app.py

app.py

@@ -1,397 +0,0 @@
-
-# app.py (trend charts + downloadable PNGs)
-import os
-import json
-import tempfile
-from datetime import datetime, timedelta
-from typing import List, Dict, Any, Tuple
-
-import gradio as gr
-import pandas as pd
-import requests
-import folium
-import matplotlib
-matplotlib.use("Agg")
-import matplotlib.pyplot as plt
-
-BASE_URL = "https://opendata.cwa.gov.tw/api/v1/rest/datastore/E-A0015-001"
-
-TILE_CHOICES = {
-    "OpenStreetMap": "OpenStreetMap",
-    "CartoDB Positron": "CartoDB positron",
-    "Stamen Terrain": "Stamen Terrain",
-    "Esri World Imagery (衛星)": "Esri.WorldImagery"
-}
-
-def validate_iso(dt: str) -> str:
-    if not dt:
-        return ""
-    try:
-        datetime.strptime(dt, "%Y-%m-%dT%H:%M:%S")
-        return dt
-    except ValueError:
-        raise gr.Error("時間格式需為 yyyy-MM-ddThh:mm:ss")
-
-def build_params(limit: int|None, offset: int|None, fmt: str, sort: str|None, timeFrom: str|None, timeTo: str|None):
-    params = []
-    api_key = os.getenv("CWA_API_KEY")
-    if not api_key:
-        raise gr.Error("缺少授權碼：請到 Space 的 Settings → Repository secrets 新增 CWA_API_KEY。")
-    params.append(("Authorization", api_key))
-    if limit is not None: params.append(("limit", str(limit)))
-    if offset is not None: params.append(("offset", str(offset)))
-    if fmt: params.append(("format", fmt))
-    if sort: params.append(("sort", sort))
-    if timeFrom: params.append(("timeFrom", timeFrom))
-    if timeTo: params.append(("timeTo", timeTo))
-    return params
-
-def http_get(url: str, params: List[Tuple[str,str]]) -> Dict[str, Any]:
-    sess = requests.Session()
-    resp = sess.get(url, params=params, timeout=(5, 20))
-    resp.raise_for_status()
-    if "application/json" in resp.headers.get("Content-Type","").lower() or resp.text.strip().startswith("{"):
-        return resp.json()
-    else:
-        return {"raw": resp.text}
-
-def extract_records(payload: Dict[str, Any]):
-    recs = payload.get("records")
-    if isinstance(recs, dict):
-        for k, v in recs.items():
-            if isinstance(v, list):
-                return v
-    result = payload.get("result")
-    if isinstance(result, dict) and isinstance(result.get("records"), list):
-        return result["records"]
-    for key in ("Earthquake","earthquakes","data","items"):
-        v = payload.get(key)
-        if isinstance(v, list):
-            return v
-    return []
-
-def flatten_row(row: Dict[str, Any]) -> Dict[str, Any]:
-    out = {}
-    for key in ("EarthquakeNo","ReportImageURI","Web","ReportColor","ReportContent"):
-        if key in row:
-            out[key] = row.get(key)
-    eqi = row.get("EarthquakeInfo")
-    if isinstance(eqi, dict):
-        out["OriginTime"] = eqi.get("OriginTime")
-        out["Depth_km"] = eqi.get("FocalDepth")
-        mag = eqi.get("EarthquakeMagnitude") or {}
-        if isinstance(mag, dict):
-            out["Magnitude"] = mag.get("MagnitudeValue")
-            out["MagnitudeType"] = mag.get("MagnitudeType")
-        epic = eqi.get("Epicenter") or {}
-        if isinstance(epic, dict):
-            out["Epicenter"] = epic.get("Location")
-            out["EpicenterLon"] = epic.get("EpicenterLongitude")
-            out["EpicenterLat"] = epic.get("EpicenterLatitude")
-    for k in ("OriginTime","originTime","Time"):
-        if k in row and "OriginTime" not in out:
-            out["OriginTime"] = row.get(k)
-    for k in ("Depth","depth","FocalDepth"):
-        if k in row and "Depth_km" not in out:
-            out["Depth_km"] = row.get(k)
-    for k in ("Magnitude","mag"):
-        if k in row and "Magnitude" not in out:
-            out["Magnitude"] = row.get(k)
-    maxint = row.get("Intensity") or row.get("ShakingArea")
-    if isinstance(maxint, dict):
-        out["MaxIntensity"] = maxint.get("MaxIntensity")
-    return out
-
-def df_with_types(df: pd.DataFrame) -> pd.DataFrame:
-    if "OriginTime" in df.columns:
-        try:
-            df["OriginTime"] = pd.to_datetime(df["OriginTime"], format="%Y-%m-%dT%H:%M:%S", errors="coerce")
-        except Exception:
-            pass
-    if "Magnitude" in df.columns:
-        df["Magnitude"] = pd.to_numeric(df["Magnitude"], errors="coerce")
-    if "Depth_km" in df.columns:
-        df["Depth_km"] = pd.to_numeric(df["Depth_km"], errors="coerce")
-    return df
-
-def add_tw_bbox(m: folium.Map):
-    bounds = [(21.0, 119.0), (26.0, 123.0)]
-    folium.Rectangle(bounds=bounds, color="#444", fill=False, weight=2, dash_array="5").add_to(m)
-
-def add_legend(m: folium.Map):
-    html = '''
-    <div style="position: fixed; bottom: 10px; right: 10px; z-index:9999; background: rgba(255,255,255,0.9); padding: 8px 10px; border:1px solid #999; border-radius:6px; font-size:12px;">
-      <div style="font-weight:600; margin-bottom:4px;">圖例</div>
-      <div><span style="display:inline-block;width:12px;height:12px;background:#abd9e9;margin-right:6px;border:1px solid #999;"></span> M4.0–4.9</div>
-      <div><span style="display:inline-block;width:12px;height:12px;background:#fdae61;margin-right:6px;border:1px solid #999;"></span> M5.0–5.9</div>
-      <div><span style="display:inline-block;width:12px;height:12px;background:#d7191c;margin-right:6px;border:1px solid #999;"></span> M≥6.0</div>
-      <div style="margin-top:4px;">圓徑 ≈ 規模 × 2.5</div>
-    </div>
-    '''
-    folium.Marker(location=[0,0], icon=folium.DivIcon(html=html)).add_to(m)
-
-def make_map(df: pd.DataFrame, tile_choice: str) -> str:
-    if not {"EpicenterLat","EpicenterLon"}.issubset(df.columns):
-        return "<p>沒有可用的經緯度資料。</p>"
-    valid = df.dropna(subset=["EpicenterLat","EpicenterLon"]).copy()
-    if valid.empty:
-        return "<p>沒有可用的經緯度資料。</p>"
-    try:
-        valid["EpicenterLat"] = pd.to_numeric(valid["EpicenterLat"], errors="coerce")
-        valid["EpicenterLon"] = pd.to_numeric(valid["EpicenterLon"], errors="coerce")
-    except Exception:
-        pass
-    valid = valid.dropna(subset=["EpicenterLat","EpicenterLon"])
-    if valid.empty:
-        return "<p>沒有可用的經緯度資料。</p>"
-
-    tiles = TILE_CHOICES.get(tile_choice, "OpenStreetMap")
-    if tiles == "Esri.WorldImagery":
-        m = folium.Map(location=[valid["EpicenterLat"].mean(), valid["EpicenterLon"].mean()], zoom_start=6, tiles=None)
-        folium.TileLayer(
-            tiles="https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}",
-            attr="Tiles © Esri — Source: Esri, i-cubed, USDA, USGS, AEX, GeoEye, Getmapping, Aerogrid, IGN, IGP, UPR-EGP, and the GIS User Community",
-            name="Esri World Imagery"
-        ).add_to(m)
-    else:
-        m = folium.Map(location=[valid["EpicenterLat"].mean(), valid["EpicenterLon"].mean()], zoom_start=6, tiles=tiles)
-
-    add_tw_bbox(m)
-
-    for _, r in valid.iterrows():
-        lat = float(r["EpicenterLat"]); lon = float(r["EpicenterLon"])
-        mag = r.get("Magnitude", None)
-        radius = 4.0
-        try:
-            if pd.notna(mag):
-                radius = max(4.0, min(20.0, float(mag) * 2.5))
-        except Exception:
-            pass
-        color = "#2c7bb6"
-        try:
-            if mag is not None and float(mag) >= 6.0:
-                color = "#d7191c"
-            elif mag is not None and float(mag) >= 5.0:
-                color = "#fdae61"
-            elif mag is not None and float(mag) >= 4.0:
-                color = "#abd9e9"
-        except Exception:
-            pass
-        popup = folium.Popup(html=f"<b>時間</b>: {r.get('OriginTime','')}<br>"
-                                  f"<b>震央</b>: {r.get('Epicenter','')}<br>"
-                                  f"<b>規模</b>: {mag}<br>"
-                                  f"<b>深度</b>: {r.get('Depth_km','')} km", max_width=320)
-        folium.CircleMarker(location=[lat, lon], radius=radius, color=color, fill=True, fill_opacity=0.7, popup=popup).add_to(m)
-    add_legend(m)
-    return m._repr_html_()
-
-def make_trend_charts(df: pd.DataFrame, tmpdir: str) -> Tuple[str, str]:
-    mag_time_png = os.path.join(tmpdir, "mag_time.png")
-    daily_count_png = os.path.join(tmpdir, "daily_count.png")
-
-    # Magnitude vs Time
-    if "OriginTime" in df.columns and "Magnitude" in df.columns and not df.empty:
-        s = df.dropna(subset=["OriginTime","Magnitude"]).copy()
-        if not s.empty:
-            plt.figure()
-            plt.plot(s["OriginTime"], s["Magnitude"], marker="o", linestyle="-")
-            plt.xlabel("Time")
-            plt.ylabel("Magnitude")
-            plt.title("Magnitude vs Time")
-            plt.xticks(rotation=45)
-            plt.tight_layout()
-            plt.savefig(mag_time_png, dpi=150)
-            plt.close()
-        else:
-            open(mag_time_png, "wb").write(b"")
-    else:
-        open(mag_time_png, "wb").write(b"")
-
-    # Daily counts
-    if "OriginTime" in df.columns and not df.empty:
-        s = df.dropna(subset=["OriginTime"]).copy()
-        if not s.empty:
-            s["date"] = s["OriginTime"].dt.date
-            cnt = s.groupby("date").size().reset_index(name="count")
-            plt.figure()
-            plt.plot(cnt["date"], cnt["count"], marker="o", linestyle="-")
-            plt.xlabel("Date")
-            plt.ylabel("Counts")
-            plt.title("Daily Earthquake Counts")
-            plt.xticks(rotation=45)
-            plt.tight_layout()
-            plt.savefig(daily_count_png, dpi=150)
-            plt.close()
-        else:
-            open(daily_count_png, "wb").write(b"")
-    else:
-        open(daily_count_png, "wb").write(b"")
-
-    return mag_time_png, daily_count_png
-
-def to_geojson(df: pd.DataFrame, path: str) -> str:
-    if not {"EpicenterLat","EpicenterLon"}.issubset(df.columns):
-        open(path, "w", encoding="utf-8").write(json.dumps({"type":"FeatureCollection","features":[]}))
-        return path
-    features = []
-    for _, r in df.iterrows():
-        try:
-            lat = float(r.get("EpicenterLat"))
-            lon = float(r.get("EpicenterLon"))
-        except (TypeError, ValueError):
-            continue
-        props = {
-            "OriginTime": str(r.get("OriginTime","")),
-            "Epicenter": r.get("Epicenter",""),
-            "Magnitude": r.get("Magnitude",""),
-            "Depth_km": r.get("Depth_km","")
-        }
-        features.append({
-            "type": "Feature",
-            "geometry": {"type": "Point", "coordinates": [lon, lat]},
-            "properties": props
-        })
-    fc = {"type":"FeatureCollection", "features": features}
-    with open(path, "w", encoding="utf-8") as f:
-        json.dump(fc, f, ensure_ascii=False, indent=2)
-    return path
-
-def to_kml(df: pd.DataFrame, path: str) -> str:
-    def esc(s):
-        return str(s).replace("&","&amp;").replace("<","&lt;").replace(">","&gt;")
-    kml = [
-        '<?xml version="1.0" encoding="UTF-8"?>',
-        '<kml xmlns="http://www.opengis.net/kml/2.2">',
-        "<Document>"
-    ]
-    if {"EpicenterLat","EpicenterLon"}.issubset(df.columns):
-        for _, r in df.iterrows():
-            try:
-                lat = float(r.get("EpicenterLat"))
-                lon = float(r.get("EpicenterLon"))
-            except (TypeError, ValueError):
-                continue
-            name = f"M{r.get('Magnitude','')} {r.get('Epicenter','')}"
-            desc = f"時間: {r.get('OriginTime','')}\n深度: {r.get('Depth_km','')} km"
-            kml.extend([
-                "<Placemark>",
-                f"<name>{esc(name)}</name>",
-                f"<description>{esc(desc)}</description>",
-                "<Point>",
-                f"<coordinates>{lon},{lat},0</coordinates>",
-                "</Point>",
-                "</Placemark>"
-            ])
-    kml.append("</Document></kml>")
-    with open(path, "w", encoding="utf-8") as f:
-        f.write("\n".join(kml))
-    return path
-
-def fetch(time_from, time_to, limit, offset, fmt, sort, tile_choice):
-    time_from = validate_iso(time_from) if time_from else None
-    time_to = validate_iso(time_to) if time_to else None
-    params = build_params(limit=limit, offset=offset, fmt=fmt, sort=sort, timeFrom=time_from, timeTo=time_to)
-    payload = http_get(BASE_URL, params)
-    records = extract_records(payload)
-    flat = [flatten_row(r) for r in records]
-    df = pd.DataFrame(flat)
-    df = df_with_types(df)
-    if "OriginTime" in df.columns:
-        ascending = True if sort == "OriginTime" else False
-        df = df.sort_values("OriginTime", ascending=ascending)
-    tmpdir = tempfile.mkdtemp(prefix="cwa_")
-    csv_path = os.path.join(tmpdir, "cwa_quake.csv")
-    json_path = os.path.join(tmpdir, "raw.json")
-    geojson_path = os.path.join(tmpdir, "cwa_quake.geojson")
-    kml_path = os.path.join(tmpdir, "cwa_quake.kml")
-    mag_time_png, daily_count_png = make_trend_charts(df, tmpdir)
-    df.to_csv(csv_path, index=False, encoding="utf-8")
-    with open(json_path, "w", encoding="utf-8") as f:
-        json.dump(payload, f, ensure_ascii=False, indent=2)
-    to_geojson(df, geojson_path)
-    to_kml(df, kml_path)
-    total = len(df)
-    earliest = latest = ""
-    if total and "OriginTime" in df.columns:
-        earliest_row = df.iloc[0]; latest_row = df.iloc[-1]
-        def fmt_row(r):
-            ot = r.get("OriginTime","")
-            if isinstance(ot, pd.Timestamp):
-                ot = ot.strftime("%Y-%m-%dT%H:%M:%S")
-            return f"{ot} | {r.get('Epicenter','')} | M{r.get('Magnitude','')} | 深{r.get('Depth_km','')}km"
-        earliest = "最早: " + fmt_row(earliest_row)
-        latest = "最新: " + fmt_row(latest_row)
-    summary = f"取得筆數: {total}\n{earliest}\n{latest}"
-    html_map = make_map(df, tile_choice)
-    if "OriginTime" in df.columns:
-        df["OriginTime"] = df["OriginTime"].astype(str)
-    return df, summary, csv_path, json_path, html_map, geojson_path, kml_path, mag_time_png, daily_count_png
-
-def quick_range(hours: int):
-    now = datetime.now()
-    tf = (now - timedelta(hours=hours)).strftime("%Y-%m-%dT%H:%M:%S")
-    tt = now.strftime("%Y-%m-%dT%H:%M:%S")
-    return tf, tt
-
-with gr.Blocks(title="CWA 顯著有感地震報告 (E-A0015-001)") as demo:
-    gr.Markdown("# CWA 顯著有感地震報告 (E-A0015-001)")
-    gr.Markdown("**此 Space 只使用環境變數 `CWA_API_KEY` 作為授權。** 預設查詢最近 3 天。")
-
-    tf_default = (datetime.now() - timedelta(days=3)).strftime("%Y-%m-%dT%H:%M:%S")
-    tt_default = datetime.now().strftime("%Y-%m-%dT%H:%M:%S")
-
-    time_from = gr.Textbox(label="timeFrom yyyy-MM-ddThh:mm:ss", value=tf_default)
-    time_to = gr.Textbox(label="timeTo yyyy-MM-ddThh:mm:ss", value=tt_default)
-    with gr.Row():
-        btn6 = gr.Button("最近 6 小時")
-        btn12 = gr.Button("最近 12 小時")
-        btn24 = gr.Button("最近 24 小時")
-        btn3d = gr.Button("最近 3 天")
-    sort = gr.Dropdown(choices=[None, "OriginTime"], value=None, label="sort（預設降冪；選 OriginTime 會升冪）")
-    limit = gr.Number(label="limit（筆數上限）", precision=0, value=60)
-    offset = gr.Number(label="offset（起始偏移）", precision=0, value=0)
-    fmt = gr.Radio(choices=["JSON","XML"], value="JSON", label="回傳格式")
-    tile_choice = gr.Dropdown(choices=list(TILE_CHOICES.keys()), value="OpenStreetMap", label="地圖底圖")
-
-    auto_on = gr.Checkbox(label="每小時自動刷新（固定使用目前 timeFrom/timeTo）", value=False)
-    timer = gr.Timer(3600.0)
-
-    run_btn = gr.Button("查詢", variant="primary")
-
-    out_df = gr.Dataframe(label="查詢結果（扁平化）", interactive=False, wrap=True, datatype="str")
-    out_summary = gr.Textbox(label="摘要", interactive=False)
-    out_csv = gr.File(label="下載 CSV")
-    out_json = gr.File(label="下載原始 JSON")
-    out_map = gr.HTML(label="震央地圖")
-    out_geojson = gr.File(label="下載 GeoJSON")
-    out_kml = gr.File(label="下載 KML")
-    out_mag_time = gr.Image(label="Magnitude vs Time（規模-時間趨勢）")
-    out_daily_cnt = gr.Image(label="Daily Earthquake Counts（每日件數）")
-    dl_mag_time = gr.File(label="下載 趨勢圖：Magnitude vs Time (PNG)")
-    dl_daily_cnt = gr.File(label="下載 趨勢圖：每日件數 (PNG)")
-
-    def on_click(time_from, time_to, limit, offset, fmt, sort, tile_choice):
-        df, summary, csv_path, json_path, html_map, geojson_path, kml_path, mag_time_png, daily_count_png = fetch(
-            time_from, time_to, int(limit) if limit is not None else None, int(offset) if offset is not None else None,
-            fmt, sort, tile_choice
-        )
-        return df, summary, csv_path, json_path, html_map, geojson_path, kml_path, mag_time_png, daily_count_png, mag_time_png, daily_count_png
-
-    def on_tick(auto_on, time_from, time_to, limit, offset, fmt, sort, tile_choice):
-        if not auto_on:
-            return [gr.skip()] * 11
-        return on_click(time_from, time_to, limit, offset, fmt, sort, tile_choice)
-
-    run_btn.click(on_click, inputs=[time_from, time_to, limit, offset, fmt, sort, tile_choice],
-                  outputs=[out_df, out_summary, out_csv, out_json, out_map, out_geojson, out_kml, out_mag_time, out_daily_cnt, dl_mag_time, dl_daily_cnt])
-
-    btn6.click(lambda: quick_range(6), inputs=[], outputs=[time_from, time_to])
-    btn12.click(lambda: quick_range(12), inputs=[], outputs=[time_from, time_to])
-    btn24.click(lambda: quick_range(24), inputs=[], outputs=[time_from, time_to])
-    btn3d.click(lambda: ((datetime.now() - timedelta(days=3)).strftime("%Y-%m-%dT%H:%M:%S"), datetime.now().strftime("%Y-%m-%dT%H:%M:%S")), inputs=[], outputs=[time_from, time_to])
-
-    timer.tick(on_tick, inputs=[auto_on, time_from, time_to, limit, offset, fmt, sort, tile_choice],
-               outputs=[out_df, out_summary, out_csv, out_json, out_map, out_geojson, out_kml, out_mag_time, out_daily_cnt, dl_mag_time, dl_daily_cnt])
-
-if __name__ == "__main__":
-    demo.launch()