[IPython-user] ipython1 and farm tasking

Alexandre Gillet gillet@scripps....
Thu Feb 28 12:20:46 CST 2008


Hi Brian,

Thanks for your answer it help get to do what I needed and understand better
the code.
I have another question.
I am going to run my task in a non-blocking mode. My task are going to be
running for few hours. How do I get to check the status of a task? I want to
know if it is done. Do you use tc.get_task_results(id,block=False) ? It will
return None if the task is not done.

How will you find the number of task still in the queue that need to be run?


By the way what a great package. I am so glad I found it for my development.
Thanks
Alex


On 2/27/08 2:29 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/
>>  _______________________________________________
>>  IPython-user mailing list
>>  IPython-user@scipy.org
>>  http://lists.ipython.scipy.org/mailman/listinfo/ipython-user
>> 

-- 
 o Alexandre Gillet Ph.D.      email: gillet (-at-) 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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