Handle empty target groups and improve dashboard deployment#2
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Avoid failing dashboard generation when a target group has no data. If plot_cumulative_state() receives an empty DataFrame, write a small placeholder HTML page and return before computing timestamp ranges. This fixes Deploy-Dashboard failures such as: ValueError: max() iterable argument is empty for empty groups like gcv_zve.
Add per-ref concurrency to Deploy-Dashboard and ignore dashboard-only pushes so dashboard auto-commits do not retrigger the workflow. This reduces non-fast-forward push races when multiple dashboard runs try to update main at the same time.
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The Pre-Pull-Request check has passed. The remaining pending checks appear to come from the Staging workflow, which invokes the full Run-Frequent build/test matrix. This PR only touches dashboard/plot.py and deploy-dashboard.yaml. It does not change GCC build/test workflows, target matrix, GCC checkout logic, release branch handling, or Binutils behavior. The fix addresses dashboard deployment robustness: handling empty dashboard target groups and reducing dashboard auto-commit push races. Given that this is a dashboard-only infrastructure fix and the lightweight checks have passed, I plan to merge this PR to restore dashboard stability unless there are objections. |
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Avoid failing dashboard generation when a target group has no data.
If plot_cumulative_state() receives an empty DataFrame, write a small
placeholder HTML page and return before computing timestamp ranges.
And add per-ref concurrency to Deploy-Dashboard and ignore dashboard-only
pushes so dashboard auto-commits do not retrigger the workflow.
This reduces non-fast-forward push races when multiple dashboard runs
try to update main at the same time.