import json
import tempfile
import unittest
from datetime import UTC, datetime
from pathlib import Path

from app.services.phase3_kpi_export import (
    KPI_REPORT_PATH,
    PHASE3_KPI_METRICS,
    PREPOST_CSV_PATH,
    ParticipantKeys,
    build_kpi_report,
    build_prepost_csv_rows,
    paired_prepost_summary,
    write_kpi_report,
    write_prepost_csv,
)
from app.services.phase3_kpi_contract import KPI_METRIC_REQUIRED_KEYS


def fixture_rows():
    return [
        {
            "learner_id": "11111111-1111-1111-1111-111111111111",
            "measure_name": "self_efficacy",
            "timepoint": "pre",
            "raw_score": 2,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 0, 0, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 0, 1, tzinfo=UTC),
        },
        {
            "learner_id": "11111111-1111-1111-1111-111111111111",
            "measure_name": "self_efficacy",
            "timepoint": "pre",
            "raw_score": 3,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 0, 2, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 0, 3, tzinfo=UTC),
        },
        {
            "learner_id": "11111111-1111-1111-1111-111111111111",
            "measure_name": "self_efficacy",
            "timepoint": "post",
            "raw_score": 4,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 1, 0, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 1, 0, tzinfo=UTC),
        },
        {
            "learner_id": "22222222-2222-2222-2222-222222222222",
            "measure_name": "self_efficacy",
            "timepoint": "pre",
            "raw_score": 4,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 0, 5, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 0, 5, tzinfo=UTC),
        },
        {
            "learner_id": "11111111-1111-1111-1111-111111111111",
            "measure_name": "skill_proficiency",
            "timepoint": "pre",
            "raw_score": 2,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 0, 10, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 0, 10, tzinfo=UTC),
        },
        {
            "learner_id": "11111111-1111-1111-1111-111111111111",
            "measure_name": "skill_proficiency",
            "timepoint": "post",
            "raw_score": 5,
            "min_score": 1,
            "max_score": 5,
            "collected_at": datetime(2026, 6, 27, 1, 10, tzinfo=UTC),
            "updated_at": datetime(2026, 6, 27, 1, 10, tzinfo=UTC),
        },
    ]


class Phase3KpiExportTests(unittest.TestCase):
    def test_prepost_csv_rows_use_pseudonymous_participant_ids_and_latest_score(self) -> None:
        keys = ParticipantKeys()
        rows = build_prepost_csv_rows(fixture_rows(), participant_keys=keys)

        self.assertEqual(len(keys), 2)
        self.assertTrue(all(row["participant_id"].startswith("P3-") for row in rows))
        blob = json.dumps(rows, ensure_ascii=False)
        self.assertNotIn("11111111-1111-1111-1111-111111111111", blob)
        self.assertNotIn("22222222-2222-2222-2222-222222222222", blob)
        p1_pre = [
            row for row in rows
            if row["participant_id"] == "P3-001"
            and row["measure_name"] == "self_efficacy"
            and row["timepoint"] == "pre"
        ]
        self.assertEqual([{"participant_id": "P3-001", "measure_name": "self_efficacy", "timepoint": "pre", "score": "3", "collected_at": "2026-06-27T00:02:00Z"}], p1_pre)

    def test_paired_prepost_summary_uses_normalized_scores(self) -> None:
        summary = paired_prepost_summary(fixture_rows(), "self_efficacy")

        self.assertEqual(summary["participants_with_any_measure"], 2)
        self.assertEqual(summary["complete_pairs"], 1)
        self.assertEqual(summary["missing_pairs"], 1)
        self.assertEqual(summary["mean_pre"], 50.0)
        self.assertEqual(summary["mean_post"], 75.0)
        self.assertEqual(summary["mean_delta"], 25.0)

    def test_kpi_report_contains_checker_required_metric_shape(self) -> None:
        report = build_kpi_report(
            fixture_rows(),
            pilot_id="phase3-pilot-draft",
            generated_at="2026-06-28T00:00:00Z",
            review_operator="operator",
        )

        self.assertEqual(report["pilot_id"], "phase3-pilot-draft")
        self.assertEqual(report["cohort_size"], 2)
        self.assertTrue(set(PHASE3_KPI_METRICS).issubset(report["metrics"]))
        for metric in report["metrics"].values():
            self.assertTrue(KPI_METRIC_REQUIRED_KEYS.issubset(metric))
        self_efficacy = report["metrics"]["self_efficacy_prepost"]
        self.assertFalse(self_efficacy["pass"])
        self.assertEqual(self_efficacy["status"], "computed_prepost")
        self.assertEqual(self_efficacy["value"], 25.0)
        self.assertEqual(self_efficacy["source_files"], [PREPOST_CSV_PATH])
        self.assertEqual(report["metrics"]["icc"]["status"], "design_pending")

    def test_writers_create_phase3_evidence_files(self) -> None:
        rows = build_prepost_csv_rows(fixture_rows(), participant_keys=ParticipantKeys())
        report = build_kpi_report(
            fixture_rows(),
            pilot_id="phase3-pilot-draft",
            generated_at="2026-06-28T00:00:00Z",
        )
        with tempfile.TemporaryDirectory() as tmp:
            root = Path(tmp)
            write_prepost_csv(rows, root / PREPOST_CSV_PATH)
            write_kpi_report(report, root / KPI_REPORT_PATH)

            self.assertTrue((root / PREPOST_CSV_PATH).exists())
            self.assertTrue((root / KPI_REPORT_PATH).exists())
            csv_text = (root / PREPOST_CSV_PATH).read_text(encoding="utf-8")
            self.assertTrue(csv_text.startswith("participant_id,measure_name,timepoint,score,collected_at"))
            saved = json.loads((root / KPI_REPORT_PATH).read_text(encoding="utf-8"))
            self.assertEqual(saved["metrics"]["self_efficacy_prepost"]["complete_pairs"], 1)


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