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Given your background, consider trying out hylang, which transpiles to Python and can use Python libraries. I played around with it a few times a couple years a
by reagan 7y ago
Given your background, consider trying out hylang, which transpiles to Python and can use Python libraries. I played around with it a few times a couple years ago, but never developed a serious project due to limited tooling. The situation might have since improved.
I've considered putting together an LSP server for it because it'd fun to use for personal projects and scripting.
- cutler 7y agoYes, another vote for Hy. Just wish they had some more manpower to take it to 1.0. Be aware of "let" in Hy, though, as it's been removed from the core and now lives in contrib. "let" is a major part of any Lisp IMHO.
- rcarmo 7y agoYeah, that was one of the main reasons I stopped using it. They’re doing async now (which was another), but having let as a contrib macro and not in core still puts me off a bit. I wrote my entire blog engine on it - https://github.com/rcarmo/sushy/tree/master/sushy https://github.com/rcarmo/sushy/tree/master/sushy - and then ported it back to Python 3
- mark_l_watson 7y agoHylang is definitely interesting. I experimented with it an TensorFlow and eventually everything worked OK. As someone else here mentioned, Python is where most of the deep learning action is. In the end, I settled in using Python for deep learning and use a thin REST service to use my models from Common Lisp or Haskell. Another approach I used was to convert saved Keras models to something I could import into Racket. But back to the topic: Hylang is a very cool project and does let you mix Lisp and Python.