Light slices + COW

[castironpi at gmail.com]

On May 4, 7:49 am, David <wizza... at gmail.com> wrote:
> >  > D compiles to efficient machine code so Python is at a disadvantage
> >  > even if you use the same syntax (see my first example). You can make
> >  > the Python version faster, but beware of premature optimization.
>
> >  This time I don't agree with this "premature optimization" thing. My
> >  original Python version is just 5 lines long, it's readable enough,
> >  and it's a part of a large library of mine of similar functions, they
> >  must be fast because I use them all the time as building blocks in
> >  programs.
>
> Have you looked into the 'numpy' libraries? Those have highly
> optimized array/numeric processing functions. Also the have a concept
> of getting 'views' when you slice, rather than a full copy.
>
> I also suggest benchmarking your apps which use your libs and see
> where the bottlenecks are. Then you can move those to external
> compiled modules (c/pyrex/cython/shedskin/etc). You can keep your
> slower Python version around as a reference implementation.
>
> >  > What I'dlike to see is a rope[1] module for Python.
>
> >  People have already suggested it, and there's even an implementation
> >  to replace Python strings. It was refused because... I don't know why,
> >  maybe its implementation was too much more complex than the current
> >  one, and it wasn't faster in all situations (and I think Guido wants
> >  data structures that try to replace the basic built-in ones to be
> >  faster in all situations and user-transparent too).
>
> I'd be happy if there was a separate 'rope' class that you could wrap
> arbitrary long sequences in when you need to (the same way that STL
> has it separate to the string class, even though the string class has
> a lot of other optimizations (internal ref counts, etc, to avoid
> unnecessary copies)). Do you know one?
>
> David.

Persistence on the rope class might be trivial; that is, a constant
number of disk modifications be made per state modification.