"""
爬虫执行服务

运行爬虫脚本并保存结果
"""

import asyncio
import json
import re
import sys
import traceback
from datetime import datetime, timezone
from urllib.parse import urljoin, urlparse
from sqlalchemy.orm import Session

# Windows 上需要设置事件循环策略
if sys.platform == "win32":
    asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())

# 导入playwright供脚本使用
try:
    from playwright.async_api import async_playwright
    PLAYWRIGHT_AVAILABLE = True
except ImportError:
    PLAYWRIGHT_AVAILABLE = False
    async_playwright = None

from ..database import SessionLocal
from ..models import ScraperScript, ScrapeJob, ScrapeLog, ScrapeResult


def run_scraper(job_id: int, script_id: int):
    """
    执行爬虫的后台任务
    """
    db = SessionLocal()

    try:
        job = db.query(ScrapeJob).filter(ScrapeJob.id == job_id).first()
        script = db.query(ScraperScript).filter(ScraperScript.id == script_id).first()

        if not job or not script:
            return

        # 更新任务状态
        job.status = "running"
        job.started_at = datetime.utcnow()
        job.current_step = "正在初始化..."
        job.progress = 5
        db.commit()

        _add_log(db, job_id, "info", "开始执行爬虫脚本")

        # 创建日志回调函数
        def log_callback(level: str, message: str):
            _add_log(db, job_id, level, message)

        # 执行脚本
        job.current_step = "正在爬取数据..."
        job.progress = 20
        db.commit()

        result_data = _execute_script(script.script_content, log_callback)

        if result_data:
            job.progress = 80
            job.current_step = "正在保存结果..."
            db.commit()

            _add_log(db, job_id, "info", "爬取完成，正在保存结果...")

            # 计算统计信息
            schools = result_data.get("schools", [])
            schools_count = len(schools)
            programs_count = sum(len(s.get("programs", [])) for s in schools)
            faculty_count = sum(
                len(p.get("faculty", []))
                for s in schools
                for p in s.get("programs", [])
            )

            # 保存结果
            result = ScrapeResult(
                job_id=job_id,
                university_id=job.university_id,
                result_data=result_data,
                schools_count=schools_count,
                programs_count=programs_count,
                faculty_count=faculty_count
            )
            db.add(result)

            job.status = "completed"
            job.progress = 100
            job.current_step = "完成"
            job.completed_at = datetime.utcnow()

            _add_log(
                db, job_id, "info",
                f"爬取成功: {schools_count}个学院, {programs_count}个项目, {faculty_count}位导师"
            )

        else:
            job.status = "failed"
            job.error_message = "脚本执行无返回结果"
            job.completed_at = datetime.utcnow()
            _add_log(db, job_id, "error", "脚本执行失败: 无返回结果")

        db.commit()

    except Exception as e:
        error_msg = f"执行出错: {str(e)}\n{traceback.format_exc()}"
        _add_log(db, job_id, "error", error_msg)

        job = db.query(ScrapeJob).filter(ScrapeJob.id == job_id).first()
        if job:
            job.status = "failed"
            job.error_message = str(e)
            job.completed_at = datetime.utcnow()
            db.commit()

    finally:
        db.close()


def _execute_script(script_content: str, log_callback) -> dict:
    """
    执行Python脚本内容

    安全地在隔离环境中执行脚本
    """
    if not PLAYWRIGHT_AVAILABLE:
        log_callback("error", "Playwright 未安装，请运行: pip install playwright && playwright install")
        return None

    # 创建执行环境 - 包含脚本需要的所有模块
    # 注意：使用同一个字典作为 globals 和 locals，确保函数定义可以互相访问
    exec_namespace = {
        "__builtins__": __builtins__,
        "asyncio": asyncio,
        "json": json,
        "re": re,
        "datetime": datetime,
        "timezone": timezone,
        "urljoin": urljoin,
        "urlparse": urlparse,
        "async_playwright": async_playwright,
    }

    try:
        # 编译并执行脚本 - 使用同一个命名空间确保函数可互相调用
        exec(script_content, exec_namespace, exec_namespace)

        # 获取scrape函数
        scrape_func = exec_namespace.get("scrape")
        if not scrape_func:
            log_callback("error", "脚本中未找到 scrape 函数")
            return None

        # 运行异步爬虫函数
        result = asyncio.run(scrape_func(output_callback=log_callback))
        return result

    except Exception as e:
        log_callback("error", f"脚本执行异常: {str(e)}")
        raise


def _add_log(db: Session, job_id: int, level: str, message: str):
    """添加日志"""
    log = ScrapeLog(
        job_id=job_id,
        level=level,
        message=message
    )
    db.add(log)
    db.commit()