"""
Worker functions for parallel coverage calculation.

These run in separate processes and access shared memory data.
"""

from typing import List, Dict, Optional
from app.parallel.manager import SharedTerrainData, SharedBuildingData


def process_chunk(
    chunk: List[tuple],
    terrain_cache: dict,
    buildings: list,
    osm_data: dict,
    config: dict,
) -> List[dict]:
    """
    Process a chunk of grid points.

    This is the standard worker function used by both Ray and ProcessPoolExecutor.
    It re-uses the existing coverage calculation logic.
    """
    # Inject terrain cache into the module-level singleton
    from app.services.terrain_service import terrain_service
    terrain_service._tile_cache = terrain_cache

    # Build spatial index
    from app.services.spatial_index import SpatialIndex
    spatial_idx = SpatialIndex()
    if buildings:
        spatial_idx.build(buildings)

    # Process points using existing calculator
    from app.services.coverage_service import CoverageService, SiteParams, CoverageSettings

    site = SiteParams(**config['site_dict'])
    settings = CoverageSettings(**config['settings_dict'])
    svc = CoverageService()

    timing = {
        "los": 0.0, "buildings": 0.0, "antenna": 0.0,
        "dominant_path": 0.0, "street_canyon": 0.0,
        "reflection": 0.0, "vegetation": 0.0,
    }

    precomputed = config.get('precomputed')

    results = []
    for lat, lon, point_elev in chunk:
        pre = precomputed.get((lat, lon)) if precomputed else None
        point = svc._calculate_point_sync(
            site, lat, lon, settings,
            buildings, osm_data.get('streets', []),
            spatial_idx, osm_data.get('water_bodies', []),
            osm_data.get('vegetation_areas', []),
            config['site_elevation'], point_elev, timing,
            precomputed_distance=pre.get('distance') if pre else None,
            precomputed_path_loss=pre.get('path_loss') if pre else None,
        )
        if point.rsrp >= settings.min_signal:
            results.append(point.model_dump())

    return results