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"""Validate the frozen cohort and prepare one model's matched local media."""
from __future__ import annotations

import hashlib
import shutil
import json
import subprocess
from collections import Counter
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path

ROOT = Path(__file__).resolve().parent
COHORT = ROOT / "resources/cohort1015.jsonl"
COHORT_SHA256 = "1f27841f079259e7ebc5249bce114ec9542af36c7fc9a117f32eeac2f652dd62"


def sha256(path: Path) -> str:
    digest = hashlib.sha256()
    with path.open("rb") as stream:
        for block in iter(lambda: stream.read(8 * 1024 * 1024), b""):
            digest.update(block)
    return digest.hexdigest()


def read_jsonl(path: Path) -> list[dict]:
    return [json.loads(line) for line in path.read_text(encoding="utf-8").splitlines() if line.strip()]


def atomic_json(path: Path, data: object) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    temporary = path.with_name(path.name + ".tmp")
    temporary.write_text(json.dumps(data, ensure_ascii=False, indent=2, sort_keys=True) + "\n", encoding="utf-8")
    temporary.replace(path)


def write_jsonl(path: Path, rows: list[dict]) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    temporary = path.with_name(path.name + ".tmp")
    temporary.write_text(
        "".join(json.dumps(row, ensure_ascii=False, sort_keys=True) + "\n" for row in rows),
        encoding="utf-8",
    )
    temporary.replace(path)


def frozen_rows() -> list[dict]:
    if sha256(COHORT) != COHORT_SHA256:
        raise ValueError("Frozen cohort SHA256 differs from the release")
    rows = read_jsonl(COHORT)
    ids = [row["videoId"] for row in rows]
    counts = Counter(row["interaction"] for row in rows)
    if len(rows) != 1015 or len(set(ids)) != 1015 or counts["event"] != 165 or counts["perspective"] != 150:
        raise ValueError(f"Frozen membership is invalid: n={len(rows)}, scopes={counts}")
    return rows


def _indexed_media(path: Path, expected_ids: set[str], label: str) -> dict[str, dict]:
    rows = read_jsonl(path)
    if len(rows) != len(expected_ids):
        raise ValueError(f"{label}: expected {len(expected_ids)} rows, got {len(rows)}")
    indexed = {}
    for row in rows:
        sample_id = row.get("sample_id", row.get("videoId"))
        if not isinstance(sample_id, str) or sample_id in indexed:
            raise ValueError(f"{label}: invalid or duplicate sample_id {sample_id!r}")
        indexed[sample_id] = row
    if set(indexed) != expected_ids:
        raise ValueError(f"{label}: missing={len(expected_ids - set(indexed))}, extra={len(set(indexed) - expected_ids)}")
    return indexed


def _check_media(row: dict, label: str) -> tuple[str, str]:
    value = row.get("path", row.get("local_video_file"))
    expected = row.get("sha256", row.get("media_sha256"))
    if not isinstance(value, str) or not isinstance(expected, str) or len(expected) != 64:
        raise ValueError(f"{label}: provide absolute path and sha256")
    path = Path(value)
    if not path.is_absolute() or not path.is_file() or path.suffix.lower() != ".mp4":
        raise ValueError(f"{label}: MP4 path missing or not absolute: {path}")
    actual = sha256(path)
    if actual != expected.lower():
        raise ValueError(f"{label}: SHA256 mismatch: {path}")
    try:
        probe = json.loads(subprocess.check_output([
            "ffprobe", "-v", "error", "-show_streams", "-of", "json", str(path),
        ], stderr=subprocess.PIPE, timeout=60))
        video = next(item for item in probe["streams"] if item["codec_type"] == "video")
        audio = next(item for item in probe["streams"] if item["codec_type"] == "audio")
        video_ok = (int(video["width"]), int(video["height"]), video["avg_frame_rate"],
                    int(video["nb_frames"])) == (768, 512, "24/1", 121)
        audio_ok = (int(audio["sample_rate"]), int(audio["channels"])) == (48000, 2)
        duration_ok = float(audio["duration"]) >= 5.0
        if not (video_ok and audio_ok and duration_ok):
            raise ValueError(f"{label}: expected 768x512, 121 frames at 24 fps, stereo 48 kHz and >=5 s audio")
    except (KeyError, StopIteration, subprocess.CalledProcessError, subprocess.TimeoutExpired) as exc:
        raise ValueError(f"{label}: ffprobe failed or missing required streams: {path}") from exc
    return str(path.resolve()), actual


def prepare(generated: Path, gt: Path | None, run_dir: Path, model_id: str) -> dict:
    if not model_id or any(character not in "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789_-" for character in model_id):
        raise ValueError("model_id may contain only letters, digits, hyphen and underscore")
    cohort = frozen_rows()
    ids = {row["videoId"] for row in cohort}
    generated_index = _indexed_media(generated, ids, "generated")
    gt_index = _indexed_media(gt, ids, "gt") if gt else None
    manifest_dir = run_dir / "manifests"
    complete_path = run_dir / "INPUTS_COMPLETE.json"
    if complete_path.exists():
        raise FileExistsError(f"Run already prepared: {complete_path}; use another run_dir")
    rows, gt_rows = [], []
    for cohort_row in cohort:
        sample_id = cohort_row["videoId"]
        media, media_sha = _check_media(generated_index[sample_id], f"generated/{sample_id}")
        gt_media, gt_sha = _check_media(gt_index[sample_id], f"gt/{sample_id}") if gt_index else ("", cohort_row["media_sha256"])
        row = {
            "sample_id": sample_id, "clip_id": f"{model_id}__{sample_id}",
            "group": model_id, "checkpoint_label": model_id,
            "local_video_file": media, "media_sha256": media_sha,
            "source_video": media, "audio_uri": media,
            "gt_file": gt_media, "gt_sha256": gt_sha,
            "imagebind_id": f"{model_id}__{sample_id}", "imagebind_group": model_id,
            "caption_av": cohort_row["caption_av"],
            "interaction": cohort_row["interaction"], "scene": cohort_row["scene"],
            "source_group": sample_id, "sample_partition": "frozen1015",
            "dataset_family": "Helixbench", "first_frame_sha256": cohort_row["first_frame_sha256"],
        }
        rows.append(row)
        gt_rows.append({"sample_id": sample_id, "media_sha256": gt_sha, **({"local_video_file": gt_media} if gt_index else {})})
    for name, selected in (
        ("all1015", rows), ("text1015", rows), ("imagebind1015", rows),
        ("event165", [r for r in rows if r["interaction"] == "event"]),
        ("perspective150", [r for r in rows if r["interaction"] == "perspective"]),
        ("gt1015", gt_rows),
    ):
        write_jsonl(manifest_dir / f"{name}.jsonl", selected)
    if not gt_index:
        _copy_reference_features(run_dir, ids)
    payload = {
        "model_id": model_id, "cohort_sha256": COHORT_SHA256,
        "generated_input_sha256": sha256(generated), "gt_input_sha256": sha256(gt) if gt else "packaged_reference_features",
        "counts": {"all": 1015, "event": 165, "perspective": 150},
        "manifests": {name: sha256(manifest_dir / f"{name}.jsonl") for name in
                      ("all1015", "text1015", "imagebind1015", "event165", "perspective150", "gt1015")},
    }
    atomic_json(complete_path, payload)
    return payload


def validate_prepared(run_dir: Path) -> dict:
    payload = json.loads((run_dir / "INPUTS_COMPLETE.json").read_text())
    if payload["cohort_sha256"] != COHORT_SHA256:
        raise ValueError("Prepared run uses a different frozen cohort")
    for name, expected in payload["manifests"].items():
        path = run_dir / "manifests" / f"{name}.jsonl"
        if sha256(path) != expected:
            raise ValueError(f"Manifest modified after preparation: {name}")
    return payload


def verify_media_manifest(run_dir: Path, include_gt: bool = True) -> None:
    """Reject changed or missing MP4 files before using cached model features."""
    names = ("all1015", "gt1015") if include_gt else ("all1015",)
    rows = [row for name in names for row in read_jsonl(run_dir / "manifests" / f"{name}.jsonl") if "local_video_file" in row]
    def check(row: dict) -> None:
        path = Path(row["local_video_file"])
        if not path.is_file() or sha256(path) != row["media_sha256"]:
            raise ValueError(f"Media changed since prepare: {path}")
    with ThreadPoolExecutor(max_workers=8) as pool:
        list(pool.map(check, rows))


def _copy_reference_features(run_dir: Path, ids: set[str]) -> None:
    """Verify packaged GT features, then copy them into the standard run layout."""
    source_root = ROOT.parents[2] / "reference"
    index = json.loads((source_root / "SHA256SUMS.json").read_text())
    expected = {f"{metric}/gt/{sample_id}.npz" for metric in ("passt", "vggish") for sample_id in ids}
    if set(index) != expected:
        raise ValueError("Packaged reference features must cover the frozen 1015 twice")
    for relative, digest in index.items():
        source = source_root / relative
        if sha256(source) != digest:
            raise ValueError(f"Reference feature changed: {relative}")
        dest = run_dir / "results" / relative
        dest.parent.mkdir(parents=True, exist_ok=True)
        shutil.copy2(source, dest)


def verify_packaged_gt_features(run_dir: Path) -> None:
    """Ensure cached GT arrays still match the published reference package."""
    source_root = ROOT.parents[2] / "reference"
    index = json.loads((source_root / "SHA256SUMS.json").read_text())
    for relative, digest in index.items():
        path = run_dir / "results" / relative
        if sha256(path) != digest:
            raise ValueError(f"Packaged GT feature changed: {relative}")