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Build and test conda-recipe-cf for Intel Python CI - #400
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marked this pull request as ready for review
October 23, 2026 20:42
jharlow-intel
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antonwolfy,
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October 23, 2026 20:42
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🔵 Needs a closer look
Full-version builds and the external Jenkins handoff remain unverified and need maintainer validation.
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What changed in this PR
Adds GitHub Actions build and test support for mkl_fft’s conda-forge packages, preparing the repository for Intel Python CI’s future Jenkins integration.
Changes:
- Derives Linux and Windows build matrices from recipe Python variants, limiting pull requests to the two newest regular versions.
- Adds package-building and isolated testing scripts, with pytest JUnit reporting.
- Configures artifact naming, pins Miniforge, and documents the CI integration.
| File | Description |
|---|---|
conda-recipe-cf/conda_build_config.yaml |
Declares Python variants and NumPy 2. |
conda-recipe-cf/AGENTS.md |
Documents the recipe’s matrix role. |
ci/test.py |
Tests the installed package and writes JUnit results. |
ci/README.md |
Explains CI operation and local usage. |
ci/matrix.py |
Derives platform and Python build matrices. |
ci/hooks.py |
Installs artifacts into isolated test environments. |
ci/config.yml |
Defines workflow, artifact names, and test requirements. |
ci/build.py |
Builds and collects packages for a selected Python version. |
AGENTS.md |
Adds the Intel Python CI directory reference. |
.github/workflows/intel-ci.yml |
Orchestrates matrix generation, builds, and package tests. |
.github/AGENTS.md |
Documents the workflow and its matrix source. |
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Adds what Intel Python CI (gh-ci) needs: a ci/ directory and .github/workflows/intel-ci.yml. The workflow builds conda-recipe-cf with conda-build and the wheels with cibuildwheel, for every platform and Python version the recipe and pyproject.toml declare, and tests each package in a clean environment with ci/test.py. Intel's Jenkins tests them again, scans them, runs ci/benchmark.py on the newest Linux package, and publishes a release tag's tested packages as its GitHub Release. conda-recipe-cf/ is now the only recipe: conda-recipe/ and conda-package.yml, which built it against Intel's channel and copied wheels out through WHEELS_OUTPUT_FOLDER, are removed. conda-package-cf.yml reports the same check names, so the required checks still run. conda_build_config.yaml now lists the Python versions, and numpy: '2', as conda-build otherwise defaults to 1.26. The wheels' run-time requirement on mkl comes from [tool.gh-ci] wheel-requires in pyproject.toml, which ci/build.py adds to each wheel: in [project] it would fail the recipe's pip check, as conda-forge's mkl has no pip metadata.
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Description
Adds what Intel Python CI (gh-ci) needs from mkl_fft: a
ci/directory and a new workflow,.github/workflows/intel-ci.yml. The workflow buildsconda-recipe-cffor every platform and Python version the recipe declares, and tests each package in a clean conda-forge environment withci/test.py. Intel's Jenkins then waits for that run, tests each package again on its own machines, scans it, and for a release tag publishes the packages it tested. Jenkins isn't switched on for mkl_fft yet, so until it is, this only adds a GitHub Actions workflow.ci/matrix.py,ci/build.py,ci/hooks.py: the shared gh-ci scripts, standard library only. Here they look forconda-recipe-cf/first and build Linux and Windows on GitHub-hosted runners.hooks.pyinstalls the test requirements fromci/config.yml, the way Jenkins does.ci/test.py: runspytest --pyargs mkl_fftagainst the installed package and writes a JUnit report.ci/benchmark.py: becausebenchmarks/exists, Jenkins runs it once per pull request or tag, with the newest regular Linux package, on a bare-metal benchmarking machine. It runs the asv suite against the installed package: one quick sample of each benchmark on a pull request, a full measurement on a tag. A failing benchmark fails it; nothing compares the timings with a baseline yet.ci/config.yml: the workflow, the artifact names (mkl_fft {platform} Python {python}, asconda-package-cf.ymlnames them) and the test requirements,pytest,scipy >=1.10andmkl-service, and the benchmark requirements,psutil,scipy >=1.10andmkl-service, with asv from PyPI, as conda-forge has no asv for Python 3.15 yet.conda-recipe-cf/conda_build_config.yaml: now lists the Python versions, the onesconda-package-cf.ymlbuilds today, forci/matrix.py, andnumpy: '2'. Without a NumPy variant, conda-build falls back to NumPy 1.26, which has no builds for Python 3.13 and newer.conda-package-cf.ymlpasses--pythonand--numpyitself, so it is unaffected.ci/README.mdand AGENTS.md notes.A pull request builds the oldest and the newest regular Python versions on Linux and Windows; pushes to
masterand tags build them all.Miniforge is pinned to 26.7.2-0. Miniforge 26.9.4-0, released on 22 October, makes
setup-miniconda'sconda initfail on Windows runners, and the existingconda-package*.ymlworkflows, which installlatest, hit it too on this pull request.Overlap with #398. It also sets
numpy: '2'inconda_build_config.yamland drops Python 3.10, so whichever lands second needs a small rebase, and if 3.10 goes it should leave thepython:list here too.conda-package-cf.ymlandintel-ci.ymlnow both buildconda-recipe-cf; retiring one can be a follow-up.Verification
ci/test.pyagainst each package: 2769 passed on Linux and 2763 on Windows, on both versions.ci/benchmark.pyin quick mode, against an installed mkl_fft, ran all 46 benchmarks and exited 0, with the results underGH_CI_RESULTS.pre-commit runon every changed file, all hooks passing, andzizmoronintel-ci.yml, no findings.python ci/matrix.pylists 14 builds, Linux and Windows for 3.10 to 3.15 and 3.14t; with--event pull_requestit lists 3.10 and 3.15 on both.ci/config.ymlloads with gh-ci's own parser.Not verified