Files
ewoooc/tests/test_pchome_same_item_reconciliation.py

599 lines
22 KiB
Python

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",
"target_search_term": "巴黎萊雅 膠原輕盈乳霜 60ml",
"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"
assert result["blocked_candidates"][0]["source_name"] == "蘭蔻 玫瑰霜 60ml"
assert result["blocked_candidates"][0]["search_term"] == "巴黎萊雅 膠原輕盈乳霜 60ml"
assert result["blocked_candidates"][0]["comparison_mode"]
assert result["blocked_candidates"][0]["reasons"]
def test_independent_verifier_prefers_exact_sheet_pack_over_unit_candidate():
from services.pchome_growth_same_item_reconciliation import (
verify_same_item_candidates,
)
target = _target(
"P-GATSBY-42",
"GATSBY 潔面濕紙巾超值包42張入",
199,
1,
)
candidates = [
{
"product_id": "M-GATSBY-42",
"name": "【GATSBY】潔面濕紙巾超值包42張入(2款任選)",
"price": 179,
"target_pchome_product_id": "P-GATSBY-42",
"target_search_term": "gatsby 潔面濕紙巾 42張",
"auto_compare_type": "manual_review",
},
{
"product_id": "M-GATSBY-15",
"name": "【GATSBY】潔面濕紙巾15張入(3款任選)",
"price": 89,
"target_pchome_product_id": "P-GATSBY-42",
"target_search_term": "gatsby 潔面濕紙巾 42張",
"auto_compare_type": "manual_review",
},
]
result = verify_same_item_candidates(
[target],
candidates,
identity={
"trace_id": "trace-gatsby-pack",
"run_id": "run-gatsby-pack",
"work_item_id": "GROWTH-P0-001-B",
},
)
assert result["selected_candidate_count"] == 1
assert result["verified_candidates"][0]["product_id"] == "M-GATSBY-42"
assert result["verified_candidates"][0]["auto_compare_type"] == "total_price"
assert result["verified_candidate_count"] == 2
assert result["blocked_candidate_count"] == 0
unit_result = verify_same_item_candidates(
[target],
[candidates[1]],
identity={
"trace_id": "trace-gatsby-unit",
"run_id": "run-gatsby-unit",
"work_item_id": "GROWTH-P0-001-B",
},
)
assert unit_result["selected_candidate_count"] == 1
unit_candidate = unit_result["verified_candidates"][0]
assert unit_candidate["auto_compare_type"] == "unit_price"
assert unit_candidate["target_price_basis"] == "unit_price"
assert unit_candidate["target_unit_price_comparison"]["comparable"] is True
assert unit_candidate["target_unit_price_comparison"]["unit_label"] == ""
def test_independent_verifier_never_treats_outer_sheet_pack_as_exact_total_price():
from services.pchome_growth_same_item_reconciliation import (
verify_same_item_candidates,
)
target = _target(
"P-GATSBY-42",
"GATSBY 潔面濕紙巾超值包42張入",
199,
1,
)
result = verify_same_item_candidates(
[target],
[{
"product_id": "M-GATSBY-42-X4",
"name": "【GATSBY】潔面濕紙巾超值包42張入*4包(4款任選)",
"price": 495,
"target_pchome_product_id": "P-GATSBY-42",
"target_search_term": "gatsby 潔面濕紙巾 42張",
"auto_compare_type": "total_price",
}],
identity={
"trace_id": "trace-gatsby-outer-pack",
"run_id": "run-gatsby-outer-pack",
"work_item_id": "GROWTH-P0-001-B",
},
)
assert result["selected_candidate_count"] == 1
candidate = result["verified_candidates"][0]
assert candidate["auto_compare_type"] == "unit_price"
assert candidate["same_item_reconciliation"]["candidate_claim_drift"] is True
assert candidate["target_match_type"] == "same_product_different_pack"
assert candidate["target_price_basis"] == "unit_price"
assert candidate["target_unit_price_comparison"]["unit_label"] == ""
assert candidate["target_unit_price_comparison"]["momo_total_quantity"] == 168
assert candidate["target_unit_price_comparison"]["competitor_total_quantity"] == 42
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_exact_offer_readback_survives_target_leaving_dynamic_top50():
from services.pchome_growth_same_item_reconciliation import (
build_coverage_post_verifier,
readback_external_offer_candidates,
)
engine = create_engine("sqlite:///:memory:")
identity = {
"trace_id": "trace-db-readback",
"run_id": "run-db-readback",
"work_item_id": "GROWTH-P0-001-B",
}
candidate = {
"target_pchome_product_id": "P-LEAVES-TOP50",
"product_id": "M-EXACT",
"same_item_candidate_fingerprint": "fingerprint-exact",
"same_item_reconciliation": identity,
}
with engine.begin() as conn:
conn.execute(text("""
CREATE TABLE external_offers (
id INTEGER PRIMARY KEY,
source_code TEXT NOT NULL,
ingestion_method TEXT NOT NULL,
pchome_product_id TEXT NOT NULL,
source_product_id TEXT NOT NULL,
match_status TEXT NOT NULL,
data_quality_status TEXT NOT NULL,
raw_payload_json TEXT NOT NULL,
observed_at TEXT NOT NULL
)
"""))
conn.execute(text("""
INSERT INTO external_offers (
id, source_code, ingestion_method, pchome_product_id,
source_product_id, match_status, data_quality_status,
raw_payload_json, observed_at
) VALUES (
1, 'momo_reference', 'targeted_momo_search',
'P-LEAVES-TOP50', 'M-EXACT', 'verified', 'verified',
:raw_payload, '2026-07-14T13:00:00'
)
"""), {
"raw_payload": json.dumps({
"same_item_reconciliation": identity,
"same_item_candidate_fingerprint": "fingerprint-exact",
})
})
exact_readback = readback_external_offer_candidates(engine, [candidate])
result = build_coverage_post_verifier(
before_payload={
"stats": {"mapping_rate": 0, "mapped_count": 0},
"opportunities": [{
"pchome_product_id": "P-LEAVES-TOP50",
"sales_7d": 10000,
"external_price": None,
}],
},
after_payload={
"stats": {"mapping_rate": 0, "mapped_count": 0},
"opportunities": [{
"pchome_product_id": "P-NEW-TOP50-ROW",
"sales_7d": 10000,
"external_price": None,
}],
},
verified_candidates=[candidate],
sync_result={
"written_count": 1,
"independent_readback_required": True,
"independent_readback": exact_readback,
},
)
assert exact_readback["status"] == "verified"
assert exact_readback["readback_pass_count"] == 1
assert result["status"] == "verified"
assert result["all_checks_passed"] is True
assert result["readback"][0]["readback_source"] == "external_offers_exact_identity"
assert result["readback"][0]["identity_passed"] is True
assert result["readback"][0]["observed_candidate_fingerprint"] == "fingerprint-exact"
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)
target.update({"sales_7d": 8000, "revenue_at_risk": 8000})
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",
"product_id": "M-1",
"name": "商品 100ml",
"price": 90,
"target_search_term": "商品 100ml",
"target_match_score": 0.99,
"target_comparison_mode": "total_price",
"target_match_type": "exact",
"target_price_basis": "total_price",
"target_alert_tier": "price_alert_exact",
"auto_compare_type": "total_price",
"same_item_candidate_fingerprint": "fingerprint-1",
"same_item_reconciliation": {
"independent_verifier_passed": True,
},
}],
"review_candidates": [],
"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)
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 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"
assert evidence["target"]["sales_7d"] == 8000
assert evidence["candidate_evidence"]["verified_candidate_count"] == 1
assert evidence["candidate_evidence"]["verified_candidates"][0]["source_product_id"] == "M-1"
assert evidence["candidate_evidence"]["verified_candidates"][0]["search_term"] == "商品 100ml"
assert evidence["next_machine_action"] == "continue_next_revenue_weighted_batch"
assert readback["receipts"][0]["next_machine_action"] == (
"continue_next_revenue_weighted_batch"
)
assert readback["receipts"][0]["candidate_evidence_summary"] == {
"verified_candidate_count": 1,
"review_candidate_count": 0,
"blocked_candidate_count": 0,
"reason_codes": [],
"verifier_reasons": [],
}
def test_rejected_pack_candidate_persists_autonomous_retry_action():
from services.pchome_growth_same_item_reconciliation import (
ensure_evidence_receipt_table,
persist_reconciliation_receipts,
read_latest_reconciliation_receipts,
)
engine = create_engine("sqlite:///:memory:")
ensure_evidence_receipt_table(engine)
target = _target(
"P-GATSBY-42",
"GATSBY 潔面濕紙巾超值包42張入",
199,
1,
)
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"