array, list, performance...
tim.one at comcast.net
Fri Jun 7 20:26:18 CEST 2002
> li = [x0, x1, x2, ...]
> li.append(x) appending is O(1)
> (actually, it SOMETIMES takes O(len(li)) as it
> resizes the list. But if you grow a list by
> continually appending, the amortized time is
> linear (ie, constant amortized time per element)
> Append is often enough linear in the length of the list
> that growing by appending is O(len(li) * len(li)).
> For Python 2.2 Michael is correct. For Python 2.1 and earlier, you're
> correct "in theory", although in practice it was often
> linear-time anyway,> depending on internal details of the platform
[back to Ype]
> Good news.
> Multiplying the list's size by a constant factor when necessary would
> give O(log(len(li)) * len(li)) behaviour, so how was this made
> O(len(li)) in 2.2?
By increasing a list's size (when needed) by an amount proportional to its
> I checked 'What's new in 2.2' but found nothing about this.
Probably not. I don't write up a news item when I optimize away a useless
branch in the code either <wink>. Seriously, it's an internal
implementation detail, and, like I said, it often *acted* linear-time
anyway. The only platforms I know of where it appeared to make a real
difference were assorted flavors of Windows, and some flavor of BSD Unix (I
don't recall which). On those it helped a lot in cases of extreme list
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