import json
import os
import stat

import numpy as np
import pytest

from hermes_vision.recognize import best_match, cosine, load_db, save_db


def vec(seed, noise=0.0, base=None):
    r = np.random.default_rng(seed)
    v = r.normal(size=128).astype(np.float32) if base is None else base
    return v + noise * r.normal(size=128).astype(np.float32)


def test_cosine_basics():
    a = vec(1)
    assert cosine(a, a) == pytest.approx(1.0)
    assert cosine(a, -a) == pytest.approx(-1.0)


def test_best_match_picks_the_closest_person_and_rejects_strangers():
    alice, bob = vec(1), vec(2)
    db = {'alice': [alice, vec(1, 0.3, alice)], 'bob': [bob]}
    assert best_match(vec(9, 0.2, alice), db)[0] == 'alice'
    assert best_match(vec(9, 0.2, bob), db)[0] == 'bob'
    name, sim = best_match(vec(77), db)            # an unrelated face
    assert name == '' and sim < 0.363


def test_empty_db_matches_nobody():
    assert best_match(vec(1), {}) == ('', -1.0)


def test_db_roundtrip_is_private_and_atomic(tmp_path):
    path = str(tmp_path / 'sub' / 'faces.json')
    save_db({'alice': [vec(1), vec(2)]}, path)
    assert stat.S_IMODE(os.stat(path).st_mode) == 0o600
    assert stat.S_IMODE(os.stat(os.path.dirname(path)).st_mode) == 0o700
    back = load_db(path)
    assert list(back) == ['alice'] and len(back['alice']) == 2
    assert np.allclose(back['alice'][0], vec(1))
    assert [f for f in os.listdir(os.path.dirname(path)) if f.startswith('.faces-')] == []   # no temp litter
    assert json.load(open(path)).keys() == {'alice'}


def test_load_missing_db_is_empty(tmp_path):
    assert load_db(str(tmp_path / 'nope.json')) == {}