Impressions of Rust

I recently had an opportunity to write some production Rust code and as a programming language nerd I was very interested in the opportunity to experience what Rust development is really like and had a few observations to share.

A few years ago I went through the Rust book and found a lot to like in the language, but never had an excuse to do much with it. Now I was working through an issue to switch rules_prerender CSS bundling to use Parcel and required some changes to Parcel's Rust codebase to make that happen. Specifically, I wanted to add support for a custom resolver, so @import statements in CSS could be resolved to arbitrary paths on the file system in order to be compatible with bazel-out/ file structure. I also wanted that resolver to be implementable in JavaScript, so rules_prerender wouldn't need to ship custom Rust code, which would introduce significant deployment complexity which it wouldn't otherwise need to deal with.

Updating Parcel to support a custom JS resolver pulled on a number of interesting challenges, including:

  • Working with async/await
  • Working with multi-threading
  • JavaScript interoperability
  • Node-API

Based on this experience, here are a few observations about the Rust language and ecosystem. Keep in mind that it's my first real foray into Rust (aside from some toy programs) and I'm coming at this from a web developer perspective, not a systems programming perspective (I did a lot of C/C++ college but barely touched it since).

Borrow Checking

The borrow checker is easily the biggest feature and selling point of the Rust language, and there's a lot to like there. Having a static analysis tool directly built into the compiler and the language design which points out memory safety bugs and how to fix them is truly incredible, especially in an increasingly security-minded industry. In my entire experience, I never encountered any runtime failures. I only ever saw one segmentation fault when I tried to use std::mem::transmute() as a hacky workaround for something it was definitely not supposed to transmute, so that one is on me.

And it's not just removing segfault errors, but also having the confidence to know that I'm using any given API correctly. It removes an entire dimension of documentation around ownership, thread safety, and the responsibilities of the callee and the caller. This allows the compiler to subtly guide the developer towards the correct solution to their particular problem.

But while the borrow checker is a huge benefit in comparison to a C++ world, I do see some significant regressions in comparison to a JavaScript world. As a web developer in the build tooling space, I frequently hear suggestions that we rewrite existing tooling in native-compiled languages like Rust or Go. There are many caveats to that approach, but the one I'll mention here is that moving from a garbage collected world to a borrow checked world introduces a significant learning and conceptual overhead bourne by the developer.

There are now a whole new class of potential issues, design considerations, and challenges that Rust introduces to web developers which I think is often under-estimated. While writing Rust I frequently heard myself saying: "but I just don't care about this ownership error, fixing this doesn't help me do what I actually want to do". Of course, in a Rust program you do care, you have to care about this stuff.

The mental model is so different from what I'm used to that I'm never 100% sure I'm actually solving a particular problem the "right" way. Are my lifetimes set up correctly? Does my ownership make sense? Am I using the right primitives for this problem? In this context, I was making a PR for a repo I had no prior relationship with, so I didn't have the luxury of a co-worker whom I could tap on the shoulder and ask to sanity check this kind of stuff.

These points aren't so much a critique of Rust, as they are the trade-offs it has made as a language and the level of abstraction the developer sits at. Are you writing code in which you care about the memory layout, data ownership, and allocation? If so, Rust is probably a great option in that space. But if not, it's likely the wrong tool for the job.

I can at least appreciate the strongly opinionated nature of the Rust language and how clearly it communicates exactly what you're getting into with it: a world of zero-cost abstractions, minimal runtime, and memory safety. Rust is very unapologetically itself, and I mean that in the best possible way. However it's also important to recognize that these aren't exactly features, they're trade-offs. And what the language traded for them was complexity in the mental model. That's not necessarily a bad trade-off, and I'm glad Rust went the direction it did. However, this is a trade-off to keep in mind whenever faced with the question "Should we use Rust to solve this problem?"


The Rust compiler itself is great at calling out errors, detailing what's wrong, why its wrong, and what your options are to fix it. Visualizing this as a graph, we can model this developer journey like so, where the Rust compiler guides the developer down of web of flawed solutions to the correct solution.

A graph with dozens of nodes with arrows connecting them. The legend identifies these nodes as "possible solutions", while the arrows are "error messages", guiding the developer from one solution to another. At the end of the graph is a green node labeled "actual solution" with a single path of green arrows leading from the start to that final solution.

This is awesome and often leads to the compiler helping you "discover" aspects of the problem space that might not have been obvious. Unfortunately the reality is that the path to success is simply not always clear, and my developer journey usually looked more like this:

The same graph as before, but with an additional red line labeled "Me". The line scribbles all over the graph as it attempts to find the green path, but consistently fails. It takes wrong turns, doubles backs, and even returns back to the starting node before eventually finding its way to the final solution.

Fixing one ownership issue often just shifts the problem to another place, and without a strong understanding of this mental model, it can be very difficult to identify which path from any given node is actually the "right" one, which gets closer to the real solution.

As a concrete example of this, during my work here I initially tried to everything synchronous and single-threaded since the codebase was not async and I figured that would make the initial implementation easier. I found that this actually made things harder because of a non-obvious chain of complexity:

  1. Interoperability with JavaScript in this context inherently pulls on multi-threading concepts.
    • The Parcel codebase was already multi-threaded, so everything needed to be Send + Sync compatible, with no easy "chill compiler, this is just a prototype" workaround.
  2. Multi-threading in this context inherently pulls on async/await issues.
    • The Rust function exposed to JS could work synchronously, but since I had to use thread-safe APIs, they expected the main thread to be free for the JS event loop, which is non-trivial to do without async/await.
  3. Using async/await in this manner in Rust means we need to make the JS call async as well.

It took several hours to figure out that the problem "x is not Send + Sync" effectively requires the solution "Make the JS function async" and my attempts to solve a smaller-scale problem (single-threaded, no async/await) were actually making things harder, rather than easier.

A lack of escape hatches can also make things trickier to debug. If I don't understand a value in TypeScript, I can usually cast to any and console.log() to understand what that value is and how I should be using it. There's no real equivalent in Rust as far as I can tell. You can println!("{:?}", value) if the type implements Debug (Node-API JS types do not), but there's no easy as any or a good way of debugging lifetime issues. A lot of this is just the different mental model Rust uses, so an as any wouldn't help anyways, and I'm not sure what reasonable approach would allow ignoring or tweaking invalid lifetimes to get a program that would help you figure out what their correct lifetimes should be.

On several occasions I found myself with a program which I considered to be valid and memory-safe, but struggled to convince the Rust compiler that it is indeed a valid memory-safe program. Sometimes the compiler would point out a flaw in my understanding and help guide me to the correct solution, but the compiler just as frequently had a flaw in its own understanding which I was failing to communicate to it. Those errors are particularly frustrating because the time and effort spent doesn't feel productive since it isn't about the problem you actually want to solve, but rather getting the language and its tooling to let you solve the problem.

Of course, debugging is hard in general, and that's true for any language. A compiler can never know the exact solution to any particular error, only some general ideas of a direction you can take that might lead to a fix. I think the challenge with Rust is that the increased complexity and lower level of abstraction (compared to JS) makes this a bigger issue than I'm used to.

The flip side of this is that when the compiler does successfully indicate a flaw in your reasoning and communicates it to you effectively, Rust can feel incredibly productive. When it all clicks, the compiler teaches you something about the problem space which you didn't realize, and you successfully follow that green path on the first try, it feels amazing. Those instances are definitely the most fun I've had programming in a long time. And isn't that what really matters?


On a more positive note, I absolutely love, which pulls API documentation from published crates. This is a really cool way of making documentation consistently available for all crates without having to go hunting for how each package does things and following types between them. Clicking through functions and type definitions is so smooth and consistent, just a fantastic experience all around.

This unfortunately doesn't solve the writing part of writing documentation, and some crates are certainly under-documented. However I always had that content immediately at my fingertips which really helped with the process. The whole thing makes me really jealous and want a similar feature for NPM.

I do wish there was a more standard pattern for enabling features inside crates. One friction point is that different crates are less up-front about all their features, what each of them do, and which symbols are hidden behind them. I would love to see a compiler error which reads "foo::bar doesn't exist, but it is supported by the foo crate behind the bar feature, consider enabling that in your Cargo.toml."


I used VSCode for most of this process and found the editing experience to be decent, but lacking in comparison to TypeScript (one of the gold standards for this kind of thing in VSCode at least). A few of the areas which caused me challenges were:

  • The language service would frequently highlight entire function bodies as the cause of an error, which gets noisy and unwieldy.
  • "Go to definition" usually worked from my source code, but I couldn't do the same from library code, leading me to visit even more than I really should have needed to.
  • Inspecting types via mouseover was much less helpful than I wanted. It would often should the declared type rather than the resolved type. So I would see Future<Output = Self::Output> rather than Future<Output = i32>, which made debugging types much harder.

JavaScript Interoperability

Since the main goal of this work was to expose a JavaScript API for custom resolvers in Parcel, much of the challenge came from JS interoperability. I was expecting to have to deal with WebAssembly, but apparently Parcel still uses Node-API for the relevant API since WebAssembly doesn't have direct file system access.

If you're not familiar with it, Node-API is the system for building native NodeJS add-ons and calling them from JavaScript. The biggest constraint with this system is that JavaScript only ever runs on the main thread, so any Node-API types like JsString, JsNumber, and JsFunction can only be referenced from the main thread (not sure how JS worker interop works here). Since Parcel is multi-threaded, most of the challenge came from figuring out how to use these types only from the main thread.

Fortunately Rust is really helpful here. Its ownership model ports really well to multithreaded programming. The JS types don't implemented Send or Sync, so I would get clear type errors if I ever accidentally referenced something from the wrong thread, so I never encountered any race conditions (I did kind of get a deadlock at one point, more on that later). Whenever the program compiled, it had a very high chance of actually doing what I wanted, which I think is a strong indicator of how good the compiler is.

Here are a few interesting details, though if you really want the nitty-gritty you can look at the pull request.


There is a ThreadsafeFunction type for calling JS functions from worker threads, though it took me a while to really understand what this is doing and why the API is structure the way it is. The example is the best documentation and also does not explain most of the reasoning for it.

use napi::JsFunction;
use napi::threadsafe_function::{

/// Rust type of the arguments passed to the JS function.
struct JsArgs {
    message: String,
    sender: String,

fn test_threadsafe_function(js_func: JsFunction) -> napi::Result<()> {
    // Create a thread-safe reference to a JS function.
    let threadsafe_js_func: ThreadsafeFunction<JsArgs, ErrorStrategy::Fatal> =
            0 /* max_queue_size (0 means unlimited). */,
            // Invoked on the main thead, converts `JsArgs`
            // to JavaScript values.
            |ctx: ThreadSafeCallContext<JsArgs>| {
                // Return a `Result<Vec<JsUnknown>>` which
                // are passed to the JS function.

    // Invoked on the current thread (may not be main). {
        message: String::from("Hello!"),
        sender: String::from("Rust"),
    }, ThreadsafeFunctionCallMode::Blocking);


This creates a thread-safe function with JsArgs declared as its arguments. This is a Rust type which represents the arguments being passed to the JS function before they are converted to their JS equivalents. It is constructed on the worker thread and placed in a queue when .call() is invoked. Once the JS event loop is ready to process the invocation, it pulls the item from this queue and uses the callback in .create_threadsafe_function() to convert JsArgs into Result<Vec<JsUnknown>>. That callback is invoked on the main thread, so you have full access to the JS types. This is a direct result of the need to limit JS symbols to the main thread and why this API works the way it does. I think you can actually return Result<Vec<ToNapiValue>>, but if you're returning heterogenous types, this can confuse the compiler. Everything has an .into_unknown() to convert to the base JsUnknown type which can make the type homogenous.

If you want a Rust function to return a Promise to JS, you have to use a very similar looking API called execute_tokio_future(). This has a similar pattern of taking a Future<Output = SomeRustType> and a transformation function running on the main thread which converts the result to a Node-API JS type.

The general pattern here is that you want to do as much work as you can outside the callback, so it happens off the main thread. Then use the callback solely to convert the arguments from Rust types into JS types.

One other thing that tripped me up with ThreadsafeFunction in particular is that Node-API uses ErrorStrategy::CalleeHandled by default. This means the JS function should be written to receive the call like so:

function myReceiver(err: any, message: string, sender: string) {
    if (err) {

    doSomethingWithSuccess(message, sender);

This follows NodeJS callback conventions, where an optional error is passed as the first argument (if the JsArgs -> Result<Vec<JsUnknown>> conversion fails), with the actual data following. In my case, there is no use case where the resolver should be called with an error, so ErrorStrategy::Fatal made more sense and would just call the function directly with the Result<Vec<JsUnknown>>.

function myReceiver(message: string, sender: string) {
    // No error case to worry about!
    doSomethingWithSuccess(message, sender);

Unfortunately, ThreadsafeFunction doesn't currently seem to have any support for capturing return values. This means the resolved file path that the resolver returns gets dropped entirely. My workaround for this was to modify the JS function signature to instead use a callback to invoke Rust with the response.

import * as path from 'path';

function myResolver(
    specifier: string,
    originatingFile: string,
    // Rust callback invoked with the result.
    callback: (err: any, result: string) => void,
) {
    const resolved = path.join(originatingFile, '..', specifier);
    callback(null, resolved);

The Rust side then used a CallbackFuture to wait for this function to be invoked and capture the result. Since this would be an un-ergonomic API on the JS side, I added a small adapter which translated a Promise API structure into this callback design.

// Wraps the `bundleAsync` export and converts the `resolve`
// option from a Promise API to a callback API.
const { bundleAsync: realBundleAsync } = module.exports;
module.exports.bundleAsync = ({ resolve, ...opts }) => {
    return realBundleAsync({
        resolve: normalizeJsCallback(resolve),

// The version of `resolve` exposed to JS implementations
// which returns a `Promise`.
type PromiseBasedResolve = (
    specifier: string,
    originatingFile: string,
) => Promise<string>;

// The version of `resolve` which invokes the Rust callback.
type CallbackBasedResolve = (
    specifier: string,
    originatingFile: string,
    rustCallback: (err: any, result: string) => void,
) => void;

// Converts the Promise-based of `resolve` to the
// callback-based version.
function normalizeJsCallback(userResolve: PromiseBasedResolve): CallbackBasedResolve {
    return (
        specifier: string,
        originatingFile: string,
        rustCallback: (err: any, result: string) => void,
    ) {
        Promise.resolve(userResolve(specifier, originatingFile)).then(
            (result) => rustCallback(null, result),
            (err) => rustCallback(err, null),

// Example usage with the `Promise`-based API.
    resolve(specifier: string, originatingFile: string) {
        const resolved =
            path.join(originatingFile, '..', specifier);
        return Promise.resolve(resolved);
    // ...

This gives JS implementations of resolve() a fully Promise based API, hiding the ugly callback under the hood.

Synchronous Callbacks

Parcel's bundle() function which I wanted to add a custom resolver to was actually synchronous, meaning a resolver which returns a Promise can't really work. However, file resolution might not be asynchronous, such as the path.join() implementation above. So in theory, a synchronous bundle() should be possible as long as the custom resolver is synchronous, right?

import { bundle } from '@parcel/css';

    // Synchronous implementation, should work.
    resolve(specifier: string, originatingFile: string) {
        return path.join(originatingFile, '..', specifier);

    // ...

However this isn't possible with ThreadsafeFunction. As mentioned earlier, ThreadsafeFunction actually queues an invocation and waits for the main thread to become available, effectively scheduling an event on the JavaScript event loop. If the main thread is always blocked, then the invocation will never happen. Since the main thread is executing the Rust implementation of bundle(), it never has an opportunity to invoke the JS event loop and resolve() will never be invoked. I had effectively blocked the main thread waiting for an event to trigger, but an event can never trigger because the main thread is blocked. Deadlocked!

The function call is still queued, so I found calling the JS function but not blocking on it and then adding an asynchronous timeout to the end of the function allowed resolve() to be invoked (albeit after bundle() had already returned).

import { bundle } from '@parcel/css';

// Rust call to JS `resolve()` gets scheduled here, but can't happen because the
// main thread is still in this function.
    resolve(specifier: string, originatingFile: string) {
        console.log(`Resolving ${specifier} from ${originatingFile}.`);
        return path.join(originatingFile, '..', specifier);

    // ...

// Yields to the event loop, so *now* `resolve()` gets invoked and prints.
await new Promise((resolve) => {
    setTimeout(() => resolve(), 1_000);

The shared main thread makes a synchronous callback with ThreadsafeFunction quite tricky. In Parcel's case, the main thread doesn't need to do anything special and mostly waits for worker threads / acts as its own worker thread. I believe it is still possible to manually free the main thread with your own "event loop" and process cross-thread JS function invocations while waiting for worker threads. I don't think ThreadsafeFunction actually has any API to support this, so you'd basically have to re-implement your own version of ThreadsafeFunction to do it.

To summarize, ThreadsafeFunction doesn't support synchronous callbacks to JavaScript from worker threads. The easiest solution is to make the callback asynchronous so the main thread returns a Promise with execute_tokio_future().

Functional Design

Moving away from Node-API and back to traditional Rust: I had a lot of fun with Rust's functional design patterns. Iterators work really smoothly, Option and Result are fantastic, pattern matching is really expressive and intuitive, and enums work perfectly. I've done some of this before in other contexts like Haskell, but this was my first opportunity to use APIs which are actually designed to use Option and Result, with first class language support for monadic operations like ?.

Many of these concepts are pretty easy to add into any language, but the great part about Rust is that it has powerful, standardized primitives which the whole ecosystem can leverage. No unexpected runtime errors and no unchecked nulls. This should really be the standard for all future languages and I would love to see a stronger effort to migrate towards these patterns in existing languages.

The one unfortunate part is that it sometimes felt like every API was returning Result and it littered most of the code with ? operators after every call. It's not that big a deal since ? is such a lightweight addition, but I wonder how different this really is from traditional error handling if they just get propagated 99% of the time anyways.


I was also a little sad that there's no equivalent to TypeScripts union operator (|) in Rust. This means that have a function return one of multiple things requires a named enum type and can't be anonymously constructed from a union of existing types.

function numberOrString(value: number | string): void {
    console.log(`Value: ${value}`);

numberOrString(1); // Value: 1
numberOrString('test'); // Value: test
// Must declare the enum and give it an explicit name name.
enum NumberOrString {

fn number_or_string(value: NumberOrString) {
    match value {
        NumberOrString::IsNumber(num) =>
            println!("Value: {}", num),
        NumberOrString::IsString(str) =>
            println!("Value: {}", str),

fn main() {
    number_or_string(NumberOrString::IsNumber(1)); // Value: 1
        String::from("test"))); // Value: test

I thought it would bother me more than it did, but it actually didn't come up too often, so it's a relatively minor complaint. You could use an implementation of Either, though there doesn't seem to be a standard version and it doesn't scale too well. I do know that number | string in TypeScript is not discriminated (no data telling me which type is in the variable, I'd have to typeof it). By contrast, NumberOrString is discriminated which allows match to work as well as does. That said, I would still love to see some kind of union operator in Rust to make this a little lighter-weight for simple cases.

Mixing Option and ?

One particularly annoying challenge I came across was mapping Option types with operations that might fail and how they interact with the ? operator:

fn main() -> Result<(), ()> {
    // Works: `?` is great!
    println!("{}", maybe_concat("First", " Second")?);

    // error[E0277]: the `?` operator can only be used in a
    // closure that returns `Result` or `Option`
    let result = Some("Hello")
        .map(|value| maybe_concat(&value, " World")?);
    println!("{:?}", result);


fn maybe_concat(first: &str, second: &str) -> Result<String, ()> {
    Ok(String::from(first) + second)

Since the ? is used in a closure within, is isn't able to make an early return from main() on failure. I couldn't find a good workaround to this which used .map(), so the best I could come up with was to avoid the closure altogether:

fn main() -> Result<(), ()> {
    // Inline the `.map()` call with a `match`.
    // Avoids the closure, so `?` still works.
    let result = match Some("hello") {
        Some(value) => Some(maybe_concat(&value, " world")?),
        None => None,
    println!("{:?}", result);


This works but just screams at me to use a .map() call. That None => None and Some(value) => Some(fn(value)) is exactly what a .map() function is for. I'm not sure what the right solution to this would be beyond the Rust compiler magically jumping out of main(), which is maybe possible, but definitely sounds like a bad idea.


Most of the effort here was trying to get Parcel to support custom resolvers implemented in JavaScript. However I was very easily able to set up a custom resolver implemented in Rust. I could have stopped there and just written my own usage in Rust rather than JavaScript. I did consider this option but ultimately decided against it because my use case was itself a JS library for others to consume (called rules_prerender, you should check it out if you're into Bazel or static site generators). I could have written a resolver there in Rust, but then I would run into the problem of deployment, how do users depend on the Rust part of the library?

This would have required cross-compiling my Rust resolver and Parcel into a bunch of different architectures, shipping them on NPM, installing the right one, and then invoking it. This was a lot of complexity I didn't want to address for a 5-line resolver, but was trivial for a JS resolver. So instead of solving that problem, I decided to go through all this multi-threaded, async Node-API stuff contributed to a library I don't own, and write a way-too-long blog post about it.

The "stonks" meme featuring a man in a suit with a blank mannequin head looking confidently at a line graph moving up and to the right with a bunch of meaningless numbers in the background. The subtitle reads: "Efficiency".


An area I struggled a lot with were discovering and choosing between the many different versions of the same operation which had slightly different semantics or names. For example, what kind of Fn or .iter() operation should I do? I eventually came to understand that these have direct parallels to Rust's ownership model:

Languagefoo&foo&mut foo

Once I understood that correlation, I had a much easier time understanding which of these I should be using for any particular problem. Some useful references for both of these are:

This also helped teach me a few common conventions:

  • .into_*() means "convert and take ownership".
  • .ok_*() means "convert into a Result type".
    • Except for Result which confusingly converts into an Option.
  • unwrap_*() means "extract from the object".
  • unwrap() means "extract from the object or panic because I don't want to deal with error handling right now".
  • .expect() means "assert that I got a valid result".
  • .try_*() means "does things with Result types".

These conventions took some time for me to get used to and I haven't seen them written down explicitly in this kind of format together, so hopefully this is helpful to someone out there (also may not be 100% accurate).

One adapter in particular that tripped me up was .clone(), specifically &str.clone() and &PathBuf.clone(). Both of these are fairly useless IMHO because they will take a borrowed reference to an object, clone it, and then return another borrowed reference. Eventually I discovered .to_owned() which clones the string and returns an owned version of the new object, which is almost always what you would want in that situation.

map() functions also had some inconsistencies between types which I found quite confusing. For example:

Option and Result seem to be mostly aligned, but Iterator and Future both disagree on the name of their flat map operation. The lack of function overloading also makes distinctions like vs Future.then() much more annoying to use than they really should be.

These adapters are also a bit tricky for documentation. Since many of them are implemented as extension functions, some type documentation is fairly minimal and unhelpful for typical usage. Future is a good example of this which has a great overview of the primitive and how polling works, but no details about how to actually use a Future from a practical perspective. All the functions you really care about are under FutureExt and much harder to find.

This is compounded by adapter types that are never actually referenced and only ever returned and consumed by adapter functions. For example, makes a lot of sense to me as a function invocation, but futures::future::Map as a type makes no logical sense to me. It doesn't fit a functional mental model and makes it much harder to work with. I'm sure there's a good reason as to why these kinds of types need to exist (probably because a dyn Future isn't Sized?) but they clutter the API surface and documentation with noise that really doesn't benefit the user. This is particularly annoying when Googling "Rust Future map" and finding futures::future::Map instead of the function that you actually wanted.

async / await

I'll admit I was a bit scared to jump into async / await stuff when the need arose, as I was under the impression the feature was still relatively new and there was no built in runtime. Fortunately I found the experience pretty straightforward and reasonably well supported. In particular, await can mostly be thought of as syntactic sugar for Futures, which closely aligns to how await works with Promises in JavaScript and was an easy mental model to pick up for me.

That said, there are some rough edges, however they are mostly smoothed over by community crates. Async recursion, async traits, and async tests are three areas in particular which stood out to me, but attribute macros mostly make things "just work" without a whole lot of issues.

Macros in general seem like a really powerful feature, but I'm not totally convinced they're a good idea yet. Implementations are practically unreadable to me, generated code is hard to understand or debug, and compile errors become incredibly noisy. One error I captured looked like this:

   Compiling playground v0.0.1 (/playground)
error[E0277]: `std::sync::MutexGuard<'_, &mut Data>` cannot be sent between threads safely
  --> src/
11 | #[async_recursion::async_recursion]
   | ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ `std::sync::MutexGuard<'_, &mut Data>` cannot be sent between threads safely
   = help: within `futures::stream::futures_ordered::OrderWrapper<impl futures::Future<Output = Data>>`, the trait `std::marker::Send` is not implemented for `std::sync::MutexGuard<'_, &mut Data>`
   = note: required because it appears within the type `for<'r, 's, 't0, 't1, 't2, 't3, 't4, 't5, 't6, 't7, 't8, 't9, 't10, 't11, 't12> {ResumeTy, std::sync::Mutex<&'r mut Data>, &'s std::sync::Mutex<&'t0 mut Data>, Result<std::sync::MutexGuard<'t1, &'t2 mut Data>, PoisonError<std::sync::MutexGuard<'t3, &'t4 mut Data>>>, &'t5 mut std::sync::MutexGuard<'t6, &'t7 mut Data>, std::sync::MutexGuard<'t8, &'t9 mut Data>, &'t10 mut &'t11 mut Data, &'t12 mut Nested, u64, Duration, Sleep, ()}`
   = note: required because it appears within the type `[static generator@src/ 35:6]`
   = note: required because it appears within the type `from_generator::GenFuture<[static generator@src/ 35:6]>`
   = note: required because it appears within the type `impl futures::Future<Output = Data>`
   = note: required because it appears within the type `futures::stream::futures_ordered::OrderWrapper<impl futures::Future<Output = Data>>`
   = note: required because of the requirements on the impl of `std::marker::Send` for `FuturesUnordered<futures::stream::futures_ordered::OrderWrapper<impl futures::Future<Output = Data>>>`
   = note: required because it appears within the type `FuturesOrdered<impl futures::Future<Output = Data>>`
   = note: required because it appears within the type `Collect<FuturesOrdered<impl futures::Future<Output = Data>>, Vec<Data>>`
   = note: required because it appears within the type `futures::future::join_all::JoinAllKind<impl futures::Future<Output = Data>>`
   = note: required because it appears within the type `JoinAll<impl futures::Future<Output = Data>>`
   = note: required because it appears within the type `for<'r, 's, 't0, 't1, 't2, 't3, 't4, 't5> {ResumeTy, Vec<Data>, &'r mut [Data], std::slice::IterMut<'s, Data>, [closure@src/ 35:6], std::iter::Map<std::slice::IterMut<'t2, Data>, [closure@src/ 35:6]>, JoinAll<impl futures::Future<Output = Data>>, ()}`
   = note: required because it appears within the type `[static generator@src/ 39:2]`
   = note: required because it appears within the type `from_generator::GenFuture<[static generator@src/ 39:2]>`
   = note: required because it appears within the type `impl futures::Future<Output = ()>`
   = note: required for the cast to the object type `dyn futures::Future<Output = ()> + std::marker::Send`
   = note: this error originates in the attribute macro `async_recursion::async_recursion` (in Nightly builds, run with -Z macro-backtrace for more info)

For more information about this error, try `rustc --explain E0277`.
error: could not compile `playground` due to previous error

This was trying to tell me "MutexGuard can't be passed across an async boundary" but exactly which mutex and how the mistake is made is completely lost in the macro.

While I'm by no means an expert in Rust, I think I have reasonable handle on most of its concepts to be able to work with them fairly effectively. One concept I definitely do not understand is pinning. It didn't come up too much in this particular project, but I've encountered plenty of errors in the past where I have to Pin and Box all my Futures and wasn't able to find any explanations which really made sense to me. Hopefully that's something I can get a better handle on eventually.


So that's a bunch of random thoughts about my experience with Rust. Overall, I definitely had a lot of fun with it and I think it's a really well designed language. This experience has convinced me that I will never write C++ again, however I'm not ready to abandon TypeScript just yet. The trade-offs Rust makes are only really applicable in very particular scenarios, so I don't feel a strong need to rewrite all our existing web tooling from scratch. It can certainly have some value in specific circumstances, but I still believe you should profile and optimize your JavaScript to make sure the language and runtime is actually the limiting factor and Rust gives significant performance benefits to justify the increase in complexity. If so, then Rust is a fantastic option to manage that complexity, just make sure it is essential complexity and not accidental complexity.