"""Load raw evaluation dataset records from disk.

Supports CSV and JSONL formats. Returns a list of plain dicts — normalization
into NormalizedSample is handled by normalizers.py.
"""

from __future__ import annotations

import csv
import json
from pathlib import Path
from typing import Any


def load_dataset_records(path: Path | str) -> list[dict[str, Any]]:
    """Load raw records from a CSV or JSONL file.

    Each row becomes a plain dict. Lists stored as JSON strings in CSV columns
    are left as-is; normalizers handle parsing.
    """
    file_path = Path(path)
    if not file_path.is_file():
        raise FileNotFoundError(f"Dataset file not found: {file_path}")

    suffix = file_path.suffix.lower()
    if suffix in (".jsonl", ".ndjson"):
        return _load_jsonl(file_path)
    if suffix in (".csv",):
        return _load_csv(file_path)
    # Fall back to CSV for unknown extensions.
    return _load_csv(file_path)


def _load_csv(path: Path) -> list[dict[str, Any]]:
    """Read a CSV file into a list of row dicts."""
    with path.open(encoding="utf-8", newline="") as fh:
        reader = csv.DictReader(fh)
        return [dict(row) for row in reader]


def _load_jsonl(path: Path) -> list[dict[str, Any]]:
    """Read a JSONL file into a list of record dicts."""
    records: list[dict[str, Any]] = []
    with path.open(encoding="utf-8") as fh:
        for lineno, line in enumerate(fh, 1):
            line = line.strip()
            if not line:
                continue
            try:
                obj = json.loads(line)
            except json.JSONDecodeError as exc:
                raise ValueError(f"Invalid JSON on line {lineno} of {path}: {exc}") from exc
            if not isinstance(obj, dict):
                raise ValueError(f"Expected JSON object on line {lineno} of {path}, got {type(obj).__name__}")
            records.append(obj)
    return records