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Proposal: remove some ipyparallel-specific functionality #17

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minrk opened this issue May 12, 2015 · 9 comments · Fixed by #71
Open

Proposal: remove some ipyparallel-specific functionality #17

minrk opened this issue May 12, 2015 · 9 comments · Fixed by #71

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@minrk
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minrk commented May 12, 2015

Mainly the apply message-related bits. These aren't part of the wider Jupyter message protocol, and are wholly Python specific. These can be moved to ipyparallel, and attached to the Kernel in a subclass.

@minrk minrk added this to the 4.0 milestone May 12, 2015
@takluyver
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No objections from me.

@minrk
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minrk commented Jul 14, 2015

Missed the boat for 4.0 on this one, but I still think it's the right move in the long run.

@minrk minrk modified the milestones: 5.0, 4.0 Jul 14, 2015
@dsblank
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dsblank commented Oct 12, 2015

FYI, we use the ipyparallel bits in wrapper kernels (via metakernel) to run other languages in parallel. This is quite powerful, and hope that we can keep that functionality.

@minrk
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minrk commented Oct 12, 2015

@dsblank how do you use those kernels in parallel? Are you using ipyparallel at all? I mainly mean to remove the native-serialization stuff (data-pub, apply), not anything else, which shouldn't affect any kernels other than IPython.

@minrk
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minrk commented Oct 27, 2015

@dsblank I've implemented most of what I intended in ipython/ipyparallel#61. I don't understand enough about how your use of parallel in metakernel works, so I don't know how to tell what would be affected. Can you provide some examples that I can test with?

@dsblank
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dsblank commented Oct 27, 2015

Sorry for the delay. Here is a short example:

  1. Install a metakernel-based kernel: pip3 install metakernel_bash --user
  2. Start a cluster
  3. Start the kernel
  4. Start remote kernels: %parallel metakernel_bash MetaKernelBash
  5. Execute a command: %px uname

Hopefully that will still work. Thanks!

@minrk
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minrk commented Oct 27, 2015

@dsblank thanks, that still works after the above PR. Since it looks like you are sitting on top of the existing IPython engines and clients, moving the implementation shouldn't have any effect on your use case.

@dsblank
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dsblank commented Oct 27, 2015

Thanks for checking @minrk ! It is quite nice to have Parallel Java, Parallel Scheme, Parallel Cobol ...

@Carreau
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Carreau commented Sep 12, 2018

bump to 6.0 ?

@minrk minrk modified the milestones: 5.0, 6.0 Sep 13, 2018
@Carreau Carreau removed this from the 6.0 milestone Jul 1, 2021
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4 participants