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b1ff711260
Even after batching the data writes, the handler still wrote to the DB per property through the orchestrator's SubTask bookkeeping: create + start + complete each self-committed, and _cascade re-listed every sibling and re-saved the parent on every transition — ~5 writes per property plus an O(N^2) cascade. - TaskOrchestrator.run_subtasks: create all children in one INSERT, run each (failures isolated per child), then persist all terminal states in one bulk save and cascade the parent once. Children go WAITING -> terminal; the transient IN_PROGRESS row is never written. - SubTaskRepository.create_many / save_many (bulk INSERT / bulk fetch + update). - _cascade short-circuits when the Task is already FAILED (terminal) — skips the sibling roll-up entirely. - modelling_e2e handler fans out via run_subtasks instead of per-property create_child_subtask + run_subtask. Per N-property batch the SubTask bookkeeping drops from ~5N writes + an O(N^2) cascade to ~2 writes + 1 cascade. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .. | ||
| bulk_upload | ||
| comparable_properties | ||
| epc | ||
| fuel_rates | ||
| geospatial | ||
| landlord_overrides | ||
| magic_plan | ||
| materials | ||
| plan | ||
| product | ||
| property | ||
| property_baseline | ||
| scenario | ||
| solar | ||
| spatial | ||
| tasks | ||
| unstandardised_address | ||
| uploaded_file | ||
| __init__.py | ||
| postgres_unit_of_work.py | ||
| unit_of_work.py | ||