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Update cwa_service.py
Browse files- cwa_service.py +167 -75
cwa_service.py
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# cwa_service.py
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import os
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import requests
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#
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CWA_API_URL = f"https://opendata.cwa.gov.tw/api/v1/rest/datastore/E-A0015-001?Authorization={CWA_API_KEY}&format=JSON"
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def get_latest_earthquake():
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"""
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Returns:
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tuple: 包含地震詳細資訊的訊息和報告圖片的 URL。如果出錯則返回錯誤訊息和 None。
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"""
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try:
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)
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return message, report_image_url
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else:
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return "目前無法獲取最新的地震資訊。", None
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except requests.exceptions.RequestException as e:
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print(f"Error fetching data from CWA API: {e}")
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return f"連接中央氣象署 API 時發生錯誤: {e}", None
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except (KeyError, IndexError) as e:
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print(f"Error parsing CWA API response: {e}")
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return "解析地震資料時發生錯誤,可能是資料格式有變。", None
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except Exception as e:
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return f"發生未知錯誤: {e}", None
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# cwa_service.py (修正與優化版本)
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import requests
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import re
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import pandas as pd # 請確保 'pandas' 已加入 requirements.txt
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from datetime import datetime, timedelta, timezone
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from config import CWA_API_KEY, CWA_ALARM_API, CWA_SIGNIFICANT_API
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# 定義台北時區 (UTC+8)
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TAIPEI_TZ = timezone(timedelta(hours=8))
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def _to_float(x) -> float | None:
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"""將輸入值穩健地轉換為浮點數,從字串中提取第一個數字。"""
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if x is None: return None
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s = str(x).strip()
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m = re.search(r"[-+]?\d+(?:\.\d+)?", s)
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return float(m.group()) if m else None
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def _parse_cwa_time(s: str) -> tuple[str, str]:
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"""
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穩健地解析 CWA API 可能回傳的兩種時間格式 (ISO 格式或本地時間格式)。
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返回 (台北時間字串, UTC時間字串)。
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"""
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if not s: return ("未知", "未知")
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dt_utc = None
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try:
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# 嘗試解析 ISO 8601 格式 (例如 "2025-08-22T14:06:15Z")
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dt_utc = datetime.fromisoformat(s.replace("Z", "+00:00"))
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except ValueError:
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# 如果失敗,嘗試解析本地時間格式 (例如 "2025-08-22 14:06:15")
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try:
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dt_local = datetime.strptime(s, "%Y-%m-%d %H:%M:%S")
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# 假設此格式為台北時間,並轉換為標準 UTC 時間
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dt_local = dt_local.replace(tzinfo=TAIPEI_TZ)
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dt_utc = dt_local.astimezone(timezone.utc)
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except Exception:
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# 如果兩種格式都失敗,直接返回原始字串
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return (s, "未知")
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if dt_utc:
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tw_str = dt_utc.astimezone(TAIPEI_TZ).strftime("%Y-%m-%d %H:%M")
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utc_str = dt_utc.astimezone(timezone.utc).strftime("%Y-%m-%d %H:%M")
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return (tw_str, utc_str)
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return (s, "未知")
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def fetch_cwa_alarm_list(limit: int = 5) -> str:
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"""獲取最新的地震預警列表。"""
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try:
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r = requests.get(CWA_ALARM_API, timeout=10)
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r.raise_for_status()
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payload = r.json()
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except Exception as e:
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return f"❌ 地震預警查詢失敗:{e}"
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items = payload.get("data", [])
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if not items: return "✅ 目前沒有地震預警。"
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# 依據時間排序,確保最新的在最前面
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def _key(it):
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try: return datetime.fromisoformat(it.get("originTime", "").replace("Z", "+00:00"))
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except: return datetime.min.replace(tzinfo=timezone.utc)
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items = sorted(items, key=_key, reverse=True)
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lines = ["🚨 地震預警(最新):", "-" * 20]
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for it in items[:limit]:
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mag = _to_float(it.get("magnitudeValue"))
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depth = _to_float(it.get("depth"))
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tw_str, _ = _parse_cwa_time(it.get("originTime", ""))
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# [修正] 移除不必要的 .replace('{', '{{'),直接使用 str() 即可
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identifier = str(it.get('identifier', '—'))
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msg_type = str(it.get('msgType', '—'))
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msg_no = str(it.get('msgNo', '—'))
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location_desc_list = it.get('locationDesc')
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areas = ", ".join(str(area) for area in location_desc_list) if isinstance(location_desc_list, list) and location_desc_list else "—"
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mag_str = f"{mag:.1f}" if mag is not None else "—"
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depth_str = f"{depth:.0f}" if depth is not None else "—"
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lines.append(
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f"事件: {identifier} | 類型: {msg_type}#{msg_no}\n"
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f"規模/深度: M{mag_str} / {depth_str} km\n"
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f"時間: {tw_str}(台灣)\n"
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f"地點: {areas}"
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)
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return "\n\n".join(lines).strip()
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def _parse_significant_earthquakes(obj: dict) -> pd.DataFrame:
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"""從 CWA API 的 JSON 回應中解析出顯著地震資料,並轉換為 Pandas DataFrame。"""
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records = obj.get("records", {})
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quakes = records.get("Earthquake", [])
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rows = []
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for q in quakes:
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ei = q.get("EarthquakeInfo", {})
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# 使用非常防禦性的方式取得資料,以應對 API 欄位名稱大小寫不一致或變動的問題
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epic = ei.get("Epicenter") or ei.get("epicenter") or {}
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mag_info = ei.get("Magnitude") or ei.get("magnitude") or {}
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depth_raw = ei.get("FocalDepth") or ei.get("depth")
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mag_raw = mag_info.get("MagnitudeValue") or mag_info.get("magnitudeValue")
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rows.append({
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"ID": q.get("EarthquakeNo"), "Time": ei.get("OriginTime"),
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"Lat": _to_float(epic.get("EpicenterLatitude") or epic.get("epicenterLatitude")),
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"Lon": _to_float(epic.get("EpicenterLongitude") or epic.get("epicenterLongitude")),
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"Depth": _to_float(depth_raw),
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"Magnitude": _to_float(mag_raw),
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"Location": epic.get("Location") or epic.get("location"),
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"URL": q.get("Web") or q.get("ReportURL"),
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"ImageURL": q.get("ReportImageURI"), # 也順便解析圖片 URL
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})
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df = pd.DataFrame(rows)
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if not df.empty and "Time" in df.columns:
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# 使用 pandas 內建功能將時間欄位轉換為帶有時區的 datetime 物件
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df["Time"] = pd.to_datetime(df["Time"], errors="coerce", utc=True).dt.tz_convert(TAIPEI_TZ)
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return df
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def fetch_significant_earthquakes(days: int = 7, limit: int = 5) -> str:
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"""獲取過去 N 天內的顯著地震列表。"""
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if not CWA_API_KEY: return "❌ 顯著地震查詢失敗:管理者尚未設定 CWA_API_KEY。"
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now = datetime.now(timezone.utc)
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time_from = (now - timedelta(days=days)).strftime("%Y-%m-%d")
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params = {"Authorization": CWA_API_KEY, "format": "JSON", "timeFrom": time_from}
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try:
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r = requests.get(CWA_SIGNIFICANT_API, params=params, timeout=15)
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r.raise_for_status()
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data = r.json()
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df = _parse_significant_earthquakes(data)
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if df.empty: return f"✅ 過去 {days} 天內沒有顯著有感地震報告。"
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# 依時間排序並取前 N 筆
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df = df.sort_values(by="Time", ascending=False).head(limit)
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lines = [f"🚨 CWA 最新顯著有感地震 (近{days}天内):", "-" * 20]
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for _, row in df.iterrows():
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mag_str = f"{row['Magnitude']:.1f}" if pd.notna(row['Magnitude']) else "—"
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depth_str = f"{row['Depth']:.0f}" if pd.notna(row['Depth']) else "—"
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lines.append(
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f"時間: {row['Time'].strftime('%Y-%m-%d %H:%M') if pd.notna(row['Time']) else '—'}\n"
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f"地點: {row['Location'] or '—'}\n"
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f"規模: M{mag_str} | 深度: {depth_str} km\n"
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f"報告: {row['URL'] or '無'}"
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)
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return "\n\n".join(lines)
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except Exception as e:
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return f"❌ 顯著地震查詢失敗:{e}"
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def fetch_latest_significant_earthquake() -> dict | None:
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"""獲取最新的一筆顯著地震的詳細資料 (包含圖片)。"""
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try:
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if not CWA_API_KEY:
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raise ValueError("錯誤:尚未設定 CWA_API_KEY Secret。")
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params = {"Authorization": CWA_API_KEY, "format": "JSON", "limit": 1, "orderby": "OriginTime desc"}
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r = requests.get(CWA_SIGNIFICANT_API, params=params, timeout=15)
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r.raise_for_status()
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data = r.json()
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df = _parse_significant_earthquakes(data)
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if df.empty:
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return None
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latest_eq_data = df.iloc[0].to_dict()
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# 將 Time object 轉換為格式化的字串,方便後續使用
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if pd.notna(latest_eq_data.get("Time")):
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latest_eq_data["TimeStr"] = latest_eq_data["Time"].strftime('%Y-%m-%d %H:%M')
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return latest_eq_data
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except Exception as e:
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# [優化] 發生錯誤時,印出日誌並回傳 None,避免程式崩潰
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print(f"[錯誤] 獲取最新顯著地震失敗: {e}")
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return None
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