import os
import subprocess

import geopandas
from shapely import wkt

from datalayers.datasources.base_layer import BaseLayer
from datalayers.utils import get_engine
from shapes.models import Shape


class HealthsitesioFacilities(BaseLayer):
    def __init__(self) -> None:
        super().__init__()

        # table name for the cleaned records
        # can not be osm_airports. this name is used for the parameter!
        # but we want to store queried POIs as well
        self.raw_vector_data_table = "data_healthsitesio_facilities"

    def download(self):
        url = "https://healthsites.io/api/public/facilities/shapefile/Ghana/download"
        file_name = "Ghana.zip"

        if not os.path.isfile(self.get_data_path() / file_name):
            self._save_url_to_file(
                url, folder=self.get_data_path(), file_name=file_name
            )

        if os.path.isfile(self.get_data_path() / "LICENSE.txt"):
            return
        try:
            in_file = self.get_data_path() / file_name
            out_dir = self.get_data_path().as_posix()
            subprocess.run(
                f"unzip {in_file} -d {out_dir}",
                shell=True,
                capture_output=True,
                check=True,
            )
        except subprocess.CalledProcessError as error:
            self.layer.warning("Could not unzip files: %s", error.stderr)

        gdf = geopandas.read_file(self.get_data_path() / "Ghana-node.shp")
        gdf.to_postgis(
            self.raw_vector_data_table,
            con=get_engine(),
            index=False,
            if_exists="replace",
        )

    def process(self, shapes=None, save_output=False, param_dir=None):
        if shapes is None:
            shapes = Shape.objects.all()

        gdf = geopandas.read_postgis(
            f"SELECT * FROM {self.raw_vector_data_table}",
            geom_col="geometry",
            con=get_engine(),
        )

        for shape in shapes:
            mask = [wkt.loads(shape.geometry.wkt)]

            # clip to only facilities within area of interest
            gdfx = gdf[gdf["geometry"].within(mask[0])]

            self.rows.append({"year": 2024, "shape_id": shape.id, "value": len(gdfx)})

        self.save()