Drop Python 3.10
Description
Related Issue
- [ ] Closes #
- [ ] Related to #
Checklist
- [ ] Checked that the pre-commit linting/style checks pass
- [ ] Included tests that prove the fix is effective or that the new feature works
- [ ] Added necessary documentation (docstrings and/or example notebooks)
- [ ] If you are a pro: each commit corresponds to a relevant logical change
Type of change
- [ ] New feature / enhancement
- [ ] Bug fix
- [ ] Documentation
- [ ] Maintenance
- [ ] Other (please specify):
📚 Documentation preview 📚: https://pytensor--1253.org.readthedocs.build/en/1253/
Codecov Report
:white_check_mark: All modified and coverable lines are covered by tests.
:white_check_mark: Project coverage is 81.65%. Comparing base (b05acfd) to head (04b2d67).
:warning: Report is 16 commits behind head on main.
Additional details and impacted files
@@ Coverage Diff @@
## main #1253 +/- ##
==========================================
- Coverage 81.67% 81.65% -0.03%
==========================================
Files 232 232
Lines 53132 53078 -54
Branches 9410 9405 -5
==========================================
- Hits 43396 43340 -56
- Misses 7283 7285 +2
Partials 2453 2453
| Files with missing lines | Coverage Δ | |
|---|---|---|
| pytensor/link/c/basic.py | 87.74% <100.00%> (-0.02%) |
:arrow_down: |
| pytensor/link/numba/dispatch/elemwise.py | 94.82% <100.00%> (ø) |
|
| pytensor/npy_2_compat.py | 100.00% <100.00%> (ø) |
|
| pytensor/tensor/basic.py | 91.80% <100.00%> (ø) |
|
| pytensor/tensor/blas.py | 73.52% <100.00%> (ø) |
|
| pytensor/tensor/einsum.py | 97.11% <100.00%> (+0.01%) |
:arrow_up: |
| pytensor/tensor/elemwise.py | 90.01% <100.00%> (ø) |
|
| pytensor/tensor/extra_ops.py | 88.54% <100.00%> (-0.02%) |
:arrow_down: |
| pytensor/tensor/math.py | 92.86% <100.00%> (-0.02%) |
:arrow_down: |
| pytensor/tensor/nlinalg.py | 94.98% <100.00%> (ø) |
|
| ... and 5 more |
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Does this mean we can also drop numpy<2 and related CI matrix?
Yeah I think that the plan was to drop numpy < 2.0 and python 3.10 together if I remember correctly
Let's do it. There is stuff in npy_compat as well
There is stuff remaining but I want to check this for now.
I was wondering if I need to increment the c code version after removing the compatibility headers?
I was wondering if I need to increment the c code version after removing the compatibility headers?
I don't think so, the generated C code didn't change if you are using numpy>2.0, and you can't use the old one anymore now. Could be wrong ofc
I don't think so, the generated C code didn't change if you are using numpy>2.0
Even with this commit? a0ad2464
Even with this commit? https://github.com/pymc-devs/pytensor/commit/a0ad24641926b39cedf78863c4c36660e08bf90f
Can you check if we bumped the C versions when we added that header thing to those Ops? If we did, then maybe let's be safe and bump again
Can you check if we bumped the C versions when we added that header thing to those Ops? If we did, then maybe let's be safe and bump again
This is the commit that introduced that header, it changed the C code in other ways too but it did bump the C versions: https://github.com/pymc-devs/pytensor/pull/1194/commits/0aa10c0bccf2b573e906073962cb6ef15eea4eb8
Right, let's rebump then. Thanks for checking it
looks good just a small question
Thanks a ton @Armavica
Anything else missing?
Thanks a ton @Armavica
Anything else missing?
I can't think of anything else
The PyPI CI seems to be failing
Not sure what this is about, I will debug in a few days
I think it's trying to build something with python 3.10. Also are you rebased from main?
Specifically this job may need the python version specified (the one above build_universal_wheel specifies it for example): https://github.com/pymc-devs/pytensor/blob/4312d8c6bd0dc6f708bd3327d66bf9750ab3ce46/.github/workflows/pypi.yml#L186
Specifically this job may need the python version specified (the one above
build_universal_wheelspecifies it for example):https://github.com/pymc-devs/pytensor/blob/4312d8c6bd0dc6f708bd3327d66bf9750ab3ce46/.github/workflows/pypi.yml#L186
Thank you, it looks like that did the trick
LGTM. I asked @lucianopaz and @maresb to also take a look in case they spot something else problematic. Specifically I suspect @maresb needs to be in the loop for the conda release anyway
Thanks again @Armavica