from __future__ import annotations

import argparse
from collections import Counter, defaultdict
from pathlib import Path
from typing import Any

from src.data.io_utils import read_jsonl, write_csv

DEFAULT_LABEL_ORDER = ["SUPPORTS", "REFUTES", "NEI", "CONFLICTING"]

def infer_split(path: Path, rows: list[dict[str, Any]]) -> str:
    splits = sorted({str(row.get("split")) for row in rows if row.get("split")})
    if len(splits) == 1:
        return splits[0]
    stem = path.stem
    if stem.startswith("claims_"):
        return stem.removeprefix("claims_")
    return stem

def distribution_rows(input_path: Path, label_order: list[str]) -> list[dict[str, Any]]:
    rows = read_jsonl(input_path)
    grouped: dict[str, list[dict[str, Any]]] = defaultdict(list)
    fallback_split = infer_split(input_path, rows)
    for row in rows:
        grouped[str(row.get("split") or fallback_split)].append(row)

    output_rows: list[dict[str, Any]] = []
    for split, split_rows in sorted(grouped.items()):
        counts = Counter(str(row.get("label") or "UNLABELED") for row in split_rows)
        labels = list(label_order)
        labels.extend(label for label in sorted(counts) if label not in labels)
        total = len(split_rows)
        out: dict[str, Any] = {"Split": split, "Total": total}
        for label in labels:
            out[label] = counts.get(label, 0)
        for label in labels:
            out[f"{label}_pct"] = round(counts.get(label, 0) / max(1, total) * 100, 4)
        output_rows.append(out)
    return output_rows

def main() -> None:
    parser = argparse.ArgumentParser()
    parser.add_argument("--input", type=Path, required=True)
    parser.add_argument("--output", type=Path, required=True)
    parser.add_argument("--label-order", nargs="*", default=DEFAULT_LABEL_ORDER)
    args = parser.parse_args()

    rows = distribution_rows(args.input, args.label_order)
    write_csv(args.output, rows)
    print(f"Wrote {len(rows)} label distribution rows to {args.output}")

if __name__ == "__main__":
    main()