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Comment by gmantastic | Hacker News Reader

It's selectively adding C-like type declarations to Python code speed up the slow bits. C code is then generated and compiled into a Python extension module. This is similar to adding type information to Common Lisp code to allow the compiler to optimise it.

http://docs.cython.org/src/quickstart/cythonize.html

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My impression was that you sometimes have to refactor your Python to make the code more C-like. From what I have heard generators aren't supported, and there are other situations where you need to make your loops (and other elements of your code) more C-like.

That's not the case?

You just add typing to your python and you're good to go?

There's some info on semantic differences here: http://docs.cython.org/src/userguide/limitations.html - it doesn't bring up much, and the design goal is full language compatibility. I've only played with it so far, but it's case of optionally adding type info, and also writing some distutils scaffolding to say how to build the module as a cython extension. This is then callable from Python via the regular import mechanism.

Thanks for the link. I was just poking around the Cython site myself, and it looks like they've come a long way since I last looked into it. It seems that they're getting much closer to full compatibility.

It makes me wonder if we're closing in on the day when Cython gets rolled into Python proper, and you can just "import static-types" to activate optional typing, then add some static typing to your code, and you would get Java performance from your Python code.

"and you would get Java performance from your Python code."

Nah, I doubt it would ever use _that_ much memory.

:) I guess what I meant to say was Java speed (or greater) Python.

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