#!/usr/bin/env python3
"""Dataset loader for ChessBenchmate Aggregated dataset."""

import msgpack
from pathlib import Path
from typing import Iterator, Dict, Any


def stream_positions(data_dir: str, shard_range: tuple = None) -> Iterator[Dict[str, Any]]:
    """Stream positions from all shards.

    Args:
        data_dir: Directory containing the .msgpack files
        shard_range: Optional (start, end) tuple to limit shards

    Yields:
        Dict with 'fen' and 'moves' keys
    """
    data_path = Path(data_dir)
    shard_files = sorted(data_path.glob('train-*.msgpack'))

    if shard_range:
        start, end = shard_range
        shard_files = shard_files[start:end]

    for shard_file in shard_files:
        with open(shard_file, 'rb') as f:
            unpacker = msgpack.Unpacker(f, raw=False)
            for record in unpacker:
                yield record


def count_positions(data_dir: str) -> tuple:
    """Count total positions and moves in the dataset.

    Returns:
        Tuple of (num_positions, num_moves)
    """
    total_positions = 0
    total_moves = 0

    for record in stream_positions(data_dir):
        total_positions += 1
        total_moves += len(record['moves'])

    return total_positions, total_moves


if __name__ == '__main__':
    import sys

    if len(sys.argv) < 2:
        print("Usage: python dataset.py <data_dir>")
        sys.exit(1)

    data_dir = sys.argv[1]

    print(f"Sampling positions from {data_dir}...")
    for i, record in enumerate(stream_positions(data_dir)):
        print(f"\nPosition {i+1}:")
        print(f"  FEN: {record['fen']}")
        print(f"  Moves: {len(record['moves'])}")
        for move, eval in list(record['moves'].items())[:3]:
            print(f"    {move}: win_prob={eval['win_prob']:.3f}, mate={eval['mate']}")
        if i >= 4:
            break