from __future__ import annotations

import random
import sys
import unittest
from copy import deepcopy
from pathlib import Path

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

from turn_detection.data import (  # noqa: E402
    SplitValidationError,
    assert_no_split_leakage,
    assign_leave_one_out,
    assign_splits,
    build_split_report,
    find_split_leakage,
    iter_leave_one_out_folds,
    parse_split_ratios,
)


def sample_rows(groups: int = 100) -> list[dict]:
    rows = []
    for index in range(groups):
        group_id = f"group-{index:03d}"
        group_keys = [f"record:{index}", f"audio:{index}"]
        # Every tenth component has two linked rows.
        copies = 2 if index % 10 == 0 else 1
        for copy in range(copies):
            rows.append(
                {
                    "record_id": f"row-{index}-{copy}",
                    "group_id": group_id,
                    "group_keys": group_keys,
                    "audio_sha256": f"hash-{index}",
                    "endpoint": bool(index % 2),
                    "language": "hi" if index % 3 == 0 else "en",
                    "dataset": "human" if index % 4 == 0 else "synthetic",
                }
            )
    return rows


class SplitAssignmentTests(unittest.TestCase):
    def test_deterministic_irrespective_of_input_order(self) -> None:
        rows = sample_rows()
        shuffled = deepcopy(rows)
        random.Random(7).shuffle(shuffled)
        first = assign_splits(rows, ratios={"train": 0.8, "validation": 0.2}, seed=11)
        second = assign_splits(shuffled, ratios={"train": 0.8, "validation": 0.2}, seed=11)
        first_map = {row["record_id"]: row["split"] for row in first}
        second_map = {row["record_id"]: row["split"] for row in second}
        self.assertEqual(first_map, second_map)
        assert_no_split_leakage(first)

    def test_ratios_are_close_without_splitting_groups(self) -> None:
        result = assign_splits(sample_rows(), ratios={"train": 0.8, "validation": 0.2})
        report = build_split_report(result)
        train_fraction = report["split_counts"]["train"] / len(result)
        self.assertAlmostEqual(train_fraction, 0.8, delta=0.04)
        self.assertTrue(report["leakage"]["is_valid"])

    def test_balances_fifty_fifty_endpoint_with_correlated_strata(self) -> None:
        rows = []
        for index in range(200):
            endpoint = index % 2 == 0
            rows.append(
                {
                    "record_id": f"balanced-{index}",
                    "group_id": f"balanced-group-{index}",
                    "group_keys": [f"audio:balanced-{index}"],
                    "audio_sha256": f"balanced-{index}",
                    "endpoint": endpoint,
                    # Deliberately correlate language/source with endpoint.
                    "language": "hi" if endpoint else ("en" if index % 4 else "mr"),
                    "dataset": "human" if endpoint else "synthetic",
                }
            )
        result = assign_splits(rows, ratios={"train": 0.8, "validation": 0.2}, seed=19)
        for split, expected_per_label in (("train", 80), ("validation", 20)):
            counts = {
                label: sum(row["split"] == split and row["endpoint"] is label for row in result)
                for label in (False, True)
            }
            self.assertLessEqual(abs(counts[False] - expected_per_label), 2)
            self.assertLessEqual(abs(counts[True] - expected_per_label), 2)

    def test_holdout_field_never_crosses(self) -> None:
        result = assign_splits(
            sample_rows(),
            ratios={"train": 0.5, "validation": 0.5},
            holdout_fields=("dataset",),
        )
        splits_by_dataset: dict[str, set[str]] = {}
        for row in result:
            splits_by_dataset.setdefault(row["dataset"], set()).add(row["split"])
        self.assertTrue(all(len(splits) == 1 for splits in splits_by_dataset.values()))
        report = build_split_report(result, holdout_fields=("dataset",))
        reported = {
            value
            for values in report["holdouts"]["dataset"]["by_split"].values()
            for value in values
        }
        self.assertEqual(reported, set(splits_by_dataset))
        self.assertEqual(report["holdouts"]["dataset"]["crossing_values"], {})
        self.assertEqual(report["domain_shift"]["kind"], "domain_shift_stress_test")
        self.assertIn("confounded", report["domain_shift"]["caution"])
        self.assertIn("synthetic", report["domain_shift"]["slice_counts"])

    def test_leave_one_source_out_helper_names_exact_source(self) -> None:
        rows = sample_rows(20)
        result = assign_leave_one_out(rows, field="dataset", held_out_value="human")
        self.assertTrue(
            all(row["split"] == "validation" for row in result if row["dataset"] == "human")
        )
        self.assertTrue(
            all(row["split"] == "train" for row in result if row["dataset"] == "synthetic")
        )
        report = build_split_report(result, holdout_fields=("dataset",))
        self.assertIn("human", report["holdouts"]["dataset"]["by_split"]["validation"])
        folds = list(iter_leave_one_out_folds(rows, field="dataset", values=("synthetic",)))
        self.assertEqual(folds[0][0], "synthetic")
        self.assertTrue(
            all(
                row["split"] == "validation" for row in folds[0][1] if row["dataset"] == "synthetic"
            )
        )

    def test_leakage_detector_checks_hash_even_if_group_ids_are_wrong(self) -> None:
        rows = [
            {"group_id": "a", "group_keys": ["audio:x"], "audio_sha256": "x", "split": "train"},
            {
                "group_id": "b",
                "group_keys": ["audio:x"],
                "audio_sha256": "x",
                "split": "validation",
            },
        ]
        report = find_split_leakage(rows)
        self.assertFalse(report["is_valid"])
        self.assertIn("x", report["audio_hash_crossings"])
        with self.assertRaises(SplitValidationError):
            assert_no_split_leakage(rows)

    def test_ratio_parser_normalizes_weights(self) -> None:
        ratios = parse_split_ratios(["train=8", "validation=2"])
        self.assertEqual(ratios, {"train": 0.8, "validation": 0.2})
        with self.assertRaises(ValueError):
            parse_split_ratios(["train=1", "train=1"])


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