Remove numpy<2 pin for pmdarima compatibility#18933
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The pmdarima issue (alkaline-ml/pmdarima#577) has been fixed, so we can remove the numpy<2 pin that was added in PR #18566. Changes: - Removed numpy<2 pin from .github/workflows/master.yml (python job) - Removed numpy<2 pin from mlflow/ml-package-versions.yml (pmdarima requirements) Co-authored-by: harupy <17039389+harupy@users.noreply.github.com>
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[WIP] Remove numpy pin in master.yml
Remove numpy<2 pin for pmdarima compatibility
Nov 20, 2025
harupy
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Nov 20, 2025
Per feedback, pmdarima versions below 2.1.0 still require numpy<2, so adding version-specific constraint. Co-authored-by: harupy <17039389+harupy@users.noreply.github.com>
harupy
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Nov 20, 2025
Incrementing N from 0 to 1 in py-cache-key action to force cache refresh and ensure numpy 2.x is used after removing the numpy<2 pin. Co-authored-by: harupy <17039389+harupy@users.noreply.github.com>
Signed-off-by: harupy <17039389+harupy@users.noreply.github.com>
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Nov 20, 2025
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Signed-off-by: harupy <17039389+harupy@users.noreply.github.com> Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: harupy <17039389+harupy@users.noreply.github.com> Co-authored-by: Harutaka Kawamura <hkawamura0130@gmail.com> Signed-off-by: Tian Lan <sky.blue266000@gmail.com>
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Related Issues/PRs
Addresses pmdarima issue alkaline-ml/pmdarima#577 which has been fixed upstream in pmdarima >= 2.1.0.
What changes are proposed in this pull request?
The numpy<2 pin was added in PR #18566 as a workaround for pmdarima incompatibility with numpy 2.x. Since the upstream issue is resolved in pmdarima >= 2.1.0, the blanket pin is no longer necessary.
Changes:
pip install "numpy<2"from.github/workflows/master.ymlpython job"< 2.1.0": ["numpy<2"]to pmdarima requirements inmlflow/ml-package-versions.yml.github/actions/py-cache-key/action.ymlto invalidate pip cache and ensure numpy 2.x is usedThis ensures that pmdarima versions < 2.1.0 (including the currently tested 2.0.4) still get numpy<2 as required, while future versions >= 2.1.0 won't have the numpy<2 constraint. The cache key increment forces a cache refresh so CI will use numpy 2.x after the pin is removed.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/tracking: Tracking Service, tracking client APIs, autologgingarea/models: MLmodel format, model serialization/deserialization, flavorsarea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflowsarea/gateway: MLflow AI Gateway client APIs, server, and third-party integrationsarea/prompts: MLflow prompt engineering features, prompt templates, and prompt managementarea/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionalityarea/projects: MLproject format, project running backendsarea/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notesShould this PR be included in the next patch release?
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