On Thu, Mar 14, 2013 at 7:50 PM, Ronan Lamy <[email protected]> wrote:
> Le 14/03/2013 09:42, Ondřej Čertík a écrit :
>
>> Mateusz and I discussed this last few days (I visited him in Wroclaw) and
>> I think we both agreed that a good idea is for me (or others) to
>> finish the experimental
>> C++ core (https://github.com/certik/csympy) so that we can run some
>> benchmarks and play with several things like hashes and
>> canonicalization and at the same time keep
>> working sympy (assumptions as you wrote, and other things).
>>
>> The general idea is to have an API, so that we can keep sympy in pure
>> Python by default,
>> but if needed, be able to use a faster C++ core for the raw symbolics.
>> One thing is to decouple the core a little bit more from the rest of
>> sympy, which should happen anyway.
>
>
> Reimplementing all the core in C++ sounds like a crazy amount of work,
> especially since the core actually pulls in half of sympy. Even if you
> manage it, I seriously doubt that the 2 implementations could be kept in
> sync either. So I don't think it's worth it. (Well, it's your time, though.
> You're obviously free to spend it however you like)

Haha, so is SymPy in Python. ;) But we did that anyway.

>
>
>>
>> In general, I think it's quite amazing how fast Python actually is,
>> that sympy can compete very well
>> with for example Maxima, if the right data structures and algorithms
>> are used. So I think it's a good idea
>> to keep sympy in pure Python. But have an optional C++ core is
>> something that I feel is necessary, if nothing, at least to have an
>> idea of how fast one can get.
>
>
> If you want to see how fast one can get, it's probably way easier to use
> PyPy (making sure that you're measuring jitted code, and to exclude the
> compilation overhead).

Hm, our Cython code (https://github.com/certik/sympyx) is much faster
already than anything that I was able to do in pypy. But maybe they
got faster. I'll be happy to be proven wrong.

Ondrej

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