examples: add zhaopin AI job scrapers + SQLite analysis

- scrape_zhaopin_ai.py: lightweight no-login list scraper
- scrape_zhaopin_full.py: SQLite storage, resumable crawl, detail-page JD
- analyze_zhaopin.py: stats by city/salary/education/experience/skills
- scrape_zhipin_ai.py: BOSS Zhipin variant (login-based, fallback)
- gitignore scraper data artifacts and browser profile

.gitignore

@@ -6,3 +6,9 @@ build/
 .pytest_cache/
 .venv/
 firefox-source/
+# scraper runtime artifacts (examples/) — data outputs & browser profiles
+*.db
+zhaopin_*.json
+zhaopin_*.csv
+ai_jobs.csv
+examples/.zhipin_profile/

examples/analyze_zhaopin.py

@@ -0,0 +1,169 @@
+"""智联招聘抓取数据分析 —— 读取 SQLite, 按城市/薪资/学历/经验/技能做统计。
+
+纯标准库, 无需 pandas。
+
+用法:
+  python examples/analyze_zhaopin.py                      # 全量分析
+  python examples/analyze_zhaopin.py --keyword AI         # 只看某关键词
+  python examples/analyze_zhaopin.py --city 北京          # 只看某城市
+  python examples/analyze_zhaopin.py --top 15             # 排行榜取前 15
+  python examples/analyze_zhaopin.py --db zhaopin_jobs.db
+"""
+from __future__ import annotations
+
+import argparse
+import json
+import re
+import sqlite3
+import statistics
+from collections import Counter
+
+WORKDAYS_PER_MONTH = 21.75  # 日薪 -> 月薪折算
+
+
+def parse_salary(s: str) -> tuple[int, int] | None:
+    """把薪资字符串解析成 (月薪下限, 月薪上限) 元。无法解析返回 None。"""
+    if not s or "面议" in s:
+        return None
+    s = s.strip()
+    is_daily = "/天" in s or "元/天" in s
+    is_wan = "万" in s
+    nums = re.findall(r"\d+(?:\.\d+)?", s)
+    if not nums:
+        return None
+    vals = [float(x) for x in nums[:2]]
+    if len(vals) == 1:
+        vals = [vals[0], vals[0]]
+    lo, hi = vals[0], vals[1]
+    if is_wan:
+        lo, hi = lo * 10000, hi * 10000
+    if is_daily:
+        lo, hi = lo * WORKDAYS_PER_MONTH, hi * WORKDAYS_PER_MONTH
+    return int(lo), int(hi)
+
+
+def city_of(location: str) -> str:
+    return (location or "").split("·")[0].strip() or "未知"
+
+
+SALARY_BUCKETS = [
+    (0, 5000, "<5k"),
+    (5000, 8000, "5-8k"),
+    (8000, 12000, "8-12k"),
+    (12000, 18000, "12-18k"),
+    (18000, 25000, "18-25k"),
+    (25000, 10**9, ">=25k"),
+]
+
+
+def bucket_of(mid: float) -> str:
+    for lo, hi, label in SALARY_BUCKETS:
+        if lo <= mid < hi:
+            return label
+    return "?"
+
+
+def bar(n: int, maxn: int, width: int = 30) -> str:
+    if maxn <= 0:
+        return ""
+    return "█" * max(1, round(n / maxn * width))
+
+
+def section(title: str) -> None:
+    print("\n" + "=" * 56)
+    print(title)
+    print("=" * 56)
+
+
+def rank_table(counter: Counter, top: int, label: str) -> None:
+    if not counter:
+        print("  (无数据)")
+        return
+    maxn = counter.most_common(1)[0][1]
+    for name, n in counter.most_common(top):
+        print(f"  {name[:18]:<18} {n:>4}  {bar(n, maxn)}")
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--db", default="zhaopin_jobs.db")
+    ap.add_argument("--keyword", default=None, help="按关键词过滤")
+    ap.add_argument("--city", default=None, help="按城市过滤")
+    ap.add_argument("--top", type=int, default=12, help="排行榜条数")
+    args = ap.parse_args()
+
+    conn = sqlite3.connect(args.db)
+    q = ("SELECT title,salary,experience,education,location,company,"
+         "job_tags,company_tags,skills FROM jobs")
+    params: list = []
+    if args.keyword:
+        q += " WHERE keyword=?"
+        params.append(args.keyword)
+    rows = conn.execute(q, params).fetchall()
+
+    if args.city:
+        rows = [r for r in rows if city_of(r[4]) == args.city]
+
+    if not rows:
+        print("没有匹配的数据。先用 scrape_zhaopin_full.py 抓一些, 或检查过滤条件。")
+        return
+
+    n_total = len(rows)
+    print(f"分析样本: {n_total} 条"
+          + (f" | 关键词={args.keyword}" if args.keyword else "")
+          + (f" | 城市={args.city}" if args.city else ""))
+
+    cities, edus, exps = Counter(), Counter(), Counter()
+    skill_freq, salary_buckets = Counter(), Counter()
+    mids: list[float] = []
+    n_salary_parsed = 0
+
+    for (title, salary, exp, edu, loc, comp, jtags, ctags, skills) in rows:
+        cities[city_of(loc)] += 1
+        edus[(edu or "未知").strip() or "未知"] += 1
+        exps[(exp or "未知").strip() or "未知"] += 1
+        # 技能: 合并 skills + job_tags
+        for src in (skills, jtags):
+            try:
+                for t in json.loads(src or "[]"):
+                    t = t.strip()
+                    if t:
+                        skill_freq[t] += 1
+            except Exception:
+                pass
+        rng = parse_salary(salary)
+        if rng:
+            n_salary_parsed += 1
+            mid = (rng[0] + rng[1]) / 2
+            mids.append(mid)
+            salary_buckets[bucket_of(mid)] += 1
+
+    section("城市分布 (Top)")
+    rank_table(cities, args.top, "城市")
+
+    section("薪资区间分布 (按月薪中位点)")
+    if mids:
+        order = {label: i for i, (_, _, label) in enumerate(SALARY_BUCKETS)}
+        maxn = max(salary_buckets.values())
+        for label in sorted(salary_buckets, key=lambda x: order.get(x, 99)):
+            n = salary_buckets[label]
+            print(f"  {label:<8} {n:>4}  {bar(n, maxn)}")
+        print(f"\n  可解析薪资: {n_salary_parsed}/{n_total} 条 (面议等已排除)")
+        print(f"  月薪中位点  平均: {statistics.mean(mids):>8,.0f} 元")
+        print(f"            中位数: {statistics.median(mids):>8,.0f} 元")
+        print(f"          最低/最高: {min(mids):,.0f} / {max(mids):,.0f} 元")
+    else:
+        print("  (无可解析薪资)")
+
+    section("学历要求")
+    rank_table(edus, args.top, "学历")
+
+    section("经验要求")
+    rank_table(exps, args.top, "经验")
+
+    section("技能/标签词频 (Top)")
+    rank_table(skill_freq, args.top, "技能")
+
+
+if __name__ == "__main__":
+    main()

examples/scrape_zhaopin_ai.py

@@ -0,0 +1,120 @@
+"""抓取智联招聘「AI 相关」岗位 —— 免登录, 渲染搜索结果页直接解析。
+
+合规提醒:
+  - 仅抓取公开展示的岗位标题/薪资/公司/标签等字段。
+  - 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。
+
+用法:
+  python examples/scrape_zhaopin_ai.py                         # 默认抓 "AI" 前 3 页
+  python examples/scrape_zhaopin_ai.py --keyword 大模型 --pages 5
+  python examples/scrape_zhaopin_ai.py --keyword AI --jl 530   # 530=北京
+  python examples/scrape_zhaopin_ai.py --headful               # 显示浏览器窗口
+
+城市编码(jl): 北京530 上海538 广州763 深圳765 杭州653 成都801 武汉736 南京635
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import random
+import time
+from urllib.parse import quote
+
+from invisible_playwright import InvisiblePlaywright
+
+# 在渲染后的页面里一次性提取所有卡片, 比逐个 query 更快更稳。
+# 选择器来自对真实页面的探测 (见 _probe_zhaopin.py)。
+_EXTRACT_JS = r"""
+() => {
+  const txt = (el) => el ? el.innerText.trim() : "";
+  const cards = Array.from(document.querySelectorAll(".joblist-box__item"));
+  return cards.map(card => {
+    const nameA = card.querySelector("a.jobinfo__name");
+    const info  = Array.from(card.querySelectorAll(".jobinfo__other-info-item"))
+                       .map(e => e.innerText.trim());
+    // 第一个 other-info 是地点(带图标), 取其 span; 其余按顺序是经验/学历
+    const locSpan = card.querySelector(".jobinfo__other-info-item span");
+    const companyA = card.querySelector("a.companyinfo__name");
+    return {
+      title:       txt(nameA),
+      link:        nameA ? nameA.href : "",
+      salary:      txt(card.querySelector(".jobinfo__salary")),
+      job_tags:    Array.from(card.querySelectorAll(".jobinfo__tag .joblist-box__item-tag"))
+                        .map(e => e.innerText.trim()),
+      location:    locSpan ? locSpan.innerText.trim() : (info[0] || ""),
+      experience:  info[1] || "",
+      education:   info[2] || "",
+      company:     companyA ? (companyA.getAttribute("title") || companyA.innerText).trim()
+                            : "",
+      company_url: companyA ? companyA.href : "",
+      company_tags: Array.from(card.querySelectorAll(".companyinfo__tag .joblist-box__item-tag"))
+                         .map(e => e.innerText.trim()),
+    };
+  });
+}
+"""
+
+
+def scrape(keyword: str, pages: int, jl: str | None, headful: bool) -> list[dict]:
+    results: list[dict] = []
+    seen: set[str] = set()
+    with InvisiblePlaywright(seed=42, headless=not headful) as browser:
+        page = browser.new_page()
+        for n in range(1, pages + 1):
+            url = f"https://sou.zhaopin.com/?kw={quote(keyword)}&p={n}"
+            if jl:
+                url += f"&jl={jl}"
+            try:
+                page.goto(url, wait_until="domcontentloaded", timeout=60000)
+                page.wait_for_selector(".joblist-box__item", timeout=20000)
+            except Exception:
+                print(f"第 {n} 页未加载出岗位列表, 跳过 (可能触发风控)。")
+                continue
+            page.wait_for_timeout(1500)  # 让懒加载内容补齐
+
+            rows = page.evaluate(_EXTRACT_JS)
+            new = 0
+            for r in rows:
+                key = r.get("link") or (r.get("title", "") + r.get("company", ""))
+                if key and key not in seen:
+                    seen.add(key)
+                    results.append(r)
+                    new += 1
+            print(f"第 {n} 页: 抓到 {len(rows)} 条 (新增 {new})")
+
+            time.sleep(random.uniform(3, 7))  # 低频, 降低风控
+    return results
+
+
+def save(rows: list[dict], stem: str) -> None:
+    with open(f"{stem}.json", "w", encoding="utf-8") as f:
+        json.dump(rows, f, ensure_ascii=False, indent=2)
+    if rows:
+        fields = ["title", "salary", "experience", "education", "location",
+                  "company", "job_tags", "company_tags", "link", "company_url"]
+        with open(f"{stem}.csv", "w", newline="", encoding="utf-8-sig") as f:
+            w = csv.DictWriter(f, fieldnames=fields, extrasaction="ignore")
+            w.writeheader()
+            for r in rows:
+                row = dict(r)
+                row["job_tags"] = " / ".join(row.get("job_tags") or [])
+                row["company_tags"] = " / ".join(row.get("company_tags") or [])
+                w.writerow(row)
+    print(f"\n已保存 {len(rows)} 条 → {stem}.json / {stem}.csv")
+
+
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--keyword", default="AI", help="搜索关键词")
+    ap.add_argument("--pages", type=int, default=3, help="抓取页数")
+    ap.add_argument("--jl", default=None, help="城市编码, 不填=全国")
+    ap.add_argument("--headful", action="store_true", help="显示浏览器窗口")
+    args = ap.parse_args()
+
+    rows = scrape(args.keyword, args.pages, args.jl, args.headful)
+    save(rows, stem=f"zhaopin_{args.keyword}")
+
+
+if __name__ == "__main__":
+    main()

examples/scrape_zhaopin_full.py

@@ -0,0 +1,277 @@
+"""智联招聘 AI 岗位爬虫（完整版）—— 免登录 + SQLite + 断点续抓 + 详情页 JD 全文。
+
+特性:
+  * 写入 SQLite (INSERT OR IGNORE 去重, 每条提交, 中断不丢数据)
+  * 断点续抓:
+      - 列表阶段: 记录每个 (keyword, jl) 已抓到的最大页码, 重跑从下一页继续
+      - 详情阶段: 只抓还没有 JD 的岗位, 重跑自动补齐
+  * 详情页: 进入每个岗位页面抓 职位描述(JD)全文 + 技能标签
+
+合规提醒: 仅抓公开岗位字段, 不抓招聘者个人联系方式; 低频自用, 遵守站点条款。
+
+用法:
+  # 抓列表(前5页) + 进详情页抓 JD
+  python examples/scrape_zhaopin_full.py --keyword AI --pages 5
+
+  # 只抓列表, 不进详情
+  python examples/scrape_zhaopin_full.py --keyword 大模型 --pages 5 --no-detail
+
+  # 中断后直接重跑同一命令 => 自动从断点继续
+  python examples/scrape_zhaopin_full.py --keyword AI --pages 5
+
+  # 导出已抓数据到 CSV
+  python examples/scrape_zhaopin_full.py --export ai_jobs.csv
+
+  # 重置某关键词的列表进度(重新从第1页抓)
+  python examples/scrape_zhaopin_full.py --keyword AI --reset
+"""
+from __future__ import annotations
+
+import argparse
+import csv
+import json
+import random
+import re
+import sqlite3
+import time
+from contextlib import closing
+from urllib.parse import quote
+
+from invisible_playwright import InvisiblePlaywright
+
+DB_DEFAULT = "zhaopin_jobs.db"
+
+_LIST_JS = r"""
+() => {
+  const txt = (el) => el ? el.innerText.trim() : "";
+  return Array.from(document.querySelectorAll(".joblist-box__item")).map(card => {
+    const nameA = card.querySelector("a.jobinfo__name");
+    const info  = Array.from(card.querySelectorAll(".jobinfo__other-info-item"))
+                       .map(e => e.innerText.trim());
+    const locSpan = card.querySelector(".jobinfo__other-info-item span");
+    const companyA = card.querySelector("a.companyinfo__name");
+    return {
+      title:   txt(nameA),
+      link:    nameA ? nameA.href : "",
+      salary:  txt(card.querySelector(".jobinfo__salary")),
+      job_tags: Array.from(card.querySelectorAll(".jobinfo__tag .joblist-box__item-tag"))
+                     .map(e => e.innerText.trim()),
+      location: locSpan ? locSpan.innerText.trim() : (info[0] || ""),
+      experience: info[1] || "",
+      education:  info[2] || "",
+      company: companyA ? (companyA.getAttribute("title") || companyA.innerText).trim() : "",
+      company_url: companyA ? companyA.href : "",
+      company_tags: Array.from(card.querySelectorAll(".companyinfo__tag .joblist-box__item-tag"))
+                         .map(e => e.innerText.trim()),
+    };
+  });
+}
+"""
+
+_DETAIL_JS = r"""
+() => {
+  const c = document.querySelector(".describtion-card__detail-content");
+  const skills = Array.from(document.querySelectorAll(".describtion-card__skills-item"))
+                      .map(e => e.innerText.trim());
+  return { jd: c ? c.innerText.trim() : "", skills };
+}
+"""
+
+
+# ── DB ──────────────────────────────────────────────────────────────────
+def init_db(path: str) -> sqlite3.Connection:
+    conn = sqlite3.connect(path)
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS jobs (
+            job_id       TEXT PRIMARY KEY,
+            title        TEXT,
+            salary       TEXT,
+            experience   TEXT,
+            education    TEXT,
+            location     TEXT,
+            company      TEXT,
+            company_url  TEXT,
+            job_tags     TEXT,
+            company_tags TEXT,
+            link         TEXT,
+            jd_text      TEXT,
+            skills       TEXT,
+            keyword      TEXT,
+            created_at   TEXT DEFAULT (datetime('now','localtime')),
+            detail_at    TEXT
+        )
+    """)
+    conn.execute("""
+        CREATE TABLE IF NOT EXISTS progress (
+            scope     TEXT PRIMARY KEY,   -- f"{keyword}|{jl}"
+            last_page INTEGER DEFAULT 0
+        )
+    """)
+    conn.commit()
+    return conn
+
+
+def job_id_from_link(link: str) -> str:
+    m = re.search(r"/jobdetail/([^.?/]+)\.htm", link)
+    return m.group(1) if m else link
+
+
+def get_last_page(conn: sqlite3.Connection, scope: str) -> int:
+    row = conn.execute("SELECT last_page FROM progress WHERE scope=?", (scope,)).fetchone()
+    return row[0] if row else 0
+
+
+def set_last_page(conn: sqlite3.Connection, scope: str, page: int) -> None:
+    conn.execute(
+        "INSERT INTO progress(scope,last_page) VALUES(?,?) "
+        "ON CONFLICT(scope) DO UPDATE SET last_page=excluded.last_page",
+        (scope, page),
+    )
+    conn.commit()
+
+
+def upsert_job(conn: sqlite3.Connection, r: dict, keyword: str) -> bool:
+    jid = job_id_from_link(r.get("link", ""))
+    if not jid:
+        return False
+    cur = conn.execute(
+        """INSERT OR IGNORE INTO jobs
+           (job_id,title,salary,experience,education,location,company,
+            company_url,job_tags,company_tags,link,keyword)
+           VALUES(?,?,?,?,?,?,?,?,?,?,?,?)""",
+        (jid, r.get("title"), r.get("salary"), r.get("experience"),
+         r.get("education"), r.get("location"), r.get("company"),
+         r.get("company_url"),
+         json.dumps(r.get("job_tags") or [], ensure_ascii=False),
+         json.dumps(r.get("company_tags") or [], ensure_ascii=False),
+         r.get("link"), keyword),
+    )
+    conn.commit()
+    return cur.rowcount > 0
+
+
+# ── 抓取 ────────────────────────────────────────────────────────────────
+def crawl_list(conn, page, keyword: str, pages: int, jl: str | None) -> None:
+    scope = f"{keyword}|{jl or ''}"
+    start = get_last_page(conn, scope) + 1
+    if start > pages:
+        print(f"[列表] '{keyword}' 已抓到第 {start-1} 页, 目标 {pages} 页, 无需续抓。")
+        return
+    print(f"[列表] '{keyword}' 从第 {start} 页抓到第 {pages} 页")
+    for n in range(start, pages + 1):
+        url = f"https://sou.zhaopin.com/?kw={quote(keyword)}&p={n}"
+        if jl:
+            url += f"&jl={jl}"
+        try:
+            page.goto(url, wait_until="domcontentloaded", timeout=60000)
+            page.wait_for_selector(".joblist-box__item", timeout=20000)
+        except Exception:
+            print(f"  第 {n} 页未加载出列表, 停止本轮 (重跑可从此页续)。")
+            break
+        page.wait_for_timeout(1200)
+        rows = page.evaluate(_LIST_JS)
+        new = sum(upsert_job(conn, r, keyword) for r in rows)
+        set_last_page(conn, scope, n)
+        print(f"  第 {n} 页: {len(rows)} 条 (新增 {new})")
+        time.sleep(random.uniform(3, 7))
+
+
+def crawl_details(conn, page, keyword: str | None, limit: int | None) -> None:
+    q = "SELECT job_id,link FROM jobs WHERE (jd_text IS NULL OR jd_text='') AND link!=''"
+    params: list = []
+    if keyword:
+        q += " AND keyword=?"
+        params.append(keyword)
+    q += " ORDER BY created_at"
+    if limit:
+        q += f" LIMIT {int(limit)}"
+    todo = conn.execute(q, params).fetchall()
+    if not todo:
+        print("[详情] 没有待补充 JD 的岗位。")
+        return
+    print(f"[详情] 待抓 JD: {len(todo)} 条")
+    for i, (jid, link) in enumerate(todo, 1):
+        try:
+            page.goto(link, wait_until="domcontentloaded", timeout=60000)
+            page.wait_for_selector(".describtion-card__detail-content", timeout=15000)
+            page.wait_for_timeout(800)
+            data = page.evaluate(_DETAIL_JS)
+        except Exception as e:
+            print(f"  [{i}/{len(todo)}] {jid} 抓取失败: {str(e)[:60]}")
+            continue
+        conn.execute(
+            "UPDATE jobs SET jd_text=?, skills=?, detail_at=datetime('now','localtime') "
+            "WHERE job_id=?",
+            (data.get("jd", ""),
+             json.dumps(data.get("skills") or [], ensure_ascii=False), jid),
+        )
+        conn.commit()  # 逐条提交 => 中断安全
+        jd_len = len(data.get("jd", ""))
+        print(f"  [{i}/{len(todo)}] {jid} JD {jd_len} 字")
+        time.sleep(random.uniform(2, 5))
+
+
+# ── 导出 ────────────────────────────────────────────────────────────────
+def export_csv(conn, path: str, keyword: str | None) -> None:
+    q = ("SELECT title,salary,experience,education,location,company,"
+         "job_tags,company_tags,skills,jd_text,link FROM jobs")
+    params: list = []
+    if keyword:
+        q += " WHERE keyword=?"
+        params.append(keyword)
+    rows = conn.execute(q, params).fetchall()
+    cols = ["title", "salary", "experience", "education", "location", "company",
+            "job_tags", "company_tags", "skills", "jd_text", "link"]
+    with open(path, "w", newline="", encoding="utf-8-sig") as f:
+        w = csv.writer(f)
+        w.writerow(cols)
+        for row in rows:
+            row = list(row)
+            for idx in (6, 7, 8):  # json 数组列 -> 用 / 连接
+                try:
+                    row[idx] = " / ".join(json.loads(row[idx] or "[]"))
+                except Exception:
+                    pass
+            w.writerow(row)
+    print(f"已导出 {len(rows)} 条 -> {path}")
+
+
+# ── main ────────────────────────────────────────────────────────────────
+def main() -> None:
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--keyword", default="AI", help="搜索关键词")
+    ap.add_argument("--pages", type=int, default=3, help="列表抓取页数")
+    ap.add_argument("--jl", default=None, help="城市编码, 不填=全国")
+    ap.add_argument("--db", default=DB_DEFAULT, help="SQLite 文件路径")
+    ap.add_argument("--no-detail", action="store_true", help="只抓列表, 不进详情页")
+    ap.add_argument("--detail-limit", type=int, default=None, help="本轮最多抓多少条 JD")
+    ap.add_argument("--headful", action="store_true", help="显示浏览器窗口")
+    ap.add_argument("--reset", action="store_true", help="重置该关键词的列表进度")
+    ap.add_argument("--export", metavar="CSV", help="导出已抓数据到 CSV 后退出")
+    args = ap.parse_args()
+
+    with closing(init_db(args.db)) as conn:
+        if args.export:
+            export_csv(conn, args.export, args.keyword if args.keyword != "AI" else None)
+            return
+        if args.reset:
+            scope = f"{args.keyword}|{args.jl or ''}"
+            conn.execute("DELETE FROM progress WHERE scope=?", (scope,))
+            conn.commit()
+            print(f"已重置进度: {scope}")
+
+        with InvisiblePlaywright(seed=42, headless=not args.headful) as browser:
+            page = browser.new_page()
+            crawl_list(conn, page, args.keyword, args.pages, args.jl)
+            if not args.no_detail:
+                crawl_details(conn, page, args.keyword, args.detail_limit)
+
+        total = conn.execute("SELECT COUNT(*) FROM jobs").fetchone()[0]
+        with_jd = conn.execute(
+            "SELECT COUNT(*) FROM jobs WHERE jd_text IS NOT NULL AND jd_text!=''"
+        ).fetchone()[0]
+        print(f"\n库内合计 {total} 条, 其中含 JD 全文 {with_jd} 条 -> {args.db}")
+
+
+if __name__ == "__main__":
+    main()

examples/scrape_zhipin_ai.py

@@ -0,0 +1,112 @@
+"""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()