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task: coverity - #3070
task: coverity#3070jharlow-intel wants to merge 5 commits into
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View rendered docs @ https://intelpython.github.io/dpnp/pull/3070/index.html |
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Array API standard conformance tests for dpnp=0.21.0dev15=np2py314h8d9cdd5_10 ran successfully. |
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coverage: 82.613%. remained the same — task/coverity into master |
| # Mirrors the build-time requirements in pyproject.toml. dpnp still uses | ||
| # classic scikit-build, so setup.py is the build entry point. | ||
| run: | | ||
| pip install cmake cython ninja numpy scikit-build setuptools wheel \ |
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Do we need to pin cython to some version to have a stable report?
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Yes, pinned to cython==3.3.0 in 73c91ca, matching the mkl_fft and mkl-service scans. A Cython upgrade rewrites the generated C and shuffles the CIDs, so an unpinned install would reset the triage whenever PyPI moves. 3.3.0 is also what conda-forge currently resolves for cython>=3.1.0, so the scan builds the same thing as the regular CI until we bump it deliberately.
Unpinned `cython` resolves to whatever PyPI has that Monday, and a Cython upgrade rewrites the generated C, which shuffles Coverity CIDs and loses their triage. Pin 3.3.0, the version conda-forge currently resolves for the regular builds, matching the mkl_fft and mkl-service scans. Also align the upload-artifact pin with master (v7.0.2).
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https://scan.coverity.com/projects/intelpython-dpnp?tab=overview
Pretty much the same as the others