feat(runtime): support mapping-based scheduler configs - #1523
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Cause: environments currently accept scheduler strings or ready-made scheduler objects, which makes policy-driven runtime configuration harder to express consistently. Change: let resolve_scheduler() accept mapping configs via type/name/kind, normalize common load-aware aliases, and pass through LoadAwareScheduler options such as strategy and max_concurrent. Validation: python3 -m compileall src/sage/runtime/scheduler.py src/tests/test_runtime_local_consolidation.py; PYTHONPATH=/private/tmp/sage-testdeps:src python3 -m pytest src/tests/test_runtime_local_consolidation.py -q -k scheduler
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Hi team, any update on this PR? |
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This PR adds a small runtime API ergonomics improvement around scheduler selection.
Today Environment setup effectively accepts either a scheduler string or a pre-built scheduler object. That works, but it makes policy-driven configuration a bit awkward when the caller already has structured config data.
This change lets resolve_scheduler() accept mapping-based configs in addition to the existing string/object forms. In particular it:
I kept the scope intentionally small:
Validation used for this patch:
One note: there is a separate pre-existing failure in test_local_environment_round_robins_unkeyed_parallel_map_locally when running the entire file. This PR does not touch that behavior, so I kept validation scoped to the scheduler tests only.