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The committed gate needs frozen, reproducible data without dumping real UK addresses into the repo. Add: - harness anonymise_payload + stable_hash: hash street address + cert number into opaque, dedup-stable tokens; blank secondary address lines + post_town; keep postcode + all component/lodged fields (gov data is OGL). Unit-tested. - scripts/build_epc_prediction_fixture.py: curate qualifying postcodes (>=1 SAP 10.2 target + >=2 distinct addresses) from the local scratch corpus, anonymise, freeze under tests/fixtures/epc_prediction/. - The frozen fixture: 15 postcodes / 280 certs / 36 SAP-10.2 targets. Verified no plaintext address_line_1 and post_town all blank. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .. | ||
| eon | ||
| analyse_api_sap_clusters.py | ||
| build_epc_prediction_fixture.py | ||
| decompose_api_cost_error.py | ||
| download_cotality_evidence.py | ||
| elmhurst_input_sheet.py | ||
| eval_api_sap_accuracy.py | ||
| fetch_2026_epc_sample.py | ||
| fetch_cohort2_api_jsons.py | ||
| fetch_epc_bulk_sample.py | ||
| fetch_epc_dump.py | ||
| fetch_epc_prediction_corpus.py | ||
| historic_epc_demo.py | ||
| init_db.py | ||
| profile_api_error.py | ||
| rename_sharepoint_files.py | ||
| run_audit_generator_local.py | ||
| run_modelling_cohort.py | ||
| run_modelling_e2e.py | ||
| run_property_report.py | ||
| sero_address_list.csv | ||
| validate_epc_prediction.py | ||