Closed je-cook closed 1 year ago
It would be great to merge this PR and have a new release, so we can use numba-scipy
with newer scipy versions. Is there any timeline on merging this PR?
@david-zwicker I'll raise this at the public Numba meeting tomorrow. Thanks for the PR @je-cook.
Hi, is there any feeling on when this could be merged? Its limiting our access to some f2py improvements that were added in numpy 1.23 so I'm hoping soonish :)
gentle ping @stuartarchibald @esc is there any update on this or any chance it can be merged?
gentle ping @stuartarchibald @esc is there any update on this or any chance it can be merged?
Thank you for asking about this. Perhaps @brandonwillard has some input on this too?
gentle ping @stuartarchibald @esc is there any update on this or any chance it can be merged?
Thank you for asking about this. Perhaps @brandonwillard has some input on this too?
I'm all for this update, as long as the tests pass, of course (and it looks like CI is awaiting approval).
Thanks @brandonwillard, @esc could you approve the CI run so we can move forward with this?
/azp run
It looks like CI is bust somehow:
==================================== ERRORS ====================================
_______________________ ERROR collecting test_sparse.py ________________________
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/numba_scipy/tests/test_sparse.py:4: in <module>
import scipy.sparse
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/sparse/__init__.py:229: in <module>
from .base import *
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/sparse/base.py:8: in <module>
from .sputils import (isdense, isscalarlike, isintlike,
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/sparse/sputils.py:[16](https://github.com/numba/numba-scipy/actions/runs/4729770315/jobs/8706873616?pr=90#step:5:17): in <module>
supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/sparse/sputils.py:16: in <listcomp>
supported_dtypes = [np.typeDict[x] for x in supported_dtypes]
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/numpy/__init__.py:320: in __getattr__
raise AttributeError("module {!r} has no attribute "
E AttributeError: module 'numpy' has no attribute 'typeDict'
_______________________ ERROR collecting test_special.py _______________________
ImportError while importing test module '/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/numba_scipy/tests/test_special.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:
/usr/local/miniconda/envs/test_env/lib/python3.8/importlib/__init__.py:127: in import_module
return _bootstrap._gcd_import(name[level:], package, level)
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/numba_scipy/tests/test_special.py:11: in <module>
import scipy.special as sc
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/special/__init__.py:643: in <module>
from .basic import *
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/special/basic.py:[19](https://github.com/numba/numba-scipy/actions/runs/4729770315/jobs/8706873616?pr=90#step:5:20): in <module>
from . import orthogonal
/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/scipy/special/orthogonal.py:81: in <module>
from numpy import (exp, inf, pi, sqrt, floor, sin, cos, around, int,
E ImportError: cannot import name 'int' from 'numpy' (/usr/local/miniconda/envs/test_env/lib/python3.8/site-packages/numpy/__init__.py)
=========================== short test summary info ============================
ERROR test_sparse.py - AttributeError: module 'numpy' has no attribute 'typeD...
ERROR test_special.py
!!!!!!!!!!!!!!!!!!! Interrupted: 2 errors during collection !!!!!!!!!!!!!!!!!!!!
============================== 2 errors in 10.[31](https://github.com/numba/numba-scipy/actions/runs/4729770315/jobs/8706873616?pr=90#step:5:32)s ==============================
Error: Process completed with exit code 2.
And on azure, we are seeing:
Hmm odd, from what I can tell those numpy imports were removed in numpy>v1.21.
It also looks weird because I had missed the setup.py version change so I'd have thought it would actually have been the old scipy that was tested...
i've pushed the scipy change, but not quite sure how to do interdependent versioning if we need numpy<=1.21 & scipy<=1.7.3 or numpy>1.21 & scipy>1.7.3
Does anyone know why I need to approve the workflow everytime?
Also, does anyone know what is up with the Azure images?
Does anyone know why I need to approve the workflow everytime?
I think its because this is my first PR to the project, on another project I've got it set to 'require approval for first time contributors' and it seems to be the case that you have to approve for all updates (for us at least)
Does anyone know why I need to approve the workflow everytime?
I think its because this is my first PR to the project, on another project I've got it set to 'require approval for first time contributors' and it seems to be the case that you have to approve for all updates (for us at least)
yeah, that makes sense, I'll keep approving them until this PR is merged then.
Also, does anyone know what is up with the Azure images?
could it be, that the image is outdated and now longer available?
Also, does anyone know what is up with the Azure images?
could it be, that the image is outdated and now longer available?
Tryin' to bump the Azure Linux Image here: https://github.com/numba/numba-scipy/pull/95
I forgot to quote 3.10 so it will probably fail without that
Also, does anyone know what is up with the Azure images?
could it be, that the image is outdated and now longer available?
Tryin' to bump the Azure Linux Image here: #95
Seems to work, you should be able to merge this PR https://github.com/je-cook/numba-scipy/pull/1 to add my commit to this PR.
So, looks like this is moving along some more now and the Azure tests are running again... but ....
https://github.com/numba/numba-scipy/pull/95#issuecomment-1534686759
Hi @esc I've just updated everything and I think I need approval to change the macOS VM image for azure as macOS-10.15 doesnt exist like you fixed in #95.
Hopefully this time I've caught everything :slightly_smiling_face:
Hi @esc I've just updated everything and I think I need approval to change the macOS VM image for azure as macOS-10.15 doesnt exist like you fixed in #95.
Hopefully this time I've caught everything 🙂
Splendid, thank you!
/azp run
@brandonwillard can I get a second set of eys 👀 on this? it LGTM from my end.
@je-cook good news, this one tested as green.
Looks like github was not as clever as I hoped and if you leave out a variable in an include outside of the matrix it defaults to an empty string and doesnt cycle through the matrix for that value!
OK, looks like the test matrix is all green, However, I see that there are tests for Python 3.6 and 3.7 -- now I am confused as to why we want these? The latest Numba release only supports 3.8, 3.9, 3.10 and 3.11..
See also: the version support table for Numba.
https://numba.readthedocs.io/en/stable/user/installing.html#version-support-information
Happy to drop them if we're keeping in lockstep with numba itself. I just didn't want to deprecate anything without wider consent
I'm not sure whether the 32bit version will work with the newer stuff but we'll see!
I'm not sure whether the 32bit version will work with the newer stuff but we'll see!
I don't think we support 32-bit anymore. But I am not certain as of when that's the case. @stuartarchibald do you know if we have a hardware-support table too?
@je-cook what's up with the Numpy 1.24 on conda issue?
I think its because numba 0.57 (which added numpy 1.24 support) is not on the conda repo yet. Thats my best guess looking around the azure logs for a few minutes, https://dev.azure.com/numba/numba-scipy/_build/results?buildId=15042&view=results
I think its because numba 0.57 (which added numpy 1.24 support) is not on the conda repo yet. Thats my best guess looking around the azure logs for a few minutes, https://dev.azure.com/numba/numba-scipy/_build/results?buildId=15042&view=results
Yes, looking at:
https://anaconda.org/conda-forge/numba/files
I concur with this assessment. I would like to find out when 0.57 is likely to land in CF and then decide on how to proceed.
I think its because numba 0.57 (which added numpy 1.24 support) is not on the conda repo yet. Thats my best guess looking around the azure logs for a few minutes, https://dev.azure.com/numba/numba-scipy/_build/results?buildId=15042&view=results
Yes, looking at:
https://anaconda.org/conda-forge/numba/files
I concur with this assessment. I would like to find out when 0.57 is likely to land in CF and then decide on how to proceed.
Looking at:
https://github.com/conda-forge/llvmlite-feedstock/pull/69
and
https://github.com/conda-forge/numba-feedstock/pull/115
it may been some time until 0.57.0 lands in conda-forge -- thus I would suggest to merge this PR as it get's the job done and then add in 1.24 when 0.57.0 lands on CF. Are well good with that?
@je-cook thank you for the patch! @brandonwillard thank you for the review!
Apologies for posting in a Merged PR, but I was wondering if there were any plans to package this change into a new patch version on PyPI
(i.e. version 0.3.2
?)
Apologies for posting in a Merged PR, but I was wondering if there were any plans to package this change into a new patch version on
PyPI
(i.e. version0.3.2
?)
Feel free to open a new release request as an issue on github and I'll see what I can do about a release. 👍
This PR bumps scipy version to allow installation of numpy >=1.23 alongside numba and numba-scipy
As discussed in #88 the scipy upgrade was waiting for anaconda to have a later release in its default repo which it now does (https://anaconda.org/anaconda/scipy).
I have pinned to less than the next minor version of scipy as it is unlikely behaviour will change on patch version changes. If you would like this stricter let me know.
Closes #88
EDIT
Scipy have bumped the deprecation to after 1.11.0 (see https://github.com/scipy/scipy/issues/15596) and 1.10.0 is now on the anaconda repo.