[IPython-user] ipython1 and farm tasking
Flavio Coelho
fccoelho@gmail....
Thu Feb 28 06:39:35 CST 2008
HI Brian,
Very interesting these new features in Ipython1, I am anxious to try them!
I have a technical question though:
How are objects pushed to processes? as pickles?
can you push an Unpicklable object?
My problem is as follows: I want to have multiple processes writing to
a ZODB database. In order to do that, each process has to see the same
DB object (which is unpickleable) and open a connection to it. I have
been trying to do this with parallel-python but it was not possible
since objects are moved around as pickles....
I am hoping I can do this with Ipython1.
thanks in advance,
Flávio
On Wed, Feb 27, 2008 at 7:29 PM, Brian Granger <ellisonbg.net@gmail.com> wrote:
> Alex,
>
> First, I would suggest updating your ipython1 install from our svn
> repository. We are about to push out a major new version and the
> documentation is _much_ better. Also, there are many new features
> that will hopefully help you. Here is a simple example (using the
> latest svn of ipython1):
>
> In [1]: from ipython1.kernel import client
>
> In [2]: mec = client.MultiEngineClient(('127.0.0.1',10105))
>
> In [3]: tc = client.TaskClient(('127.0.0.1',10113))
>
> In [4]: def fold_package(x):
> ...: return 2.0*x
> ...:
>
> In [5]: mec.push_function(dict(fold_package=fold_package))
> Out[5]: [None, None, None, None]
>
> In [6]: tasks =
> [client.Task("y=fold_package(x)",push={'x':x},pull=('y',)) for x in
> range(128)]
>
> In [7]: task_ids = [tc.run(t) for t in tasks]
>
> In [8]: tc.barrier(task_ids)
>
> In [9]: task_results = [tc.get_task_result(tid) for tid in task_ids]
>
> In [10]: results = [tr.ns.y for tr in task_results]
>
> In [11]: print results
> [0.0, 2.0, 4.0, 6.0, 8.0, 10.0, 12.0, 14.0, 16.0, 18.0, 20.0, 22.0,
> 24.0, 26.0, 28.0, 30.0, 32.0, 34.0, 36.0, 38.0, 40.0, 42.0, 44.0,
> 46.0, 48.0, 50.0, 52.0, 54.0, 56.0, 58.0, 60.0, 62.0, 64.0, 66.0,
> 68.0, 70.0, 72.0, 74.0, 76.0, 78.0, 80.0, 82.0, 84.0, 86.0, 88.0,
> 90.0, 92.0, 94.0, 96.0, 98.0, 100.0, 102.0, 104.0, 106.0, 108.0,
> 110.0, 112.0, 114.0, 116.0, 118.0, 120.0, 122.0, 124.0, 126.0, 128.0,
> 130.0, 132.0, 134.0, 136.0, 138.0, 140.0, 142.0, 144.0, 146.0, 148.0,
> 150.0, 152.0, 154.0, 156.0, 158.0, 160.0, 162.0, 164.0, 166.0, 168.0,
> 170.0, 172.0, 174.0, 176.0, 178.0, 180.0, 182.0, 184.0, 186.0, 188.0,
> 190.0, 192.0, 194.0, 196.0, 198.0, 200.0, 202.0, 204.0, 206.0, 208.0,
> 210.0, 212.0, 214.0, 216.0, 218.0, 220.0, 222.0, 224.0, 226.0, 228.0,
> 230.0, 232.0, 234.0, 236.0, 238.0, 240.0, 242.0, 244.0, 246.0, 248.0,
> 250.0, 252.0, 254.0]
>
> Or if you don't need load balancing:
>
> # This sends the fold_package function for you!
> results = mec.map(fold_package, range(128))
>
> Let us know if you run into other problems.
>
> Cheers,
>
> Brian
>
>
>
> On Mon, Feb 25, 2008 at 7:44 PM, Alexandre Gillet <gillet@scripps.edu> wrote:
> > Hi,
> >
> > I just started using ipython1 do to distribute job on multiple cpu. I
> > am having some issue and I am not sure how it works.
> > I want to pass a function to be run by each task on each client.
> > In the following code, the function fold_package need to be run on each
> > client.
> >
> > packages_list=[ '3114', '3115','3116']
> > # create a remote controller instance
> > rc = kernel.RemoteController(('127.0.0.1',10105))
> > # create task controller instance
> > tc = kernel.TaskController(('127.0.0.1', 10113))
> > # commands won't block by default
> > rc.block = False
> > # get id of available engine
> > engines_id = rc.getIDs()
> > # process the list of packages by dispatching them to different computer
> > # create the task list
> > tasks = [kernel.Task("fold_package(%s)"%t) for t in packages_list]
> > # test task controller
> > taskIDs = [tc.run(t) for t in tasks]
> >
> >
> > when I run that code I get:
> > NameError: name 'fold_package' is not defined
> >
> > My questions are;
> > How do you pass a function define in my script to the client engine?
> > Or Do I have to create a package that will contains my function and
> > installed it on each client?
> >
> > Thanks for any advices and answers.
> > Alex
> >
> > --
> > o Alexandre Gillet Ph.D. email: gillet@scripps.edu
> > / The Scripps Research Institute,
> > o Dept. Molecular Biology, MB-5,
> > \ 10550 North Torrey Pines Road,
> > o La Jolla, CA 92037-1000, USA.
> > / tel: (858) 784-2053
> > o fax: (858) 784-2860
> > web: http://mgl.scripps.edu/projects/tangible_models/
> > _______________________________________________
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> >
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