On Tue, Jan 20, 2015 at 11:48:10AM +0200, Paul Sokolovsky wrote:
> Hello,
>
> On Tue, 20 Jan 2015 18:15:02 +1300
> Greg Ewing <greg.ew...@canterbury.ac.nz> wrote:
>
> > Guido van Rossum wrote:
> > > On Mon, Jan 19, 2015 at 11:43 AM, Paul Sokolovsky
> > > <pmis...@gmail.com <mailto:pmis...@gmail.com>> wrote:
> > >
> > > b.lower_inplace()
> > > b.lower_i()
> > >
> > > Please don't go there. The use cases are too rare.
> >
> > And if you have such a use case, it's not too
> > hard to do
> >
> > b[:] = b.lower()
>
> The point of inplace operations (memoryview's, other stuff already in
> Python) is to avoid unneeded memory allocation and copying. For 1Tb
> bytearray with 1Tb of RAM, it will be very hard to do. (Ditto for 100K
> bytearray with 150K RAM.)
You can just loop through the bytearray and assign elements. I use
something along the lines of this for PyParallel where I'm operating on
bytearrays that are backed by underlying socket buffers, where I don't
want to do any memory allocations/reallocations:
def toupper_bytes(data):
assert isinstance(data, bytearray)
a = ord('a')
z = ord('z')
for i in range(0, len(data)):
c = data[i]
if c >= a and c <= z:
data[i] = c - 32
Low overhead, mostly stays within the same ceval frame. Should be a
walk in the park for PyPy, Cython or Numba to optimize, too.
Trent.
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