How to make Python run as fast (or faster) than Julia

[Chris Angelico]

On Tue, Feb 27, 2018 at 2:02 AM, bartc <bc at freeuk.com> wrote:
> On 26/02/2018 14:04, bartc wrote:
>>
>> On 26/02/2018 13:42, Ned Batchelder wrote:
>
>
>>   Well, once you notice that the
>>>
>>> Python code had N=1e5, and the C code had N=1e9 :)   If you want to
>>> experiment, with N=1e5, the final number should be 5255210926702073855.
>>
>>
>> OK, I'll try that.
>
>
> I have that Python version working now. It's necessary to apply that masking
> function to wherever numbers can get bigger.
>
> I don't know how long a 1-billion loop will take, but a 10-million loop took
> 46 seconds on Python 3.6, and 21 seconds on PyPy 2.7 from a couple of years
> ago. (And on Windows, which has a somewhat slower CPython than Linux.)

You're still reimplementing the C code in Python, which is
inefficient. Have you considered going back to the *actual algorithm*
and implementing that idiomatically in Python? I think you'll find
that (a) the code is more readable, and (b) the run time is much
lower.

ChrisA