Init

app.py

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+# app.py
+# Gradio app: Xweather hourly forecast table (next 12 hours)
+# Requirements: pip install gradio requests pandas python-dateutil
+
+import os
+import requests
+import pandas as pd
+import gradio as gr
+from zoneinfo import ZoneInfo
+
+BASE_URL = "https://data.api.xweather.com/forecasts/"
+
+CLIENT_ID = "BlZV8kShcnDxJ2ugQ3b65"
+CLIENT_SECRET = "JYvA8vAJJqEO6yP5QixQw59V3oUKqO9HHvj7ZI2R"
+
+def fetch_hourly_table(location: str):
+    """
+    location: either 'lat,lon' (e.g., '-6.29,106.82') or a place string (e.g., 'Jakarta, ID')
+    returns: (pandas.DataFrame, info_markdown)
+    """
+    if not CLIENT_ID or not CLIENT_SECRET:
+        return None, "❌ Missing API credentials. Please set XWEATHER_CLIENT_ID and XWEATHER_CLIENT_SECRET."
+
+    location = (location or "").strip()
+    if not location:
+        return None, "❌ Enter a location (e.g., '-6.29,106.82' or 'Jakarta, ID')."
+
+    # Build request
+    # {id} may be 'city,cc' or 'lat,lon'. Keep comma unescaped so the API recognizes coordinates.
+    url = BASE_URL + requests.utils.quote(location, safe=",")
+    params = {
+        "client_id": CLIENT_ID,
+        "client_secret": CLIENT_SECRET,
+        "filter": "1hr",  # hourly periods
+        "limit": 12       # next 12 hours
+    }
+
+    try:
+        r = requests.get(url, params=params, timeout=20)
+    except requests.RequestException as e:
+        return None, f"❌ Network error: {e}"
+
+    if r.status_code == 404:
+        # Common case: no coverage for that location
+        return None, f"⚠️ No forecast coverage for this location (404). Try a nearby city or adjust coordinates."
+    if r.status_code != 200:
+        # Show a short snippet of the response for debugging
+        body = r.text[:400]
+        return None, f"❌ API error {r.status_code}:\n```\n{body}\n```"
+
+    try:
+        data = r.json()
+    except ValueError:
+        return None, "❌ Failed to parse JSON response."
+
+    # Xweather returns a top-level list of records for this endpoint
+    # (loc/place/periods/profile per record)
+    # Fallbacks included in case the format changes.
+    records = []
+    if isinstance(data, list):
+        records = data
+    elif isinstance(data, dict) and "response" in data:
+        records = data["response"]
+    else:
+        records = [data]
+
+    if not records or "periods" not in records[0]:
+        return None, "⚠️ Unexpected response format or no periods returned."
+
+    rec = records[0]
+    periods = (rec.get("periods") or [])[:12]
+    if not periods:
+        return None, "⚠️ No hourly periods returned."
+
+    # Use location timezone if provided
+    tz_str = (rec.get("profile") or {}).get("tz")
+    tz = None
+    if tz_str:
+        try:
+            tz = ZoneInfo(tz_str)
+        except Exception:
+            tz = None
+
+    rows = []
+    for p in periods:
+        # Prefer ISO time (already timezone-aware with offset)
+        iso = p.get("dateTimeISO") or p.get("validTime")
+        dt = pd.to_datetime(iso) if iso else None
+        if tz and getattr(dt, "tzinfo", None) is not None:
+            try:
+                dt = dt.tz_convert(tz)
+            except Exception:
+                pass
+
+        rows.append({
+            "Time": dt.strftime("%Y-%m-%d %H:%M %Z") if isinstance(dt, pd.Timestamp) else iso,
+            "Weather": p.get("weatherPrimary") or p.get("weather"),
+            "Temp (°C)": p.get("tempC") if p.get("tempC") is not None else p.get("avgTempC"),
+            "Feels (°C)": p.get("feelslikeC") if p.get("feelslikeC") is not None else p.get("avgFeelslikeC"),
+            "Humidity (%)": p.get("humidity"),
+            "POP (%)": p.get("pop"),
+            "Precip (mm)": p.get("precipMM"),
+            "Wind (kph)": p.get("windSpeedKPH"),
+            "Wind Dir": p.get("windDir"),
+            "Visibility (km)": p.get("visibilityKM"),
+            "Cloud Cover (%)": p.get("sky"),
+        })
+
+    df = pd.DataFrame(rows)
+
+    place = rec.get("place") or {}
+    place_str = ", ".join([x for x in [place.get("name"), place.get("state"), place.get("country")] if x])
+    loc_str = f"**Location**: {place_str or location}"
+    tz_info = f" • **Timezone**: {tz_str}" if tz_str else ""
+    meta = f"{loc_str}{tz_info} • Periods: {len(df)} (filter=1hr, limit=12)"
+
+    return df, meta
+
+with gr.Blocks(fill_height=True) as demo:
+    gr.Markdown("## Xweather — Hourly Forecast (Next 12 Hours)")
+    with gr.Row():
+        loc = gr.Textbox(
+            label="Location",
+            placeholder="lat,lon (e.g., -6.21,106.85) or place name (e.g., 'Jakarta, ID')",
+            value="0.46876,116.16879"
+        )
+        btn = gr.Button("Get forecast", variant="primary")
+    out_table = gr.Dataframe(label="Hourly forecast", interactive=False, wrap=True)
+    out_info = gr.Markdown()
+
+    btn.click(fetch_hourly_table, inputs=loc, outputs=[out_table, out_info])
+
+if __name__ == "__main__":
+    # For local runs; on Spaces, Gradio will call this file directly.
+    demo.launch()

requirements.txt

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+gradio>=4.0.0
+requests
+pandas
+plotly
+python-dotenv