A better streams API is possible for JavaScript

A better streams API is possible for JavaScript(blog.cloudflare.com)

447 points by nnx 79 days ago | 156 comments

conartist6 79 days ago |

As it happens i have an even better API than this article proposes!

They propose just using an async iterator of UInt8Array. I almost like this idea, but it's not quite all the way there.

They propose this:

  type Stream<T> = {
    next(): Promise<{ done, value: UInt8Array<T> }>
  }

I propose this, which I call a stream iterator!

  type Stream<T> = {
    next(): { done, value: T } | Promise<{ done, value: T }>
  }

Obviously I'm gonna be biased, but I'm pretty sure my version is also objectively superior:

- I can easily make mine from theirs

- In theirs the conceptual "stream" is defined by an iterator of iterators, meaning you need a for loop of for loops to step through it. In mine it's just one iterator and it can be consumed with one for loop.

- I'm not limited to having only streams of integers, they are

- My way, if I define a sync transform over a sync input, the whole iteration can be sync making it possible to get and use the result in sync functions. This is huge as otherwise you have to write all the code twice: once with sync iterator and for loops and once with async iterators and for await loops.

- The problem with thrashing Promises when splitting input up into words goes away. With async iterators, creating two words means creating two promises. With stream iterators if you have the data available there's no need for promises at all, you just yield it.

- Stream iterators can help you manage concurrency, which is a huge thing that async iterators cannot do. Async iterators can't do this because if they see a promise they will always wait for it. That's the same as saying "if there is any concurrency, it will always be eliminated."

Joker_vD 79 days ago | |

> Obviously I'm gonna be biased, but I'm pretty sure my version is also objectively superior:

> - I can easily make mine from theirs

That... doesn't make it superior? On the contrary, theirs can't be easily made out of yours, except by either returning trivial 1-byte chunks, or by arbitrary buffering. So their proposal is a superior primitive.

On the whole, I/O-oriented iterators probably should return chunks of T, otherwise you get buffer bloat for free. The readv/writev were introduced for a reason, you know.

robby_w_g 79 days ago | | |

> So their proposal is a superior primitive.

This lines up with my thinking. The proposal should give us a building block in the form of the primitive. I would expect the grandparent comment’s API to be provided in a library built on top of a language level primitive.

conartist6 79 days ago | | |

As an abstraction I would say it does make mine superior that it captures everything theirs can and more that theirs can't.

Plus theirs involves the very concrete definition of an array, which might have 100 prototype methods in JS, each part of their API surface. I have one function in my API surface.

flowerbreeze 79 days ago | |

I think the more generic stream concept is interesting, but their proposal is based on different underlying assumptions.

From what it looks like, they want their streams to be compatible with AsyncIterator so it'd fit into existing ecosystem of iterators.

And I believe the Uint8Array is there for matching OS streams as they tend to move batches of bytes without having knowledge about the data inside. It's probably not intended as an entirely new concept of a stream, but something that C/C++ or other language that can provide functionality for JS, can do underneath.

For example my personal pet project of a graph database written in C has observers/observables that are similar to the AsyncIterator streams (except one observable can be listened to by more than one observer) moving about batches of Uint8Array (or rather uint8_t* buffer with capacity/count), because it's one of the fastest and easiest thing to do in C.

It'd be a lot more work to use anything other than uint8_t* batches for streaming data. What I mean by that, is that any other protocol that is aware of the type information would be built on top of the streams, rather than being part of the stream protocol itself for this reason.

conartist6 79 days ago | | |

Yeah it makes sense to me that the actual network socket is going to move data around in buffers. I'm just offering an abstraction over that so that you can write code that is wholly agnostic to how data is stored.

And yes, because it's a new abstraction the compat story is interesting. We can easily wrap any source so we'll have loads of working sources. The fight will be getting official data sinks that support a new kind of stream

paulddraper 79 days ago | |

Your idea is flatten the UInt8Array into the stream.

While I understand the logic, that's a terrible idea.

* The overhead is massive. Now every 1KiB turns into 1024 objects. And terrible locality.

* Raw byte APIs...network, fs, etc fundamentally operate on byte arrays anyway.

In the most respectful way possible...this idea would only be appealing to someone who's not used to optimizing systems for efficiency.

conartist6 79 days ago | | |

JS engines actually are optimized to make that usage pattern fast.

Small, short-lived objects with known key ordering (monomorphism) are not a major cost in JS because the GC design is generational. The smallest, youngest generation of objects can be quickly collected with an incremental GC because the perf assumption is that most of the items in the youngest generation will be garbage. This allows collection to be optimized by first finding the live objects in the gen0 pool, copying them out, then throwing away the old gen0 pool memory and replacing it with a new chunk.

fwip 79 days ago | | |

I agree with your post, but in practice, couldn't you get back that efficiency by setting T = UInt8Array? That is, write your stream to send / receive arrays.

My reference point is from a noob experience with Golang - where I was losing a bunch of efficiency to channel overhead from sending millions of small items. Sending batches of ~1000 instead cut that down to a negligible amount. It is a little less ergonomic to work with (adding a nesting level to your loop).

hinkley 79 days ago | |

I did a microbenchmark recently and found that on node 24, awaiting a sync function is about 90 times slower than just calling it. If the function is trivial, which can often be the case.

If you go back a few versions, that number goes up to around 105x. I don’t recall now if I tested back to 14. There was an optimization to async handling in 16 that I recall breaking a few tests that depended on nextTick() behavior that stopped happening, such that the setup and execution steps started firing in the wrong order, due to a mock returning a number instead of a Promise.

I wonder if I still have that code somewhere…

billywhizz 79 days ago | | |

that sounds way off. there is a big perf hit to async, but it appears to be roughly 100 nanoseconds overhead per call. when benchmarking you have to ensure your function is not going to be optimized away if it doesn't do anything or inputs/outputs never change.

you can run this to see the overhead for node.js Bun and Deno: https://gist.github.com/billywhizz/e8275a3a90504b0549de3c075...

rrr_oh_man 79 days ago | | |

> I did a microbenchmark recently and found that on node 24, awaiting a sync function is about 90 times slower than just calling it. If the function is trivial, which can often be the case.

I dabble in JS and… what?! Any idea why?

conartist6 79 days ago | | |

Here is my test harness and results: https://github.com/conartist6/async-perf

paxys 79 days ago | |

There is no such thing as Uint8Array<T>. Uint8Array is a primitive for a bunch of bytes, because that is what data is in a stream.

Adding types on top of that isn't a protocol concern but an application-level one.

85392_school 79 days ago | | |

A Uint8Array can be backed by buffers other than ArrayBuffer, which is where the types [0] come from.

[0] https://github.com/microsoft/TypeScript/blob/924810c077dd410...

softfalcon 79 days ago | | |

> Adding types on top of that isn't a protocol concern but an application-level one.

I agree with this.

I have had to handle raw byte streams at lower levels for a lot of use-cases (usually optimization, or when developing libs for special purposes).

It is quite helpful to have the choice of how I handle the raw chunks of data that get queued up and out of the network layer to my application.

Maybe this is because I do everything from C++ to Javascript, but I feel like the abstractions of cleanly getting a stream of byte arrays is already so many steps away from actual network packet retrieval, serializing, and parsing that I am a bit baffled folks want to abstract this concern away even more than we already do.

I get it, we all have our focuses (and they're ever growing in Software these days), but maybe it's okay to still see some of the bits and bytes in our systems?

pgt 79 days ago | |

This is similar to how Clojure transducers are implemented: "give me the next thing plz." – https://clojure.org/reference/transducers

lucideer 79 days ago | |

Other angles of critique & consideration already covered well by sibling commenters. One extra consideration (unrelated to streams, more general) is the API design & dev UX/DX:

  type Stream<T> = {
    next(): { done, value: T } | Promise<{ done, value: T }>
  }

the above can effectively be discussed as a combination of the following:

  type Stream<T> = {
    next(): { done, value: T }
  }
  type Stream<T> = {
    next(): Promise<{ done, value: T }>
  }

You've covered the justifications for the 2nd signature, but it's a messy API. Specifically:

> My way, if I define a sync transform over a sync input, the whole iteration can be sync making it possible to get and use the result in sync functions. This is huge as otherwise you have to write all the code twice: once with sync iterator and for loops and once with async iterators and for await loops.

Writing all the code twice is cleaner in every implementation scenario I can envisage. It's very rare I want generalised flexibility on an API call - that leads to a lot of confusion & ambiguity when reading/reviewing code, & also when adding to/editing code. Any repetitiveness in handling both use-cases (separately) can easily be handled with well thought-out composition.

conartist6 79 days ago | | |

How is it cleaner? I used to actually do that. I wrote everything twice. I even built fancy tools to help me write everything twice.

But the bigger problem here is that sync and async aren't enough. You almost need to write everything three times: sync, async, and async-batched. And that async-batched code is gonna be gnarly and different from the other two copies and writing it in the first place and keeping it in sync is gonna give you headaches.

To see how it played out for me take a look at the difference between:

https://github.com/iter-tools/regex/blob/a35a0259bf288ccece2... https://github.com/iter-tools/regex/blob/a35a0259bf288ccece2... https://github.com/iter-tools/regex/blob/a35a0259bf288ccece2...

soulofmischief 79 days ago | |

In the language I've been working on for a couple months, Eidos, streams are achieved through iterators as well. It's dead simple. And lazy for loops are iterators, and there is piping syntax. This means you can do this (REPL code):

  >> fn double(iter: $iterator<i32>) {
    return *for x in iter { $yield( x * 2 )}
  }

  >> fn add_ten(iter: $iterator<i32>) {
    return *for x in iter { $yield( x + 10 )}
  }

  >> fn print_all(iter: $iterator<i32>) {
    for x in iter { $print( x )}
  }

  >> const source = *for x in [1, 2, 3] { $yield( x )}

  >> source |> double |> add_ten |> print_all
  12
  14
  16

You get backpressure for free, and the compiler can make intelligent decisions, such as automatic inlining, unrolling, kernel fusing, etc. depending on the type of iterators you're working with.

hinkley 79 days ago | |

I think the context that some other responders are missing is that in some functional languages, like Elixir, streams and iterators are used idiomatically to do staged transforms of data without necessitating accumulation at each step.

They are those languages versions of goroutines, and JavaScript doesn’t have one. Generators sort of, but people don’t use them much, and they don’t compose them with each other.

So if we are going to fix Streams, an implementation that is tuned only for IO-bound workflows at the expense of transform workflows would be a lost opportunity.

conartist6 79 days ago | |

There's one more interesting consequence: you rid yourself of the feedback problem.

To see the problem let's create a stream with feedback. Lets say we have an assembly line that produces muffins from ingredients, and the recipe says that every third muffin we produce must be mushed up and used as an ingredient for further muffins. This works OK until someone adds a final stage to the assembly line, which puts muffins in boxes of 12. Now the line gets completely stuck! It can't get a muffin to use on the start of the line because it hasn't made a full box of muffins yet, and it can't make a full box of muffins because it's starved for ingredients after 3.

If we're mandated to clump the items together we're implicitly assuming that there's no feedback, yet there's also no reason that feedback shouldn't be a first-class ability of streams.

amelius 79 days ago | |

How do you send multiple sub-streams in parallel?

spankalee 79 days ago |

Async iterables aren't necessarily a great solution either because of the exact same promise and stack switching overhead - it can be huge compared to sync iterables.

If you're dealing with small objects at the production side, like individual tag names, attributes, bindings, etc. during SSR., the natural thing to do is to just write() each string. But then you see that performance is terrible compared to sync iterables, and you face a choice:

  1. Buffer to produce larger chunks and less stack switching. This is the exact same thing you need to do with Streams. or

  2. Use sync iterables and forgo being able to support async components.

The article proposes sync streams to get around this some, but the problem is that in any traversal of data where some of the data might trigger an async operation, you don't necessarily know ahead of time if you need a sync or async stream or not. It's when you hit an async component that you need it. What you really want is a way for only the data that needs it to be async.

We faced this problem in Lit-SSR and our solution was to move to sync iterables that can contain thunks. If the producer needs to do something async it sends a thunk, and if the consumer receives a thunk it must call and await the thunk before getting the next value. If the consumer doesn't even support async values (like in a sync renderToString() context) then it can throw if it receives one.

This produced a 12-18x speedup in SSR benchmarks over components extracted from a real-world website.

I don't think a Streams API could adopt such a fragile contract (ie, you call next() too soon it will break), but having some kind of way where a consumer can pull as many values as possible in one microtask and then await only if an async value is encountered would be really valuable, IMO. Something like `write()` and `writeAsync()`.

The sad thing here is that generators are really the right shape for a lot of these streaming APIs that work over tree-like data, but generators are far too slow.

matheus-rr 79 days ago |

The practical pain with Web Streams in Node.js is that they feel like they were designed for the browser use case first and backported to the server. Any time I need to process large files or pipe data between services, I end up fighting with the API instead of just getting work done.

The async iterable approach makes so much more sense because it composes naturally with for-await-of and plays well with the rest of the async/await ecosystem. The current Web Streams API has this weird impedance mismatch where you end up wrapping everything in transform streams just to apply a simple operation.

Node's original stream implementation had problems too, but at least `.pipe()` was intuitive. You could chain operations and reason about backpressure without reading a spec. The Web Streams spec feels like it was written by the kind of person who thinks the solution to a complex problem is always more abstraction.

zarzavat 79 days ago | |

It's news to me that anyone actually uses the web streams in node. I thought they were just for interoperability, for code that needs to run on both client and server.

apitman 79 days ago | | |

You need to use them for things like Cloudflare and Denos HTTP servers, which is actually a fairly common (and nice) pattern:

https://blog.val.town/blog/the-api-we-forgot-to-name/

bikeshaving 79 days ago |

A long time ago, I wrote an abstraction called a Repeater. Essentially, the idea behind it is, what would the Promise constructor look like if it was translated to async iterables.

  import { Repeater } from "@repeaterjs/repeater";
  
  const keys = new Repeater(async (push, stop) => {
    const listener = (ev) => {
      if (ev.key === "Escape") {
        stop();
      } else {
        push(ev.key);
      }
    };
    window.addEventListener("keyup", listener);
    await stop;
    window.removeEventListener("keyup", listener);
  });
  const konami = ["ArrowUp", "ArrowUp", "ArrowDown", "ArrowDown", "ArrowLeft", "ArrowRight", "ArrowLeft", "ArrowRight", "b", "a"];
  (async function() {
    let i = 0;
    for await (const key of keys) {
      if (key === konami[i]) {
        i++;
      } else {
        i = 0;
      }
      if (i >= konami.length) {
        console.log("KONAMI!!!");
        break; // removes the keyup listener
      }
    }
  })();

https://github.com/repeaterjs/repeater

It’s one of those abstractions that’s feature complete and stable, and looking at NPM it’s apparently getting 6.5mil+ downloads a week for some reason.

Lately I’ve just taken the opposite view of the author, which is that we should just use streams, especially with how embedded they are in the `fetch` proposals and whatever. But the tee critique is devastating, so maybe the author is right. It’s exciting to see people are still thinking about this. I do think async iterables as the default abstraction is the way to go.

jnbridge 79 days ago |

The tension between "streams as lazy sequences" vs "streams as async event channels" isn't unique to JavaScript. Every major runtime has hit this wall:

- Java went through it with java.util.stream (pull-based, lazy) vs Reactive Streams/Project Reactor (push-based, backpressure-aware). The result was two completely separate APIs that don't compose well.

- .NET actually handled this better with IAsyncEnumerable<T> in C# 8 — a single abstraction that's pull-based but async-aware. It composes naturally with LINQ and doesn't require a separate reactive library for most use cases.

- Go side-stepped the problem entirely with goroutines and channels, making the whole streams abstraction unnecessary for most cases.

What I find interesting about this proposal is it's trying to learn from that prior art. The biggest mistake Java made was bolting async streams on top of a synchronous abstraction and then needing a completely separate spec (Reactive Streams) for the async case. If JavaScript can get a single unified abstraction that handles both sync iteration and async backpressure, that would be a genuine improvement over what exists in most other runtimes.

szmarczak 79 days ago |

> This pattern has caused connection pool exhaustion in Node.js applications using undici (the fetch() implementation built into Node.js), and similar issues have appeared in other runtimes.

That's an inherent flaw of garbage collected languages. Requiring to explicitly close a resource feels like writing C. Otherwise you have a memory leak or resource exhaustion, because the garbage collector may or may not free the resource. Even C++ is better at this, because it does reference counting instead.

tracker1 79 days ago |

One minor niggle on freeing resources... I'm hoping it becomes more popular with libraries, but there's using/await using with disppse/disposeAsync which works similarly to C#'s use of using.

I'm working on a db driver that uses it by convention as part of connection/pool usage cleanup.

cogman10 79 days ago |

Seems pretty similar to the design of OKIO in java [1]. With pretty similar goals ultimately. Here's a presentation on the internal details and design decisions. [2]

[1] https://github.com/square/okio

[2] https://www.youtube.com/watch?v=Du7YXPAV1M8

kg 79 days ago |

It's a real shame that BYOB (bring your own buffer) reads are so complex and such a pain in the neck because for large reads they make a huge difference in terms of GC traffic (for allocating temporary buffers) and CPU time (for the copies).

In an ideal world you could just ask the host to stream 100MB of stuff into a byte array or slice of the wasm heap. Alas.

amluto 79 days ago | |

I wonder if you can get most of the benefit BYOB with a much simpler API:

    for await (const chunk of stream) {
        // process the chunk
        stream.returnChunk(chunk);
    }

This would be entirely optional. If you don’t return the chunk and instead let GC free it, you get the normal behavior. If you do return it, then the stream is permitted to return it again later.

(Lately I’ve been thinking that a really nice stream or receive API would return an object with a linear type so that you must consume it and possibly even return it. This would make it impossible to write code where task cancellation causes you to lose received data. Sadly, mainstream languages can’t do this directly.)

ralusek 79 days ago |

I tinkered with an alternative to stream interfaces:

https://github.com/ralusek/streamie

allows you to do things like

    infiniteRecords
    .map(item => doSomeAsyncThing(item), { concurrency: 5 });

And then because I found that I often want to switch between batching items vs dealing with single items:

    infiniteRecords
    .map(item => doSomeAsyncSingularThing(item), { concurrency: 5 })
    .map(groupOf10 => doSomeBatchThing(groupsOf10), { batchSize: 10 })
    // Can flatten back to single items
    .map(item => backToSingleItem(item), { flatten: true });

z3t4 79 days ago |

I like Node.JS streams. It's very satisfying to rent a 250MB memory machine and let it process GB's of data using streams.

steve_adams_86 79 days ago |

I ran into a performance issues a few months ago where native streams were behaving terribly, and it seemed to be due to bad back-pressure implementation.

I tried several implementations, tweaked settings, but ultimately couldn't get around it. In some cases I had bizarre drops in activity when the consumer was below capacity.

It could have been related to the other issue they mention, which is the cost of using promises. My streams were initiating HEAPS of promises. The cost is immense when you're operating on a ton of data.

Eventually I had to implement some complex logic to accomplish batching to reduce the number of promises, then figure out some clever concurrency strategies to manage backpressure more manually. It worked well.

Once I was happy with what I had, I ported it from Deno to Go and the result was so stunningly different. The performance improvement was several orders of magnitude.

I also built my custom/native solution using the Effect library, and although some people claim it's inefficient and slow, it out-performed mine by something like 15% off the shelf, with no fine-tuning or clever ideas. I wished I'd used it from the start.

The difference is likely in that it uses a fiber-based model rather than promises at the execution layer, but I'm not sure.

yonran 79 days ago |

I don’t know how ReadableStream.tee() got specified to backpressure when the faster branch is not consumed, since this is the opposite of what nodejs does when multiple Writables attached via Readable.pipe() and also the opposite of what the requirements document (https://github.com/whatwg/streams/blob/e9355ce79925947e8eb49...) says: “letting the speed of the slowest output determine the speed of the tee”.

I like the idea of the more ergonomic, faster api in new-stream with no buffering except at Stream.push(). NodeJS and web streams put infinitely expandable queues at every ReadableStream and WritableStream so that you can synchronously res.write(chunk) as much as you want with abandon. This API basically forces you to use generators that yield instead of synchronously writing chunks.

nateb2022 79 days ago |

Regarding the benchmarks, "Async iteration (8KB × 1000): ~530 GB/s vs ~35 GB/s": how do you achieve 530 GB/s throughput on an M1 Pro which has a 200GB/s memory bandwidth? The "~275 GB/s" figure for chained transforms has the same problem.

I suspect the benchmarks, if not most of this project, suffer from poor quality control on vibecoded implementations.

esprehn 79 days ago |

Web Streams do feel rather painful compared to other languages. The author ends up basically describing kotlin flows which are great and I wish the web would adopt that model (Observables wanted to be that but the API is much worse than flows in practice).

Fwiw the original Streams API could have been simpler even without async iterators.

  interface Stream<T> {
    // Return false from the callback to stop early.
    // Result is if the stream was completed.
    forEach(callback: (chunk: T) => Promise<boolean | undefined>): Promise<boolean>
  }

Similarly adding a recycleBuffer(chunk) method would have gone a long way towards BYOB without all the ceremony.

If we're optimizing allocations we can also avoid all the {done,value} records and return a semaphore value for the end in the proposed API.

(Web) API design is really difficult and without a voice in the room pushing really hard on ergonomics and simplicity it's easy to solve all the use cases but end up with lots of awkward corners and costs later.

adamnemecek 79 days ago |

It might be a good idea to look into the research on streams as coalgebras, there is quite a bit, for example here https://cs.ru.nl/~jrot/CTC20/.

Coalgebras might seem too academic but so were monads at some point and now they are everywhere.

socketcluster 79 days ago |

https://socketcluster.io/ has had such stream implementation and backpressure management since at least 2019.

Here's the WritableConsumableStream module:

https://github.com/SocketCluster/writable-consumable-stream

SocketCluster solves the problem of maintaining message order with async processing.

This feature is even more useful now with LLMs as you can process data live, transform streams with AI with no risk of mangling the message order.

I may have been the first person to use a for-await-of loop in this way with backpressure. At least on an open source project.

rhodey 79 days ago |

the pull-stream module and its ecosystem is relevant here

the idea is basically just use functions. no classes and very little statefulness

https://www.npmjs.com/package/pull-stream

notnullorvoid 79 days ago |

There's a lot I like about this API, mainly the pull-based iterator approach. I don't really see what the value of the sync APIs are though. What's the difference of just using iterators directly for sync streams?

jonkoops 79 days ago | |

It avoids the overhead of Promises, so I can imagine that this would be quite useful if you know that blocking the thread is fine for a little while (e.g. in a worker).

notnullorvoid 79 days ago | | |

I mean the APIs like `Stream.pullSync` you could do that with a regular (non-async) iterator/generator.

jenkings 79 days ago |

As I’m sure many have, I wrote a wrapper around AyncIterables so I could use them more succinctly. However I wasn’t concerned with performance as I was using it in a lambda handling small batches or scanning items from a DB and streaming pages back.

https://github.com/juliantcook/fluent-async-iterator

I had hoped we would have a better API by now.

It was also very useful for CLI tools utilising unix pipes.

bennettpompi1 79 days ago |

I really enjoyed reading this article however I can't help but feeling that if you need anything described within it probably shouldn't be writing JS in the first place

paulddraper 79 days ago |

Just use AsyncIterator<UIntArray>.

The objection is

> The Web streams spec requires promise creation at numerous points — often in hot paths and often invisible to users. Each read() call doesn't just return a promise; internally, the implementation creates additional promises for queue management, pull() coordination, and backpressure signaling.

But that's 95% manageable by altering buffer sizes.

And as for that last 5%....what are you doing with JS to begin with?

sillyboi 79 days ago |

The real win here isn’t just performance,it’s convergence.

When ReadableStream behaves the same in the browser, Workers, and other runtimes, stream-based code becomes portable and predictable. That reduces subtle backpressure bugs and eliminates “works here but not there” edge cases.

Standardization at the streams layer is a big deal for building reliable streaming systems across environments.

thehamkercat 79 days ago | |

Yep, it isn't just x; it's y

sholladay 79 days ago |

As a maintainer on the Ky team, I give a big thumbs up to this proposal.

We have run into many problems with web streams over the years and solving them has always proven to be hairy, including the unbounded memory growth from response.clone().

The Deno team implemented a stream API inspired by Go, which I was happy with, until they ultimately acquiesced to web streams.

This proposal shares some of those principles as well.

etler 79 days ago |

There are many use cases where having a value stream is very useful. I do agree having a separate simpler byte only stream would make sense though. I think the current capabilities of web streams should be kept and an IOStream could be added for optimizing byte streams.

Ideally splitting out the use cases would allow both implementations to be simpler, but that ship has probably sailed.

socalgal2 79 days ago |

Promises should not be a big overhead. If they are, that seems like a bug in JS engines.

At a native level (C++/rust), a Promise is just a closure added to a list of callbacks for the event loop. Yes, if you did 1 per streamed byte then it would be huge but if you're doing 1 promise per megabyte, (1000 per gig), it really shouldn't add up 1% of perf.

pornel 79 days ago | |

In Rust, a Future can have only exactly one listener awaiting it, which means it doesn't need dynamic allocation and looping for an arbitrary number of .then() callbacks. This allows merging a chain of `.await`ed futures into a single state machine. You could get away with awaiting even on every byte.

conartist6 79 days ago | |

I'm fairly sure it's not Promises that are actually the heavy part but the `await` keyword as used in the `for await` loop. That's because await tries to preserve the call stack for debugging, making it a relatively high-level expensive construct from a perf perspective where a promise is a relatively low-level cheap one.

So if you're going to flatten everything into one stream then you can't have a for loop implementation that defensively awaits on every step, or else it'll be slooooooooow. That's my proposal for the change to the language is a syntax like

  for await? (value of stream) {
  }

which would only do the expensive high-level await when the underlying protocol forced it to by returning a promise-valued step.

esprehn 79 days ago | | |

Async call stacks is an optional feature when the devtools is open. There shouldn't be overhead from await like that?

apatheticonion 79 days ago |

What's wrong with a `Read` `Write` interface like every other language?

    const buffer = new UInt8Array(256)
    const bytesRead = await reader.read(buffer)
    if (bytesRead === 0) {
      // Done
      return
    }

dilap 79 days ago |

> The problems aren't bugs; they're consequences of design decisions that may have made sense a decade ago, but don't align with how JavaScript developers write code today.

> I'm not here to disparage the work that came before — I'm here to start a conversation about what can potentially come next.

Terrible LLM-slop style. Is Mr Snell letting an LLM write the article for him or has he just appropriated the style?

jasnell 79 days ago | |

Heh, I was using emdashes and tricolons long before LLMs appropriated the style but I did let the agent handle some of the details on this. Honestly, it really is just easier sometimes... Especially for blogs posts like this when I've also got a book I'm writing, code to maintain etc. Use tools available to make life easier.

dilap 79 days ago | | |

I think you'd be much better served by writing something rough that maintains your own voice!

silisili 79 days ago | | |

I'm not sure any emdash use at all is what people are calling out typically(maybe it is?), more the sheer number of them typical in LLM written stuff.

Just ctrl-f'ing through previous public posts, I think there were a total of 7 used across about that many posts. This one for example had 57. I'm not good enough in proper English to know what the normal number is supposed to be, just pointing that out.

n_e 79 days ago | | |

I found your article both interesting and readable.

It doesn't really matter what tools are used if the result is good

hackrmn 79 days ago | | |

Just want to raise my hand and say I too have been using em dashes for considerably longer than LLM has been on every hacker's lips. It's obviously not great being accused of being an AI just because one has a particular style of writing...

eis 79 days ago | | |

People are understandably a bit sensitized and sceptical after the last AI generated blog post (and code slop!) by Cloudflare blew up. Personally I'm fine with using AI to help write stuff as long as everything is proof-read and actually represents the authors thoughts. I would have opted to be a bit more careful and not use AI for a few blog posts after the last incident though if I was working at Cloudflare...

azangru 79 days ago | |

What was it specifically about the style that stood out as incongruous, or that hindered comprehension? What was it that made you stumble and start paying close attention to the style rather than to the message? I am looking at the two examples, and I can't see anything wrong with them, especially in the context of the article. They both employ the same rhetorical technique of antithesis, a juxtaposition of contrasting ideas. Surely people wrote like this before? Surely no-one complained?

jsheard 79 days ago | | |

The problem is less with the style itself and more that it's strongly associated with low-effort content which is going to waste the readers time. It would be nice to be able to give everything the benefit of the doubt, but humans have finite time and LLMs have infinite capacity for producing trite or inaccurate drivel, so readers end up reflexively using LLM tells as a litmus test for (lack of) quality in order to cut through the noise.

You might say well, it's on the Cloudflare blog so it must have some merit, but after the Matrix incident...

nebezb 79 days ago | |

The idea is well articulated and comes across clear. What’s the issue? Taking a magnifying glass to the whole article to find sentence structure you think is “LLM-slop” is an odd way to dismiss the article entirely.

I’ve read my fair share of LLM slop. This doesn’t qualify.

jitl 79 days ago | |

cloudflare does seem to love ai written everything

lapcat 79 days ago | |

You’ve got it backwards: LLMs were trained on human writing and appropriated our style.

have_faith 79 days ago | | |

Partially true. They've been trained and then aligned towards a preferred style. They don't use em-dashes because they are over-represented in the training material (majority of people don't use them).

GoblinSlayer 79 days ago | | |

They converge...

mhh__ 79 days ago |

I've only used them in dotnet, I would be very interested to read any strong opinions about the use of Streams both in practice and as an abstract point in API design.

austin-cheney 79 days ago | |

Streams are how modern operating systems work, most commonly to transfer audio, video, file system, and network data from hardware to channels available for applications. So a common scenario is to stream data from a file and pipe it to a network interface for transfer to other computers or to a web browser.

murmansk 79 days ago |

For gods sake, finally, somebody have said this!

nottorp 79 days ago |

Well, it's also possible to replace JavaScript with a better language, it's just too late for it...

shevy-java 79 days ago |

We deserve a better language than JavaScript.

Sadly it will never happen. WebAssembly failed to keep some of its promises here.

gejose 79 days ago | |

There's always a comment like this in most discussions about javascript.

krashidov 79 days ago | |

> WebAssembly failed to keep some of its promises here

classic case of not using an await before your promise

teaearlgraycold 79 days ago | |

As wonky as JS is I really like it. Typescript has done such a good job at making it fun to use.

postalrat 79 days ago | |

Where can I find these not kept promises?

nindalf 79 days ago | | |

They haven't yet made languages other than JavaScript first-class languages for the web - https://hacks.mozilla.org/2026/02/making-webassembly-a-first.... I wouldn't call this a broken promise, but it was something people were hoping would take less than a decade.

halfmatthalfcat 79 days ago |

The Observables spec should just get merged and implemented.

https://github.com/tc39/proposal-observable

bakkoting 79 days ago | |

Observables has moved to WHATWG [1] and been implemented in Chrome, although I don't know if the other browsers have expressed any interest (and there's still some issues [2] to be worked through).

But Observables really do not solve the problems being talked about in this post.

[1] https://github.com/WICG/observable [2] https://github.com/WICG/observable/issues/216

user3939382 79 days ago |

“ The Streams Standard was developed between 2014 and 2016 with an ambitious goal to provide "APIs for creating, composing, and consuming streams of data that map efficiently to low-level I/O primitives." Before Web streams, the web platform had no standard way to work with streaming data.”

This is what UDP is for. Everything actually has to be async all the way down and since it’s not, we’ll just completely reimplement the OS and network on top of itself and hey maybe when we’re done with that we can do it a third time to have the cloud of clouds.

The entire stack we’re using right down to the hardware is not fit for purpose and we’re burning our talent and money building these ever more brittle towering abstractions.

afavour 79 days ago | |

UDP is a protocol, not an API

mlhpdx 79 days ago | | |

True. But it’s also true that trying to shoehorn every use case into TCP streams is counter productive.

A stream API can layer over UDP as well (reading in order of arrival with packet level framing), but such a stream would a bit weird and incompatible with many stream consumers (e.g. [de]compression). A UDP API is simpler and more naturally event (packet) oriented. The concepts don’t mix well.

Still, it would be nice if they browser supported a UDP API instead of the weird and heavy DTLS and QUIC immitations.

delaminator 79 days ago | |

We're too busy building products while waiting for the perfect system to arrive.

user3939382 79 days ago | | |

I’m building everything from first principles, I’m not climbing the exponential curve with some billionaire that has to finance it.

let resolveRef; const promise = new Promise((res) => { resolveRef = res; }); const callback = (data) => { // Do work... resolveRef(data); // This "triggers" the await }; Object.assign(callback, promise);