"""EvalHarness CLI. Zero third-party deps beyond the data layer (pydantic)."""

import argparse
import json
import sys
from concurrent.futures import ThreadPoolExecutor, as_completed


def _overrides(args):
    """Optional DatasetSpec field overrides shared by fetch/stats/show."""
    if getattr(args, 'cache_dir', None):
        from evalharness.data.dataset import set_cache_root

        set_cache_root(args.cache_dir)
    ov = {}
    for k in ('source', 'split', 'subset'):
        v = getattr(args, k, None)
        if v is not None:
            ov[k] = v
    return ov


def _cmd_data_list(_args) -> int:
    from evalharness.data import list_datasets

    specs = list_datasets()
    if not specs:
        print('no datasets registered')
        return 0
    name_w = max(len(s.name) for s in specs)
    type_w = max(len(s.task_type) for s in specs)
    for s in specs:
        print(f'{s.name:<{name_w}}  {s.task_type:<{type_w}}  {s.source}  {s.description}')
    print(f'\n{len(specs)} dataset(s) registered')
    return 0


def _fetch_one(name: str, force: bool, overrides) -> str:
    from evalharness.data import get_dataset

    ds = get_dataset(name, **overrides)
    ds.materialize(force=force)
    origin = 'cache' if ds.lineage.get('from') == 'cache' else 'source'
    return f'{name}: {len(ds)} sample(s) [{origin}]  ->  {ds.cache_dir}'


def _cmd_data_fetch(args) -> int:
    names = args.names
    if len(names) == 1:
        print(_fetch_one(names[0], args.force, _overrides(args)))
        return 0
    # Concurrent prefetch: downloads are I/O-bound, threads suffice.
    # Per-dataset file locks inside materialize() guard shared cache entries.
    ok = True
    with ThreadPoolExecutor(max_workers=args.workers) as pool:
        futures = {pool.submit(_fetch_one, n, args.force, _overrides(args)): n for n in names}
        for fut in as_completed(futures):
            try:
                print(fut.result())
            except Exception as e:  # one failure must not block the rest
                ok = False
                print(f'{futures[fut]}: FAILED ({e})', file=sys.stderr)
    return 0 if ok else 1


def _cmd_data_stats(args) -> int:
    from evalharness.data import get_dataset

    stats = get_dataset(args.name, **_overrides(args)).stats()
    print(json.dumps(stats, ensure_ascii=False, indent=2))
    return 0


def _cmd_data_show(args) -> int:
    from evalharness.data import get_dataset

    ds = get_dataset(args.name, **_overrides(args))
    for s in ds[: args.n]:
        print(json.dumps(s.model_dump(), ensure_ascii=False, indent=2))
        print('---')
    return 0


def _cmd_data_unload(args) -> int:
    from evalharness.data import get_dataset

    for name in args.names:
        ds = get_dataset(name, **_overrides(args))
        removed = ds.unload()
        print(f'{name}: cache {"removed" if removed else "not present (nothing to do)"}  ->  {ds.cache_dir}')
    return 0


def _add_override_flags(p: argparse.ArgumentParser) -> None:
    p.add_argument('--source', help='override DatasetSpec.source (e.g. a local dir)')
    p.add_argument('--split', help='override DatasetSpec.split')
    p.add_argument('--subset', help='override DatasetSpec.subset')
    p.add_argument('--cache-dir', help='cache root (default: $EVALHARNESS_CACHE or ~/.cache/evalharness)')


def _cmd_eval_list(_args) -> int:
    from evalharness.eval import list_evals

    names = list_evals()
    print('\n'.join(names) if names else 'no eval recipes registered')
    print(f'\n{len(names)} eval recipe(s) registered')
    return 0


def _cmd_eval_run(args) -> int:
    from evalharness.eval import evaluate, get_eval
    from evalharness.data import get_dataset

    ds = get_dataset(args.dataset, **_overrides(args))
    preds = [json.loads(line) for line in open(args.predictions, encoding='utf-8') if line.strip()]
    preds = [p.get('raw', p.get('prediction', '')) if isinstance(p, dict) else p for p in preds]
    report = evaluate(ds, preds, model=args.model)
    if args.out:
        report.save(args.out)
        print(f'saved -> {args.out}')
    from evalharness.viz import render

    print(render(report, style=args.style))
    return 0


def _cmd_viz_show(args) -> int:
    from evalharness.viz import render

    print(render([*args.reports], style=args.style, **({'n': args.n} if args.n else {})))
    return 0


def build_parser() -> argparse.ArgumentParser:
    parser = argparse.ArgumentParser(prog='evalharness', description='EvalHarness CLI')
    sub = parser.add_subparsers(dest='command', required=True)

    data = sub.add_parser('data', help='dataset plugin commands')
    dsub = data.add_subparsers(dest='data_command', required=True)

    p = dsub.add_parser('list', help='list registered datasets (no download)')
    p.set_defaults(func=_cmd_data_list)

    p = dsub.add_parser('fetch', help='materialize dataset(s) into the cache')
    p.add_argument('names', nargs='+')
    p.add_argument('--force', action='store_true', help='re-download and rebuild the cache')
    p.add_argument('--workers', type=int, default=8, help='concurrent downloads (default 8)')
    _add_override_flags(p)
    p.set_defaults(func=_cmd_data_fetch)

    p = dsub.add_parser('unload', help='drop cache entries (raw + samples); images belong to the sandbox layer')
    p.add_argument('names', nargs='+')
    _add_override_flags(p)
    p.set_defaults(func=_cmd_data_unload)

    p = dsub.add_parser('stats', help='materialize and show dataset statistics')
    p.add_argument('name')
    _add_override_flags(p)
    p.set_defaults(func=_cmd_data_stats)

    p = dsub.add_parser('show', help='print the first N samples')
    p.add_argument('name')
    p.add_argument('-n', type=int, default=2)
    _add_override_flags(p)
    p.set_defaults(func=_cmd_data_show)

    # ---- eval ----
    ev = sub.add_parser('eval', help='evaluation recipes & runs')
    esub = ev.add_subparsers(dest='eval_command', required=True)

    p = esub.add_parser('list', help='list registered eval recipes')
    p.set_defaults(func=_cmd_eval_list)

    p = esub.add_parser('run', help='score predictions against a dataset')
    p.add_argument('dataset', help='dataset name (recipe auto-resolved)')
    p.add_argument('predictions', help='jsonl: one raw string or {"raw": ...} per sample')
    p.add_argument('--model', default='', help='model tag recorded in the report')
    p.add_argument('--out', help='save the EvalReport json here')
    p.add_argument('--style', default='text', help='result render style (text/md/radar/errors)')
    _add_override_flags(p)
    p.set_defaults(func=_cmd_eval_run)

    # ---- viz ----
    vz = sub.add_parser('viz', help='render saved EvalReport artifacts')
    zsub = vz.add_subparsers(dest='viz_command', required=True)

    p = zsub.add_parser('show', help='render report file(s)')
    p.add_argument('reports', nargs='+')
    p.add_argument('--style', default='text',
                   help='text | md | md_compare (multi) | radar | errors')
    p.add_argument('-n', type=int, help='for errors style: how many samples')
    p.set_defaults(func=_cmd_viz_show)

    return parser


def main(argv=None) -> int:
    args = build_parser().parse_args(argv)
    return args.func(args)


if __name__ == '__main__':
    sys.exit(main())