"""抓取 BOSS 直聘「AI 相关」岗位（自用 / 学习用途）。

合规提醒:
  - 仅抓取公开展示的岗位标题/薪资/公司等字段, 不抓取招聘者个人联系方式。
  - 低频请求, 遵守目标站点服务条款; 风险自负。

首次使用:
  python scrape_zhipin_ai.py --login      # 打开浏览器, 手动扫码登录一次
之后:
  python scrape_zhipin_ai.py --keyword AI --city 101010100 --pages 3
"""
from __future__ import annotations

import argparse
import csv
import json
import random
import time
from pathlib import Path
from urllib.parse import quote

from invisible_playwright import InvisiblePlaywright

PROFILE_DIR = Path(__file__).parent / ".zhipin_profile"  # 持久化登录态
SEED = 20240614  # 固定 seed → 跨会话指纹一致, 配合持久化 profile


def login_flow() -> None:
    """首次手动登录: 打开页面, 你扫码, 登录态写入 PROFILE_DIR。"""
    with InvisiblePlaywright(seed=SEED, profile_dir=PROFILE_DIR) as ctx:
        page = ctx.new_page()
        page.goto("https://www.zhipin.com/web/user/?ka=header-login",
                  wait_until="domcontentloaded")
        print("请在打开的浏览器中扫码登录, 登录完成后回到终端按回车...")
        input()  # 等你登录完成
        print("登录态已保存到", PROFILE_DIR)


def scrape(keyword: str, city: str, pages: int) -> list[dict]:
    results: list[dict] = []
    with InvisiblePlaywright(seed=SEED, profile_dir=PROFILE_DIR) as ctx:
        page = ctx.new_page()
        for n in range(1, pages + 1):
            url = (
                "https://www.zhipin.com/web/geek/job"
                f"?query={quote(keyword)}&city={city}&page={n}"
            )
            page.goto(url, wait_until="domcontentloaded")

            # 等列表渲染; 选择器需按实际页面结构核对/调整
            try:
                page.wait_for_selector("li.job-card-wrapper", timeout=15000)
            except Exception:
                print(f"第 {n} 页未出现岗位列表, 可能需要登录或触发了验证码。")
                # 给你时间手动过验证码
                input("处理完页面后按回车继续...")

            rows = page.eval_on_selector_all(
                "li.job-card-wrapper",
                """els => els.map(e => ({
                    title:   e.querySelector('.job-name')?.innerText?.trim(),
                    salary:  e.querySelector('.salary')?.innerText?.trim(),
                    company: e.querySelector('.company-name')?.innerText?.trim(),
                    tags:    Array.from(e.querySelectorAll('.tag-list li'))
                                  .map(t => t.innerText.trim()),
                    area:    e.querySelector('.job-area')?.innerText?.trim(),
                    link:    e.querySelector('a.job-card-left')?.href
                             || e.querySelector('a')?.href,
                }))""",
            )
            print(f"第 {n} 页抓到 {len(rows)} 条")
            results.extend(rows)

            # 低频: 随机停顿, 降低风控触发概率
            time.sleep(random.uniform(4, 9))
    return results


def save(rows: list[dict], stem: str) -> None:
    Path(f"{stem}.json").write_text(
        json.dumps(rows, ensure_ascii=False, indent=2), encoding="utf-8"
    )
    if rows:
        keys = ["title", "salary", "company", "area", "tags", "link"]
        with open(f"{stem}.csv", "w", newline="", encoding="utf-8-sig") as f:
            w = csv.DictWriter(f, fieldnames=keys, extrasaction="ignore")
            w.writeheader()
            for r in rows:
                r = dict(r)
                r["tags"] = " / ".join(r.get("tags") or [])
                w.writerow(r)
    print(f"已保存 {len(rows)} 条 → {stem}.json / {stem}.csv")


def main() -> None:
    ap = argparse.ArgumentParser()
    ap.add_argument("--login", action="store_true", help="首次手动登录")
    ap.add_argument("--keyword", default="AI", help="搜索关键词")
    ap.add_argument("--city", default="101010100", help="城市编码 (101010100=北京)")
    ap.add_argument("--pages", type=int, default=3, help="抓取页数")
    args = ap.parse_args()

    if args.login:
        login_flow()
        return

    rows = scrape(args.keyword, args.city, args.pages)
    save(rows, stem=f"zhipin_{args.keyword}")


if __name__ == "__main__":
    main()