upstream/ipython Files · examples/Parallel Computing/workflow/job_wrapper.py

Backport PR : fix iteration over Client...

Backport PR : fix iteration over Client I didn't intend for Client to be iterable, but defining `__getitem__` makes it iterable as long as engine IDs are continuous (not always the case). This explicitly defines `__iter__` so it behaves consistently. closes

Brian E. Granger - - Load All Authors

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             job_wrapper.py
        
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      #!/usr/bin/env python

      """Python wrapper around a submitted workflow job.

      In reality this would be a more sophisticated script, here we only illustrate

      the basic idea by considering that a submitted 'job' is a Python string to be

      executed.

      """

      import sys

      argv = sys.argv

      from IPython.parallel.engine import EngineFactory

      from IPython.parallel.ipengineapp import launch_new_instance

      ns = {}

      # job

      exec sys.argv[1] in ns

      # this should really use Config:

      EngineFactory.user_ns = ns

      # start engine with job namespace

      launch_new_instance()

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				#!/usr/bin/env python
				"""Python wrapper around a submitted workflow job.

				In reality this would be a more sophisticated script, here we only illustrate
				the basic idea by considering that a submitted 'job' is a Python string to be
				executed.
				"""

				import sys

				argv = sys.argv

				from IPython.parallel.engine import EngineFactory
				from IPython.parallel.ipengineapp import launch_new_instance

				ns = {}

				# job
				exec sys.argv[1] in ns

				# this should really use Config:
				EngineFactory.user_ns = ns

				# start engine with job namespace
				launch_new_instance()