Update cwa_service.py

cwa_service.py

@@ -31,8 +31,9 @@ def fetch_cwa_alarm_list(limit: int = 5) -> str:
     # ... (此函式內容不變) ...
     return "\n\n".join(lines).strip()
 
-# --- 顯著有感地震 (E-A0015-001) (此區塊不變) ---
+# --- 顯著有感地震 (E-A0015-001) ---
 def _parse_significant_earthquakes(obj: dict) -> pd.DataFrame:
+    """最穩健的解析邏輯，供 /significant 和 /latest 共用"""
     records = obj.get("records") or obj.get("Records") or {}
     quakes = records.get("earthquake") or records.get("Earthquake") or []
     rows = []
@@ -40,8 +41,10 @@ def _parse_significant_earthquakes(obj: dict) -> pd.DataFrame:
         ei = q.get("EarthquakeInfo") or q.get("earthquakeInfo") or {}
         epic = ei.get("Epicenter") or ei.get("epicenter") or {}
         mag_info = ei.get("Magnitude") or ei.get("magnitude") or ei.get("EarthquakeMagnitude") or {}
+        
         depth_raw = ei.get("FocalDepth") or ei.get("depth") or ei.get("Depth")
         mag_raw = mag_info.get("MagnitudeValue") or mag_info.get("magnitudeValue") or mag_info.get("Value") or mag_info.get("value")
+        
         rows.append({
             "ID": q.get("EarthquakeNo"), "Time": ei.get("OriginTime"),
             "Lat": _to_float(epic.get("EpicenterLatitude") or epic.get("epicenterLatitude")),
@@ -70,6 +73,7 @@ def fetch_significant_earthquakes(days: int = 7, limit: int = 5) -> str:
         df = _parse_significant_earthquakes(data)
         if df.empty: return f"✅ 過去 {days} 天內沒有顯著有感地震報告。"
         df = df.sort_values(by="Time", ascending=False).head(limit)
+        
         lines = [f"🚨 CWA 最新顯著有感地震 (近{days}天內):", "-" * 20]
         for _, row in df.iterrows():
             mag_str = f"{row['Magnitude']:.1f}" if pd.notna(row['Magnitude']) else "—"
@@ -84,52 +88,35 @@ def fetch_significant_earthquakes(days: int = 7, limit: int = 5) -> str:
     except Exception as e:
         return f"❌ 顯著地震查詢失敗：{e}"
 
-
 # --- 最新一筆顯著地震 ---
 def fetch_latest_significant_earthquake() -> dict | None:
-    """從 CWA 獲取最新一筆顯著有感地震的詳細資料，包含報告圖。"""
+    """[修改] 從 CWA 獲取最新一筆顯著地震，並重用 _parse_significant_earthquakes 解析邏輯"""
     if not CWA_API_KEY:
         raise ValueError("錯誤：尚未設定 CWA_API_KEY Secret。")
     
     now = datetime.now(timezone.utc)
-    time_from = (now - timedelta(days=1)).strftime("%Y-%m-%dT%H:%M:%S")
-
-    params = {
-        "Authorization": CWA_API_KEY,
-        "format": "JSON",
-        "timeFrom": time_from,
-        "limit": 1,
-        # [修正] 移除不支援的 sort 參數，API 預設即為時間倒序
-        # "sort": "OriginTime desc" 
-    }
+    time_from = (now - timedelta(days=2)).strftime("%Y-%m-%dT%H:%M:%S")
+    params = {"Authorization": CWA_API_KEY, "format": "JSON", "limit": 1}
     
     r = requests.get(CWA_SIGNIFICANT_API, params=params, timeout=15)
     r.raise_for_status()
     data = r.json()
 
-    quakes = data.get("records", {}).get("Earthquake", [])
-    if not quakes:
+    # 直接調用最穩健的解析函式
+    df = _parse_significant_earthquakes(data)
+    if df.empty:
         return None
 
-    q = quakes[0]
-    ei = q.get("EarthquakeInfo", {})
-    epic = q.get("Epicenter", {})
-    mag_info = ei.get("Magnitude", {})
-    
-    depth_raw = ei.get("FocalDepth") or ei.get("Depth")
-    mag_raw = mag_info.get("MagnitudeValue") or mag_info.get("value") or mag_info.get("Magnitude")
+    # 將 DataFrame 的第一筆資料轉為字典
+    latest_eq_data = df.sort_values(by="Time", ascending=False).iloc[0].to_dict()
     
-    result = {
-        "Time": ei.get("OriginTime"),
-        "Location": epic.get("Location"),
-        "Magnitude": _to_float(mag_raw),
-        "Depth": _to_float(depth_raw),
-        "URL": q.get("Web"),
-        "ImageURL": q.get("ReportImageURI")
-    }
-    
-    if result["Time"]:
-        dt = pd.to_datetime(result["Time"]).tz_localize("UTC").tz_convert(TAIPEI_TZ)
-        result["TimeStr"] = dt.strftime('%Y-%m-%d %H:%M')
+    # 從原始資料中手動加入圖片網址 (因為解析函式沒處理這個)
+    quakes = data.get("records", {}).get("Earthquake", [])
+    if quakes:
+        latest_eq_data["ImageURL"] = quakes[0].get("ReportImageURI")
+
+    # 格式化時間字串
+    if pd.notna(latest_eq_data.get("Time")):
+        latest_eq_data["TimeStr"] = latest_eq_data["Time"].strftime('%Y-%m-%d %H:%M')
 
-    return result
+    return latest_eq_data