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The app container has no outbound DNS, so astropy's IERS_Auto can never download a fresh Earth-orientation table and always falls back to the copy bundled with astropy-iers-data at image build. Once that copy's predictive data passed 30 days old, any date beyond it raised ValueError, and because backfill_dark_hours deliberately computes 35 days ahead, every run failed. astro_night now configures astropy to skip the download and accept the aged table. Dark hours only need the sun's altitude to a fraction of a degree, and the bundled UT1-UTC predictions are good to milliseconds, so the computed values are unchanged. Verified by reproducing the production error locally with downloads disabled and comparing against the online baseline. Users see the stats timeline efficiency keep rendering for the current month and the recurring task_failure event in the job monitor goes away.
Improve Dark Hours Calculation Reliability
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What's fixed