"""
Downsample LeRobot v2.x local dataset by episode (default 10%) and save to a new directory.

This script does not rely on HuggingFace's filter/save_to_disk; it directly utilizes the disk layout of the LeRobot dataset:
- meta/episodes.jsonl           One episode per line (contains episode_index and length)
- meta/episodes_stats.jsonl     Statistics for one episode per line (contains episode_index)
- data/chunk-XXX/episode_XXXXXX.parquet
- videos/chunk-XXX/<video_key>/episode_XXXXXX.mp4
"""

from __future__ import annotations

import argparse
import json
import math
import random
import shutil
from pathlib import Path
from typing import Dict, Iterable, List, Sequence, Set, Tuple


def _read_jsonl(path: Path) -> Iterable[dict]:
    with path.open("r", encoding="utf-8") as f:
        for line in f:
            line = line.strip()
            if not line:
                continue
            yield json.loads(line)


def _write_jsonl(path: Path, rows: Iterable[dict]) -> None:
    path.parent.mkdir(parents=True, exist_ok=True)
    with path.open("w", encoding="utf-8") as f:
        for r in rows:
            f.write(json.dumps(r, ensure_ascii=False) + "\n")


def _copy_file(src: Path, dst: Path) -> None:
    dst.parent.mkdir(parents=True, exist_ok=True)
    shutil.copy2(src, dst)


def _detect_video_keys(videos_dir: Path) -> List[str]:
    """
    Read subdirectory names under videos/chunk-000 as the list of video_keys.
    Example: ["observation.images.front", "observation.images.wrist"]
    """
    chunk0 = videos_dir / "chunk-000"
    if not chunk0.exists():
        return []
    keys: List[str] = []
    for p in chunk0.iterdir():
        if p.is_dir():
            keys.append(p.name)
    keys.sort()
    return keys


def _sample_episode_indices_from_rows(
    episodes_rows: Sequence[dict],
    fraction: float,
    seed: int,
) -> Tuple[List[int], Dict[int, int]]:
    """Sample from rows of episodes.jsonl.

    Returns:
    - List of selected old episode_indices (ascending)
    - Mapping of old episode_index -> length (containing only selected episodes)
    """
    if not episodes_rows:
        raise RuntimeError("episodes_rows is empty, cannot sample")

    episode_ids = [int(r["episode_index"]) for r in episodes_rows]
    lengths_all = {int(r["episode_index"]): int(r["length"]) for r in episodes_rows}

    total = len(episode_ids)
    k = int(math.floor(total * fraction))
    k = max(1, min(total, k))

    rng = random.Random(seed)
    chosen = rng.sample(episode_ids, k=k)
    chosen.sort()

    lengths = {ep: lengths_all[ep] for ep in chosen}
    return chosen, lengths


def _rewrite_episode_index_in_parquet(src_parquet: Path, dst_parquet: Path, new_episode_index: int) -> None:
    """Write a new parquet file and replace the episode_index column with new_episode_index."""
    try:
        import pyarrow as pa  # type: ignore
        import pyarrow.parquet as pq  # type: ignore
    except Exception as e:  # pragma: no cover
        raise RuntimeError(
            "pyarrow is required to rewrite episode_index in parquet. "
            "Please install pyarrow in the current environment (usually included in LeRobot/datasets)."
        ) from e

    table = pq.read_table(src_parquet)
    if "episode_index" not in table.column_names:
        raise KeyError(f"{src_parquet} missing episode_index column, cannot reindex")

    col_idx = table.schema.get_field_index("episode_index")
    new_col = pa.array([int(new_episode_index)] * table.num_rows, type=table.schema.field(col_idx).type)
    table = table.set_column(col_idx, "episode_index", new_col)

    dst_parquet.parent.mkdir(parents=True, exist_ok=True)
    pq.write_table(table, dst_parquet)


def _filter_jsonl_by_episode_index(
    src_path: Path,
    dst_path: Path,
    keep: Set[int],
) -> None:
    def gen() -> Iterable[dict]:
        for row in _read_jsonl(src_path):
            if int(row.get("episode_index", -1)) in keep:
                yield row

    _write_jsonl(dst_path, gen())


def _update_info_json(
    src_info_path: Path,
    dst_info_path: Path,
    selected_episodes: Sequence[int],
    selected_lengths: Dict[int, int],
    video_keys: Sequence[str],
) -> None:
    info = json.loads(src_info_path.read_text(encoding="utf-8"))

    total_episodes = len(selected_episodes)
    total_frames = int(sum(selected_lengths.get(ep, 0) for ep in selected_episodes))

    # Maintain chunks_size and path templates, only update stats and split ranges
    info["total_episodes"] = total_episodes
    info["total_frames"] = total_frames
    if "splits" in info and isinstance(info["splits"], dict):
        info["splits"]["train"] = f"0:{total_episodes}"

    # Number of videos usually equals number of episodes * number of video_keys;
    # If videos are not copied (video_keys is empty), set total_videos to 0 to avoid inconsistency.
    info["total_videos"] = int(total_episodes * len(video_keys)) if video_keys else 0

    # total_chunks: Max chunk covered by selected episodes + 1 (at least 1)
    chunks_size = int(info.get("chunks_size", 1000))
    max_chunk = max(int(ep) // chunks_size for ep in selected_episodes) if selected_episodes else 0
    info["total_chunks"] = int(max_chunk + 1)

    dst_info_path.parent.mkdir(parents=True, exist_ok=True)
    dst_info_path.write_text(json.dumps(info, ensure_ascii=False, indent=4) + "\n", encoding="utf-8")


def downsample_episodes(
    repo_id: Path,
    out_repo_id: Path,
    fraction: float = 0.1,
    seed: int = 0,
    copy_videos: bool = True,
    overwrite: bool = False,
    reindex_episodes: bool = True,
) -> None:
    repo_id = repo_id.resolve()
    out_repo_id = out_repo_id.resolve()

    if out_repo_id.exists():
        if not overwrite:
            raise FileExistsError(f"Output directory already exists: {out_repo_id} (use --overwrite to overwrite)")
        shutil.rmtree(out_repo_id)

    # Check necessary files
    src_meta = repo_id / "meta"
    src_data = repo_id / "data"
    src_videos = repo_id / "videos"
    src_info = src_meta / "info.json"
    src_episodes = src_meta / "episodes.jsonl"
    src_stats = src_meta / "episodes_stats.jsonl"

    for p in (src_info, src_episodes, src_data):
        if not p.exists():
            raise FileNotFoundError(f"Missing necessary path: {p}")

    # Read episodes.jsonl and sample (here selected is 'old episode_index')
    episodes_rows = list(_read_jsonl(src_episodes))
    selected_old, lengths_old = _sample_episode_indices_from_rows(episodes_rows, fraction=fraction, seed=seed)
    keep_old_set = set(selected_old)

    # Critical: LeRobotDataset defaults to iterating range(total_episodes) to generate file paths,
    # so to "load directly with new path", episode indices must be 0..N-1 consecutive,
    # and the episode_index column inside parquet must also match.
    if reindex_episodes:
        old_to_new = {old_ep: new_ep for new_ep, old_ep in enumerate(selected_old)}
        selected_new = list(range(len(selected_old)))
        lengths_new = {old_to_new[old_ep]: lengths_old[old_ep] for old_ep in selected_old}
    else:
        old_to_new = {old_ep: old_ep for old_ep in selected_old}
        selected_new = selected_old
        lengths_new = lengths_old

    # Read chunks_size / video_keys
    info = json.loads(src_info.read_text(encoding="utf-8"))
    chunks_size = int(info.get("chunks_size", 1000))
    video_keys = _detect_video_keys(src_videos) if copy_videos else []

    # Output directory skeleton
    (out_repo_id / "meta").mkdir(parents=True, exist_ok=True)
    (out_repo_id / "data").mkdir(parents=True, exist_ok=True)
    if copy_videos:
        (out_repo_id / "videos").mkdir(parents=True, exist_ok=True)

    # Generate meta/episodes.jsonl (output by new episode_index, ensuring 0..N-1)
    episodes_by_old = {int(r["episode_index"]): r for r in episodes_rows}

    def gen_new_episodes_jsonl() -> Iterable[dict]:
        for old_ep in selected_old:
            r = dict(episodes_by_old[old_ep])
            r["episode_index"] = int(old_to_new[old_ep])
            yield r

    _write_jsonl(out_repo_id / "meta" / "episodes.jsonl", gen_new_episodes_jsonl())

    # Generate meta/episodes_stats.jsonl (also reindex, and fix internal stats['episode_index'])
    if src_stats.exists():
        stats_by_old: Dict[int, dict] = {}
        for row in _read_jsonl(src_stats):
            old_ep = int(row.get("episode_index", -1))
            if old_ep in keep_old_set:
                stats_by_old[old_ep] = row

        def gen_new_stats_jsonl() -> Iterable[dict]:
            for old_ep in selected_old:
                row = dict(stats_by_old[old_ep])
                new_ep = int(old_to_new[old_ep])
                row["episode_index"] = new_ep
                st = row.get("stats")
                if isinstance(st, dict) and "episode_index" in st and isinstance(st["episode_index"], dict):
                    epst = dict(st["episode_index"])
                    epst["min"] = [new_ep]
                    epst["max"] = [new_ep]
                    epst["mean"] = [float(new_ep)]
                    epst["std"] = [0.0]
                    st["episode_index"] = epst
                    row["stats"] = st
                yield row

        _write_jsonl(out_repo_id / "meta" / "episodes_stats.jsonl", gen_new_stats_jsonl())

    # Copy tasks.jsonl as is (works fine without trimming)
    src_tasks = src_meta / "tasks.jsonl"
    if src_tasks.exists():
        _copy_file(src_tasks, out_repo_id / "meta" / "tasks.jsonl")

    _update_info_json(
        src_info_path=src_info,
        dst_info_path=out_repo_id / "meta" / "info.json",
        selected_episodes=selected_new,
        selected_lengths=lengths_new,
        video_keys=video_keys,
    )

    # Optional: Copy README / .gitattributes (doesn't affect loading, but good for management)
    for extra in (repo_id / "README.md", repo_id / ".gitattributes"):
        if extra.exists():
            _copy_file(extra, out_repo_id / extra.name)

    # Copy/rewrite data / videos files
    for old_ep in selected_old:
        new_ep = int(old_to_new[old_ep])

        old_chunk = int(old_ep) // chunks_size
        new_chunk = int(new_ep) // chunks_size
        old_name = f"episode_{int(old_ep):06d}"
        new_name = f"episode_{int(new_ep):06d}"

        src_parquet = src_data / f"chunk-{old_chunk:03d}" / f"{old_name}.parquet"
        dst_parquet = out_repo_id / "data" / f"chunk-{new_chunk:03d}" / f"{new_name}.parquet"
        if not src_parquet.exists():
            raise FileNotFoundError(f"Parquet not found: {src_parquet}")

        if reindex_episodes:
            _rewrite_episode_index_in_parquet(src_parquet, dst_parquet, new_episode_index=new_ep)
        else:
            _copy_file(src_parquet, dst_parquet)

        if copy_videos and video_keys:
            for key in video_keys:
                src_mp4 = src_videos / f"chunk-{old_chunk:03d}" / key / f"{old_name}.mp4"
                if src_mp4.exists():
                    dst_mp4 = out_repo_id / "videos" / f"chunk-{new_chunk:03d}" / key / f"{new_name}.mp4"
                    _copy_file(src_mp4, dst_mp4)

    print(
        "Downsampling complete:\n"
        f"- Input: {repo_id}\n"
        f"- Output: {out_repo_id}\n"
        f"- Selected episodes: {len(selected_old)} / {json.loads(src_info.read_text(encoding='utf-8')).get('total_episodes', 'unknown')}\n"
        f"- reindex_episodes: {reindex_episodes}\n"
        f"- copy_videos: {copy_videos} (video_keys={video_keys})"
    )


def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--repo_id", type=str, default="/workspace/ghsun/libero_plus_lerobot", help="Input dataset directory")
    parser.add_argument(
        "--out_repo_id",
        type=str,
        default="/workspace/ghsun/libero_plus_lerobot_10pct",
        help="Output dataset directory",
    )
    parser.add_argument("--fraction", type=float, default=0.1, help="Fraction of episodes to sample (default 0.1)")
    parser.add_argument("--seed", type=int, default=0, help="Random seed (for reproducibility)")
    parser.add_argument("--no_videos", action="store_true", help="Do not copy videos (only copy parquet and meta)")
    parser.add_argument(
        "--keep_original_episode_index",
        action="store_true",
        help="Keep original episode_index (do not reindex). Note: New directory cannot be loaded directly as repo_id, must pass episodes=original_index_list when creating LeRobotDataset.",
    )
    parser.add_argument("--overwrite", action="store_true", help="Delete and recreate if output directory exists")
    args = parser.parse_args()

    downsample_episodes(
        repo_id=Path(args.repo_id),
        out_repo_id=Path(args.out_repo_id),
        fraction=args.fraction,
        seed=args.seed,
        copy_videos=not args.no_videos,
        overwrite=args.overwrite,
        reindex_episodes=not args.keep_original_episode_index,
    )


if __name__ == "__main__":
    main()