upstream/ipython Files · docs/examples/parallel/multienginemap.py

Backport PR : ipcluster broken with any batch (PBS/LSF/SGE)...

Backport PR : ipcluster broken with any batch (PBS/LSF/SGE) I have setup ipcluster_config.py to start with LSF: ``` c.IPClusterStart.controller_launcher_class = 'LSF' c.IPClusterStart.engine_launcher_class = 'LSF' ``` But the ipcluster command fails to start the engines: ``` ipcluster start --profile=lsf -n 10 ``` The problem is fixed if I add quotes to the launch command string ```cmd``` in ```launcher.py```. ``` diff --git a/IPython/parallel/apps/launcher.py b/IPython/parallel/apps/launcher.py index e752d2a..6035303 100644 --- a/IPython/parallel/apps/launcher.py +++ b/IPython/parallel/apps/launcher.py @@ -73,7 +73,7 @@ WINDOWS = os.name == 'nt' # Paths to the kernel apps #----------------------------------------------------------------------------- -cmd = "from IPython.parallel.apps.%s import launch_new_instance; launch_new_instance()" +cmd = "\"from IPython.parallel.apps.%s import launch_new_instance; launch_new_instance()\"" ipcluster_cmd_argv = [sys.executable, "-c", cmd % "ipclusterapp"] ```

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      from __future__ import print_function

      from IPython.parallel import Client

      rc = Client()

      view = rc[:]

      result = view.map_sync(lambda x: 2*x, range(10))

      print("Simple, default map: ", result)

      ar = view.map_async(lambda x: 2*x, range(10))

      print("Submitted map, got AsyncResult: ", ar)

      result = ar.r

      print("Using map_async: ", result)

      @view.parallel(block=True)

      def f(x): return 2*x

      result = f.map(range(10))

      print("Using a parallel function: ", result)

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				from __future__ import print_function

				from IPython.parallel import Client

				rc = Client()
				view = rc[:]
				result = view.map_sync(lambda x: 2*x, range(10))
				print("Simple, default map: ", result)

				ar = view.map_async(lambda x: 2*x, range(10))
				print("Submitted map, got AsyncResult: ", ar)
				result = ar.r
				print("Using map_async: ", result)

				@view.parallel(block=True)
				def f(x): return 2*x

				result = f.map(range(10))
				print("Using a parallel function: ", result)