Currently, no language ports of Timefold Solver are planned. Unfortunately, FFI (foreign function interface) have a terrible performance penalty, and since we would be doing multiple FFI calls for moves, it can easily become 100x slower just from FFI overhead.
This basically means you have two choices:
1. Translate the constraints from the new language to Java bytecode at runtime.
2. Translate the entire solver to a new language.
We did (1) for a bit for CPython, but since CPython bytecode constantly change and break (and is so poorly documented) it was a nightmare to maintain. You can find a blog post of me explaining it a bit more here: https://timefold.ai/blog/java-vs-python-speed. The CPython port is no longer maintained, and has quite a few missing features.
That being said, we have a wide range of ready made models that you can access via an API, which might fit your use case (you can see a list at https://docs.timefold.ai/).
This basically means you have two choices:
1. Translate the constraints from the new language to Java bytecode at runtime. 2. Translate the entire solver to a new language.
We did (1) for a bit for CPython, but since CPython bytecode constantly change and break (and is so poorly documented) it was a nightmare to maintain. You can find a blog post of me explaining it a bit more here: https://timefold.ai/blog/java-vs-python-speed. The CPython port is no longer maintained, and has quite a few missing features.
That being said, we have a wide range of ready made models that you can access via an API, which might fit your use case (you can see a list at https://docs.timefold.ai/).