smartstring VS ZIO

Your use case sounds like it will involve a lot of small strings that use a subset of UTF-8. If you’re concerned about performance, you could look into something like smartstring. Sixbit also looks interesting, but it looks like it won’t give you any more characters and it’d probably require additional computation to do the conversion (and they’d have to be converted back out).

> If you have a long-running async function, then pass parameters by value! If you have a polymorphic async function, then return your result in a Box.

I've taken to making heavy use of the smallvec and smartstring crates for this. Most lists and strings are small in practice. Using smallvec / smartstring lets you keep most clone() calls allocation-free. This in turn lets you use owned objects, which are easier to reason about - for you and the borrow checker. And you keep a lot of the performance of just passing around references.

I tried to use async rust a couple of years ago, and fell on my face in the process. Most of my rust at the moment is designed to compile to wasm - and then I'm leaning on nodejs for networking and IO. Writing async networked code is oh so much easier to reason about in javascript. When GAT, TAIT and some other language features to fix async land I'll muster up the courage to make another attempt. But rust's progress at fixing these problems feels painfully slow.

https://crates.io/crates/smallvec / https://crates.io/crates/smartstring

Just to point out, smartstring no longer assumes String memory layout. From the changelog:

There's some really good crates that implement SSO floating around - eg, SmartString. But I agree - its a pity they're needed. Swift built this into the core string type in the language. I think that was the right call.

Comparatively: * SmolStr can inline up to 22 bytes but does not adjust down for 32-bit architectures, meaning it's potentially wasting memory on 32-bit archs. Similarly though it's immutable and Clone is O(1) * SmartString can inline up to 23 bytes, but it's mutable and Clone is O(n). Also this crate makes assumptions about the memory layout of a String, which in theory should be fine, but is a slight caveat.

SmartString is used to store identifiers (which tends to be short, fewer than 23 characters, and ASCII-based) because they can usually be stored inline. Map keys now also use SmartString.

I’ve been using smartstrings, which is both excellent and maintained. https://github.com/bodil/smartstring

scala has 2 healthy and pretty complete lib ecosystems : check out typelevel and ZIO. Both are FP oriented, which might not be your cup of tea at first glance but I would encourage you to try em out ! Softest introduction would be to start with the typelevel cats library and build up from there. The excellent Scala with Cats will ease you softly into an FP mindset. It's a bit dated and for scala 2 only but translating to Scala 3 is a very good exercise if you feel so inclined !

Last but not least, Scala is currently the language with one of the best effect systems in my opinion (https://zio.dev/). Kotlin for example has copied the approach with https://arrow-kt.io/ which I think is great actually. But when comparing Scala and Kotlin here, Scala wins by a large margin, it is a completely different world. It's like building a highly concurrent system in Erlang vs C.

Of course, if you don't want to learn things like union types, traits/typeclasses and effects (similar to async/await but more powerful) you will be annoyed by Scala. But once you learned them, you can never go back.

ZIO

Links: - https://dotty.epfl.ch/ - https://scala-native.org/en/stable/ - https://www.scala-js.org/ - https://typelevel.org/ - https://zio.dev/ - https://github.com/scala-native/scala-native/pull/3120 - https://github.com/lampepfl/dotty/pull/16517 - https://dotty.epfl.ch/docs/reference/experimental/index.html - https://scala-cli.virtuslab.org/ - https://scalameta.org/metals/ - https://docs.scala-lang.org/scala3/guides/migration/compatibility-intro.html - https://www.scala-lang.org/blog/2023/04/18/faster-scalajs-development-with-frontend-tooling.html - https://www.scala-lang.org/blog/2022/08/17/long-term-compatibility-plans.html

For the Rx approach, The ZIO framework for Scala has a streaming API that can meet those sorts of requirements. e.g.

This tutorial will introduce how to build from scratch, a REST microservice using the ZIO framework, and examples of ZIO dependency injection, ZIO HTTP, JSON, JDBC, and others from the ZIO environment. The source code is available here

I use ZIO (http://zio.dev) for Scala which makes parallel programming trivial.

Wraps different styles of asynchronicity e.g. callbacks, futures, fibers into one coherent model. And has excellent resource management so you can be sure that when you are forking a task that it will always clean up after itself.

Have yet to see anything that comes close whilst still being practical i.e. you can leverage the very large ecosystem of Java libraries.

The one advantage Rust has over Scala is that it detects data races at compile time, and that's a big time saver if you use low level thread synchronization. However, if you write pure FP code with ZIO or Cats Effect that's basically a non-issue anyway.