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- run_modelling_e2e --from-db re-models from already-persisted inputs (reads each Property's Effective EPC + planning protections + solar from the DB) and skips every live fetcher — zero gov-API calls. With --persist it re-writes the Plan and, for lodged-EPC Properties, the Baseline. Self-contained loop; the live-fetch path is untouched. Makes local re-runs instant and avoids tripping the gov API's per-IP rate limit (6000 req / 5 min) during iteration. - EpcClientService.REQUEST_TIMEOUT 10s -> 30s: a cold per-UPRN search can exceed 10s and the old timeout turned it into a timeout-then-retry; 30s rides it out. Note: an open perf question remains — modelling is fast in isolation (<0.5s/ property) but a long-lived --persist run shows ~1 min/property; suspected in the persist path (plan.save / baseline) or connection handling, NOT the API. Left mid-diagnosis for handover. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> |
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| .. | ||
| chatgpt | ||
| epc_client | ||
| landlord_overrides | ||
| magic_plan | ||
| openai | ||
| postgres | ||
| s3 | ||
| solar | ||
| __init__.py | ||
| address2uprn_queue_client.py | ||
| sqs_client.py | ||