import json
from pathlib import Path

import pymysql

from app import create_app
from app.extensions import db
from app.ml.naive_bayes_classifier import NaiveBayesSpamClassifier
from app.models import DetectionConfig, SpamTrainingSample, User


BASE_DIR = Path(__file__).resolve().parent
MYSQL_CONFIG_PATH = BASE_DIR / "mysqlconfig.json"
SPAM_SEED_PATH = BASE_DIR / "seed" / "spam_samples_seed.json"


def load_mysql_cfg() -> dict:
    if not MYSQL_CONFIG_PATH.exists():
        raise FileNotFoundError(f"未找到配置文件: {MYSQL_CONFIG_PATH}")
    with MYSQL_CONFIG_PATH.open("r", encoding="utf-8-sig") as file:
        return json.load(file)


def create_database(mysql_cfg: dict) -> None:
    conn = pymysql.connect(
        host=mysql_cfg.get("host", "127.0.0.1"),
        port=int(mysql_cfg.get("port", 3306)),
        user=mysql_cfg["user"],
        password=mysql_cfg["password"],
        charset=mysql_cfg.get("charset", "utf8mb4"),
        autocommit=True,
    )
    try:
        with conn.cursor() as cursor:
            cursor.execute(
                f"CREATE DATABASE IF NOT EXISTS `{mysql_cfg['database']}` DEFAULT CHARACTER SET {mysql_cfg.get('charset', 'utf8mb4')}"
            )
    finally:
        conn.close()


def ensure_seed_file() -> None:
    if SPAM_SEED_PATH.exists():
        return
    SPAM_SEED_PATH.parent.mkdir(parents=True, exist_ok=True)
    defaults = [
        {"text": "点击链接领取1000元现金红包，先到先得", "label": "spam"},
        {"text": "今晚项目例会改到19点，记得带周报", "label": "ham"},
        {"text": "恭喜你成为幸运用户，马上回复领取大奖", "label": "spam"},
        {"text": "明天上午10点客户演示，请提前准备材料", "label": "ham"},
    ]
    with SPAM_SEED_PATH.open("w", encoding="utf-8") as file:
        json.dump(defaults, file, ensure_ascii=False, indent=2)


def seed_samples() -> tuple[int, int]:
    ensure_seed_file()
    with SPAM_SEED_PATH.open("r", encoding="utf-8-sig") as file:
        rows = json.load(file)

    created = 0
    updated = 0

    for item in rows:
        text = " ".join((item.get("text") or "").strip().split())
        label = (item.get("label") or "").strip().lower()
        if len(text) < 2 or label not in {"spam", "ham"}:
            continue

        sample = SpamTrainingSample.query.filter_by(text=text).first()
        if sample:
            sample.label = label
            sample.is_active = True
            sample.source = sample.source or "seed"
            updated += 1
            continue

        sample = SpamTrainingSample(text=text, label=label, source="seed", is_active=True)
        db.session.add(sample)
        created += 1

    db.session.commit()
    return created, updated


def ensure_detection_config(mysql_cfg: dict) -> float:
    cfg = DetectionConfig.query.order_by(DetectionConfig.id.asc()).first()
    if cfg:
        return float(cfg.spam_threshold)

    init_cfg = mysql_cfg.get("detection_init", {}) if isinstance(mysql_cfg, dict) else {}
    try:
        threshold = float(init_cfg.get("spam_threshold", 0.75))
    except Exception:
        threshold = 0.75

    threshold = min(max(threshold, 0.01), 0.99)
    cfg = DetectionConfig(spam_threshold=threshold)
    db.session.add(cfg)
    db.session.commit()
    return threshold


def init_admin(mysql_cfg: dict) -> str:
    admin_cfg = mysql_cfg.get("admin_init", {})
    if not admin_cfg.get("create_default_admin", True):
        return "默认管理员创建已关闭"

    username = admin_cfg.get("username", "admin")
    password = admin_cfg.get("password", "Admin@123456")
    nickname = admin_cfg.get("nickname", "系统管理员")

    admin = User.query.filter_by(username=username).first()
    if admin:
        return f"管理员已存在: {username}"

    admin = User(username=username, nickname=nickname, is_admin=True)
    admin.set_password(password)
    db.session.add(admin)
    db.session.commit()
    return f"管理员已创建: {username}"


def train_initial_model(model_path: str) -> dict:
    rows = SpamTrainingSample.query.filter_by(is_active=True).order_by(SpamTrainingSample.id.asc()).all()
    samples = [{"text": row.text, "label": row.label} for row in rows]
    clf = NaiveBayesSpamClassifier(model_path)
    return clf.train(samples)


def main():
    mysql_cfg = load_mysql_cfg()
    create_database(mysql_cfg)

    app = create_app()
    with app.app_context():
        db.create_all()
        created, updated = seed_samples()
        threshold = ensure_detection_config(mysql_cfg)
        admin_msg = init_admin(mysql_cfg)
        model_meta = train_initial_model(app.config["NB_MODEL_PATH"])

    print("数据库初始化完成")
    print(f"- 样本新增: {created}")
    print(f"- 样本更新: {updated}")
    print(f"- 初始阈值: {threshold}")
    print(f"- {admin_msg}")
    print(f"- 模型版本: {model_meta.get('version')}")


if __name__ == "__main__":
    main()