Files
kgod c06f595559 feat: add crawl scripts for recruitment websites
- btyy (倍特药业), fullsemi (富芯半导体): 北森平台爬虫
- hotjob (中国五矿): hotjob平台爬虫
- leinao (中科类脑): 静态HTML爬虫
- task_fetcher: 原子锁获取任务
- post.md: 抓取技能文档
- export_har: mitmproxy HAR导出工具
2026-05-27 23:48:30 +08:00

217 lines
7.1 KiB
Python

import requests
import hashlib
import time
from datetime import datetime
from bs4 import BeautifulSoup
CATEGORY_DB_MAP = {
"7": 0, # /job/7 社招
"8": 1, # /job/8 校招
}
def parse_to_db(records, task_crawl_id, company_id="leinao", company="中科类脑"):
"""将解析后的岗位数据清洗为 app_job_data 表所需格式"""
results = []
for r in records:
job_title = (r.get("job_title") or "").strip()
if not job_title:
continue
description = r.get("description") or ""
detail_url = r.get("detail_url") or ""
recruit_category = r.get("recruit_category", 0)
content_hash = hashlib.md5(
f"{job_title}|{company_id}|{description}".encode("utf-8")
).hexdigest()
item = {
"task_crawl_id": task_crawl_id,
"job_title": job_title,
"company_id": company_id,
"company": company,
"detail_url": detail_url,
"recruit_category": recruit_category,
"content_hash": content_hash,
}
if r.get("location"):
item["location"] = r["location"]
if r.get("salary"):
item["salary"] = r["salary"]
if r.get("education"):
item["education"] = r["education"]
if r.get("experience"):
item["experience"] = r["experience"]
if description:
item["description"] = description
post_date = r.get("post_date") or ""
if post_date:
item["expire_at"] = post_date + " 00:00:00"
else:
item["expire_at"] = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
results.append(item)
return results
class LeinaoJobCrawler:
"""中科类脑招聘官网爬虫 (www.leinao.ai)"""
BASE_URL = "https://www.leinao.ai"
CATEGORY_MAP = {
"shezhao": "7",
"xiaozhao": "8",
}
def __init__(self):
self.session = requests.Session()
self.session.headers.update({
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/146.0.0.0 Safari/537.36",
})
def _get_job_list(self, category_id):
"""获取岗位列表页,解析HTML"""
url = f"{self.BASE_URL}/job/{category_id}"
resp = self.session.get(url)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, "html.parser")
links = soup.find_all("a", href=lambda h: h and "/jobdetail/" in h)
records = []
for link in links:
href = link.get("href", "")
job_id = href.split("/")[-1]
cells = link.find_all(["div", "span", "p", "generic"])
texts = [t.get_text(strip=True) for t in link.children if hasattr(t, 'get_text')]
all_text = link.get_text(separator="|", strip=True).split("|")
all_text = [t for t in all_text if t]
record = {
"job_id": job_id,
"detail_url": f"{self.BASE_URL}{href}",
"recruit_category": CATEGORY_DB_MAP.get(category_id, 0),
}
if len(all_text) >= 1:
record["job_title"] = all_text[0]
if len(all_text) >= 2:
loc = all_text[1]
record["location"] = loc if loc != "不限" else None
if len(all_text) >= 3:
record["job_type"] = all_text[2]
if len(all_text) >= 4:
record["category_name"] = all_text[3]
if len(all_text) >= 5:
record["post_date"] = all_text[4]
if len(all_text) >= 6:
record["org"] = all_text[5]
records.append(record)
position_ids = [r["job_id"] for r in records]
return {"total": len(records), "records": records, "position_ids": position_ids}
def get_shezhao_list(self):
"""获取社会招聘列表"""
return self._get_job_list(self.CATEGORY_MAP["shezhao"])
def get_xiaozhao_list(self):
"""获取校园招聘列表"""
return self._get_job_list(self.CATEGORY_MAP["xiaozhao"])
def get_shixi_list(self):
"""获取实习招聘列表(该网站无实习分类)"""
return {"total": 0, "records": [], "position_ids": []}
def get_position_detail(self, job_id):
"""获取岗位详情"""
url = f"{self.BASE_URL}/jobdetail/{job_id}"
resp = self.session.get(url)
resp.raise_for_status()
soup = BeautifulSoup(resp.text, "html.parser")
main = soup.find("main") or soup
title_tag = soup.find("title")
job_title = title_tag.get_text().replace("-中科类脑", "").strip() if title_tag else ""
paragraphs = main.find_all("p")
description_parts = []
for p in paragraphs:
text = p.get_text(strip=True)
if text and len(text) > 5:
description_parts.append(text)
h6_tags = main.find_all("h6")
location = None
salary = None
experience = None
for h6 in h6_tags:
text = h6.get_text(strip=True).replace("\xa0", " ")
if "薪资" in text or "工作经验" in text:
parts = [p.strip() for p in text.split() if p.strip()]
for part in parts:
if "薪资:" in part:
sal = part.replace("薪资:", "")
if sal and sal != "面议":
salary = sal
elif "工作经验:" in part:
exp = part.replace("工作经验:", "")
if exp and exp != "不限":
experience = exp
elif "·" in part and "不限" not in part:
location = part
return {
"job_id": job_id,
"job_title": job_title,
"description": "\n".join(description_parts),
"location": location,
"salary": salary,
"experience": experience,
"detail_url": f"{self.BASE_URL}/jobdetail/{job_id}",
}
def crawl_all(self):
"""爬取所有岗位列表+详情"""
all_records = []
for name, cat_id in self.CATEGORY_MAP.items():
job_list = self._get_job_list(cat_id)
recruit_cat = CATEGORY_DB_MAP.get(cat_id, 0)
print(f"[{name}] 共 {job_list['total']} 个岗位")
for r in job_list["records"]:
time.sleep(0.3)
detail = self.get_position_detail(r["job_id"])
detail["recruit_category"] = recruit_cat
detail["post_date"] = r.get("post_date")
all_records.append(detail)
return all_records
if __name__ == "__main__":
crawler = LeinaoJobCrawler()
print("=" * 60)
print("中科类脑 - 招聘岗位爬取")
print("=" * 60)
all_details = crawler.crawl_all()
print(f"\n[数据清洗]")
task_crawl_id = 0
parsed = parse_to_db(all_details, task_crawl_id)
print(f" 清洗完成: {len(parsed)}")
if parsed:
print("\n--- 样例 ---")
for k, v in parsed[0].items():
print(f" {k}: {str(v)[:100]}")