#!/usr/bin/env python3
"""
Split scans.csv into per-machine metadata CSVs.

Reads the combined scans.csv produced by the scraper and writes one CSV per
machine containing only the website-sourced metadata columns (no mosaic paths,
download status, or error fields).

Usage:
  python scripts/export_machine_metadata.py
  python scripts/export_machine_metadata.py --input archives/scans.csv --output-dir archives/by_machine
"""

from __future__ import annotations

import argparse
import csv
import sys
from collections import defaultdict
from pathlib import Path

METADATA_COLUMNS = [
    "machine",
    "machine_id",
    "scan_id",
    "name",
    "scan_time",
    "start_x",
    "start_y",
    "end_x",
    "end_y",
    "dx",
    "dy",
    "nx",
    "ny",
    "total_tiles",
    "scan_lines",
    "scan_mode",
    "start_datetime",
    "end_datetime",
    "status",
    "user",
    "disk_space_mb",
]


def sanitize_machine_label(label: str) -> str:
    return label.replace("[", "").replace("]", "").replace(" ", "_").strip("_")


def parse_args() -> argparse.Namespace:
    p = argparse.ArgumentParser(description="Split scans.csv into per-machine metadata CSVs.")
    p.add_argument(
        "--input",
        default="archives/scans.csv",
        metavar="FILE",
        help="Path to scans.csv (default: archives/scans.csv)",
    )
    p.add_argument(
        "--output-dir",
        default="archives/by_machine",
        metavar="DIR",
        help="Directory for output CSVs (default: archives/by_machine)",
    )
    return p.parse_args()


def main() -> None:
    args = parse_args()
    input_path = Path(args.input)
    output_dir = Path(args.output_dir)

    if not input_path.exists():
        sys.exit(f"Input file not found: {input_path}")

    with input_path.open(newline="") as fh:
        reader = csv.DictReader(fh)
        if reader.fieldnames is None:
            sys.exit(f"{input_path} appears to be empty.")

        missing = [c for c in METADATA_COLUMNS if c not in reader.fieldnames]
        if missing:
            sys.exit(f"Expected columns not found in {input_path}: {missing}")

        rows_by_machine: dict[str, list[dict]] = defaultdict(list)
        for row in reader:
            rows_by_machine[row["machine"]].append(row)

    output_dir.mkdir(parents=True, exist_ok=True)

    for machine_label, rows in sorted(rows_by_machine.items()):
        safe_name = sanitize_machine_label(machine_label)
        out_path = output_dir / f"{safe_name}_scans_metadata.csv"
        with out_path.open("w", newline="") as fh:
            writer = csv.DictWriter(fh, fieldnames=METADATA_COLUMNS, extrasaction="ignore")
            writer.writeheader()
            writer.writerows(rows)
        print(f"  {out_path}  ({len(rows)} rows)")

    total = sum(len(r) for r in rows_by_machine.values())
    print(f"\n{len(rows_by_machine)} machine(s), {total} total rows → {output_dir}/")


if __name__ == "__main__":
    main()