import json from sqlalchemy import create_engine, text def _target(product_id, name, price, rank): return { "product_id": product_id, "name": name, "price": price, "execution_rank": rank, "execution_priority_score": 90 - rank, "revenue_share_pct": 20, "target_state": "unmatched", } def test_revenue_weighted_targets_include_candidate_validation_and_sort_by_revenue(): from services.pchome_growth_same_item_reconciliation import ( build_revenue_weighted_targets, ) payload = { "opportunities": [ { "pchome_product_id": "LOW", "product_name": "低業績未配對", "sales_7d": 100, "sales_prev_7d": 100, "priority_score": 95, "external_price": None, "recommended_action": {"code": "map_external_product"}, }, { "pchome_product_id": "HIGH", "product_name": "高業績候選", "sales_7d": 10000, "sales_prev_7d": 9000, "priority_score": 40, "external_price": None, "review_candidate": {"momo_sku": "M-1"}, "recommended_action": {"code": "review_external_candidate"}, }, { "pchome_product_id": "READY", "product_name": "已有正式比價", "sales_7d": 50000, "priority_score": 100, "external_price": {"momo_sku": "M-2"}, "recommended_action": {"code": "monitor"}, }, ] } targets = build_revenue_weighted_targets(payload, 10) assert [item["product_id"] for item in targets] == ["HIGH", "LOW"] assert targets[0]["target_state"] == "candidate_validation" assert targets[0]["execution_rank"] == 1 assert targets[0]["execution_priority_score"] > targets[1]["execution_priority_score"] def test_independent_verifier_promotes_exact_and_unit_candidates_but_rejects_conflict(): from services.pchome_growth_same_item_reconciliation import ( verify_same_item_candidates, ) targets = [ _target("P-EXACT", "理膚寶水 全面修復霜 B5 40ml", 679, 1), _target("P-UNIT", "理膚寶水 全面修復霜 B5 40ml", 679, 2), _target("P-BLOCK", "巴黎萊雅 膠原輕盈乳霜 60ml", 1249, 3), ] candidates = [ { "product_id": "M-EXACT", "name": "理膚寶水 B5 修復霜 40ml", "price": 699, "target_pchome_product_id": "P-EXACT", "auto_compare_type": "manual_review", }, { "product_id": "M-UNIT", "name": "理膚寶水 B5 全面修復霜 40ml x2 超值組", "price": 1199, "target_pchome_product_id": "P-UNIT", "auto_compare_type": "unit_price", }, { "product_id": "M-BLOCK", "name": "蘭蔻 玫瑰霜 60ml", "price": 5000, "target_pchome_product_id": "P-BLOCK", "auto_compare_type": "total_price", }, ] identity = { "trace_id": "trace-1", "run_id": "run-1", "work_item_id": "GROWTH-P0-001-B", } result = verify_same_item_candidates(targets, candidates, identity=identity) selected = {item["target_pchome_product_id"]: item for item in result["verified_candidates"]} assert result["selected_candidate_count"] == 2 assert result["blocked_candidate_count"] == 1 assert result["claim_drift_count"] == 1 assert selected["P-EXACT"]["auto_compare_type"] == "total_price" assert selected["P-UNIT"]["auto_compare_type"] == "unit_price" assert selected["P-UNIT"]["target_unit_price_comparison"]["comparable"] is True assert selected["P-EXACT"]["same_item_candidate_fingerprint"] assert result["blocked_candidates"][0]["reason_code"] == "same_item_verifier_rejected" def test_coverage_post_verifier_requires_exact_source_readback_and_reports_revenue_delta(): from services.pchome_growth_same_item_reconciliation import ( build_coverage_post_verifier, ) before = { "stats": {"mapping_rate": 0, "mapped_count": 0}, "opportunities": [ {"pchome_product_id": "P-1", "sales_7d": 8000, "external_price": None}, {"pchome_product_id": "P-2", "sales_7d": 2000, "external_price": None}, ], } after = { "stats": {"mapping_rate": 50, "mapped_count": 1}, "opportunities": [ { "pchome_product_id": "P-1", "sales_7d": 8000, "external_price": {"momo_sku": "M-1"}, }, {"pchome_product_id": "P-2", "sales_7d": 2000, "external_price": None}, ], } result = build_coverage_post_verifier( before_payload=before, after_payload=after, verified_candidates=[{ "target_pchome_product_id": "P-1", "product_id": "M-1", }], sync_result={"written_count": 1}, ) assert result["status"] == "verified" assert result["all_checks_passed"] is True assert result["comparison_ready_delta"] == 1 assert result["count_coverage_delta"] == 50 assert result["revenue_coverage_delta"] == 80 def test_receipt_schema_apply_persistence_and_public_safe_readback(): from services.pchome_growth_same_item_reconciliation import ( ensure_evidence_receipt_table, persist_reconciliation_receipts, read_latest_reconciliation_receipts, ) engine = create_engine("sqlite:///:memory:") schema = ensure_evidence_receipt_table(engine) target = _target("P-1", "商品", 100, 1) run_receipt = { "generated_at": "2026-07-14T12:00:00+00:00", "identity": { "trace_id": "trace-1", "run_id": "run-1", "work_item_id": "GROWTH-P0-001-B", }, "source_receipt": {"candidate_count": 1}, "candidate_verification": { "verified_candidates": [{"target_pchome_product_id": "P-1"}], "blocked_candidates": [], }, "coverage_diff": {"comparison_ready_delta": 1}, "risk_policy": {"risk": "medium"}, "check_mode": {"verified_candidate_count": 1}, "execution": {"written_count": 1}, "post_verifier": { "status": "verified", "readback": [{"target_pchome_product_id": "P-1", "passed": True}], }, "terminal": {"status": "verified_with_coverage_gain"}, } persistence = persist_reconciliation_receipts( engine, targets=[target], run_receipt=run_receipt, ) readback = read_latest_reconciliation_receipts(engine) assert schema["status"] == "created_and_verified" assert persistence["status"] == "persisted_and_verified" assert persistence["written_count"] == 1 assert readback["status"] == "ready" assert readback["verified_count"] == 1 assert readback["latest_run_id"] == "run-1" assert readback["receipts"][0]["work_item_id"] == "GROWTH-P0-001-B" def test_targeted_momo_search_keeps_same_source_product_per_pchome_target(): from services.momo_crawler import search_momo_products_for_pchome_products class FakeCrawler: def search_products(self, term, limit): return True, "ok", [{ "product_id": "MOMO-SAME", "name": "理膚寶水 B5 全面修復霜 40ml", "price": 699, }] success, _, candidates = search_momo_products_for_pchome_products( [ {"product_id": "P-1", "name": "理膚寶水 全面修復霜 B5 40ml", "price": 679}, {"product_id": "P-2", "name": "理膚寶水 全面修復霜 B5 40ml", "price": 679}, ], limit_per_product=3, max_products=2, max_terms_per_product=2, crawler=FakeCrawler(), ) assert success is True assert len(candidates) == 2 assert {item["target_pchome_product_id"] for item in candidates} == {"P-1", "P-2"} def test_dashboard_exposes_count_and_revenue_coverage_without_a_text_wall(): from pathlib import Path template = Path("templates/dashboard_v2.html").read_text(encoding="utf-8") assert "正式比價覆蓋" in template assert "業績涵蓋" in template assert "growth.comparison_revenue_coverage_rate" in template def test_same_item_reconciliation_route_returns_durable_readback(monkeypatch): from flask import Flask from routes import ai_routes as routes from services.pchome_growth_same_item_reconciliation import ( ensure_evidence_receipt_table, ) engine = create_engine("sqlite:///:memory:") ensure_evidence_receipt_table(engine) with engine.begin() as conn: conn.execute(text(""" INSERT INTO external_offer_evidence_receipts ( receipt_id, pchome_product_id, automation_decision, payload_hash, evidence_delta_json, apply_status ) VALUES ( 'sameitem-route', 'P-1', 'candidate_rejected', 'hash-1', :evidence, 'no_write' ) """), { "evidence": json.dumps({ "identity": { "trace_id": "trace-route", "run_id": "run-route", "work_item_id": "GROWTH-P0-001-B", }, "post_verifier": {"status": "no_write_verified"}, }) }) monkeypatch.setattr(routes, "_create_icaim_dashboard_engine", lambda _: engine) app = Flask(__name__) with app.test_request_context( "/api/ai/pchome-growth/same-item-reconciliation?limit=5" ): response = routes.api_pchome_growth_same_item_reconciliation.__wrapped__() payload = response.get_json() assert payload["status"] == "ready" assert payload["receipt_count"] == 1 assert payload["latest_run_id"] == "run-route"