Hello all,
I am interested in making a non-trivial improvement to list.sort(), but
before I put in the work, I want to test the waters and see if this is
something the community would accept. Basically, I want to implement radix
sort for lists of strings. So list.sort() would detect if it is sorti
On Sun, Sep 11, 2016 at 5:45 PM, Elliot Gorokhovsky
wrote:
> I am interested in making a non-trivial improvement to list.sort(), but
> before I put in the work, I want to test the waters and see if this is
> something the community would accept. Basically, I want to implement radix
> sort for list
> On Sep 11, 2016, at 12:45 AM, Elliot Gorokhovsky
> wrote:
>
> I am interested in making a non-trivial improvement to list.sort(), but
> before I put in the work, I want to test the waters and see if this is
> something the community would accept. Basically, I want to implement radix
> sort
Thanks for the link. If you look at the conclusion it says "We recommend
American flag sort as an all-round algorithm for sorting strings."
On Sun, Sep 11, 2016, 11:30 AM Raymond Hettinger <
raymond.hettin...@gmail.com> wrote:
>
> > On Sep 11, 2016, at 12:45 AM, Elliot Gorokhovsky
> wrote:
> >
>
> I am interested in making a non-trivial improvement to list.sort() [...]
Would your proposed new sorting algorithm be stable? The language
currently guarantees stability for `list.sort` and `sorted`.
--
Mark
___
Python-Dev mailing list
Python-Dev@pyt
The sort can be made stable, but that requires the allocation of an
equal-sized auxiliary array. To quote from the paper: "Both list-based and
two-array sorts entail Θ(n) space overhead. That overhead shrinks to
Θ(logn) in American flag sort, which, like quicksort, trades off stability
for space ef
On Sun, Sep 11, 2016 at 7:43 PM, Elliot Gorokhovsky
wrote:
> So I suppose the thing to do is to benchmark stable radix sort against
> timsort and see if it's still worth it.
Agreed; it would definitely be interesting to see benchmarks for the
two-array stable sort as well as the American Flag un
> On Sep 11, 2016, at 11:58 AM, Mark Dickinson wrote:
>
>> So I suppose the thing to do is to benchmark stable radix sort against
>> timsort and see if it's still worth it.
>
> Agreed; it would definitely be interesting to see benchmarks for the
> two-array stable sort as well as the American
On 9/11/2016 3:45 AM, Elliot Gorokhovsky wrote:
Hello all,
I am interested in making a non-trivial improvement to list.sort(),
This is non-trivial, and harder than you seem to think it is.
> but
before I put in the work, I want to test the waters and see if this is
something the community wo
[redirected from python-dev, to python-ideas;
please send followups only to python-ideas]
[Elliot Gorokhovsky ]
> ...
> TL;DR: Should I spend time making list.sort() detect if it is sorting
> lexicographically and, if so, use a much faster algorithm?
It will be fun to find out ;-)
As Mark, and
On 09/11/2016 10:48 PM, Terry Reedy wrote:
[...]
Second, with respect to timsort in particular: timsort is designed to
exploit structure and run faster than O(n*logn) in special cases. If a
list is already sorted, timsort will do one O(n) scan and stop. Any
radix sort will take several times lo
Wow, Tim himself! Regarding performance on semi-ordered data: we'll have to
benchmark to see, but intuitively I imagine radix would meet Timsort
because verifying that a list of strings is sorted takes Omega(nw) (which
gives a lower bound on Timsort), where w is the word length. Radix sort is
Theta
On Sep 11 2016, Terry Reedy wrote:
> Tim Peters investigated and empirically determined that an
> O(n*n) binary insort, as he optimized it on real machines, is faster
> than O(n*logn) sorting for up to around 64 items.
Out of curiosity: is this test repeated periodically on different
architecture
On Tue, Sep 13, 2016, at 13:24, Nikolaus Rath wrote:
> On Sep 11 2016, Terry Reedy wrote:
> > Tim Peters investigated and empirically determined that an
> > O(n*n) binary insort, as he optimized it on real machines, is faster
> > than O(n*logn) sorting for up to around 64 items.
>
> Out of curios
[Terry Reedy ]
>> Tim Peters investigated and empirically determined that an
>> O(n*n) binary insort, as he optimized it on real machines, is faster
>> than O(n*logn) sorting for up to around 64 items.
[Nikolaus Rath ]
> Out of curiosity: is this test repeated periodically on different
> architect
Nikolaus Rath writes:
> Out of curiosity: is this test repeated periodically on different
> architectures? Or could it be that it only ever was true 10 years
> ago on Tim's Power Mac G5 (or whatever he used)?
This is the same Tim Peters of the eponymous test for readability of
syntax: "Syntax
On Sep 13 2016, Tim Peters wrote:
> [Terry Reedy ]
>>> Tim Peters investigated and empirically determined that an
>>> O(n*n) binary insort, as he optimized it on real machines, is faster
>>> than O(n*logn) sorting for up to around 64 items.
>
> [Nikolaus Rath ]
>> Out of curiosity: is this test re
17 matches
Mail list logo