I have only read the posts on this thread, but the description sounded more like a AOT compiler (like Cython, Pythran, Nuitka) than a JIT compiler (like PyPy or Numba).
PS : PyPy has its own codegen AFAIK, it doesn't use LLVM.
On Sun, 8 Sep 2019 12:28:45 -0400 David Mertz email@example.com wrote:
Also PyPy and Numba.
Cython actually seems a bit different. Without annotations in a superset language, Cython programs mostly just use the same CPython runtime libraries. However, with a few type annotations sprinkled in (but not actual Python syntax), it can get big speedups).
PyPy actually tried to do direct-to-machine-code for a while. But my understanding is that they decided—as did Numba—that building on top of the work of LLVM was more effective (and more cross-architecture).
Obviously, the ad for a commercial product leaves a bad taste in my mouth. But it's also not like there aren't already 5 or more open source projects that do a similar thing better already.
On Sun, Sep 8, 2019, 12:03 PM Antoine Pitrou solipsis-xNDA5Wrcr86sTnJN9+BGXg@public.gmane.org wrote:
How is your approach different from, say, Cython, Nuitka or Pythran?
On Sun, 08 Sep 2019 15:56:04 -0000 "Mark @pysoniq" firstname.lastname@example.org wrote:
The availability of a free extension every 30 days is a big benefit to
the Python community that may not be immediately obvious. That’s not your standard freemium, as it has all the “features” of the paid product -- full registers, multicore, SIMD and other optimizations – so when we say it’s $600 per year of advanced software, that’s true. Our view is that the free extension every 30 days can make a huge difference to a developer with funding limitations (like us). If that free extension makes their project much more successful, then the entire Python community benefits.
We considered this as an open source project, but we haven’t done that
for two reasons:
We have looked for and not found a large enough community of volunteers
who have the skills to translate Python directly to assembly language without intermediate representation, and optimize the instructions, to make it open source.
Open source projects are often very underfunded and don’t have enough
volunteers even from a larger pool of possible people. For example, at PyCon 2019 Victor Stinner eloquently discussed the funding problems at python.org – a shrinking volunteer base and growing issues list.
If I am wrong and there is a large enough group with the requisite
skills, then of course we’re very open to the idea of open source, but the technologies used are very leading edge. And again, if you view it with nuance, the $600 a year (12 extensions) could make a huge difference to an under-funded project, of which there are many!
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