libwebsockets VS java

This is just the endemic result of C++ lacking a package manager.

Every library starts out small, adds its own vendored utilities, adds its own dependencies, and eventually becomes boost.

To be fair to this project, theyve worked quite hard to make the library consumable by others… but yes, its hard to look at the code like https://github.com/warmcat/libwebsockets/blob/50ba61082dc40b...

…and not go… really? As part of the core of libwebsocket?

When you read the justification it’s mostly “well we have a good framework now, so why not use it for other things too?”

C++ life.

/shrug

I'm trying to setup a project using libwebsockets.

Libwebsockets a powerful and lightweight pure C library\ (48 comments)

and how others have implemented the client

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.

Hope this is not too late to answer your question. In theory there are no official Java tutorials for Tensorflow 2. The Java implementation is still under development at https://github.com/tensorflow/java

To give a contrasting perspective, I think the Java ecosystem is much better suited for many data science tasks, and has a growing and well-maintained set of libraries for general purpose machine learning. I won't list them all, but TF-Java, DJL et al. have implementations of many modern architectures and there are a number of excellent libraries (CoreNLP, Lucene et al.) for working with text.

Here's the latest java git repo https://github.com/tensorflow/java