import os
import requests
from loguru import logger
from dotenv import load_dotenv

load_dotenv()

# ── City config ──────────────────────────────────────────────────────────────
# These cities have active temperature markets on Polymarket
TARGET_CITIES = {
    "New York":     {"lat": 40.7128, "lon": -74.0060, "apify": "New York, New York"},
    "London":       {"lat": 51.5074, "lon": -0.1278,  "apify": "London, England"},
    "Miami":        {"lat": 25.7617, "lon": -80.1918,  "apify": "Miami, Florida"},
    "Tokyo":        {"lat": 35.6762, "lon": 139.6503,  "apify": "Tokyo, Japan"},
    "Los Angeles":  {"lat": 34.0522, "lon": -118.2437, "apify": "Los Angeles, California"},
}


# ── Apify fetcher ────────────────────────────────────────────────────────────
def fetch_weather_apify(cities: dict = TARGET_CITIES) -> dict:
    """
    Fetch 10-day weather forecast via Apify's weather-scraper actor.
    Returns a dict keyed by city name.
    """
    token = os.getenv("APIFY_API_TOKEN")
    if not token:
        raise ValueError("APIFY_API_TOKEN not set in .env")

    from apify_client import ApifyClient
    client = ApifyClient(token)
    locations = [info["apify"] for info in cities.values()]

    logger.info(f"Fetching Apify weather for: {locations}")

    run_input = {
        "locations": locations,
        "timeFrame": "ten_day",
        "units": "imperial",
        "maxItems": len(locations) * 10,
        "proxyConfiguration": {"useApifyProxy": True},
    }

    run = client.actor("epctex/weather-scraper").call(run_input=run_input)
    items = list(client.dataset(run["defaultDatasetId"]).iterate_items())

    # Map back by city name
    results = {}
    for city_name in cities:
        city_data = [
            item for item in items
            if cities[city_name]["apify"].split(",")[0].lower()
            in str(item.get("city", "")).lower()
        ]
        if city_data:
            results[city_name] = city_data
            logger.success(f"  ✓ {city_name}: {len(city_data)} forecast records")
        else:
            logger.warning(f"  ✗ {city_name}: no data from Apify, falling back")
            results[city_name] = _fetch_openmeteo_single(city_name, cities[city_name])

    return results


# ── Open-Meteo fallback ──────────────────────────────────────────────────────
def _fetch_openmeteo_single(city_name: str, city_info: dict) -> list:
    """
    Free fallback: Open-Meteo gives hourly/daily temp forecasts.
    Returns list of daily dicts matching Apify output shape.
    """
    url = "https://api.open-meteo.com/v1/forecast"
    params = {
        "latitude":    city_info["lat"],
        "longitude":   city_info["lon"],
        "daily":       "temperature_2m_max,temperature_2m_min,precipitation_sum,weathercode",
        "temperature_unit": "fahrenheit",
        "forecast_days": 10,
        "timezone":    "auto",
    }
    resp = requests.get(url, params=params, timeout=10)
    resp.raise_for_status()
    data = resp.json()["daily"]

    records = []
    for i, date in enumerate(data["time"]):
        records.append({
            "city":        city_name,
            "date":        date,
            "temperature": f"{data['temperature_2m_max'][i]}/{data['temperature_2m_min'][i]}",
            "high_f":      data["temperature_2m_max"][i],
            "low_f":       data["temperature_2m_min"][i],
            "precipitation": data["precipitation_sum"][i],
            "source":      "open-meteo",
        })

    logger.info(f"  Open-Meteo fallback: {city_name} → {len(records)} days")
    return records


def fetch_weather_openmeteo(cities: dict = TARGET_CITIES) -> dict:
    """Fetch all cities directly from Open-Meteo (no Apify needed)."""
    results = {}
    for city_name, info in cities.items():
        results[city_name] = _fetch_openmeteo_single(city_name, info)
    return results


def get_today_high(city_name: str, weather_data: dict) -> float | None:
    """Extract today's high temperature for a city from fetched weather data."""
    records = weather_data.get(city_name, [])
    if not records:
        return None

    today = records[0]  # First record = today

    # Handle Apify format: "temperature": "24/16"
    if isinstance(today.get("temperature"), str) and "/" in today["temperature"]:
        try:
            return float(today["temperature"].split("/")[0])
        except ValueError:
            pass

    # Handle Open-Meteo format
    return today.get("high_f")


def summarize_weather(weather_data: dict) -> str:
    """
    Returns a human-readable weather summary string for the LLM agent prompt.
    """
    lines = ["=== Current Weather Forecasts ==="]
    for city, records in weather_data.items():
        if not records:
            lines.append(f"  {city}: No data available")
            continue
        today = records[0]

        temp = today.get("temperature", "N/A")
        if today.get("high_f"):
            temp = f"{today['high_f']}°F high / {today.get('low_f', '?')}°F low"

        forecast = today.get("forecast", today.get("weathercode", "N/A"))
        lines.append(f"  {city}: {temp}  |  Conditions: {forecast}")

    return "\n".join(lines)