struct.Struct lets you encode Python objects into structured memory.
It accepts a format string, and optionally a buffer and offset to/from
which to read/write the structure. What do you think of random access
for the results?
(unproduced)
>>packer= struct.Struct( 'IIIf255p' )
packer.pack_into( buf, off, 10, 20, 30, 0.5, 'abc' )
packer.unpack_from( buf, off, 2 ) #reads field 2
30
Does this take a PEP, or just a patch submission? 6  1255 
On Mon, 25 Aug 2008 13:03:09 -0700, castironpi wrote:
struct.Struct lets you encode Python objects into structured memory. It
accepts a format string, and optionally a buffer and offset to/from
which to read/write the structure. What do you think of random access
for the results?
(unproduced)
>>>packer= struct.Struct( 'IIIf255p' )
packer.pack_into( buf, off, 10, 20, 30, 0.5, 'abc' )
packer.unpack_from( buf, off, 2 ) #reads field 2
30
I don't like it for the same reason I don't like index access on tuples
or lists that represent a "record" -- the numbers are quite meaningless.
Names for the components result in much easier to understand source code,
so I would prefer to use `ctypes` or `construct` to create such a record.
Ciao,
Marc 'BlackJack' Rintsch
On Aug 25, 4:25*pm, Marc 'BlackJack' Rintsch <bj_...@gmx.netwrote:
On Mon, 25 Aug 2008 13:03:09 -0700, castironpi wrote:
struct.Struct lets you encode Python objects into structured memory. It
accepts a format string, and optionally a buffer and offset to/from
which to read/write the structure. *What do you think of random access
for the results?
(unproduced)
>>packer= struct.Struct( 'IIIf255p' )
packer.pack_into( buf, off, 10, 20, 30, 0.5, 'abc' )
packer.unpack_from( buf, off, 2 ) #reads field 2
30
I don't like it for the same reason I don't like index access on tuples
or lists that represent a "record" -- the numbers are quite meaningless. *
Names for the components result in much easier to understand source code,
so I would prefer to use `ctypes` or `construct` to create such a record.
Ciao,
* * * * Marc 'BlackJack' Rintsch
I'm interested in the speed benefit, so you don't have to reconstruct
the entire 'record' just to read/write one 'field'. How in ctypes?
On Aug 25, 4:49*pm, castironpi <castiro...@gmail.comwrote:
On Aug 25, 4:25*pm, Marc 'BlackJack' Rintsch <bj_...@gmx.netwrote:
On Mon, 25 Aug 2008 13:03:09 -0700, castironpi wrote:
struct.Struct lets you encode Python objects into structured memory. It
accepts a format string, and optionally a buffer and offset to/from
which to read/write the structure. *What do you think of random access
for the results?
(unproduced)
>>>packer= struct.Struct( 'IIIf255p' )
>>>packer.pack_into( buf, off, 10, 20, 30, 0.5, 'abc' )
>>>packer.unpack_from( buf, off, 2 ) #reads field 2
30
I don't like it for the same reason I don't like index access on tuples
or lists that represent a "record" -- the numbers are quite meaningless.. *
Names for the components result in much easier to understand source code,
so I would prefer to use `ctypes` or `construct` to create such a record.
Ciao,
* * * * Marc 'BlackJack' Rintsch
I'm interested in the speed benefit, so you don't have to reconstruct
the entire 'record' just to read/write one 'field'. *How in ctypes?
Model the constructor after 'namedtuple' type.
(unproduced)
>>packer= struct.Struct( 'IIIf255p', 'i1', 'i2', 'i3', 'afloat', 'name')
packer.pack_into( buf, off, 10, 20, 30, 0.5, 'abc' )
packer.unpack_from( buf, off, 'i3' )
30
>>packer.unpack_from( buf, off )
( 10, 20, 30, 0.5, 'abc' )
You still get marginal speed benefit in sequential access. You avoid
the construction of n-1 objects.
On Mon, 25 Aug 2008 14:49:14 -0700, castironpi wrote:
I'm interested in the speed benefit, so you don't have to reconstruct
the entire 'record' just to read/write one 'field'. How in ctypes?
Only the field accessed is converted.
Ciao,
Marc 'BlackJack' Rintsch
On Aug 25, 11:47*pm, Marc 'BlackJack' Rintsch <bj_...@gmx.netwrote:
On Mon, 25 Aug 2008 14:49:14 -0700, castironpi wrote:
I'm interested in the speed benefit, so you don't have to reconstruct
the entire 'record' just to read/write one 'field'. *How in ctypes?
Only the field accessed is converted.
Ciao,
* * * * Marc 'BlackJack' Rintsch
I know that. I was asking how to write 'unpack_from( buf, off, 2 )',
when buf is a non-ctypes buffer.
On Aug 26, 12:41*am, castironpi <castiro...@gmail.comwrote:
On Aug 25, 11:47*pm, Marc 'BlackJack' Rintsch <bj_...@gmx.netwrote:
On Mon, 25 Aug 2008 14:49:14 -0700, castironpi wrote:
I'm interested in the speed benefit, so you don't have to reconstruct
the entire 'record' just to read/write one 'field'. *How in ctypes?
Only the field accessed is converted.
Ciao,
* * * * Marc 'BlackJack' Rintsch
I know that. *I was asking how to write 'unpack_from( buf, off, 2 )',
when buf is a non-ctypes buffer.
The code with ctypes is more elegant than I thought.
from ctypes import *
prototype= PYFUNCTYPE( c_int, py_object, POINTER(c_void_p),
POINTER(c_uint) )
PyObject_AsWriteBuffer= prototype( ( "PyObject_AsWriteBuffer",
pythonapi ) )
def refas( buf, offset, tp ):
''' return an instance of |tp| that refers to |offset| bytes into
buffer |buf| '''
_b, _s= c_void_p(0), c_uint(0)
PyObject_AsWriteBuffer( buf, byref(_b), byref(_s) ) #should return
0
c= cast( _b.value+ offset, POINTER( tp ) )
return c.contents
'tp' can be any class that is derived from ctypes.Structure. 'buf'
can be any object that supports the buffer protocol, including
'mmap'. Remember when mapping pointers to store offsets, not memory
addresses.
I'd like to know how supported this is considered to be, across
platforms and versions. Can I rely on this in the future? This thread has been closed and replies have been disabled. Please start a new discussion. Similar topics
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