"""Iterate local single-episode LeRobot datasets using episodes.csv."""
import argparse
import csv
from pathlib import Path

from lerobot.datasets.lerobot_dataset import LeRobotDataset


def iter_datasets(root, names=None, limit=4):
    root = Path(root).resolve()
    selected = set(names) if names else None
    loaded = 0
    with (root / "episodes.csv").open(newline="") as stream:
        for row in csv.DictReader(stream):
            name = row["episode"]
            if selected is not None and name not in selected:
                continue
            path = root / row["episode_path"]
            if not (path / "meta/info.json").is_file():
                raise FileNotFoundError(f"Extract the corresponding shard first: {name}")
            dataset = LeRobotDataset(repo_id=f"Crobotia/{name}", root=path,
                                     video_backend="pyav")
            yield name, dataset
            loaded += 1
            if limit is not None and loaded >= limit:
                return
    if loaded == 0:
        raise ValueError("No selected episode was found in episodes.csv")


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--root", type=Path, default=Path("."))
    parser.add_argument("--episodes", nargs="+", help="Episode names from episodes.csv")
    parser.add_argument("--limit", type=int, default=4, help="Maximum episodes to load (default: 4)")
    args = parser.parse_args()
    if args.limit < 1:
        parser.error("--limit must be positive")
    for name, dataset in iter_datasets(args.root, args.episodes, args.limit):
        sample = dataset[0]
        print(name, dataset.num_frames, sample["task"], tuple(sample["observation.state"].shape))