- 3 anomaly types: behind_schedule, ahead_of_schedule, low_utilization - 3 severity levels: low, medium, high - expected / actual / variance_pct (mirrors anomaly_detection service output) - 4-state lifecycle: new -> acknowledged -> resolved (or dismissed) - action_acknowledge / action_dismiss / action_resolve transitions - ondelete='cascade' on asset_id (anomalies follow the asset) - 4 new tests (63 total) Made-with: Cursor
6 lines
179 B
Python
6 lines
179 B
Python
from . import fusion_asset_category
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from . import fusion_asset
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from . import fusion_asset_depreciation_line
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from . import fusion_asset_disposal
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from . import fusion_asset_anomaly
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