Assume modules with __file__ attribute are not dynamic #85
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Fixes cloudpipe#84 If a module has a `__file__` attribute then we assume that it is not dynamically generated. This allows the common case to be much faster than otherwise.
Member
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No counter cases that I'm aware of. @minrk, @takluyver, @Carreau -- this module is used for pickling functions and sending them over a network. It's used in IPython parallel. Do any of you have any ideas for Matthew's question? |
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The only thing I can think of is the use of %autoreload in IPython (maybe
%run). That's all I can think of, and seem like a reasonable thing not to
support.
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Contributor
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No known counter-examples from me. |
Contributor
Author
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Any objections to merging this then? |
rgbkrk
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This brings in fixes and upgrades from the [cloudpickle](https://github.com/cloudpipe/cloudpickle) module, notably: * Import submodules accessed by pickled functions (cloudpipe/cloudpickle#80) * Support recursive functions inside closures (cloudpipe/cloudpickle#89, cloudpipe/cloudpickle#90) * Fix ResourceWarnings and DeprecationWarnings (cloudpipe/cloudpickle#88) * Assume modules with __file__ attribute are not dynamic (cloudpipe/cloudpickle#85) * Make cloudpickle Python 3.6 compatible (cloudpipe/cloudpickle#72) * Allow pickling of builtin methods (cloudpipe/cloudpickle#57) * Add ability to pickle dynamically created modules (cloudpipe/cloudpickle#52) * Support method descriptor (cloudpipe/cloudpickle#46) * No more pickling of closed files, was broken on Python 3 (cloudpipe/cloudpickle#32)
ghost
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Aug 22, 2017
## What changes were proposed in this pull request? Based on apache#18282 by rgbkrk this PR attempts to update to the current released cloudpickle and minimize the difference between Spark cloudpickle and "stock" cloud pickle with the goal of eventually using the stock cloud pickle. Some notable changes: * Import submodules accessed by pickled functions (cloudpipe/cloudpickle#80) * Support recursive functions inside closures (cloudpipe/cloudpickle#89, cloudpipe/cloudpickle#90) * Fix ResourceWarnings and DeprecationWarnings (cloudpipe/cloudpickle#88) * Assume modules with __file__ attribute are not dynamic (cloudpipe/cloudpickle#85) * Make cloudpickle Python 3.6 compatible (cloudpipe/cloudpickle#72) * Allow pickling of builtin methods (cloudpipe/cloudpickle#57) * Add ability to pickle dynamically created modules (cloudpipe/cloudpickle#52) * Support method descriptor (cloudpipe/cloudpickle#46) * No more pickling of closed files, was broken on Python 3 (cloudpipe/cloudpickle#32) * ** Remove non-standard __transient__check (cloudpipe/cloudpickle#110)** -- while we don't use this internally, and have no tests or documentation for its use, downstream code may use __transient__, although it has never been part of the API, if we merge this we should include a note about this in the release notes. * Support for pickling loggers (yay!) (cloudpipe/cloudpickle#96) * BUG: Fix crash when pickling dynamic class cycles. (cloudpipe/cloudpickle#102) ## How was this patch tested? Existing PySpark unit tests + the unit tests from the cloudpickle project on their own. Author: Holden Karau <[email protected]> Author: Kyle Kelley <[email protected]> Closes apache#18734 from holdenk/holden-rgbkrk-cloudpickle-upgrades.
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Fixes #84
If a module has a
__file__attribute then we assume that it is notdynamically generated. This allows the common case to be much faster
than otherwise.
However, it is not clear to me that this is always entirely safe. Are there counter-examples where this could cause an issue?