"""Google Solar API data acquisition.

Handles geocoding, GeoTIFF download (RGB, building mask, DSM),
and parsing with CRS normalization to EPSG:4326.
"""

import io
import numpy as np
import requests
import rasterio
from rasterio.crs import CRS
from PIL import Image


def geocode_address(address: str, api_key: str) -> tuple[float, float, str]:
    """Convert address to lat/lng using Google Geocoding API."""
    url = "https://maps.googleapis.com/maps/api/geocode/json"
    params = {"address": address, "key": api_key}

    response = requests.get(url, params=params)
    data = response.json()

    if data["status"] != "OK":
        raise ValueError(f"Geocoding failed: {data['status']}")

    location = data["results"][0]["geometry"]["location"]
    formatted_address = data["results"][0]["formatted_address"]
    return location["lat"], location["lng"], formatted_address


def fetch_geotiff(
    lat: float, lng: float, api_key: str, radius_meters: int = 50
) -> tuple[bytes, bytes | None, bytes | None, dict]:
    """Fetch RGB GeoTIFF, building mask, and DSM from Google Solar API.

    Downloads at 0.1 m/pixel resolution. Tries HIGH quality first,
    falls back to MEDIUM.

    Returns:
        (rgb_bytes, mask_bytes, dsm_bytes, layers_info)
    """
    layers_url = "https://solar.googleapis.com/v1/dataLayers:get"
    params = {
        "location.latitude": lat,
        "location.longitude": lng,
        "radiusMeters": radius_meters,
        "view": "FULL_LAYERS",
        "requiredQuality": "HIGH",
        "pixelSizeMeters": 0.1,
        "key": api_key,
    }

    response = requests.get(layers_url, params=params)

    if response.status_code != 200:
        params["requiredQuality"] = "MEDIUM"
        response = requests.get(layers_url, params=params)

    if response.status_code != 200:
        raise ValueError(
            f"Data Layers API error: {response.status_code} - {response.text}"
        )

    layers = response.json()

    # RGB imagery
    rgb_url = layers.get("rgbUrl")
    if not rgb_url:
        raise ValueError("No RGB imagery available for this location")

    rgb_response = requests.get(f"{rgb_url}&key={api_key}")
    if rgb_response.status_code != 200:
        raise ValueError(f"Failed to download RGB GeoTIFF: {rgb_response.status_code}")

    # Building mask
    mask_bytes = None
    mask_url = layers.get("maskUrl")
    if mask_url:
        mask_response = requests.get(f"{mask_url}&key={api_key}")
        if mask_response.status_code == 200:
            mask_bytes = mask_response.content

    # DSM (Digital Surface Model)
    dsm_bytes = None
    dsm_url = layers.get("dsmUrl")
    if dsm_url:
        dsm_response = requests.get(f"{dsm_url}&key={api_key}")
        if dsm_response.status_code == 200:
            dsm_bytes = dsm_response.content

    return rgb_response.content, mask_bytes, dsm_bytes, layers


def _reproject_bounds(crs, bounds):
    """Reproject bounds to EPSG:4326 if needed."""
    if crs and crs != CRS.from_epsg(4326):
        from rasterio.warp import transform_bounds

        bounds = transform_bounds(crs, CRS.from_epsg(4326), *bounds)
    return bounds


def parse_geotiff(geotiff_bytes: bytes) -> tuple[Image.Image, tuple]:
    """Parse RGB GeoTIFF. Returns (PIL Image, bounds) with WGS84 bounds."""
    with rasterio.open(io.BytesIO(geotiff_bytes)) as src:
        if src.count >= 3:
            r, g, b = src.read(1), src.read(2), src.read(3)
            img_array = np.stack([r, g, b], axis=-1)
        else:
            band = src.read(1)
            img_array = np.stack([band] * 3, axis=-1)

        bounds = _reproject_bounds(src.crs, src.bounds)

    return Image.fromarray(img_array.astype(np.uint8)), bounds


def parse_building_mask(mask_bytes: bytes | None) -> tuple[np.ndarray | None, tuple | None]:
    """Parse building mask GeoTIFF. Binary: 1=building, 0=not."""
    if not mask_bytes:
        return None, None

    with rasterio.open(io.BytesIO(mask_bytes)) as src:
        mask = src.read(1)
        bounds = _reproject_bounds(src.crs, src.bounds)

    return mask, bounds


def parse_dsm(dsm_bytes: bytes | None) -> tuple[np.ndarray | None, tuple | None]:
    """Parse DSM GeoTIFF. Returns float height array in meters."""
    if not dsm_bytes:
        return None, None

    with rasterio.open(io.BytesIO(dsm_bytes)) as src:
        dsm = src.read(1)
        bounds = _reproject_bounds(src.crs, src.bounds)

    return dsm, bounds