I know but I thought there was something in the implementation that made it
quicker than a plain for loop. Thinking about it though that's probably only
if you're building a list in your loop. Oh well.

2009/7/16 Richard Jones <[email protected]>

> List comp is a for loop with the added overhead of constructing a list :-)
>
>
>     Richard
>
> Posted from my superabacus
>
> On 16/07/2009, at 8:42 AM, Adam Bark <[email protected]> wrote:
>
> That's what I thought, how about a list comp though? They're sometimes
> quicker. Oh of course if you only need to run it on x86 you could use psyco
> to speed up that section of the code.
>
> 2009/7/15 Richard Jones < <[email protected]>[email protected]>
>
>>
>> Using map/lambda is always going to be much slower than a for loop.
>>
>>
>>     Richard
>>
>> On 16/07/2009, at 4:43 AM, rollbak wrote:
>>
>> >
>> > I think the fastest approach using just python is to use map built-in
>> > function.
>> >
>> > If you have the following loop:
>> > eg: for s in sprites:
>> >       s.update(dx,dy)
>> >
>> > you can re-write it like this:
>> > eg: map(lambda s: s.update(dx,dy))
>> >
>> > regards,
>> >
>> > Lucas
>> >
>> > On Jul 14, 12:05 pm, Eric Burgess <[email protected]> wrote:
>> >> Pyglet provides some great ways to reduce function-call overhead for
>> >> sprites (groups and batches).  But I still find myself looping
>> >> through
>> >> X sprites Y times a second, where X*Y can get quite large, doing
>> >> things like "x+=dx;y+=dy".  I know there are packages like SciPy that
>> >> can add an entire "dx" array to an "x" array at C-speed, but I'd
>> >> rather not add the dependency.
>> >>
>> >> Is there a "best practice" for doing this sort of thing in pure
>> >> Python?
>> > >
>>
>>
>>
>>
>
>
>
> >
>

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