599 lines
22 KiB
Python
599 lines
22 KiB
Python
import json
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from sqlalchemy import create_engine, text
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def _target(product_id, name, price, rank):
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return {
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"product_id": product_id,
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"name": name,
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"price": price,
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"execution_rank": rank,
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"execution_priority_score": 90 - rank,
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"revenue_share_pct": 20,
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"target_state": "unmatched",
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}
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def test_revenue_weighted_targets_include_candidate_validation_and_sort_by_revenue():
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from services.pchome_growth_same_item_reconciliation import (
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build_revenue_weighted_targets,
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)
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payload = {
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"opportunities": [
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{
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"pchome_product_id": "LOW",
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"product_name": "低業績未配對",
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"sales_7d": 100,
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"sales_prev_7d": 100,
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"priority_score": 95,
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"external_price": None,
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"recommended_action": {"code": "map_external_product"},
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},
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{
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"pchome_product_id": "HIGH",
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"product_name": "高業績候選",
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"sales_7d": 10000,
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"sales_prev_7d": 9000,
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"priority_score": 40,
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"external_price": None,
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"review_candidate": {"momo_sku": "M-1"},
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"recommended_action": {"code": "review_external_candidate"},
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},
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{
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"pchome_product_id": "READY",
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"product_name": "已有正式比價",
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"sales_7d": 50000,
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"priority_score": 100,
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"external_price": {"momo_sku": "M-2"},
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"recommended_action": {"code": "monitor"},
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},
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]
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}
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targets = build_revenue_weighted_targets(payload, 10)
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assert [item["product_id"] for item in targets] == ["HIGH", "LOW"]
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assert targets[0]["target_state"] == "candidate_validation"
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assert targets[0]["execution_rank"] == 1
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assert targets[0]["execution_priority_score"] > targets[1]["execution_priority_score"]
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def test_independent_verifier_promotes_exact_and_unit_candidates_but_rejects_conflict():
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from services.pchome_growth_same_item_reconciliation import (
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verify_same_item_candidates,
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)
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targets = [
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_target("P-EXACT", "理膚寶水 全面修復霜 B5 40ml", 679, 1),
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_target("P-UNIT", "理膚寶水 全面修復霜 B5 40ml", 679, 2),
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_target("P-BLOCK", "巴黎萊雅 膠原輕盈乳霜 60ml", 1249, 3),
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]
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candidates = [
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{
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"product_id": "M-EXACT",
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"name": "理膚寶水 B5 修復霜 40ml",
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"price": 699,
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"target_pchome_product_id": "P-EXACT",
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"auto_compare_type": "manual_review",
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},
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{
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"product_id": "M-UNIT",
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"name": "理膚寶水 B5 全面修復霜 40ml x2 超值組",
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"price": 1199,
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"target_pchome_product_id": "P-UNIT",
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"auto_compare_type": "unit_price",
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},
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{
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"product_id": "M-BLOCK",
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"name": "蘭蔻 玫瑰霜 60ml",
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"price": 5000,
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"target_pchome_product_id": "P-BLOCK",
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"target_search_term": "巴黎萊雅 膠原輕盈乳霜 60ml",
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"auto_compare_type": "total_price",
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},
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]
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identity = {
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"trace_id": "trace-1",
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"run_id": "run-1",
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"work_item_id": "GROWTH-P0-001-B",
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}
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result = verify_same_item_candidates(targets, candidates, identity=identity)
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selected = {item["target_pchome_product_id"]: item for item in result["verified_candidates"]}
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assert result["selected_candidate_count"] == 2
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assert result["blocked_candidate_count"] == 1
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assert result["claim_drift_count"] == 1
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assert selected["P-EXACT"]["auto_compare_type"] == "total_price"
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assert selected["P-UNIT"]["auto_compare_type"] == "unit_price"
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assert selected["P-UNIT"]["target_unit_price_comparison"]["comparable"] is True
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assert selected["P-EXACT"]["same_item_candidate_fingerprint"]
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assert result["blocked_candidates"][0]["reason_code"] == "same_item_verifier_rejected"
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assert result["blocked_candidates"][0]["source_name"] == "蘭蔻 玫瑰霜 60ml"
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assert result["blocked_candidates"][0]["search_term"] == "巴黎萊雅 膠原輕盈乳霜 60ml"
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assert result["blocked_candidates"][0]["comparison_mode"]
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assert result["blocked_candidates"][0]["reasons"]
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def test_independent_verifier_prefers_exact_sheet_pack_over_unit_candidate():
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from services.pchome_growth_same_item_reconciliation import (
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verify_same_item_candidates,
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)
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target = _target(
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"P-GATSBY-42",
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"GATSBY 潔面濕紙巾超值包42張入",
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199,
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1,
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)
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candidates = [
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{
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"product_id": "M-GATSBY-42",
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"name": "【GATSBY】潔面濕紙巾超值包42張入(2款任選)",
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"price": 179,
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"target_pchome_product_id": "P-GATSBY-42",
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"target_search_term": "gatsby 潔面濕紙巾 42張",
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"auto_compare_type": "manual_review",
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},
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{
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"product_id": "M-GATSBY-15",
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"name": "【GATSBY】潔面濕紙巾15張入(3款任選)",
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"price": 89,
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"target_pchome_product_id": "P-GATSBY-42",
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"target_search_term": "gatsby 潔面濕紙巾 42張",
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"auto_compare_type": "manual_review",
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},
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]
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result = verify_same_item_candidates(
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[target],
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candidates,
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identity={
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"trace_id": "trace-gatsby-pack",
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"run_id": "run-gatsby-pack",
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"work_item_id": "GROWTH-P0-001-B",
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},
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)
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assert result["selected_candidate_count"] == 1
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assert result["verified_candidates"][0]["product_id"] == "M-GATSBY-42"
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assert result["verified_candidates"][0]["auto_compare_type"] == "total_price"
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assert result["verified_candidate_count"] == 2
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assert result["blocked_candidate_count"] == 0
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unit_result = verify_same_item_candidates(
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[target],
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[candidates[1]],
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identity={
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"trace_id": "trace-gatsby-unit",
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"run_id": "run-gatsby-unit",
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"work_item_id": "GROWTH-P0-001-B",
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},
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)
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assert unit_result["selected_candidate_count"] == 1
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unit_candidate = unit_result["verified_candidates"][0]
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assert unit_candidate["auto_compare_type"] == "unit_price"
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assert unit_candidate["target_price_basis"] == "unit_price"
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assert unit_candidate["target_unit_price_comparison"]["comparable"] is True
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assert unit_candidate["target_unit_price_comparison"]["unit_label"] == "張"
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def test_independent_verifier_never_treats_outer_sheet_pack_as_exact_total_price():
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from services.pchome_growth_same_item_reconciliation import (
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verify_same_item_candidates,
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)
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target = _target(
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"P-GATSBY-42",
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"GATSBY 潔面濕紙巾超值包42張入",
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199,
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1,
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)
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result = verify_same_item_candidates(
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[target],
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[{
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"product_id": "M-GATSBY-42-X4",
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"name": "【GATSBY】潔面濕紙巾超值包42張入*4包(4款任選)",
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"price": 495,
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"target_pchome_product_id": "P-GATSBY-42",
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"target_search_term": "gatsby 潔面濕紙巾 42張",
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"auto_compare_type": "total_price",
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}],
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identity={
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"trace_id": "trace-gatsby-outer-pack",
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"run_id": "run-gatsby-outer-pack",
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"work_item_id": "GROWTH-P0-001-B",
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},
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)
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assert result["selected_candidate_count"] == 1
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candidate = result["verified_candidates"][0]
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assert candidate["auto_compare_type"] == "unit_price"
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assert candidate["same_item_reconciliation"]["candidate_claim_drift"] is True
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assert candidate["target_match_type"] == "same_product_different_pack"
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assert candidate["target_price_basis"] == "unit_price"
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assert candidate["target_unit_price_comparison"]["unit_label"] == "張"
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assert candidate["target_unit_price_comparison"]["momo_total_quantity"] == 168
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assert candidate["target_unit_price_comparison"]["competitor_total_quantity"] == 42
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def test_coverage_post_verifier_requires_exact_source_readback_and_reports_revenue_delta():
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from services.pchome_growth_same_item_reconciliation import (
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build_coverage_post_verifier,
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)
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before = {
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"stats": {"mapping_rate": 0, "mapped_count": 0},
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"opportunities": [
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{"pchome_product_id": "P-1", "sales_7d": 8000, "external_price": None},
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{"pchome_product_id": "P-2", "sales_7d": 2000, "external_price": None},
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],
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}
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after = {
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"stats": {"mapping_rate": 50, "mapped_count": 1},
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"opportunities": [
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{
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"pchome_product_id": "P-1",
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"sales_7d": 8000,
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"external_price": {"momo_sku": "M-1"},
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},
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{"pchome_product_id": "P-2", "sales_7d": 2000, "external_price": None},
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],
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}
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result = build_coverage_post_verifier(
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before_payload=before,
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after_payload=after,
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verified_candidates=[{
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"target_pchome_product_id": "P-1",
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"product_id": "M-1",
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}],
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sync_result={"written_count": 1},
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)
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assert result["status"] == "verified"
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assert result["all_checks_passed"] is True
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assert result["comparison_ready_delta"] == 1
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assert result["count_coverage_delta"] == 50
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assert result["revenue_coverage_delta"] == 80
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def test_exact_offer_readback_survives_target_leaving_dynamic_top50():
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from services.pchome_growth_same_item_reconciliation import (
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build_coverage_post_verifier,
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readback_external_offer_candidates,
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)
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engine = create_engine("sqlite:///:memory:")
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identity = {
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"trace_id": "trace-db-readback",
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"run_id": "run-db-readback",
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"work_item_id": "GROWTH-P0-001-B",
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}
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candidate = {
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"target_pchome_product_id": "P-LEAVES-TOP50",
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"product_id": "M-EXACT",
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"same_item_candidate_fingerprint": "fingerprint-exact",
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"same_item_reconciliation": identity,
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}
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with engine.begin() as conn:
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conn.execute(text("""
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CREATE TABLE external_offers (
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id INTEGER PRIMARY KEY,
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source_code TEXT NOT NULL,
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ingestion_method TEXT NOT NULL,
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pchome_product_id TEXT NOT NULL,
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source_product_id TEXT NOT NULL,
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match_status TEXT NOT NULL,
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data_quality_status TEXT NOT NULL,
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raw_payload_json TEXT NOT NULL,
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observed_at TEXT NOT NULL
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)
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"""))
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conn.execute(text("""
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INSERT INTO external_offers (
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id, source_code, ingestion_method, pchome_product_id,
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source_product_id, match_status, data_quality_status,
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raw_payload_json, observed_at
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) VALUES (
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1, 'momo_reference', 'targeted_momo_search',
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'P-LEAVES-TOP50', 'M-EXACT', 'verified', 'verified',
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:raw_payload, '2026-07-14T13:00:00'
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)
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"""), {
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"raw_payload": json.dumps({
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"same_item_reconciliation": identity,
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"same_item_candidate_fingerprint": "fingerprint-exact",
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})
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})
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exact_readback = readback_external_offer_candidates(engine, [candidate])
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result = build_coverage_post_verifier(
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before_payload={
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"stats": {"mapping_rate": 0, "mapped_count": 0},
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"opportunities": [{
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"pchome_product_id": "P-LEAVES-TOP50",
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"sales_7d": 10000,
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"external_price": None,
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}],
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},
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after_payload={
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"stats": {"mapping_rate": 0, "mapped_count": 0},
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"opportunities": [{
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"pchome_product_id": "P-NEW-TOP50-ROW",
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"sales_7d": 10000,
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"external_price": None,
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}],
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},
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verified_candidates=[candidate],
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sync_result={
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"written_count": 1,
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"independent_readback_required": True,
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"independent_readback": exact_readback,
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},
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)
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assert exact_readback["status"] == "verified"
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assert exact_readback["readback_pass_count"] == 1
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assert result["status"] == "verified"
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assert result["all_checks_passed"] is True
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assert result["readback"][0]["readback_source"] == "external_offers_exact_identity"
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assert result["readback"][0]["identity_passed"] is True
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assert result["readback"][0]["observed_candidate_fingerprint"] == "fingerprint-exact"
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def test_receipt_schema_apply_persistence_and_public_safe_readback():
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from services.pchome_growth_same_item_reconciliation import (
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ensure_evidence_receipt_table,
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persist_reconciliation_receipts,
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read_latest_reconciliation_receipts,
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)
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engine = create_engine("sqlite:///:memory:")
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schema = ensure_evidence_receipt_table(engine)
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target = _target("P-1", "商品", 100, 1)
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target.update({"sales_7d": 8000, "revenue_at_risk": 8000})
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run_receipt = {
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"generated_at": "2026-07-14T12:00:00+00:00",
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"identity": {
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"trace_id": "trace-1",
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"run_id": "run-1",
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"work_item_id": "GROWTH-P0-001-B",
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},
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"source_receipt": {"candidate_count": 1},
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"candidate_verification": {
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"verified_candidates": [{
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"target_pchome_product_id": "P-1",
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"product_id": "M-1",
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"name": "商品 100ml",
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"price": 90,
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"target_search_term": "商品 100ml",
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"target_match_score": 0.99,
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"target_comparison_mode": "total_price",
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"target_match_type": "exact",
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"target_price_basis": "total_price",
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"target_alert_tier": "price_alert_exact",
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"auto_compare_type": "total_price",
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"same_item_candidate_fingerprint": "fingerprint-1",
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"same_item_reconciliation": {
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"independent_verifier_passed": True,
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},
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}],
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"review_candidates": [],
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"blocked_candidates": [],
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},
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"coverage_diff": {"comparison_ready_delta": 1},
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"risk_policy": {"risk": "medium"},
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"check_mode": {"verified_candidate_count": 1},
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"execution": {"written_count": 1},
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"post_verifier": {
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"status": "verified",
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"readback": [{"target_pchome_product_id": "P-1", "passed": True}],
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},
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"terminal": {"status": "verified_with_coverage_gain"},
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}
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persistence = persist_reconciliation_receipts(
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engine,
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targets=[target],
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run_receipt=run_receipt,
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)
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readback = read_latest_reconciliation_receipts(engine)
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with engine.connect() as conn:
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evidence = conn.execute(text(
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"SELECT evidence_delta_json FROM external_offer_evidence_receipts"
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)).scalar_one()
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evidence = json.loads(evidence)
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assert schema["status"] == "created_and_verified"
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assert persistence["status"] == "persisted_and_verified"
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assert persistence["written_count"] == 1
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assert readback["status"] == "ready"
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assert readback["verified_count"] == 1
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assert readback["latest_run_id"] == "run-1"
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assert readback["receipts"][0]["work_item_id"] == "GROWTH-P0-001-B"
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assert evidence["target"]["sales_7d"] == 8000
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assert evidence["candidate_evidence"]["verified_candidate_count"] == 1
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assert evidence["candidate_evidence"]["verified_candidates"][0]["source_product_id"] == "M-1"
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assert evidence["candidate_evidence"]["verified_candidates"][0]["search_term"] == "商品 100ml"
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assert evidence["next_machine_action"] == "continue_next_revenue_weighted_batch"
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assert readback["receipts"][0]["next_machine_action"] == (
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"continue_next_revenue_weighted_batch"
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)
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assert readback["receipts"][0]["candidate_evidence_summary"] == {
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"verified_candidate_count": 1,
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"review_candidate_count": 0,
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"blocked_candidate_count": 0,
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"reason_codes": [],
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"verifier_reasons": [],
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}
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def test_rejected_pack_candidate_persists_autonomous_retry_action():
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from services.pchome_growth_same_item_reconciliation import (
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ensure_evidence_receipt_table,
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persist_reconciliation_receipts,
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read_latest_reconciliation_receipts,
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)
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engine = create_engine("sqlite:///:memory:")
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ensure_evidence_receipt_table(engine)
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target = _target(
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"P-GATSBY-42",
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"GATSBY 潔面濕紙巾超值包42張入",
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199,
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1,
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)
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run_receipt = {
|
|
"generated_at": "2026-07-15T00:30:00+00:00",
|
|
"identity": {
|
|
"trace_id": "trace-pack-retry",
|
|
"run_id": "run-pack-retry",
|
|
"work_item_id": "GROWTH-P0-001-B",
|
|
},
|
|
"candidate_verification": {
|
|
"verified_candidates": [],
|
|
"review_candidates": [],
|
|
"blocked_candidates": [{
|
|
"target_pchome_product_id": "P-GATSBY-42",
|
|
"source_product_id": "M-GATSBY-15",
|
|
"source_name": "GATSBY 潔面濕紙巾15張入",
|
|
"source_price": 89,
|
|
"search_term": "gatsby 潔面濕紙巾 42張",
|
|
"reason_code": "same_item_verifier_rejected",
|
|
"match_score": 0.92,
|
|
"hard_veto": True,
|
|
"comparison_mode": "blocked",
|
|
"match_type": "mismatch",
|
|
"price_basis": "none",
|
|
"alert_tier": "none",
|
|
"reasons": ["count_conflict"],
|
|
}],
|
|
},
|
|
"post_verifier": {"status": "no_write_verified", "readback": []},
|
|
"terminal": {"status": "verified_no_write"},
|
|
}
|
|
|
|
persistence = persist_reconciliation_receipts(
|
|
engine,
|
|
targets=[target],
|
|
run_receipt=run_receipt,
|
|
)
|
|
readback = read_latest_reconciliation_receipts(engine)
|
|
with engine.connect() as conn:
|
|
evidence = conn.execute(text(
|
|
"SELECT evidence_delta_json FROM external_offer_evidence_receipts"
|
|
)).scalar_one()
|
|
evidence = json.loads(evidence)
|
|
|
|
assert persistence["status"] == "persisted_and_verified"
|
|
assert evidence["ai_decision"] == "candidate_rejected"
|
|
assert evidence["candidate_evidence"]["reason_codes"] == [
|
|
"same_item_verifier_rejected"
|
|
]
|
|
assert evidence["candidate_evidence"]["verifier_reasons"] == [
|
|
"count_conflict"
|
|
]
|
|
assert evidence["next_machine_action"] == (
|
|
"retry_search_with_exact_pack_quantity"
|
|
)
|
|
receipt = readback["receipts"][0]
|
|
assert receipt["apply_status"] == "no_write"
|
|
assert receipt["next_machine_action"] == (
|
|
"retry_search_with_exact_pack_quantity"
|
|
)
|
|
assert receipt["candidate_evidence_summary"]["blocked_candidate_count"] == 1
|
|
assert receipt["candidate_evidence_summary"]["verifier_reasons"] == [
|
|
"count_conflict"
|
|
]
|
|
|
|
|
|
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")
|
|
css = Path("web/static/css/page-dashboard-v2.css").read_text(encoding="utf-8")
|
|
|
|
assert "業績比價覆蓋" in template
|
|
assert "growth.comparison_revenue_coverage_rate | default(0)" in template
|
|
assert "growth.comparison_revenue_coverage_width | default(0)" in template
|
|
assert "growth.comparison_ready_sales_7d" in template
|
|
assert "growth.comparison_total_sales_7d" in template
|
|
assert "growth.mapped_count" in template
|
|
assert ".growth-mapping-backlog {" in css
|
|
assert ".growth-mapping-backlog-grid {" in css
|
|
assert ".growth-automation-panel {" in css
|
|
assert ".growth-automation-steps {" in css
|
|
assert ".growth-automation-step {" in css
|
|
|
|
|
|
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"
|