Hi, Jeff,

Von: Jeff Hardy
> On Tue, Jun 3, 2014 at 1:39 PM, Doug Blank <doug.bl...@gmail.com> wrote:
>> 2) A pure-Python version would be a lot of work (perhaps building on PyPy's 
>> RPython version and converting their C) and be slow, but would be little 
>> maintenance as most of the details for the current version of numpy would be 
>> static. Requires generic Python skills to develop (a large group of people 
>> have these skills; any generic Python implementation could use).

> Anything that we can share with the PyPy/Jython teams will be a huge 
> advantage. Having a pure-Python implementation would at least allow it to 
> work, even if it wouldn't be fast (except on PyPy). It might also be a huge 
> amount of work, but if it's shared between three smallish communities it 
> might not be too bad.

I think one of the problems is to avoid the boxing of doubles to objects when 
they're stored in arrays / vectors.

> I just don't know enough about the architecture of numpy to say for sure - 
> which parts are Python, which are Cython, and which are hand-written CPython 
> modules. If they're going to depend on Cython, it's worth investing in a C# 
> backend for that (unless we can generate cross-platform C++, but .NET Native 
> might make that irrelevant anyway). It would also enable the wonderful Pandas 
> library, hopefully. Getting an idea from the numpy team where they're headed 
> would be a good idea before investing too much work in any case.

As far as I can see, IronPython is JITted after being translated by the DLR. 
Maybe we could enhance that process to involve some type inference (similar to 
RPython) where possible, and to use Cython style type hints.

With the appropriate type mappings (and possibly some hints), this could allow 
an "pure" Python version to get full .NET speed (e. G. by using .NET arrays of 
.NET double instead of python arrays).



Best regards

Markus Schaber

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