; interact with systems B and C and so on, and each machine knows what kind it
> is, and especially if it knows which kind of machine left it something in
> shared memory, there has to be a way to coordinate between them. If character
> strings in ASCII or UTF8 or EBCDIC or some kind of
something in
shared memory, there has to be a way to coordinate between them. If character
strings in ASCII or UTF8 or EBCDIC or some kind of raw are allowed, and used
with just a few characters that can spell out numbers, I would think much is
possible. If needed, perhaps a fixed size could be set
> On 2 Feb 2022, at 18:19, Jen Kris via Python-list
> wrote:
>
> It's not clear to me from the struct module whether it can actually
> auto-detect endianness.
It is impossible to auto detect endian in the general case.
> I think it must be specified, just as I had to do with int.from_byte
On Wed, 2 Feb 2022 19:16:19 +0100 (CET), Jen Kris
declaimed the following:
>It's not clear to me from the struct module whether it can actually
>auto-detect endianness. I think it must be specified, just as I had to do
>with int.from_bytes(). In my case endianness was dictated by how the four
y is also not.
>
> -Original Message-
> From: Dennis Lee Bieber
> To: python-list@python.org
> Sent: Wed, Feb 2, 2022 12:30 am
> Subject: Re: Data unchanged when passing data to Python in multiprocessing
> shared memory
>
>
> On Wed, 2 Feb 2022 00:40:22 +0100
It's not clear to me from the struct module whether it can actually auto-detect
endianness. I think it must be specified, just as I had to do with
int.from_bytes(). In my case endianness was dictated by how the four bytes
were populated, starting with the zero bytes on the left.
Feb 1, 202
m: Dennis Lee Bieber
To: python-list@python.org
Sent: Wed, Feb 2, 2022 12:30 am
Subject: Re: Data unchanged when passing data to Python in multiprocessing
shared memory
On Wed, 2 Feb 2022 00:40:22 +0100 (CET), Jen Kris
declaimed the following:
>
> breakup = int.from_bytes(byte_va
On Wed, 2 Feb 2022 00:40:22 +0100 (CET), Jen Kris
declaimed the following:
>
> breakup = int.from_bytes(byte_val, "big")
>print("this is breakup " + str(breakup))
>
>Python prints: this is breakup 32894
>
>Note that I had to switch from little endian to big endian. Python is little
>endian by
let me (and the
> list) know.
By using the struct module you can control for endian of the data.
Barry
>
> Thanks.
>
>
> Feb 1, 2022, 14:20 by ba...@barrys-emacs.org:
>
> On 1 Feb 2022, at 20:26, Jen Kris via Python-list
> wrote:
>
> I am using multipro
on-list
>> wrote:
>>
>> I am using multiprocesssing.shared_memory to pass data between NASM and
>> Python. The shared memory is created in NASM before Python is called.
>> Python connects to the shm: shm_00 =
>> shared_memory.SharedMemory(name='shm_obje
> On 1 Feb 2022, at 20:26, Jen Kris via Python-list
> wrote:
>
> I am using multiprocesssing.shared_memory to pass data between NASM and
> Python. The shared memory is created in NASM before Python is called.
> Python connects to the shm: shm_00 =
> shared_mem
I am using multiprocesssing.shared_memory to pass data between NASM and Python.
The shared memory is created in NASM before Python is called. Python connects
to the shm: shm_00 =
shared_memory.SharedMemory(name='shm_object_00',create=False).
I have used shared memory at other
On Sunday, March 23, 2014 6:37:11 PM UTC+5:30, Jens Thoms Toerring wrote:
> Simon Hardy-Francis wrote:
> > Hi Python fans, I just released my first open source project ever called
> > SharedHashFile [1]. It's a shared memory hash table written in C. Some guy
> > on Quora
Simon Hardy-Francis wrote:
> Hi Python fans, I just released my first open source project ever called
> SharedHashFile [1]. It's a shared memory hash table written in C. Some guy
> on Quora asked [2] whether there's an extension library for Python coming
> out. I would lik
Hi Python fans, I just released my first open source project ever called
SharedHashFile [1]. It's a shared memory hash table written in C. Some guy on
Quora asked [2] whether there's an extension library for Python coming out. I
would like to do one but I know little about Pyt
On 11 apr, 21:11, sturlamolden wrote:
> import numpy as np
> import sharedmem as sm
> private_array = np.zeros((10,10))
> shared_array = sm.zeros((10,10))
I am also using this to implement synchronization primitives (barrier,
lock, semaphore, event) that can be sent over an instance of
multipro
ively use multi-core CPUs.
Then why not let NumPy use shared memory in this case? It is as simple
as this:
import numpy as np
import sharedmem as sm
private_array = np.zeros((10,10))
shared_array = sm.zeros((10,10))
I.e. the code is identical (more or less).
Also, do you think shared memo
On 4/10/2011 3:29 PM, sturlamolden wrote:
On 10 apr, 18:27, John Nagle wrote:
Unless you have a performance problem, don't bother with shared
memory.
If you have a performance problem, Python is probably the wrong
tool for the job anyway.
Then why does Python h
On 8 apr, 03:10, sturlamolden wrote:
> That was easy, 64-bit support for Windows is done :-)
>
> Now I'll just have to fix the Linux code, and figure out what to do
> with os._exit preventing clean-up on exit... :-(
Now it feel dumb, it's not worse than monkey patching os._exit, which
I should h
On 10 apr, 18:27, John Nagle wrote:
> Unless you have a performance problem, don't bother with shared
> memory.
>
> If you have a performance problem, Python is probably the wrong
> tool for the job anyway.
Then why does Python have a multiprocessing module?
In m
ork" (if you're on a *nix machine).
See http://pythonwise.blogspot.com/2009/04/pmap.html for example ;)
Unless you have a performance problem, don't bother with shared
memory.
If you have a performance problem, Python is probably the wrong
tool for the job anyway.
> Now, I don't know that I actually HAVE to pass my neural network and
> input data as copies -- they're both READ-ONLY objects for the
> duration of an evaluate function (which can go on for quite a while).
One option in that case is to use "fork" (if you're on a *nix machine).
See http://pythonwi
On 9 apr, 22:18, John Ladasky wrote:
> So, there are limited advantages to trying to parallelize the
> evaluation of ONE cascade network's weights against ONE input vector.
> However, evaluating several copies of one cascade network's output,
> against several different test inputs simultaneously
have not updated the sharedmem arrays for two
> years is that I have come to the conclusion that there are better ways
> to do this (paricularly vendor tuned libraries). But since they are
> mostly useful with 64-bit (i.e. large arrays), I'll post an update
> soon.
>
> If you
al in terms of
> time and memory usage.
The expensive overhead in passing a NymPy array to
multiprocessing.Queue is related to pickle/cPickle, not IPC or making
a copy of the buffer.
For any NumPy array you can afford to copy in terms of memory, just
work with copies.
The shared memory arrays I
On Apr 7, 6:10 pm, sturlamolden wrote:
> On 8 apr, 02:38, sturlamolden wrote:
>
> > I should probably fix it for 64-bit now. Just recompiliong with 64-bit
> > integers will not work, because I intentionally hardcoded the higher
> > 32 bits to 0.
>
> That was easy, 64-bit support for Windows is do
On 8 apr, 02:38, sturlamolden wrote:
> I should probably fix it for 64-bit now. Just recompiliong with 64-bit
> integers will not work, because I intentionally hardcoded the higher
> 32 bits to 0.
That was easy, 64-bit support for Windows is done :-)
Now I'll just have to fix the Linux code, an
On 8 apr, 02:03, sturlamolden wrote:
> http://folk.uio.no/sturlamo/python/sharedmem-feb13-2009.zip
> Known issues/bugs: 64-bit support is lacking, and os._exit in
> multiprocessing causes a memory leak on Linux.
I should probably fix it for 64-bit now. Just recompiliong with 64-bit
integers will
On 4 apr, 22:20, John Ladasky wrote:
> https://bitbucket.org/cleemesser/numpy-sharedmem/src/3fa526d11578/shm...
>
> I've added a few lines to this code which allows subclassing the
> shared memory array, which I need (because my neural net objects are
> more than just
; allocated before the Pool is started. And this only works on UNIX machines.
> The
> shared memory objects that shmarray uses can only be inherited. I believe
> that's
> what Sturla was getting at.
It's a C extension that gives a buffer to NumPy. Then YOU changed how
NumPy p
On 4/7/11 1:39 PM, John Ladasky wrote:
On Apr 7, 10:44 am, Robert Kern wrote:
On 4/7/11 1:40 AM, John Ladasky wrote:
On Apr 5, 10:43 am, Philip Semanchukwrote:
And as Robert Kern pointed out, numpy arrays are also pickle-able.
OK, but SUBCLASSES of numpy.ndarray are not, in my hands,
On Apr 7, 10:44 am, Robert Kern wrote:
> On 4/7/11 1:40 AM, John Ladasky wrote:
>
> > On Apr 5, 10:43 am, Philip Semanchuk wrote:
> >> And as Robert Kern pointed out, numpy arrays are also pickle-able.
>
> > OK, but SUBCLASSES of numpy.ndarray are not, in my hands, pickling as
> > I would expect.
On 4/7/11 1:40 AM, John Ladasky wrote:
On Apr 5, 10:43 am, Philip Semanchuk wrote:
And as Robert Kern pointed out, numpy arrays are also pickle-able.
OK, but SUBCLASSES of numpy.ndarray are not, in my hands, pickling as
I would expect. I already have lots of code that is based on such
sub
On Apr 7, 2011, at 3:41 AM, John Ladasky wrote:
> Following up to my own post...
>
> On Apr 6, 11:40 pm, John Ladasky wrote:
>
>> What's up with that?
>
> Apparently, "what's up" is that I will need to implement a third
> method in my ndarray subclass -- namely, __reduce__.
>
> http://www.ma
Following up to my own post...
On Apr 6, 11:40 pm, John Ladasky wrote:
> What's up with that?
Apparently, "what's up" is that I will need to implement a third
method in my ndarray subclass -- namely, __reduce__.
http://www.mail-archive.com/numpy-discussion@scipy.org/msg02446.html
I'm burned o
Hello again, Philip,
I really appreciate you sticking with me. Hopefully this will help
someone else, too. I've done some more reading, and will offer some
minimal code below.
I've known about this page for a while, and it describes some of the
unconventional things one needs to consider when s
On Apr 5, 2011, at 12:58 PM, John Ladasky wrote:
> Hi Philip,
>
> Thanks for the reply.
>
> On Apr 4, 4:34 pm, Philip Semanchuk wrote:
>> So if you're going to use multiprocessing, you're going to use pickle, and
>> you
>> need pickleable objects.
>
> OK, that's good to know.
But as Dan Str
Hi Philip,
Thanks for the reply.
On Apr 4, 4:34 pm, Philip Semanchuk wrote:
> So if you're going to use multiprocessing, you're going to use pickle, and you
> need pickleable objects.
OK, that's good to know.
> > Pickling is still a pretty
> > vague progress to me, but I can see that you have
e sure that the shared arrays are
allocated before the Pool is started. And this only works on UNIX machines. The
shared memory objects that shmarray uses can only be inherited. I believe that's
what Sturla was getting at.
I'll take that back a little bit. Since the underlying shared memory
On Apr 4, 2011, at 9:03 PM, Dan Stromberg wrote:
> On Mon, Apr 4, 2011 at 4:34 PM, Philip Semanchuk wrote:
>
>> So if you're going to use multiprocessing, you're going to use pickle, and
>> you need pickleable objects.
>>
>
> http://docs.python.org/library/multiprocessing.html#sharing-state-be
On Mon, Apr 4, 2011 at 4:34 PM, Philip Semanchuk wrote:
> So if you're going to use multiprocessing, you're going to use pickle, and
> you need pickleable objects.
>
http://docs.python.org/library/multiprocessing.html#sharing-state-between-processes
--
http://mail.python.org/mailman/listinfo/pyt
e
duration of an evaluate function (which can go on for quite a while).
So, I have also started to investigate shared-memory approaches. I
don't know how a shared-memory object is referenced by a subprocess
yet, but presumably you pass a reference to the object, rather than
the whole object. Also
> input data as copies -- they're both READ-ONLY objects for the
> duration of an evaluate function (which can go on for quite a while).
> So, I have also started to investigate shared-memory approaches. I
> don't know how a shared-memory object is referenced by a subproces
On Mon, Apr 4, 2011 at 1:20 PM, John Ladasky wrote:
> When should one pickle and copy? When to implement an object in
> shared memory? Why is pickling apparently such a non-trivial process
> anyway? And, given that multi-core CPU's are apparently here to stay,
> should it b
ich can go on for quite a while).
So, I have also started to investigate shared-memory approaches. I
don't know how a shared-memory object is referenced by a subprocess
yet, but presumably you pass a reference to the object, rather than
the whole object. Also, it appears that subprocesses also a
On Feb 12, 3:29 am, John Nagle wrote:
>
> If you're having trouble debugging a sequential program,
> you do not want to add shared memory to the problem.
No, you don't want to add additional concurrent threads of execution.
But he's not doing that, he's just pre
nch of unit tests for the little bits but
something is unhappy when I put them all together...)
If you're having trouble debugging a sequential program,
you do not want to add shared memory to the problem.
John Nagle
--
http://mail.python.org/mailman/listinfo/python-list
it can
> start up quickly and read from the shared memory instead of loading
> the cache itself.
You can fork and set "hard" breakpoint using "import pdb; pdb.set_trace()". Not
sure how Emacs will handle that but you can use pdb from the terminal. For easy
forking see http:
On Feb 11, 6:27 am, Adam Skutt wrote:
> On Feb 10, 9:30 am, "Charles Fox (Sheffield)"
> wrote:
>
> > But when I look at posix_ipc and POSH it looks like you have to fork
> > the second process from the first one, rather than access the shared
> > memory
>
> > > > > So speed up the compile-test cycle I'm thinking about running a
> > > > > completely separate process (not a fork, but a processed launched form
> > > > > a different terminal)
>
> > > > Why _not_ fork? Load up your
On Feb 10, 9:30 am, "Charles Fox (Sheffield)"
wrote:
>
> But when I look at posix_ipc and POSH it looks like you have to fork
> the second process from the first one, rather than access the shared
> memory though a key ID as in standard C unix shared memory. Am I
> missi
ed launched form
> > > > a different terminal)
>
> > > Why _not_ fork? Load up your data, then go into a loop forking and
> > > loading/
> > > running the rest of your code in the child. This should be really
> > > easy to
> > >
your data, then go into a loop forking and
> > loading/
> > running the rest of your code in the child. This should be really
> > easy to
> > implement compared to doing something with shared memory, and solves
> > the
> > problem you're trying to solv
rate process (not a fork, but a processed launched form
> > a different terminal)
>
> Why _not_ fork? Load up your data, then go into a loop forking and
> loading/
> running the rest of your code in the child. This should be really
> easy to
> implement compared to doing some
Load up your data, then go into a loop forking and
loading/
running the rest of your code in the child. This should be really
easy to
implement compared to doing something with shared memory, and solves
the
problem you're trying to solve of long startup time just as well. It
also
protects you
y and read from the shared memory instead of loading
the cache itself.
But when I look at posix_ipc and POSH it looks like you have to fork
the second process from the first one, rather than access the shared
memory though a key ID as in standard C unix shared memory. Am I
missing something? Are
The multiprocessing module has 4 methods for sharing data between processes:
Queues
Pipes
Shared Memory Map
Server Process
Which of these use shared memory?
I understand that the 3rd (Shared Memory Map) does, but what about Queues?
Thanks,
Kevin
On 7/27/2010 12:30 PM, MRAB wrote:
Kevin Ar18 wrote:
I'm not sure my previous message went through (I wasn't subscribe), so
I'm gonna try again.
The multiprocessing module has 4 methods for sharing data between
processes:
Queues
Pipes
Shared Memory Map
Server Process
Which of t
Kevin Ar18 wrote:
I'm not sure my previous message went through (I wasn't subscribe), so I'm
gonna try again.
The multiprocessing module has 4 methods for sharing data between processes:
Queues
Pipes
Shared Memory Map
Server Process
Which of these use shared memory?
I unde
I'm not sure my previous message went through (I wasn't subscribe), so I'm
gonna try again.
The multiprocessing module has 4 methods for sharing data between processes:
Queues
Pipes
Shared Memory Map
Server Process
Which of these use shared memory?
I understand that the 3rd
On Jan 26, 9:20 pm, Aaron Brady wrote:
> Hi, Mark,
snip
> On Jan 25, 9:47 pm, Mark Wooding wrote:> Aaron Brady
> writes:
> > > I am writing an extension using shared memory. I need a data type
> > > that is able to reassign its 'ob_type' field depen
Hi, Mark,
Do you mind if I approach you off the group about this?
Aaron
On Jan 25, 9:47 pm, Mark Wooding wrote:
> Aaron Brady writes:
> > I am writing an extension using shared memory. I need a data type
> > that is able to reassign its 'ob_type' field dependi
'P' sees it. When
> > process 'Q' is looking at it, it needs to have an 'ob_type' that is
> > 'Ta' as process 'Q' sees it. If it referred to 'Ta' in process 'P'
> > when 'Q' was calling it, 'Q&#x
Aaron Brady writes:
> I am writing an extension using shared memory. I need a data type
> that is able to reassign its 'ob_type' field depending on what process
> is calling it.
That sounds scary!
> Object 'A' is of type 'Ta'. When process 'P&#x
Hello,
I am writing an extension using shared memory. I need a data type
that is able to reassign its 'ob_type' field depending on what process
is calling it.
Object 'A' is of type 'Ta'. When process 'P' is looking at it, it
needs to have an 'ob_typ
ms using socket programming,but i
> am not able to put the data in shared memory and then access it.
>
> NOTE:I want to put the data in main memory only once(on the server
> using server program) i.e. whenever client connects to the server it
> should only access the data and not cr
d server programs using socket programming,but i
> am not able to put the data in shared memory and then access it.
>
> NOTE:I want to put the data in main memory only once(on the server
> using server program) i.e. whenever client connects to the server it
> should only access the
memory.Here the server calls a module that
processes the data as per the client request and the returns some
information to the client.
I can create client and server programs using socket programming,but i
am not able to put the data in shared memory and then access it.
NOTE:I want to put the
Blubaugh, David A. schrieb:
Diez,
What you have said is extremely concerning.
I am now using VMware. With Linux as the Master and windows as the
guest operating system. I was wondering if you have ever had to develop
a share memory resource between Linux and windows within a Vmware setup?
Blubaugh, David A. wrote:
Diez,
What you have said is extremely concerning.
I am now using VMware. With Linux as the Master and windows as the
guest operating system. I was wondering if you have ever had to develop
a share memory resource between Linux and windows within a Vmware setup?
will not be forgotten,
David Blubaugh
-Original Message-
From: Diez B. Roggisch [mailto:[EMAIL PROTECTED]
Sent: Tuesday, August 26, 2008 4:54 PM
To: python-list@python.org
Subject: Re: Using Python to shared memory resources between Linux and
Windows
Blubaugh, David A. schrieb:
>
will not be forgotten,
David Blubaugh
-Original Message-
From: Diez B. Roggisch [mailto:[EMAIL PROTECTED]
Sent: Tuesday, August 26, 2008 4:54 PM
To: python-list@python.org
Subject: Re: Using Python to shared memory resources between Linux and
Windows
Blubaugh, David A. schrieb:
>
Blubaugh, David A. schrieb:
To All,
To whom else if I may ask?
I was wondering if it was possible to utilize python to share a memory
resource between a linux and windows system?? It should be stated that
both the Linux (CENTOS 5) and windows are physically located on the same
computer. Is
To All,
I was wondering if it was possible to utilize python to share a memory
resource between a linux and windows system?? It should be stated that
both the Linux (CENTOS 5) and windows are physically located on the same
computer. Is any of this possible?
Thanks,
David Blubaugh
On Feb 11, 3:41 pm, Matias Surdi <[EMAIL PROTECTED]> wrote:
> Suppose I've a process P1, which generates itself a lot of data , for
> example 2Mb.
> Then, I've a process P2 which must access P1 shared memory and,
> probably, modify this data.
> To accomplish this, I&
address in the process's
> >>> address space at which the object you specify is to be mapped.
> >>>
> >>> As far as I know, the only way two unrelated processes can share
> >>> memory via mmap is by mapping a file. An anonymous block is known
>
as I know, the only way two unrelated processes can share
>>> memory via mmap is by mapping a file. An anonymous block is known
>>> only to the process that creates it -- being anonymous, there's
>>> no way for another process to refer to it.
>> On POSIX sys
hare
> > memory via mmap is by mapping a file. An anonymous block is known
> > only to the process that creates it -- being anonymous, there's
> > no way for another process to refer to it.
>
> On POSIX systems, you can create a shared memory object without a file
> u
, there's
> no way for another process to refer to it.
On POSIX systems, you can create a shared memory object without a file
using shm_open. The function returns a file descriptor.
> However, if one process is forked from the other, the parent
> can mmap an anonymous block and t
Carl Banks wrote:
> In C you can use the mmap call to request a specific physical location
> in memory (whence I presume two different processes can mmap anonymous
> memory block in the same location)
Um, no, it lets you specify the *virtual* address in the process's
address space at which the obj
Matias Surdi <[EMAIL PROTECTED]> wrote:
>Suppose I've a process P1, which generates itself a lot of data , for
>example 2Mb.
>Then, I've a process P2 which must access P1 shared memory and,
>probably, modify this data.
>To accomplish this, I've been diggin
On Feb 11, 6:41 pm, Matias Surdi <[EMAIL PROTECTED]> wrote:
> Suppose I've a process P1, which generates itself a lot of data , for
> example 2Mb.
> Then, I've a process P2 which must access P1 shared memory and,
> probably, modify this data.
> To accomplish this, I&
Suppose I've a process P1, which generates itself a lot of data , for
example 2Mb.
Then, I've a process P2 which must access P1 shared memory and,
probably, modify this data.
To accomplish this, I've been digging around python's mmap module, but I
can't figure ho
thon charting ...]
OK, so your C++ stuff dumps to memory. Using CreateFileMapping
and MapViewOfFile? Or some other kind of global memory?
In short, if your C++ can write stuff out to shared memory
created using CreateFileMapping/MapViewOfFile with a first
param of INVALID_HANDLE_VALUE and a tag
block in
shared memory so I don't have to wait for the data to be written to a
disk.
I have about 200 shared memory segments that the simulation creates. I
did not know that my code would write to the hard drive because I use
ctypes. Could you explain that. Even if I use mmap, how could I mma
Tim wrote:
> I saw the mmap function in the shared memory example. I had some
> concern with my large memory size being written to the disk drive. I
> though it might slow down my application. The reason I am writting
> this new code is because the existing method using a file. I thou
Tim wrote:
> I reviewed the mmap function and I have a question. In the example
> code below, what is the connection between the data in shared memory
> and the mmap function. The fileno is zero. Why is it zero? The size
> makes sense because there is 256 bytes in shared memory
Hi!
I agree ; on windows mmap use Memory-Mapped-file, who use virtual
memory. And shared memory use physical memory.
The difference is OS an not Python
--
@-salutations
Michel Claveau
--
http://mail.python.org/mailman/listinfo/python-list
On Sep 10, 10:11 am, Tim Golden <[EMAIL PROTECTED]> wrote:
> Tim wrote:
> > Hello Everyone,
>
> > I am getting shared memory in python using the following.
>
> > szName = c_char_p(name)
> > hMapObject = windll.kernel32.CreateFileMappingA(INVALID_HANDLE_VALUE,
On Sep 10, 10:11 am, Tim Golden <[EMAIL PROTECTED]> wrote:
> Tim wrote:
> > Hello Everyone,
>
> > I am getting shared memory in python using the following.
>
> > szName = c_char_p(name)
> > hMapObject = windll.kernel32.CreateFileMappingA(INVALID_HANDLE_VALUE,
Tim wrote:
> Hello Everyone,
>
> I am getting shared memory in python using the following.
>
> szName = c_char_p(name)
> hMapObject = windll.kernel32.CreateFileMappingA(INVALID_HANDLE_VALUE,
> None, PAGE_READONLY, 0, TABLE_SHMEMSIZE, szName)
Hello Everyone,
I am getting shared memory in python using the following.
szName = c_char_p(name)
hMapObject = windll.kernel32.CreateFileMappingA(INVALID_HANDLE_VALUE,
None, PAGE_READONLY, 0, TABLE_SHMEMSIZE, szName)
if (hMapObject == 0):
print "OpenKey: Could not
Hendrik van Rooyen wrote:
>>> Just to get the ball rolling, I'd suggest two things:
>>>
>>> Pyro -http://pyro.sf.net
>
> This is good advice, if you have the power to run it.
What do you mean exactly by "the power to run it"?
--Irmen
--
http://mail.python.org/mailman/listinfo/python-list
From: "D.Hering" wrote:
> On May 23, 4:04 am, Tim Golden <[EMAIL PROTECTED]> wrote:
> > Robert Rawlins - Think Blue wrote:
> >
I did not see the original post either :-( ...
> > > I've got an application that runs on an embedded system, the application
> > > uses a whole bunch or dicts and othe
In article <[EMAIL PROTECTED]>,
Tim Golden <[EMAIL PROTECTED]> wrote:
.
.
.
>PyLinda - http://www-users.cs.york.ac.uk/~aw/pylinda/
>
>This implements the tuplespace paradigm. It's great
>fun to use, but as far as I know this i
On 23 May, 11:48, "D.Hering" <[EMAIL PROTECTED]> wrote:
>
> Possibly, IPython's new interactive parallel environment is what you
> are looking for:http://ipython.scipy.org/moin/Parallel_Computing
See this and related projects on the python.org Wiki:
http://wiki.python.org/moin/ParallelProcessing
On 23 May, 11:48, "D.Hering" <[EMAIL PROTECTED]> wrote:
>
> Possibly, IPython's new interactive parallel environment is what you
> are looking for:http://ipython.scipy.org/moin/Parallel_Computing
See this and related projects on the python.org Wiki:
http://wiki.python.org/moin/ParallelProcessing
On May 23, 4:04 am, Tim Golden <[EMAIL PROTECTED]> wrote:
> Robert Rawlins - Think Blue wrote:
>
> > I've got an application that runs on an embedded system, the application
> > uses a whole bunch or dicts and other data types to store state and other
> > important information.
> > I'm looking to b
On May 23, 4:04 am, Tim Golden <[EMAIL PROTECTED]> wrote:
> Robert Rawlins - Think Blue wrote:
>
> > I've got an application that runs on an embedded system, the application
> > uses a whole bunch or dicts and other data types to store state and other
> > important information.
> > I'm looking to b
En Wed, 23 May 2007 05:04:10 -0300, Tim Golden <[EMAIL PROTECTED]>
escribió:
> I noticed that the post hadn't appeared on Google
> Groups, at least. I read things via the mailing list;
> is it possible your post hasn't made it across to
> Usenet either?
I read this thru the gmane news interfase
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