Fix usage of dask-cuda in pip constraints

[KyleFromNVIDIA]

Description

Pip does not allow constraints to have extras. depends_on_dask_cuda previously had extras depending on the CUDA version, and as a result, the constraint file contained dask-cuda[cu12]. As a result, we saw the following error:

DEPRECATION: Constraints are only allowed to take the form of a package name and a version specifier. Other forms were originally permitted as an accident of the implementation, but were undocumented. The new implementation of the resolver no longer supports these forms. A possible replacement is replacing the constraint with a requirement. Discussion can be found at https://github.com/pypa/pip/issues/8210
ERROR: Constraints cannot have extras

Remove the extras in the constraints and allow the other dependencies to install the CUDA libraries instead.

This bug happened at least partly as a result of #21671.

Context:
https://github.com/rapidsai/cudf/actions/runs/30818064363/job/91710572211?pr=23472#step:13:86
https://github.com/rapidsai/cudf/actions/runs/30671159887/job/91293198335#step:13:95

Checklist

• I am familiar with the Contributing Guidelines.
• New or existing tests cover these changes.
• The documentation is up to date with these changes.

[coderabbitai]

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📥 Commits

Reviewing files that changed from the base of the PR and between 4f4d9bb and 56a398c.

📒 Files selected for processing (1)

• dependencies.yaml

🚧 Files skipped from review as they are similar to previous changes (1)

• dependencies.yaml

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📝 Walkthrough

Summary by CodeRabbit

• Changes
  • Requirements output now uses the standard dask-cuda package name without CUDA-specific extras.
  • PyProject output continues to include CUDA-specific extras where applicable.
  • Conda package behavior remains unchanged.

Walkthrough

The depends_on_dask_cuda declaration now emits unsuffixed dask-cuda for requirements output. CUDA-specific matrix handling remains limited to PyProject output. Conda behavior is unchanged.

Changes

Dask-CUDA dependency outputs

Layer / File(s)	Summary
Update Dask-CUDA dependency outputs dependencies.yaml	Requirements output includes unsuffixed dask-cuda. CUDA-specific matrix configuration applies only to PyProject output, while Conda behavior remains unchanged.

Estimated code review effort: 2 (Simple) | ~10 minutes

Suggested reviewers: msarahan

🚥 Pre-merge checks | ✅ 5

✅ Passed checks (5 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly identifies the fix for using dask-cuda in pip constraints.
Description check	✅ Passed	The description directly explains the pip constraint issue and the removal of CUDA-specific extras.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

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[jameslamb]

I don't understand this at all. What is the "bug" you're referring to here?

Including the relevant context (as a link or text) would help. I don't understand the problem this PR is trying to solve.

[jameslamb]

These changes look fine and I understand how they solve the core problem. If this passes CI, go ahead and merge it.

[KyleFromNVIDIA]

/merge

[KyleFromNVIDIA]

/merge