Update app.py

app.py

@@ -36,4 +36,199 @@ def fetch_reports(time_from, time_to):
     if not api_key:
         raise RuntimeError("請在環境變數設定 CWA_API_KEY")
     params = {"Authorization": api_key, "timeFrom": time_from, "timeTo": time_to}
-    r = requests.get(API_URL, params=params, timeout=30
+    r = requests.get(API_URL, params=params, timeout=30)
+    r.raise_for_status()
+    return r.json()
+
+# -----------------------------
+# 解析 JSON → DataFrame（彈性容錯）
+# -----------------------------
+def _safe_get(d, *keys, default=None):
+    cur = d
+    for k in keys:
+        if isinstance(cur, dict) and k in cur:
+            cur = cur[k]
+        else:
+            return default
+    return cur
+
+def _to_float(x):
+    try:
+        if x is None or str(x).strip() == "":
+            return None
+        return float(str(x).strip())
+    except Exception:
+        return None
+
+def parse_ea0015(obj):
+    """
+    支援 records/Records、earthquake/Earthquake 等大小寫差異與常見欄位。
+    輸出欄位：OriginTime, Lat, Lon, Depth_km, Magnitude, Location, ReportURL
+    """
+    records = obj.get("records") or obj.get("Records") or {}
+    quakes = records.get("earthquake") or records.get("Earthquake") or records.get("data") or []
+
+    if not isinstance(quakes, list):
+        quakes = []
+
+    rows = []
+    for q in quakes:
+        origin = (
+            _safe_get(q, "originTime")
+            or _safe_get(q, "OriginTime")
+            or _safe_get(q, "earthquakeInfo", "originTime")
+            or _safe_get(q, "EarthquakeInfo", "OriginTime")
+        )
+        lat = (
+            _safe_get(q, "epicenter", "epicenterLat")
+            or _safe_get(q, "Epicenter", "EpicenterLat")
+        )
+        lon = (
+            _safe_get(q, "epicenter", "epicenterLon")
+            or _safe_get(q, "Epicenter", "EpicenterLon")
+        )
+        depth = _safe_get(q, "depth") or _safe_get(q, "Depth")
+        mag = (
+            _safe_get(q, "magnitude", "magnitudeValue")
+            or _safe_get(q, "Magnitude", "MagnitudeValue")
+            or _safe_get(q, "magnitude", "magnitude")
+            or _safe_get(q, "Magnitude", "Magnitude")
+        )
+        loc = (
+            _safe_get(q, "epicenter", "location")
+            or _safe_get(q, "Epicenter", "Location")
+        )
+        url = _safe_get(q, "reportURL") or _safe_get(q, "ReportURL")
+
+        rows.append({
+            "OriginTime": origin,
+            "Lat": _to_float(lat),
+            "Lon": _to_float(lon),
+            "Depth_km": _to_float(depth),
+            "Magnitude": _to_float(mag),
+            "Location": loc,
+            "ReportURL": url
+        })
+
+    df = pd.DataFrame(rows)
+    if not df.empty:
+        df["OriginTime"] = pd.to_datetime(df["OriginTime"], errors="coerce")
+        df = df.sort_values("OriginTime", ascending=False, na_position="last").reset_index(drop=True)
+    return df
+
+# -----------------------------
+# 視覺化
+# -----------------------------
+def plot_trend(df):
+    if df.empty:
+        return None
+    fig, ax = plt.subplots(figsize=(6, 4))
+    ax.scatter(df["OriginTime"], df["Magnitude"])
+    ax.set_xlabel("Origin Time (Taipei)")
+    ax.set_ylabel("Magnitude")
+    ax.grid(True, linestyle="--", alpha=0.4)
+    fig.autofmt_xdate()
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=150, bbox_inches="tight")
+    plt.close(fig)
+    buf.seek(0)
+    return buf.getvalue()
+
+def plot_map(df):
+    if df.empty:
+        return None
+    lon_min, lon_max, lat_min, lat_max = 119, 123, 21, 26
+    fig, ax = plt.subplots(figsize=(6, 6))
+    ax.set_xlim(lon_min, lon_max)
+    ax.set_ylim(lat_min, lat_max)
+    mags = df["Magnitude"].fillna(0)
+    sizes = (mags.clip(lower=0) + 2) ** 3
+    ax.scatter(df["Lon"], df["Lat"], s=sizes, alpha=0.6, edgecolor="black")
+    for m in [3, 4, 5, 6]:
+        ax.scatter([], [], s=((m + 2) ** 3), alpha=0.6, edgecolor="black", label=f"M {m}")
+    ax.legend(title="Magnitude")
+    ax.grid(True, linestyle="--", alpha=0.3)
+    buf = io.BytesIO()
+    fig.savefig(buf, format="png", dpi=150, bbox_inches="tight")
+    plt.close(fig)
+    buf.seek(0)
+    return buf.getvalue()
+
+# -----------------------------
+# 主流程
+# -----------------------------
+def _format_taipei(series):
+    """把時間 Series 以台北時間顯示；naive 視為台北時間，aware 轉為台北時間。"""
+    try:
+        if series.dt.tz is None:
+            s = series.dt.tz_localize(TAIPEI_TZ)
+        else:
+            s = series.dt.tz_convert(TAIPEI_TZ)
+        return s.dt.strftime("%Y-%m-%d %H:%M:%S %Z")
+    except Exception:
+        return series.astype(str)
+
+def df_to_markdown(df, top_n=100):
+    if df.empty:
+        return "（查無資料）"
+    cols = ["OriginTime", "Magnitude", "Depth_km", "Lat", "Lon", "Location", "ReportURL"]
+    cols = [c for c in cols if c in df.columns]
+    slim = df[cols].head(top_n).copy()
+    if "OriginTime" in slim.columns:
+        slim["OriginTime"] = _format_taipei(slim["OriginTime"])
+    header = f"共 {len(df)} 筆，顯示前 {min(len(slim), top_n)} 筆\n\n"
+    return header + slim.to_markdown(index=False)
+
+def query_and_render(time_from, time_to, sort_order):
+    try:
+        raw = fetch_reports(time_from, time_to)
+        df = parse_ea0015(raw)
+        if df.empty:
+            return "（查無資料）", None, None, None
+        if sort_order == "OriginTime (舊→新)":
+            df = df.sort_values("OriginTime", ascending=True, na_position="last").reset_index(drop=True)
+        md = df_to_markdown(df)
+        trend_png = plot_trend(df)
+        map_png = plot_map(df)
+        csv_bytes = df.to_csv(index=False).encode("utf-8-sig")
+        tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".csv", prefix="CWA_E-A0015-001_")
+        tmp.write(csv_bytes); tmp.flush(); tmp.close()
+        return md, trend_png, map_png, tmp.name
+    except Exception as e:
+        return f"錯誤：{e}", None, None, None
+
+# -----------------------------
+# 介面
+# -----------------------------
+default_from, default_to = set_time_range(days=3)
+
+with gr.Blocks(fill_height=True) as demo:
+    gr.Markdown("## CWA 顯著有感地震報告 (E-A0015-001)\n預設查詢最近 3 天（台北時間）")
+
+    with gr.Column():
+        time_from = gr.Textbox(label="timeFrom yyyy-MM-ddTHH:mm:ss", value=default_from)
+        time_to   = gr.Textbox(label="timeTo yyyy-MM-ddTHH:mm:ss", value=default_to)
+
+        with gr.Row():
+            btn_12h = gr.Button("最近 12 小時")
+            btn_24h = gr.Button("最近 24 小時")
+            btn_3d  = gr.Button("最近 3 天")
+            btn_5d  = gr.Button("最近 5 天")
+
+        sort_dd = gr.Dropdown(choices=["OriginTime (新→舊)", "OriginTime (舊→新)"], value="OriginTime (新→舊)", label="排序")
+        run_btn = gr.Button("查詢", variant="primary")
+
+        table_out = gr.Markdown("（尚未查詢）")
+        trend_out = gr.Image(label="趨勢圖", type="numpy")
+        map_out   = gr.Image(label="台灣範圍圖", type="numpy")
+        dl_btn    = gr.DownloadButton(label="下載 CSV")  # 相容舊/新版
+
+    btn_12h.click(lambda: set_time_range(hours=12), outputs=[time_from, time_to])
+    btn_24h.click(lambda: set_time_range(hours=24), outputs=[time_from, time_to])
+    btn_3d.click(lambda: set_time_range(days=3), outputs=[time_from, time_to])
+    btn_5d.click(lambda: set_time_range(days=5), outputs=[time_from, time_to])
+
+    run_btn.click(query_and_render, inputs=[time_from, time_to, sort_dd], outputs=[table_out, trend_out, map_out, dl_btn])
+
+if __name__ == "__main__":
+    demo.launch()