fix: pick best targeted momo offer per pchome item

services/external_market_offer_service.py

@@ -712,6 +712,31 @@ def _targeted_candidate_needs_review(candidate: dict[str, Any]) -> bool:
     return bool(reasons & review_reason_markers)
 
 
+def _targeted_candidate_sync_rank(candidate: dict[str, Any]) -> tuple[float, float, float, float]:
+    """同一個 PChome 商品有多個候選時，挑最適合營運判斷的一筆。"""
+    auto_type = _targeted_candidate_auto_type(candidate)
+    type_rank = 3.0 if auto_type == "total_price" else 2.0 if auto_type == "unit_price" else 0.0
+    try:
+        match_score = float(candidate.get("target_match_score") or 0.0)
+    except (TypeError, ValueError):
+        match_score = 0.0
+
+    unit_price_comparison = (
+        candidate.get("target_unit_price_comparison")
+        if isinstance(candidate.get("target_unit_price_comparison"), dict)
+        else {}
+    )
+    momo_total = _to_float(unit_price_comparison.get("momo_total_quantity"))
+    pchome_total = _to_float(unit_price_comparison.get("competitor_total_quantity"))
+    quantity_delta = 999999.0
+    same_quantity = 0.0
+    if momo_total > 0 and pchome_total > 0:
+        quantity_delta = abs(momo_total - pchome_total)
+        same_quantity = 1.0 if quantity_delta <= 0.0001 else 0.0
+
+    return (type_rank, same_quantity, -quantity_delta, match_score)
+
+
 def _targeted_candidate_to_external_offer(
     candidate: dict[str, Any],
     *,
@@ -839,7 +864,7 @@ def sync_targeted_momo_candidates_to_external_offers(
 
         _ensure_external_market_source_seeds(conn)
         base_observed_at = datetime.now()
-        offers: list[dict[str, Any]] = []
+        ranked_offers: list[tuple[dict[str, Any], tuple[float, float, float, float]]] = []
         skipped_reasons: dict[str, int] = {}
         for index, candidate in enumerate(candidates):
             offer, reason = _targeted_candidate_to_external_offer(
@@ -847,9 +872,16 @@ def sync_targeted_momo_candidates_to_external_offers(
                 observed_at=base_observed_at + timedelta(microseconds=index),
             )
             if offer:
-                offers.append(offer)
+                ranked_offers.append((offer, _targeted_candidate_sync_rank(candidate)))
             else:
                 skipped_reasons[reason] = skipped_reasons.get(reason, 0) + 1
+        selected_by_pchome: dict[str, tuple[dict[str, Any], tuple[float, float, float, float]]] = {}
+        for offer, rank in ranked_offers:
+            key = str(offer.get("pchome_product_id") or offer.get("source_offer_key") or "").strip()
+            existing = selected_by_pchome.get(key)
+            if existing is None or rank > existing[1]:
+                selected_by_pchome[key] = (offer, rank)
+        offers = [offer for offer, _ in selected_by_pchome.values()]
 
         if not dry_run:
             for offer in offers: