upstream/ipython Files · docs/examples/kernel/taskmap.py

The refactoring of the Task system is nearly complete. Now there are...

The refactoring of the Task system is nearly complete. Now there are multiple types of tasks including `StringTask` and `MapTask`. Each task type is responsible for running itself and processing its own result. This makes it much easier for people to create new task types. Also, the map and parallel function support has been completely refactored and improved. This includes a map and parallel function implementation for the task controller as well as a @parallel decorator.

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      from IPython.kernel import client

      tc = client.TaskClient()

      result = tc.map(lambda x: 2*x, range(10))

      print "Simple, default map: ", result

      m = tc.mapper(block=False, clear_after=True, clear_before=True)

      tids = m.map(lambda x: 2*x, range(10))

      print "Submitted tasks, got ids: ", tids

      tc.barrier(tids)

      result = [tc.get_task_result(tid) for tid in tids]

      print "Using a mapper: ", result

      @tc.parallel()

      def f(x): return 2*x

      result = f(range(10))

      print "Using a parallel function: ", result

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				from IPython.kernel import client

				tc = client.TaskClient()

				result = tc.map(lambda x: 2*x, range(10))
				print "Simple, default map: ", result

				m = tc.mapper(block=False, clear_after=True, clear_before=True)
				tids = m.map(lambda x: 2*x, range(10))
				print "Submitted tasks, got ids: ", tids
				tc.barrier(tids)
				result = [tc.get_task_result(tid) for tid in tids]
				print "Using a mapper: ", result

				@tc.parallel()
				def f(x): return 2*x

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