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Remove __version__numpy__; simplify dependencies check. #11980

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Merged
merged 1 commit into from
Sep 1, 2018

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anntzer
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@anntzer anntzer commented Aug 30, 2018

  • There isn't really a reason to keep a ton of machinery to propagate
    __version__numpy__ as min numpy supported version throughout the
    repo; we don't do this with other dependencies so I'm sure we can
    manage manually bumping the numpy version at all places when we want
    to.
  • Kill Numpy().check() in setupext. Numpy will always be installed due
    to its presence in setup_requires -- unless you don't believe in
    setuptools...
  • Simplify the version check at import time. If the module isn't
    present, I think leaving in the ImportError that would have been
    generated is just fine (note that on recent Pythons it's actually a
    ModuleNotFoundError which contains more information, wrapping it in
    an ImportError ourselves actually decreases the amount of information
    available...

PR Summary

PR Checklist

  • Has Pytest style unit tests
  • Code is Flake 8 compliant
  • New features are documented, with examples if plot related
  • Documentation is sphinx and numpydoc compliant
  • Added an entry to doc/users/next_whats_new/ if major new feature (follow instructions in README.rst there)
  • Documented in doc/api/api_changes.rst if API changed in a backward-incompatible way

@tacaswell tacaswell added this to the v3.1 milestone Aug 30, 2018
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This should get an API change note (just to be safe), but no need for deprecation logic.

- There isn't really a reason to keep a ton of machinery to propagate
  `__version__numpy__` as min numpy supported version throughout the
  repo; we don't do this with other dependencies so I'm sure we can
  manage manually bumping the numpy version at all places when we want
  to.
- Kill Numpy().check() in setupext.  Numpy will always be installed due
  to its presence in setup_requires -- unless you don't believe in
  setuptools...
- Simplify the version check at import time.  If the module isn't
  present, I think leaving in the ImportError that would have been
  generated is just fine (note that on recent Pythons it's actually a
  ModuleNotFoundError which contains *more* information, wrapping it in
  an ImportError ourselves actually decreases the amount of information
  available...
@anntzer
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anntzer commented Aug 31, 2018

done

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5 participants