221 lines
9.4 KiB
Python
221 lines
9.4 KiB
Python
from services import webcrumbs_host_data_service as svc
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def test_webcrumbs_host_data_maps_price_alert_exact_rows(monkeypatch):
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engine = object()
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monkeypatch.setattr(
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svc,
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"fetch_top_competitor_risks",
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lambda passed_engine, limit: [
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{
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"sku": "SKU-REVIEW",
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"name": "需人工覆核的非直接告警候選",
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"momo_price": 999,
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"pchome_price": 500,
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"gap_pct": 99.8,
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"match_score": 0.95,
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"alert_tier": "identity_review",
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"match_type": "exact",
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"price_basis": "total_price",
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},
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{
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"sku": "SKU-1",
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"name": "Derma Angel 護妍天使 集中抗痘精華",
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"momo_price": 420,
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"pchome_price": 250,
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"gap_pct": 68.0,
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"match_score": 0.91,
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"alert_tier": "price_alert_exact",
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"match_type": "exact",
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"price_basis": "total_price",
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"pchome_id": "DABC123",
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"pchome_name": "Derma Angel 集中抗痘精華",
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"crawled_at": "05/31 20:50",
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}
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],
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)
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monkeypatch.setattr(
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svc,
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"fetch_competitor_coverage",
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lambda passed_engine: {
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"valid_matches": 88,
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"match_rate": 12.3,
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"fresh_matches": 70,
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"fresh_match_rate": 79.5,
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"decision_ready_matches": 70,
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"decision_ready_rate": 9.8,
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"decision_support_count": 105,
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"decision_support_rate": 14.7,
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"decision_support_non_exact_count": 35,
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"catalog_comparable_count": 12,
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"catalog_comparable_rate": 1.7,
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"catalog_variant_review_count": 7,
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"catalog_unit_review_count": 3,
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"catalog_identity_review_count": 2,
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"catalog_review_plan": {
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"variant_review": 7,
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"unit_review": 3,
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"identity_review": 2,
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"total": 12,
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},
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"unit_comparable_count": 23,
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"stale_matches": 18,
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"pending": 612,
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},
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)
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monkeypatch.setattr(
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svc,
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"fetch_competitor_review_queue",
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lambda passed_engine, limit: [
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{
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"sku": "SKU-REVIEW",
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"name": "人工覆核精華液",
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"decision_envelope": {
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"decision_id": "review_queue:SKU-REVIEW",
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"severity": "P2",
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"subject": {
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"sku": "SKU-REVIEW",
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"name": "人工覆核精華液",
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"momo_price": 399,
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"competitor_price": 329,
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"competitor_product_id": "PCH-REVIEW",
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},
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"recommended_action": {
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"action": "review_accept_identity",
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"requires_hitl": True,
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},
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"expected_impact": {"candidate_gap_pct": 21.3},
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"guardrails": {
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"data_quality": "complete",
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"can_auto_execute": False,
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},
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"evidence": [
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{
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"metric": "match_score",
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"value": 0.91,
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"basis": "exact/total_price/identity_review",
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}
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],
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},
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}
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],
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)
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payload = svc.build_webcrumbs_marketplace_host_data(engine=engine, limit=5)
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assert payload["marketSnapshot"][0]["name"].startswith("SKU-1")
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assert payload["marketSnapshot"][0]["price"] == 250
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assert payload["marketSnapshot"][0]["change_pct"] == 68.0
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assert payload["aiCandidate"]["ticker"] == "SKU-1"
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assert payload["aiCandidate"]["confidence_score"] == 0.91
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assert "MOMO NT$420 vs PChome NT$250" in payload["aiCandidate"]["thesis"]
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assert payload["aiCandidate"]["release_status"] == "review_required"
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assert payload["metadata"]["writes_database"] is False
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assert payload["metadata"]["calls_llm"] is False
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assert payload["metadata"]["fetches_external"] is False
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assert payload["metadata"]["matched_count"] == 88
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assert payload["metadata"]["coverage_rate"] == 12.3
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assert payload["metadata"]["identity_coverage_rate"] == 12.3
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assert payload["metadata"]["decision_ready_count"] == 70
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assert payload["metadata"]["decision_ready_rate"] == 9.8
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assert payload["metadata"]["decision_support_count"] == 105
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assert payload["metadata"]["decision_support_rate"] == 14.7
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assert payload["metadata"]["decision_support_non_exact_count"] == 35
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assert payload["metadata"]["catalog_comparable_count"] == 12
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assert payload["metadata"]["catalog_comparable_rate"] == 1.7
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assert payload["metadata"]["catalog_variant_review_count"] == 7
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assert payload["metadata"]["catalog_unit_review_count"] == 3
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assert payload["metadata"]["catalog_identity_review_count"] == 2
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assert payload["metadata"]["catalog_review_plan"]["variant_review"] == 7
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assert payload["metadata"]["catalog_review_plan"]["unit_review"] == 3
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assert payload["metadata"]["catalog_review_plan"]["identity_review"] == 2
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assert payload["metadata"]["unit_comparable_count"] == 23
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assert payload["metadata"]["fresh_match_count"] == 70
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assert payload["metadata"]["fresh_match_rate"] == 79.5
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assert payload["metadata"]["stale_match_count"] == 18
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assert payload["metadata"]["pending_match_count"] == 612
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assert payload["metadata"]["review_queue_count"] == 1
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assert payload["metadata"]["hitl_count"] == 1
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assert payload["metadata"]["auto_execute_blocked_count"] == 1
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assert payload["metadata"]["decision_envelope_source"] == "competitor_intel_repository"
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assert payload["reviewDecisionBrief"]["items"][0]["sku"] == "SKU-REVIEW"
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assert payload["reviewDecisionBrief"]["items"][0]["can_auto_execute"] is False
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assert "review_accept_identity" in payload["reviewDecisionBrief"]["items"][0]["action"]
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assert all(row["freshness_status"] == "price_alert_exact" for row in payload["marketSnapshot"])
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def test_webcrumbs_host_data_uses_empty_state_without_risks(monkeypatch):
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monkeypatch.setattr(svc, "fetch_top_competitor_risks", lambda engine, limit: [])
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monkeypatch.setattr(svc, "fetch_competitor_review_queue", lambda engine, limit: [])
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monkeypatch.setattr(
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svc,
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"fetch_competitor_coverage",
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lambda engine: {
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"valid_matches": 3,
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"fresh_matches": 1,
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"decision_support_count": 4,
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"catalog_comparable_count": 2,
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"catalog_variant_review_count": 1,
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"catalog_unit_review_count": 1,
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"catalog_identity_review_count": 0,
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"catalog_review_plan": {
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"variant_review": 1,
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"unit_review": 1,
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"identity_review": 0,
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"total": 2,
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},
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"unit_comparable_count": 1,
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"stale_matches": 2,
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"pending": 9,
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},
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)
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payload = svc.build_webcrumbs_marketplace_host_data(engine=object(), limit=5)
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assert payload["marketSnapshot"][0]["freshness_status"] == "no_current_exact_risk"
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assert payload["aiCandidate"]["release_status"] == "blocked"
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assert payload["metadata"]["matched_count"] == 3
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assert payload["metadata"]["decision_ready_count"] == 1
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assert payload["metadata"]["decision_support_count"] == 4
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assert payload["metadata"]["catalog_comparable_count"] == 2
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assert payload["metadata"]["catalog_variant_review_count"] == 1
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assert payload["metadata"]["catalog_unit_review_count"] == 1
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assert payload["metadata"]["catalog_identity_review_count"] == 0
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assert payload["metadata"]["catalog_review_plan"]["total"] == 2
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assert payload["metadata"]["unit_comparable_count"] == 1
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assert payload["metadata"]["fresh_match_count"] == 1
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assert payload["metadata"]["stale_match_count"] == 2
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assert payload["metadata"]["pending_match_count"] == 9
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assert payload["metadata"]["review_queue_count"] == 0
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assert payload["reviewDecisionBrief"]["text"] == "（目前沒有待覆核決策信封）"
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assert "非同款、單位價或變體候選" in payload["aiCandidate"]["thesis"]
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def test_webcrumbs_seed_data_fallback_does_not_expose_demo_values(monkeypatch):
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from services import external_tool_payload_service as payload_service
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def boom(limit):
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raise RuntimeError("db unavailable")
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monkeypatch.setattr(payload_service, "build_webcrumbs_marketplace_host_data", boom)
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payload = payload_service.build_webcrumbs_seed_data(limit=5)
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assert payload["marketSnapshot"][0]["freshness_status"] == "diagnostic_unavailable"
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assert payload["aiCandidate"]["release_status"] == "blocked"
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assert "fallback demo" in payload["aiCandidate"]["thesis"]
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assert "TAIEX" not in str(payload)
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def test_webcrumbs_auth_required_seed_data_is_non_sensitive():
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from services.external_tool_payload_service import build_webcrumbs_auth_required_seed_data
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payload = build_webcrumbs_auth_required_seed_data()
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assert payload["marketSnapshot"][0]["freshness_status"] == "auth_required"
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assert payload["aiCandidate"]["release_status"] == "blocked"
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assert payload["metadata"]["source"] == "auth_required"
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assert "MOMO NT$" not in str(payload)
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assert "PChome NT$" not in str(payload)
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