from __future__ import annotations

import csv
import sys
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory

SCRIPTS_DIR = Path(__file__).resolve().parents[1] / "scripts"
sys.path.insert(0, str(SCRIPTS_DIR))

from apply_nsrdb_cloud_metric_to_climate_data import (  # noqa: E402
    POLYGON_SOURCE_TAG,
    REPRESENTATIVE_POINT_SOURCE_TAG,
    merge_metric,
)


def write_csv(path: Path, fieldnames: list[str], rows: list[dict[str, str]]) -> None:
    with path.open("w", encoding="utf-8", newline="") as handle:
        writer = csv.DictWriter(handle, fieldnames=fieldnames)
        writer.writeheader()
        writer.writerows(rows)


class ApplyNsrdbCloudMetricTests(unittest.TestCase):
    def test_polygon_area_weighted_value_wins_with_representative_fallback(self) -> None:
        with TemporaryDirectory() as temp_dir:
            base = Path(temp_dir)
            climate_data = base / "climate-data.csv"
            polygon_summary = base / "polygon-cloud.csv"
            representative_summary = base / "representative-cloud.csv"

            write_csv(
                climate_data,
                ["countyFips", "meanDailyGlobalHorizontalRadiationKwhM2Day", "clearSkyGhiReductionIndex", "source"],
                [
                    {
                        "countyFips": "01001",
                        "meanDailyGlobalHorizontalRadiationKwhM2Day": "4.8",
                        "clearSkyGhiReductionIndex": "0.9999",
                        "source": f"base + {REPRESENTATIVE_POINT_SOURCE_TAG}",
                    },
                    {
                        "countyFips": "01003",
                        "meanDailyGlobalHorizontalRadiationKwhM2Day": "4.9",
                        "clearSkyGhiReductionIndex": "",
                        "source": "base",
                    },
                    {
                        "countyFips": "01005",
                        "meanDailyGlobalHorizontalRadiationKwhM2Day": "5.0",
                        "clearSkyGhiReductionIndex": "",
                        "source": "base",
                    },
                ],
            )
            write_csv(
                polygon_summary,
                [
                    "county_fips",
                    "clearSkyGhiReductionIndex",
                    "areaWeightedClearSkyGhiReductionIndex",
                ],
                [
                    {
                        "county_fips": "01001",
                        "clearSkyGhiReductionIndex": "0.1111",
                        "areaWeightedClearSkyGhiReductionIndex": "0.2222",
                    },
                ],
            )
            write_csv(
                representative_summary,
                ["county_fips", "clearSkyGhiReductionIndex"],
                [
                    {"county_fips": "01001", "clearSkyGhiReductionIndex": "0.3333"},
                    {"county_fips": "01003", "clearSkyGhiReductionIndex": "0.4444"},
                ],
            )

            result = merge_metric(climate_data, polygon_summary, representative_summary)

            self.assertEqual(result, (3, 1, 1, 1))
            with climate_data.open("r", encoding="utf-8", newline="") as handle:
                rows = {row["countyFips"]: row for row in csv.DictReader(handle)}

        self.assertEqual(rows["01001"]["clearSkyGhiReductionIndex"], "0.2222")
        self.assertIn(POLYGON_SOURCE_TAG, rows["01001"]["source"])
        self.assertNotIn(REPRESENTATIVE_POINT_SOURCE_TAG, rows["01001"]["source"])
        self.assertEqual(rows["01003"]["clearSkyGhiReductionIndex"], "0.4444")
        self.assertIn(REPRESENTATIVE_POINT_SOURCE_TAG, rows["01003"]["source"])
        self.assertEqual(rows["01005"]["clearSkyGhiReductionIndex"], "")


if __name__ == "__main__":
    unittest.main()