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I use numba quite a bit, and with every new version, the developers have notes like: PR #1970: Optimize the power operator with a static exponent. PR #1961: Su
by bmer 10y ago
I use numba quite a bit, and with every new version, the developers have notes like:
PR #1970: Optimize the power operator with a static exponent.
PR #1961: Support printing constant strings.
PR #1927: Support np.linalg.lstsq.
My point being that the developers have to go about re-implementing (in LLVM IR?) features that are very mature in C libraries (e.g. numpy) and similarly C++ libraries.
Could it be that one gain of going from Python to C++ will be that one could take advantage of all the mature libraries that C++ has access to, without having to do this re-inventing of the wheel?
I am not sure, and regardless, I'll be using numba for a long time coming, because...I like the devs, they work hard on it, and numba works like a charm for what I need to do, so I'm not looking for an overkill.
- nerdponx 10y agoThat makes sense. Numba aside, though, it's strange to me that I see no mention of Cython on their project page. They ought to at least acknowledge that other fairly mature products exist in this space. Also, maybe it's more of a curiosity for you than a practical tool, but Stan (which is becoming the de-facto standard DSL for Bayesian statistics) compiles to C++, where it takes advantage of libraries like Eigen and Boost.
- bmer 10y agoThat's a really good point---Cython doesn't have the same issues, it's basically Pythran except it compiles to C. Yeah, no clue.