app.py

import csv
import os
import gradio as gr
import pandas as pd
import plotly.express as px

CSV_PATH = "zones.csv"

def load_zones(csv_path: str = CSV_PATH):
    if not os.path.exists(csv_path):
        raise FileNotFoundError(
            f"Can't find {csv_path}. Add zones.csv in the Space Files tab (same folder as app.py)."
        )

    zones = []
    with open(csv_path, "r", encoding="utf-8", newline="") as f:
        reader = csv.DictReader(f)
        required = {
            "zone_id",
            "zone_name",
            "latitude",
            "longitude",
            "venue_density",
            "foot_traffic_index",
            "nightlife_score",
            "daytime_score",
            "primary_vibe",
            "notes",
        }
        missing = required - set(reader.fieldnames or [])
        if missing:
            raise ValueError("zones.csv is missing columns: " + ", ".join(sorted(missing)))

        def to_float(val, default=0.0):
            try:
                return float(val)
            except (TypeError, ValueError):
                return default

        for row in reader:
            zones.append(
                {
                    "zone_id": (row.get("zone_id") or "").strip(),
                    "zone_name": (row.get("zone_name") or "").strip(),
                    "lat": to_float(row.get("latitude")),
                    "lon": to_float(row.get("longitude")),
                    "venue_density": to_float(row.get("venue_density")),
                    "foot_traffic": to_float(row.get("foot_traffic_index")),
                    "nightlife": to_float(row.get("nightlife_score")),
                    "daytime": to_float(row.get("daytime_score")),
                    "vibe": (row.get("primary_vibe") or "").strip(),
                    "notes": (row.get("notes") or "").strip(),
                }
            )
    return zones

def score_zone(zone, time_of_day: str) -> float:
    ft = zone["foot_traffic"]
    vd = zone["venue_density"]
    nl = zone["nightlife"]
    dt = zone["daytime"]

    if time_of_day == "Tonight":
        time_factor = nl
    elif time_of_day == "Weekend":
        time_factor = 0.6 * nl + 0.4 * dt
    else:  # Now
        time_factor = 0.5 * nl + 0.5 * dt

    return (0.55 * ft) + (0.30 * time_factor) + (0.15 * vd)

def build_map(df: pd.DataFrame, time_of_day: str):
    if df.empty:
        return None

    # Center roughly around Sydney
    center_lat = df["lat"].mean()
    center_lon = df["lon"].mean()

    fig = px.scatter_mapbox(
        df,
        lat="lat",
        lon="lon",
        hover_name="zone_name",
        hover_data={
            "score": ":.2f",
            "vibe": True,
            "lat": False,
            "lon": False,
        },
        size="score",
        size_max=18,
        zoom=10,
        center={"lat": center_lat, "lon": center_lon},
        title=f"Hot Zones Map ({time_of_day})",
    )
    fig.update_layout(
        mapbox_style="open-street-map",
        margin={"l": 0, "r": 0, "t": 40, "b": 0},
        height=520,
    )
    return fig

def find_hot_places(time_of_day: str, top_k: int):
    try:
        zones = load_zones(CSV_PATH)
    except Exception as e:
        return f"⚠️ {e}", None

    if not zones:
        return "No zones found in zones.csv.", None

    ranked = []
    for z in zones:
        s = score_zone(z, time_of_day)
        ranked.append((s, z))

    ranked.sort(key=lambda x: x[0], reverse=True)
    ranked = ranked[: max(1, int(top_k))]

    rows = []
    lines = []
    for i, (s, z) in enumerate(ranked, start=1):
        rows.append(
            {
                "rank": i,
                "zone_name": z["zone_name"],
                "lat": z["lat"],
                "lon": z["lon"],
                "score": s,
                "vibe": z["vibe"],
                "notes": z["notes"],
            }
        )

        lines.append(
            f"{i}. 📍 {z['zone_name']} (score: {s:.2f})\n"
            f"Vibe: {z['vibe']}\n"
            f"Why: {z['notes']}"
        )

    df = pd.DataFrame(rows)
    fig = build_map(df, time_of_day)
    return "\n\n---\n\n".join(lines), fig

with gr.Blocks() as demo:
    gr.Markdown(
        "# 🔥 Sydney Hot Places\n"
        "Zone-level hotspot ranking using **mobility-style aggregated signals** (privacy-safe proxies).\n\n"
        "**Setup:** add a `zones.csv` file in the Space Files tab (same folder as `app.py`)."
    )

    with gr.Row():
        time_input = gr.Dropdown(
            choices=["Now", "Tonight", "Weekend"],
            value="Now",
            label="When are you going out?",
        )
        top_k = gr.Slider(
            minimum=1,
            maximum=12,
            value=6,
            step=1,
            label="How many zones to show?",
        )

    btn = gr.Button("Find hot places")

    # On desktop this shows side-by-side; on phone it stacks nicely.
    with gr.Row():
        output_text = gr.Textbox(label="Ranked Zones", lines=16)
        output_map = gr.Plot(label="Map")

    btn.click(fn=find_hot_places, inputs=[time_input, top_k], outputs=[output_text, output_map])

demo.launch()