provide and more importantly, the ability to use the for loop construct directly.

struct X;

// We implement this iterator trait
impl Iterator for X {}

let x = X;

// and in the *context of a for loop*, you gain the benefit of *clean iteration*
for i in x {}

In a computational expression, the situation is reversed: you implement the functionality, let's assume for the moment it was an iterator, and in the context of the type, you gain the benefit of a for loop construct.

Now, I'm not sure the previous analogy is fully accurate in F# for a for loop but for let, it is more precise. Consider the following testable example where a construct maybe_worker is defined which modifies how binding occurs to allow options have simple mathematical equations applied to them. This works correctly regardless of whether any of the options are None or otherwise.

maybe_worker {
    let! x = Some 3
    let! y = Some 4
    let! z = Some 5

    return x * y + z
}

This type of construct is quite general and as such, allows you a lot of flexibility to apply these bindings to do various types of extra work (such as logging) however you define it. Another interesting aspect is they don't create extra operators, as can be seen here. They have reused many of the normal keywords of the language in these constructs as a kind of extension seeming to add a lot of flexibility.

Also interestingly, since these types holding these operation variants are essentially adding side effects
to and slightly modifying operations, they have had great success using them with types such as async and seq among others.

To anyone who missed this, computational expressions = do-notation.

I didn't know that. Then this form is probably less unknown than I was afraid of. I was afraid people would see my bad explanation and gloss the issue.

For reference, the paper linked above distinguishes between this type of abstraction and the do-notation Haskell utilizes and so therefore assuming them equivalent is not necessarily accurate. Those of you well versed in do-notation might find it interesting and helpful.

Isn't this just catch or am I missing something?

I don't think so. I looked for the most recent RFC on try and didn't see a catch so I'm not sure specifically what you're referring to (though it is possible I am incorrect). The following snippet in F# in this instance quite literally translates to something like this:

// F#
maybe_worker {
    let! x = Some 3
    let! y = Some 4
    let! z = Some 5

    return x * y + z
}

// Translated into a rust direct equivalent
fn maybe_worker() -> Option<i32> {
    Some(3).and_then(|x|
        Some(4).and_then(|y|
            Some(5).and_then(|z|
                Some(x * y * z)
            )
        )
    )
}

However, those comparisons don't really do it justice because implemented differently, that same F# snippet would be equivalent to this:

// Rust equivalent when logging is desired
fn maybe_worker() -> Option<i32> {
    Some(3).and_then(|x| {
        println!("Got `{}`", x);
        Some(4).and_then(|y| {
            println!("Got `{}`", y);
            Some(5).and_then(|z| {
                println!("Got `{}`", z);
                println!("Returning `Some({})`", x * y * z);
                Some(x * y * z)
            })
        })
    })
}

Now let! is only one of their operators that this supports. Using this type of binding, they added support for for loop concepts and yield operations. Many others exist to yield code which might match our conceptual models easier than otherwise.

@mdinger

@mdinger with catch that F# snippet is

do catch {
    let x = Some(3)?;
    println!("Got `{}`", x);
    let y = Some(4)?;
    println!("Got `{}`", y);
    let z = Some(5)?;
    println!("Got `{}`", z);
    println!("Returning `Some({})`", x * y * z);
    z * y * z
}

Do you mean catch from rfc #243? Is it implemented out of curiousity?

Unstable with temporary synyax of `do catch { ... }`

…

On Jun 19, 2017 7:10 AM, "mdinger" ***@***.***> wrote: Do you mean catch from rfc #243 <#243>? Is it implemented out of curiousity? — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#2034 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/AApc0mXYIkg6b5a3Yu62GOszht6lQ-zGks5sFfTKgaJpZM4N7-gL> .

@clarcharr Yes, catch and ? gives do notation for the Result and Option monads. Also, the coroutine eRFC proposes creating do notation tied to function bodies for Futures using procedural macros, aka #[async] and await!. I think the question should be what else would benefits from a do notation, like say transactional data structures or anything listed in the links above.

I was not aware of catch though it seems less flexible than the example I included (probably because it is hardcoded). I'm glad to see they're pursuing a lightweight and flexible approach to that RFC as opposed to using new keywords at every juncture.

BTW, I thought the F# approach was very interesting and different from the standard rust "macro" approach and I thought others might as well. Maybe it will be useful when devising future designs.

Before a proposal like this is relevant, I think we need to be able to reason generally regarding and_then and return for any monad, which requires at least generic associated types and possibly HKTs.

F#er here who is interested in Rust. I most commonly use the built-in computation expressions for async and sequences.

let dbQuery =
    async {

        // the ! means that the expression returns an async, so unwrap it
        let! dbData = runDbQuery ()
        let! apiData = runApiCall ()

        let saveQuery = makeSaveQuery dbData apiData
        return! save saveQuery
    }

let validate customer =
    seq {
        if String.IsNullOrWhiteSpace customer.Name then
            yield CustomerNameInvalid

        // the ! means the expression returns a sequence, so flatten it
        yield! List.map validateContacts customer.Contacts
    }

F#er here who is interested in Rust. I most commonly use the built-in computation expressions for async and sequences.

let dbQuery =
    async {

        // the ! means that the expression returns an async, so unwrap it
        let! dbData = runDbQuery ()
        let! apiData = runApiCall ()

        let saveQuery = makeSaveQuery dbData apiData
        return! save saveQuery
    }

let validate customer =
    seq {
        if String.IsNullOrWhiteSpace customer.Name then
            yield CustomerNameInvalid

        // the ! means the expression returns a sequence, so flatten it
        yield! List.map validateContacts customer.Contacts
    }

This is the beauty of computation expressions, you basically extend the language without modifying the compiler.

What is achieved in other languages with special keywords and container types (IEnumerable and yield ; Task and async/await; ) in F# you just use computation expressions ( seq{} async{} task{} ...)

Another usecase is the Bolero (fsbolero.io) wasm Frontend lib which uses computation expressions to define a dsl for its html templating. With the ability of F# compiler perform inlining when compiling the expression the resulting code is performant.

Computation expressions in this form are one of the superpowers of F#.

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Explore computational expressions in rust (do notation) #2034

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Explore computational expressions in rust (do notation) #2034

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arielb1 commented on Jun 16, 2017

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