spring-fu
kotlindl
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spring-fu | kotlindl | |
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12 | 16 | |
1,662 | 1,391 | |
0.0% | 1.9% | |
0.0 | 5.7 | |
8 months ago | 6 months ago | |
Java | Kotlin | |
Apache License 2.0 | Apache License 2.0 |
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spring-fu
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What's New in Spring Framework 6.1
The point isn't that one should reinvent the way that Tomcat is started, but that Spring Boot (by default) is using action at a distance and runtime reflection which have serious downsides if you want to understand what's actually going on because you're a) new to the technology, or b) have to debug some weird edge case.
The alternative is using explicit, reflection-less code - which you can do even with Spring, although it's experimental: https://github.com/spring-projects-experimental/spring-fu
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What are some of the biggest problems you personally face in Java?
Bean Definition -> Still needed although experimental projects like Spring Fu might remove their need in the future. Technically, there is nothing to stop you from registering beans functionally right now but the verbosity is likely to make that approach less optimal.
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I hate Spring (the Java framework)
Quarkus just moves the problem IMHO. I find it similarly convoluted to use as normal Spring. I had to deal with that a few months ago on a project. Honestly, it actually feels a lot like spring used to be; and not in a good way. Lots of annotation magic all over the place.
I use Spring Boot by default. But I aggressively limit the use of annotation magic. I've never liked the byte code hacks people do to make annotations inject magical behavior. Hard to debug and painful when it does not work as expected.
I don't think either of these frameworks have an edge over each other. You end up using a lot of the same underlying library ecosystem.
I do like the annotation less direction that Spring has been taking since they started adding Kotlin support 4-5 years ago. If you want to, you can get rid of most annotations for things like dependency injection, defining controllers, transactions etc.
Especially with Kotlin, this makes a lot of sense. With Java, dealing with builders is just a lot more painful without kotlin's DSL support. You basically end up with a lot of verbosity, method chaining, etc. But it's possible if you want to. It's a big reason, I prefer using Kotlin with Spring Boot. Makes the whole thing feel like a modern framework. The hard part with Spring Boot is being able to tell apart all the legacy and backwards compatible stuff from the actual current and proper way of doing things.
There's a project that they've been pushing to get rid of all annotations: https://github.com/spring-projects-experimental/spring-fu/tr.... I suspect a lot of that stuff might be part of spring boot 3.x later this year. And quite a bit of it is actually already part of the current version of Spring.
This makes spring boot very similar to what you'd do with ktor. All you do is call kotlin functions. No annotations. No reflection. No magic. Very little verbosity. It's all declarative. And a nice side effect is also that it makes things like spring-native easier, which they started supporting recently.
It's very similar to using ktor with koin (for dependency injection). That combination is worth a try if you are looking for something lightweight and easy to use. Spring Boot has more features and complexity but it can be as simple to use as that if you know what you are doing.
Mostly, keeping things simple is a good thing with Spring. Also, I don't tend to do everything the spring way. Spring integration is a bit of a double edged sword for example. It offers a subset of the features of the libraries that it integrates. If you want the full feature set, you end up working around that. IMHO, you should do that by default. I've removed spring integration from several projects.
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Scala at Scale at Databricks
> And that is a problem how? Stick to one style.
Switching an API from "a result or nothing" to "a result or an error message" happens all the time, and switching in the other direction is only slightly less frequent. And of course most programs have some APIs where one is appropriate and some where the other is. So consistency is valuable.
> https://github.com/spring-projects-experimental/spring-fu/tr...
Still reflection-based.
> There's nothing magical about it.
It's magical to anyone thinking in the language - it breaks the rules of the language, so you can't reason about what it does.
> Kotlin is an unmaintainable soup of features
Are you sure you're not confusing Kotlin with Scala?
> For example, Kotlin has null safety and it lets you write code using errors-as-values style "either" types - but it has two completely separate syntaxes for these things, and so it's impossible to interoperate or reuse code between those two approaches
And that is a problem how? Stick to one style.
> In practice Kotlin codebases still use magical incomprehensible reflection (Spring Boot)
https://github.com/spring-projects-experimental/spring-fu/tr...
> and magical compile-time manipulation (Kapt)
There's nothing magical about it.
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A new way to construct objects in Java
SpringFu (from Spring team): https://github.com/spring-projects-experimental/spring-fu/tree/main/jafu
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Annotation-free Spring
It's mentioned in the article, even though the examples are written in Kotlin spring-fu supports a java-based dsl.
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Kotlin Team AMA #3: Ask Us Anything
Longer term : getting rid of kotlin-reflect in Spring Framework by performing Kotlin reflection ahead-of-time and continuing to mature https://github.com/spring-projects-experimental/spring-fu for a more DSL-ish way of configuring Spring Boot are my favorite topics.
There is already a very close collaboration between Kotlin and Spring teams. I think leveraging more multiplatform capabilities and more DSL à la KoFu from https://github.com/spring-projects-experimental/spring-fu could increase Koltin usage on server side long term.
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The Modern Java Platform
There's a next stage after annotations. The current thinking is to replace annotations with function calls. It makes more sense if you use Kotlin because Java is a bit verbose when you do this and in Kotlin you get to create nice DSLs. This cuts down on use of reflection and AOP magic that spring relies on and also enables native compilation. It also makes it easier to debug and it makes it much easier to understand what is going on at the price of surprisingly little verbosity. Kofu and Jafu are basically still experimental but work quite nicely https://github.com/spring-projects-experimental/spring-fu/tr...
Another trend is native compilation. Spring native just went into beta (uses the Graal compiler). That still relies on reflection but they re-engineered the internals to be more native friendly.
Spring Boot basically added the notion of autoconfiguring libraries that simply by being on the classpath self configure in a sane way. It's one of those things that makes the experience a bit more ruby on rails like. Stuff just works with minimal coding and you customise it as needed (or not, which is perfectly valid).
Compared to XML configuration, Spring has come a long way. Separating code and configuration is still a good idea with Spring but indeed not strictly enforced. @Configuration classes can take the place of XML and if you use the bean dsl, that's basically the equivalent of using XML. Only it's type checked at compile time and a bit more readable.
kotlindl
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Kotlin Deep Learning Android app - Working
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
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What libraries do you use for machine learning and data visualizing in scala?
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.
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KotlinDL 0.3 Is Out With ONNX Integration, Object Detection API, 20+ New Models in ModelHub, and Many New Layers
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?
Introducing version 0.3 of our deep learning library, KotlinDL.
The answer to the second question (from the GitHub page):
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Machine Learning in Kotlin (Question)
I'm not in Machine Learning but maybe KotlinDL ?
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.
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Numpy for kotlin
For deep learning this is your best bet: https://github.com/jetbrains/kotlindl
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Kotlin Team AMA #3: Ask Us Anything
Please, visit our tutorials and examples for KotlinDL. It covers all possible use-cases for AI implementation at this moment.
Regarding AI: currently, you implement neural networks for solving classification and regression tasks for tabular data, or in Computer Vision with Kotlin Deep Learning Library (KotlinDL).
What are some alternatives?
koin - Koin - a pragmatic lightweight dependency injection framework for Kotlin & Kotlin Multiplatform
compose-multiplatform - Compose Multiplatform, a modern UI framework for Kotlin that makes building performant and beautiful user interfaces easy and enjoyable.
KorGE - KorGE Game Engine. Multiplatform Kotlin Game Engine
htmx - </> htmx - high power tools for HTML
Decompose - Kotlin Multiplatform lifecycle-aware business logic components (aka BLoCs) with routing (navigation) and pluggable UI (Jetpack Compose, SwiftUI, JS React, etc.)
tensorflow-keras-scala - Scala-based Keras API for the Java bindings to TensorFlow. Mirror of https://codeberg.org/sciss/tensorflow-keras-scala
kotlin-wrappers - Kotlin wrappers for popular JavaScript libraries
teavm - Compiles Java bytecode to JavaScript, WebAssembly and C
kotlinx.html - Kotlin DSL for HTML
kotlinx-datetime - KotlinX multiplatform date/time library
javalin - A simple and modern Java and Kotlin web framework [Moved to: https://github.com/javalin/javalin]