koin VS kotlindl

Let's see how we can use Koin to achieve Dependency Injection (DI) and incorporate a third-party iOS Swift SDK in a KMM project. Koin supports KMM development, making it the ideal choice for KMM projects.

Might want to tell koin that : https://insert-koin.io/

New modules allow you to easily build KVision apps with the Ballast opinionated application state management framework. You can see how Ballast (together with Koin) can help you design your application architecture in the new todomvc-ballast example.

I started looking into using Kotlin/JS, and hopefully reusing a bit of code that I have, which is using Dagger and Anvil - which of course are JVM only. So I've been looking for other solutions, namely Koin and Kodein. Koin's multibinding support is... not really amazing (e.g. here, and while Kodein does support multibinding, it doesn't seem to support things like that at the declaration site - everything needs to be specified in a "DI container" (module).

Koin

It's a Koin issue, not compose. Discussed here https://github.com/InsertKoinIO/koin/issues/1079

Now I will finish up saying Hilt is just an opinionated way to dependency injection on Android, but there are simpler frameworks out there such as Koin or Kodein that can help take away a lot of the troubles that can come when you try to make your own framework. Just know that most other frameworks tend to be runtime injection instead of compile time injection like Hilt, which can be helpful to know at compile time if you are missing a dependency in your graph as opposed to runtime when its out in the wild.

I've been using Angular a lot and I like how it works. I'm also a huge fan of koin for kotlin.

for injection, I suggest Koin (https://insert-koin.io/)

This is a really nice sample app (works out of the box) that Jetbrains have made to showcase the capabilities of this Kotlin Deep Learning library https://github.com/Kotlin/kotlindl

There are Java bindings for TensorFlow, but that's quite low level. I tried to see if I can get some Keras API for Scala, but I'm no expert and haven't had enough time to invest in this, so it's stuck in alpha. Maybe I develop it slow burning over the next year. A bit envious that Kotlin has a Keras-like library.

KotlinDL 0.3 is available now on Maven Central with a variety of new features — check out all the changes that are coming to the new release!

Could you please add an issue with your use-case and proposed solution? Or write here more details. Do you need just serialization to objects in memory? or just in bytes?

While KotlinDL seems to be a good solution by Jetbrains, I would personally stick to Java frameworks like DL4J for a better community support and likely more features.

For deep learning this is your best bet: https://github.com/jetbrains/kotlindl

So, the KotlinDL library could solve classification and regression tasks on tabular data and image data.

Thank you for your feedback! Kotlin∇ is a research prototype for building differentiable programs from basic primitives. If you’re looking for a higher-level API, KotlinDL [1] or KInference [2] might be a better fit for building end-user applications such as image, speech or language processing.

[1]: https://github.com/JetBrains/KotlinDL

[2]: https://github.com/JetBrains-Research/kinference/