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Or you could start with mypyc [1] first and if the results do not please you, then you can use Cython; some folks don't want to learn yet another programming syntax, even though it's Pythonic enough to learn it in a rather short period of time, but still...
https://github.com/mypyc/mypyc
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Sevalla
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maturin
Build and publish crates with pyo3, cffi and uniffi bindings as well as rust binaries as python packages
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A while back I concluded that you could code up most of the examples from
https://www.amazon.com/Paradigms-Artificial-Intelligence-Pro...
in Python without doing anything too out of the ordinary. I just finished
https://www.amazon.com/Lisp-Advanced-Techniques-Common/dp/01...
and came to almost the same conclusion in that most of the macro use in that book is in the syntactic sugar or performance optimization category and I didn't have a lot of projects in the queue and people demanding my time I'd try coding up the ATN and Prolog examples in Python (sorta kinda did the "CLOS" example in that I built a strange kind of meta-object facility that made "objects" backed by RDF triples)
In Java I did enough hacking on this project
https://github.com/paulhoule/ferocity/blob/main/ferocity0/sr...
to conclude I could create something that people who think "Java Sux" and "Common Lisp Sux" would really hate. If I went forward on that it would be to try "code golf not counting POM file size" by dividing ferocity into layers (like that ferocity0 which is enough to write a code generator that can stub the whole stdlib) so I could use metaprogramming to fight back against the bulkification you get from writing Java as typed S-expressions. (I'm pretty sure type erasure can be dealt with if you aren't interested in JDK 10+ features like var and switch expressions, on the other hand a system like that doesn't have to be able to code generate syntactic sugar sorts of structures because ferocity is all about being able to write syntatic sugar)
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