Skip to content

Stabilize Coverity Scan triage and document known false positives #873

Stabilize Coverity Scan triage and document known false positives

Stabilize Coverity Scan triage and document known false positives #873

Triggered via pull request September 3, 2026 18:14
Status Success
Total duration 12m 50s
Artifacts 24

conda-package.yml

on: pull_request
Matrix: build_linux
Matrix: build_windows
Matrix: test_linux
Matrix: test_windows
Fit to window
Zoom out
Zoom in

Annotations

6 warnings
build_windows (3.14, 2.3, 3.14.* *_cp314t, 3.14t)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html
build_windows (3.12, 2.3)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html
build_windows (3.14, 2.3, 3.14.* *_cp314, 3.14)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html
build_windows (3.10, 2.2)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html
build_windows (3.13, 2.3)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html
build_windows (3.11, 2.3)
WARNING conda.conda_pypi.main:notify_externally_managed_future(156): Did you know? You can install many PyPI packages with conda using the conda-pypi beta. Get started: https://docs.conda.io/projects/conda/en/stable/new-features.html

Artifacts

Produced during runtime
Name Size Digest
mkl_umath Linux Python 3.10
126 KB
sha256:95c98bf46cc83b13e98e5621c18bdbcef0c436fb8692d9b647bce23ac3496cc6
mkl_umath Linux Python 3.11
130 KB
sha256:10878e3f34d5b9e5a85ff60f64095fbec07a27d221f268fed60387c2ba849482
mkl_umath Linux Python 3.12
129 KB
sha256:80c1d88c55d9dd1aa329aa1ab70b189783b617417331222a7909f6d678438c74
mkl_umath Linux Python 3.13
129 KB
sha256:b10e74c9e656c37487cfcde6ea7c649189b53913d9d2a543bbf467aa5bbef130
mkl_umath Linux Python 3.14
130 KB
sha256:ebcca6040accf265f2395eee1196ce913f9da19ef639bc00644cf9916fa7f87b
mkl_umath Linux Python 3.14t
133 KB
sha256:eb6c2aa671adc46f54f6b9144223ac67e3fb0a4e2e6e6d075eec96ce18edcc9b
mkl_umath Linux Wheels Python 3.10
136 KB
sha256:44e132044e22c42b5db3028b24d383c42991f45bb3b8dcc177d676056b27e170
mkl_umath Linux Wheels Python 3.11
136 KB
sha256:b818ca2949a85078c8779a5b9b13dd252276f5778ff69bd90e2194028f355458
mkl_umath Linux Wheels Python 3.12
136 KB
sha256:487c6f66fda4dda966537c1dfa2ede8ade87080b9ed1671b467c34f85cc4a584
mkl_umath Linux Wheels Python 3.13
135 KB
sha256:60aabbb97a8547e0195d7826fef0cadef8c0ae970c33be4527fbea61eb513fdc
mkl_umath Linux Wheels Python 3.14
135 KB
sha256:9cda9ed929524982375f0caa059acb17eab11a944cd21fbdd413da2fedc81d44
mkl_umath Linux Wheels Python 3.14t
139 KB
sha256:a60dfd228f8dbb0d9708472c91be1b2959a1d07c91e2c26186f311032dcdc02e
mkl_umath Windows Python 3.10
144 KB
sha256:ecdb1584130bd423695cfa15baf93886e834b63ce353b4efca8ecc31fe7acd2b
mkl_umath Windows Python 3.11
148 KB
sha256:b2e23835552154b452deacafdfab7e63cbc0a526bef96b4facbb9ae95e98bb94
mkl_umath Windows Python 3.12
147 KB
sha256:13a061303a8dda0430e0d5d46f96a0fd0486a06046cf2999bbb53632af767223
mkl_umath Windows Python 3.13
147 KB
sha256:87044790c1fbd0ae0f1ef515a19ca8c4a6198cca01cc570c9b43c502a9f301b3
mkl_umath Windows Python 3.14
148 KB
sha256:56e6ba2e9b27143a7e3a02f286368d99f59d7f18e14d6a695843daea0370c95b
mkl_umath Windows Python 3.14t
153 KB
sha256:5de11772782f86e64032bb47938aa6ef60d70600a22e84d056470fba48002246
mkl_umath Windows Wheels Python 3.10
161 KB
sha256:8ae54ef86bb3101811f0c926e84058f3d0d510575dc65e4f08b5c8853aa08553
mkl_umath Windows Wheels Python 3.11
160 KB
sha256:9ffc41fd420a70d0a49e4d8c7dbdccf9a0d2034420910fde913ab11b3a6c6a00
mkl_umath Windows Wheels Python 3.12
160 KB
sha256:71de61d8dfb6523a0bbac0e45307101eb00821d55a2167321f02c2395214aa03
mkl_umath Windows Wheels Python 3.13
159 KB
sha256:b9016cc62738f3bde8bcbcfc2692110e8301e243dcae5117e1bbe4680380aad7
mkl_umath Windows Wheels Python 3.14
160 KB
sha256:6f28901e144ece47e0262a3399bea2f1978f786e62b1d09c2f89476cf9834873
mkl_umath Windows Wheels Python 3.14t
166 KB
sha256:28d15e37e1fa9c1209867a0608f443480dea6fe56c6e3f9799aa2c26dcb47e81