Update app.py

app.py

@@ -1,22 +1,32 @@
 import os
 import io
 import tempfile
+from datetime import datetime, timedelta, timezone
+
 import requests
 import pandas as pd
 import matplotlib.pyplot as plt
 import gradio as gr
-from datetime import datetime, timedelta, timezone
+
+# -------- tabulate（可選）偵測，沒裝也不會壞 --------
+try:
+    import tabulate as _tabulate  # noqa: F401
+    HAS_TABULATE = True
+except Exception:
+    HAS_TABULATE = False
 
 # -----------------------------
 # 台北時區 (UTC+8)
 # -----------------------------
 TAIPEI_TZ = timezone(timedelta(hours=8))
 
+
 def _fmt(dt: datetime) -> str:
     return dt.strftime("%Y-%m-%dT%H:%M:%S")
 
+
 def set_time_range(hours=None, days=None):
-    """依台北時間回傳 (timeFrom, timeTo)"""
+    """依台北時間回傳 (timeFrom, timeTo) 字串"""
     now = datetime.now(TAIPEI_TZ)
     if hours is not None:
         t_from = now - timedelta(hours=hours)
@@ -26,11 +36,13 @@ def set_time_range(hours=None, days=None):
         t_from = now - timedelta(days=3)
     return _fmt(t_from), _fmt(now)
 
+
 # -----------------------------
 # 取 API 資料
 # -----------------------------
 API_URL = "https://opendata.cwa.gov.tw/api/v1/rest/datastore/E-A0015-001"
 
+
 def fetch_reports(time_from, time_to):
     api_key = os.getenv("CWA_API_KEY", "").strip()
     if not api_key:
@@ -40,6 +52,7 @@ def fetch_reports(time_from, time_to):
     r.raise_for_status()
     return r.json()
 
+
 # -----------------------------
 # 解析 JSON → DataFrame（彈性容錯）
 # -----------------------------
@@ -52,6 +65,7 @@ def _safe_get(d, *keys, default=None):
             return default
     return cur
 
+
 def _to_float(x):
     try:
         if x is None or str(x).strip() == "":
@@ -60,14 +74,14 @@ def _to_float(x):
     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。
+    支援 records/Records、earthquake/Earthquake 等大小寫差異。
     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 = []
 
@@ -79,14 +93,8 @@ def parse_ea0015(obj):
             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")
-        )
+        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")
@@ -94,21 +102,20 @@ def parse_ea0015(obj):
             or _safe_get(q, "magnitude", "magnitude")
             or _safe_get(q, "Magnitude", "Magnitude")
         )
-        loc = (
-            _safe_get(q, "epicenter", "location")
-            or _safe_get(q, "Epicenter", "Location")
-        )
+        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
-        })
+        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:
@@ -116,10 +123,18 @@ def parse_ea0015(obj):
         df = df.sort_values("OriginTime", ascending=False, na_position="last").reset_index(drop=True)
     return df
 
+
 # -----------------------------
-# 視覺化
+# 視覺化（回傳「檔案路徑」以相容舊/新 Gradio）
 # -----------------------------
-def plot_trend(df):
+def _save_fig_to_tmp(fig, suffix=".png"):
+    buf_path = tempfile.NamedTemporaryFile(delete=False, suffix=suffix).name
+    fig.savefig(buf_path, format="png", dpi=160, bbox_inches="tight")
+    plt.close(fig)
+    return buf_path
+
+
+def plot_trend_path(df):
     if df.empty:
         return None
     fig, ax = plt.subplots(figsize=(6, 4))
@@ -128,13 +143,10 @@ def plot_trend(df):
     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()
+    return _save_fig_to_tmp(fig)
 
-def plot_map(df):
+
+def plot_map_path(df):
     if df.empty:
         return None
     lon_min, lon_max, lat_min, lat_max = 119, 123, 21, 26
@@ -148,17 +160,13 @@ def plot_map(df):
         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()
+    return _save_fig_to_tmp(fig)
+
 
 # -----------------------------
-# 主流程
+# 表格輸出（tabulate 可選）
 # -----------------------------
 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)
@@ -168,6 +176,21 @@ def _format_taipei(series):
     except Exception:
         return series.astype(str)
 
+
+def _to_simple_md_table(df: pd.DataFrame) -> str:
+    cols = list(df.columns)
+    header = "|" + "|".join(cols) + "|\n"
+    sep = "|" + "|".join(["---"] * len(cols)) + "|\n"
+    rows = []
+    for _, r in df.iterrows():
+        cells = []
+        for c in cols:
+            v = r.get(c, "")
+            cells.append("" if pd.isna(v) else str(v))
+        rows.append("|" + "|".join(cells) + "|")
+    return header + sep + "\n".join(rows)
+
+
 def df_to_markdown(df, top_n=100):
     if df.empty:
         return "（查無資料）"
@@ -177,26 +200,40 @@ def df_to_markdown(df, top_n=100):
     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)
+    if HAS_TABULATE:
+        table = slim.to_markdown(index=False)
+    else:
+        table = _to_simple_md_table(slim.reset_index(drop=True))
+    return header + table
+
 
+# -----------------------------
+# 主流程
+# -----------------------------
 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)
+        trend_path = plot_trend_path(df)
+        map_path = plot_map_path(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
+        csv_path = tempfile.NamedTemporaryFile(delete=False, suffix=".csv", prefix="CWA_E-A0015-001_").name
+        with open(csv_path, "wb") as f:
+            f.write(csv_bytes)
+
+        return md, trend_path, map_path, csv_path
     except Exception as e:
         return f"錯誤：{e}", None, None, None
 
+
 # -----------------------------
 # 介面
 # -----------------------------
@@ -207,28 +244,40 @@ with gr.Blocks(fill_height=True) as demo:
 
     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)
+        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")
+            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",
+        )
 
-        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
+        # 回傳檔案路徑 → Image 用 filepath 模式最穩
+        trend_out = gr.Image(label="趨勢圖", type="filepath")
+        map_out = gr.Image(label="台灣範圍圖", type="filepath")
+        dl_btn = gr.DownloadButton(label="下載 CSV")  # ���使用 file_name 參數，傳路徑即可
 
+    # 快速鍵
     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])
+    # 查詢
+    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()