New Python implementation

[Christian Gollwitzer]

Am 14.02.21 um 11:12 schrieb Paul Rubin:
> Christian Gollwitzer <auriocus at gmx.de> writes:
>> He wants that neoGFX is scriptable in Python, but instead of linking
>> with CPython, he will write his own Python implementation instead,
>> because CPython is slow/not clean/ whatever. He doesn't seem to
>> understand that this is an enormous task on its own, because the
>> interesting part of a scripting language is the standard library with
>> many decade-years of work.
> 
> I wonder how big an issue the stdlib really is.  Lots of it is written
> in Python and can port to another interpreter.  Lots more is CPython C
> API bindings to external C libraries (e.g. OpenSSL) so porting those
> would be a matter of rebinding those libraries to libffi in the cases
> where that hasn't been done already.

I'm not saying that it is unfeasible or very difficult. I'm saying that 
it is a lot of work, and for a single developer who has this as a side 
project / support for his graphics engine and who wants to beat existing 
implementations wrt. speed, I'm saying it is going to take a lot of 
time. It'definitely impossible by "defining a few JSON schema files", as 
Leigh claims with his "universal compiler". There definitely IS a lot of 
stuff in a baseline CPython interpreter - a (seemingly) simple thing 
like "print" will have an implementation of 1000 lines in C with all the 
formatting library, file I/O etc. Arbitrary precision integers - another 
library, networking - yet another and so on.

> CPython really is pretty slow, maybe because it uses so much boxed data,
> derps around with refcounts all the time, suffers memory fragmentation
> from not having a relocating GC, etc.  And that is before we even
> mention the GIL.

I don't argue with that. CPython is slow. But I'm arguing that you can't 
make it faster by multiple orders of magnitude unless you change the 
language. For numerical code, straight-forward C is usually 100x to 
1000x faster than Python, and you can reach the same performance by 
giving up dynamic typing - Cython demonstrates this quite convincingly. 
If you don't want static typing (with types close to the machine like 
fixed-width integers) than you'll have to resort to a LOT of black magic 
to even come close (PyPy, modern JS engines, ....)

	Christian