Build conda python packages independently of the Python version - #1744
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Build conda python packages independently of the Python version#1744ramakrishnap-nv wants to merge 9 commits into
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Build one cuopt wheel per (CUDA major, arch) instead of one per Python version, by targeting the CPython Limited API. This drops the cuopt wheel build from 8 CI jobs to 2 and removes the need for a new build when a Python version is added. - python/cuopt: set wheel.py-api = cp311, matching requires-python - bump cython to >=3.2.2,<3.3.0a0 for its Limited API support - name the wheel artifact with 'rapids-artifact-name --stable' (abi3) on both the producing and consuming sides - filter the wheel-build-cuopt matrix to the minimum supported Python Wheel tests still run against the full Python matrix, now all installing the single abi3 wheel. Closes #1725 Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
…tions Surfaced while adding abi3 wheel support: the first attempt invented a generic pip-arg passthrough instead of the '--stable' flag and 'RAPIDS_PY_API' env var that rmm and cudf already use, and would have missed 'rapids-artifact-name --stable' entirely. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
The cuopt wheel is now built as abi3, so CPython APIs outside the Limited API fail to compile. Point contributors at the constraint next to the existing Cython build note. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
- add abi3audit to ci/validate_wheel.sh, matching cudf/rmm. The '*abi*' name filter skips the py3-none wheels, which abi3audit rejects for having DSOs with no ABI tag. - group the cuopt wheel matrix by CUDA major rather than full CUDA version. Artifact names encode only the major, so two minors in one major would have produced two jobs racing on the same artifact name. No change to the current matrix. - skills: cudf now lives in the NVIDIA org - reword the Limited API note in CONTRIBUTING.md Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
Tighten the abi3audit selection from '*abi*' to '*-abi3-*.whl', and fail when 'python/cuopt' yields no abi3 wheel. Dropping 'wheel.py-api' would otherwise skip the audit silently and leave CI green. The check is scoped to 'python/cuopt' because libcuopt, cuopt_server and cuopt_sh_client share this script and are all 'py3-none'. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
The wheel build matrix intentionally carries a single CUDA minor per major, so grouping on the CUDA major added no coverage. Match the form used in cudf and the other RAPIDS repos instead. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
Drop the package-specific conditional so the set of packages sharing this script can change without anyone remembering to update it. The case it guarded is already caught: a cuopt wheel built without 'wheel.py-api' is tagged cp311-cp311, which fails to install in the Python 3.12+ wheel-test jobs. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
Build one set of conda python packages per CUDA x arch instead of one per Python version, taking conda-python-build from 16 jobs to 4. All three python packages have to become version-independent for the matrix filter to be safe, since they share a single output channel: - cuopt: abi3 via 'version_independent: true', built against the minimum supported Python. 'python-gil' is dropped because 'python-abi3' already depends on it transitively, and cython is raised to >=3.2.2 for its Limited API support. - cuopt-server, cuopt-sh-client: 'noarch: python'. Neither builds extension modules. build.sh passes the abi3 floor only for cuopt, so the two pure packages keep using the plain install args. Depends on #1731, which sets 'wheel.py-api' in python/cuopt. Signed-off-by: Ramakrishna Prabhu <ramakrishnap@nvidia.com>
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August 18, 2026 19:41
📝 WalkthroughWalkthroughChangesThe PR configures cuOpt and related packages for ABI3 or noarch Python builds. It updates stable artifact naming and downloads. CI matrices now select one minimum-Python build per CUDA and architecture combination. Stable Python packaging
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: 🟡 Moderate · up to The PR changes cuOpt server packages to noarch Python packages, but their conda metadata does not enforce the declared Python >=3.11 requirement; unsupported Python versions could therefore install the packages and fail at runtime. Merge should wait until the runtime constraints are added or explicitly accepted. Possibly related PRs
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In `@conda/recipes/cuopt-server/recipe.yaml`:
- Line 30: Update the runtime requirements in
conda/recipes/cuopt-server/recipe.yaml:42 and
conda/recipes/cuopt-sh-client/recipe.yaml:32 to require Python >=3.11, matching
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Follow-up to #1731, extending the CPython Limited API work to conda as @jakirkham asked. Follows the rmm rollout in rapidsai/rmm#2241, in the cudf shape (see below). xref rapidsai/build-planning#42.
Stacked on #1731 — based on that branch, so retarget to
mainonce it merges. The conda package only becomes abi3 oncewheel.py-apiis set inpython/cuopt/pyproject.toml.Takes
conda-python-buildfrom 16 jobs to 4 (one per CUDA x arch).Unlike rmm, cuOpt emits a single conda channel containing three python packages, so converting only
cuoptwould have saved nothing — the job would still run once per Python to produce the other two. All three therefore become version-independent, as cudf does:cuopt→version_independent: true,cp<ver>_abi3build string, built against the minimum supported Pythoncuopt-server,cuopt-sh-client→noarch: python; neither builds extension modulesTwo recipe details worth a look:
python-gilis dropped fromcuoptin favour ofpython =${{ py_abi_min }}+python-abi3 ${{ py_abi_min }}.*, matching cudf. The GIL constraint added in feat: add support for Python 3.14 #933 is preserved transitively:python-abi3→_python_abi3_support→python-gil.cythonin the recipe host is raised>=3.0.0→>=3.2.2to matchdependencies.yaml; the Limited API build needs it.build.shapplies the abi3 floor only tocuopt, sincePYTHON_ARGS_FOR_INSTALLis shared with the two pure packages here.Conda tests still run the full Python matrix against the single channel, which is what actually exercises the abi3 package.