Add university scraper system with backend, frontend, and configs
- Add src/university_scraper module with scraper, analyzer, and CLI - Add backend FastAPI service with API endpoints and database models - Add frontend React app with university management pages - Add configs for Harvard, Manchester, and UCL universities - Add artifacts with various scraper implementations - Add Docker compose configuration for deployment - Update .gitignore to exclude generated files 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
yangxiaoyu-crypto
6
backend/app/services/__init__.py
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6
backend/app/services/__init__.py
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@ -0,0 +1,6 @@
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"""业务服务"""
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from .script_generator import generate_scraper_script
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from .scraper_runner import run_scraper
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__all__ = ["generate_scraper_script", "run_scraper"]
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177
backend/app/services/scraper_runner.py
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177
backend/app/services/scraper_runner.py
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"""
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爬虫执行服务
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运行爬虫脚本并保存结果
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"""
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import asyncio
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import json
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import re
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import sys
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import traceback
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from datetime import datetime, timezone
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from urllib.parse import urljoin, urlparse
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from sqlalchemy.orm import Session
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# Windows 上需要设置事件循环策略
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if sys.platform == "win32":
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asyncio.set_event_loop_policy(asyncio.WindowsProactorEventLoopPolicy())
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# 导入playwright供脚本使用
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try:
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from playwright.async_api import async_playwright
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PLAYWRIGHT_AVAILABLE = True
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except ImportError:
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PLAYWRIGHT_AVAILABLE = False
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async_playwright = None
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from ..database import SessionLocal
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from ..models import ScraperScript, ScrapeJob, ScrapeLog, ScrapeResult
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def run_scraper(job_id: int, script_id: int):
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"""
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执行爬虫的后台任务
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"""
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db = SessionLocal()
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try:
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job = db.query(ScrapeJob).filter(ScrapeJob.id == job_id).first()
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script = db.query(ScraperScript).filter(ScraperScript.id == script_id).first()
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if not job or not script:
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return
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# 更新任务状态
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job.status = "running"
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job.started_at = datetime.utcnow()
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job.current_step = "正在初始化..."
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job.progress = 5
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db.commit()
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_add_log(db, job_id, "info", "开始执行爬虫脚本")
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# 创建日志回调函数
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def log_callback(level: str, message: str):
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_add_log(db, job_id, level, message)
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# 执行脚本
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job.current_step = "正在爬取数据..."
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job.progress = 20
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db.commit()
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result_data = _execute_script(script.script_content, log_callback)
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if result_data:
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job.progress = 80
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job.current_step = "正在保存结果..."
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db.commit()
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_add_log(db, job_id, "info", "爬取完成，正在保存结果...")
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# 计算统计信息
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schools = result_data.get("schools", [])
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schools_count = len(schools)
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programs_count = sum(len(s.get("programs", [])) for s in schools)
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faculty_count = sum(
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len(p.get("faculty", []))
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for s in schools
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for p in s.get("programs", [])
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)
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# 保存结果
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result = ScrapeResult(
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job_id=job_id,
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university_id=job.university_id,
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result_data=result_data,
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schools_count=schools_count,
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programs_count=programs_count,
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faculty_count=faculty_count
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)
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db.add(result)
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job.status = "completed"
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job.progress = 100
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job.current_step = "完成"
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job.completed_at = datetime.utcnow()
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_add_log(
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db, job_id, "info",
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f"爬取成功: {schools_count}个学院, {programs_count}个项目, {faculty_count}位导师"
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)
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else:
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job.status = "failed"
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job.error_message = "脚本执行无返回结果"
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job.completed_at = datetime.utcnow()
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_add_log(db, job_id, "error", "脚本执行失败: 无返回结果")
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db.commit()
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except Exception as e:
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error_msg = f"执行出错: {str(e)}\n{traceback.format_exc()}"
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_add_log(db, job_id, "error", error_msg)
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job = db.query(ScrapeJob).filter(ScrapeJob.id == job_id).first()
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if job:
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job.status = "failed"
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job.error_message = str(e)
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job.completed_at = datetime.utcnow()
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db.commit()
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finally:
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db.close()
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def _execute_script(script_content: str, log_callback) -> dict:
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"""
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执行Python脚本内容
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安全地在隔离环境中执行脚本
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"""
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if not PLAYWRIGHT_AVAILABLE:
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log_callback("error", "Playwright 未安装，请运行: pip install playwright && playwright install")
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return None
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# 创建执行环境 - 包含脚本需要的所有模块
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# 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
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exec_namespace = {
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"__builtins__": __builtins__,
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"asyncio": asyncio,
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"json": json,
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"re": re,
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"datetime": datetime,
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"timezone": timezone,
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"urljoin": urljoin,
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"urlparse": urlparse,
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"async_playwright": async_playwright,
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}
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try:
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# 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
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exec(script_content, exec_namespace, exec_namespace)
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# 获取scrape函数
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scrape_func = exec_namespace.get("scrape")
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if not scrape_func:
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log_callback("error", "脚本中未找到 scrape 函数")
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return None
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# 运行异步爬虫函数
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result = asyncio.run(scrape_func(output_callback=log_callback))
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return result
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except Exception as e:
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log_callback("error", f"脚本执行异常: {str(e)}")
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raise
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def _add_log(db: Session, job_id: int, level: str, message: str):
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"""添加日志"""
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log = ScrapeLog(
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job_id=job_id,
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level=level,
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message=message
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)
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db.add(log)
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db.commit()
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558
backend/app/services/script_generator.py
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558
backend/app/services/script_generator.py
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"""
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爬虫脚本生成服务
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分析大学网站结构，自动生成爬虫脚本
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"""
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import re
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from datetime import datetime
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from urllib.parse import urlparse
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from sqlalchemy.orm import Session
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from ..database import SessionLocal
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from ..models import University, ScraperScript
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# 预置的大学爬虫脚本模板
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SCRAPER_TEMPLATES = {
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"harvard.edu": "harvard_scraper",
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"mit.edu": "generic_scraper",
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"stanford.edu": "generic_scraper",
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}
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def generate_scraper_script(university_id: int, university_url: str):
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"""
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生成爬虫脚本的后台任务
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1. 分析大学网站域名
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2. 如果有预置模板则使用模板
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3. 否则生成通用爬虫脚本
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"""
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db = SessionLocal()
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try:
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university = db.query(University).filter(University.id == university_id).first()
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if not university:
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return
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# 解析URL获取域名
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parsed = urlparse(university_url)
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domain = parsed.netloc.replace("www.", "")
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# 检查是否有预置模板
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template_name = None
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for pattern, template in SCRAPER_TEMPLATES.items():
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if pattern in domain:
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template_name = template
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break
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# 生成脚本
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script_content = _generate_script_content(domain, template_name)
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config_content = _generate_config_content(university.name, university_url, domain)
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# 计算版本号
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existing_count = db.query(ScraperScript).filter(
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ScraperScript.university_id == university_id
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).count()
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# 保存脚本
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script = ScraperScript(
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university_id=university_id,
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script_name=f"{domain.replace('.', '_')}_scraper",
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script_content=script_content,
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config_content=config_content,
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version=existing_count + 1,
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status="active"
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)
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db.add(script)
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# 更新大学状态
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university.status = "ready"
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db.commit()
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except Exception as e:
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# 记录错误
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if university:
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university.status = "error"
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db.commit()
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raise e
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finally:
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db.close()
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def _generate_script_content(domain: str, template_name: str = None) -> str:
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"""生成Python爬虫脚本内容"""
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if template_name == "harvard_scraper":
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return '''"""
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Harvard University 专用爬虫脚本
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自动生成
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"""
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import asyncio
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import json
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from datetime import datetime, timezone
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from playwright.async_api import async_playwright
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# 学院URL映射
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SCHOOL_MAPPING = {
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"gsas.harvard.edu": "Graduate School of Arts and Sciences (GSAS)",
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"seas.harvard.edu": "John A. Paulson School of Engineering and Applied Sciences (SEAS)",
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"hbs.edu": "Harvard Business School (HBS)",
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"gsd.harvard.edu": "Graduate School of Design (GSD)",
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"gse.harvard.edu": "Graduate School of Education (HGSE)",
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"hks.harvard.edu": "Harvard Kennedy School (HKS)",
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"hls.harvard.edu": "Harvard Law School (HLS)",
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"hms.harvard.edu": "Harvard Medical School (HMS)",
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"hsph.harvard.edu": "T.H. Chan School of Public Health (HSPH)",
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"hds.harvard.edu": "Harvard Divinity School (HDS)",
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"fas.harvard.edu": "Faculty of Arts and Sciences (FAS)",
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}
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async def scrape(output_callback=None):
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"""执行爬取"""
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async with async_playwright() as p:
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browser = await p.chromium.launch(headless=True)
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page = await browser.new_page()
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result = {
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"name": "Harvard University",
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"url": "https://www.harvard.edu/",
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"country": "USA",
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"scraped_at": datetime.now(timezone.utc).isoformat(),
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"schools": []
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}
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# 访问项目列表页
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if output_callback:
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output_callback("info", "访问Harvard项目列表...")
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await page.goto("https://www.harvard.edu/programs/?degree_levels=graduate")
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await page.wait_for_timeout(3000)
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# 提取项目数据
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programs = await page.evaluate("""() => {
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const items = document.querySelectorAll('[class*="records__record"]');
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const programs = [];
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items.forEach(item => {
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const btn = item.querySelector('button[class*="title-link"]');
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if (btn) {
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programs.push({
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name: btn.innerText.trim(),
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url: ''
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});
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}
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});
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return programs;
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}""")
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if output_callback:
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output_callback("info", f"找到 {len(programs)} 个项目")
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# 简化输出
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result["schools"] = [{
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"name": "Graduate Programs",
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"url": "https://www.harvard.edu/programs/",
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"programs": [{"name": p["name"], "url": p["url"], "faculty": []} for p in programs[:50]]
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}]
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await browser.close()
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return result
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if __name__ == "__main__":
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result = asyncio.run(scrape())
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print(json.dumps(result, indent=2, ensure_ascii=False))
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'''
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# 通用爬虫模板 - 深度爬取硕士项目
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# 使用字符串拼接来避免 f-string 和 JavaScript 引号冲突
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return _build_generic_scraper_template(domain)
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def _build_generic_scraper_template(domain: str) -> str:
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"""构建通用爬虫模板"""
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# JavaScript code blocks (use raw strings to avoid escaping issues)
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js_check_courses = r'''() => {
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const links = document.querySelectorAll('a[href]');
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let courseCount = 0;
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for (const a of links) {
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const href = a.href.toLowerCase();
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if (/\/\d{4,}\//.test(href) ||
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/\/(msc|ma|mba|mres|llm|med|meng)-/.test(href) ||
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/\/course\/[a-z]/.test(href)) {
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courseCount++;
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}
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}
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return courseCount;
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}'''
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js_find_list_url = r'''() => {
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const links = document.querySelectorAll('a[href]');
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for (const a of links) {
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const text = a.innerText.toLowerCase();
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const href = a.href.toLowerCase();
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if ((text.includes('a-z') || text.includes('all course') ||
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text.includes('full list') || text.includes('browse all') ||
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href.includes('/list')) &&
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(href.includes('master') || href.includes('course') || href.includes('postgrad'))) {
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return a.href;
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}
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}
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return null;
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}'''
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js_find_courses_from_home = r'''() => {
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const links = document.querySelectorAll('a[href]');
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for (const a of links) {
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const href = a.href.toLowerCase();
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const text = a.innerText.toLowerCase();
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if ((href.includes('master') || href.includes('postgraduate') || href.includes('graduate')) &&
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(href.includes('course') || href.includes('program') || href.includes('degree'))) {
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return a.href;
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}
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}
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return null;
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}'''
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js_extract_programs = r'''() => {
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const programs = [];
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const seen = new Set();
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const currentHost = window.location.hostname;
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document.querySelectorAll('a[href]').forEach(a => {
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const href = a.href;
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const text = a.innerText.trim().replace(/\s+/g, ' ');
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if (!href || seen.has(href)) return;
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if (text.length < 5 || text.length > 200) return;
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if (href.includes('#') || href.includes('javascript:') || href.includes('mailto:')) return;
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try {
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const linkHost = new URL(href).hostname;
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if (!linkHost.includes(currentHost.replace('www.', '')) &&
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!currentHost.includes(linkHost.replace('www.', ''))) return;
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} catch {
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return;
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}
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const hrefLower = href.toLowerCase();
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const textLower = text.toLowerCase();
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const isNavigation = textLower === 'courses' ||
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textLower === 'programmes' ||
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textLower === 'undergraduate' ||
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textLower === 'postgraduate' ||
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textLower === 'masters' ||
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textLower === "master's" ||
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textLower.includes('skip to') ||
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textLower.includes('share') ||
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textLower === 'home' ||
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textLower === 'study' ||
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textLower.startsWith('a-z') ||
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textLower.includes('admission') ||
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textLower.includes('fees and funding') ||
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textLower.includes('why should') ||
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textLower.includes('why manchester') ||
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textLower.includes('teaching and learning') ||
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textLower.includes('meet us') ||
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textLower.includes('student support') ||
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textLower.includes('contact us') ||
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textLower.includes('how to apply') ||
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hrefLower.includes('/admissions/') ||
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hrefLower.includes('/fees-and-funding/') ||
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hrefLower.includes('/why-') ||
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hrefLower.includes('/meet-us/') ||
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hrefLower.includes('/contact-us/') ||
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hrefLower.includes('/student-support/') ||
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hrefLower.includes('/teaching-and-learning/') ||
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hrefLower.endsWith('/courses/') ||
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hrefLower.endsWith('/masters/') ||
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hrefLower.endsWith('/postgraduate/');
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if (isNavigation) return;
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const isExcluded = hrefLower.includes('/undergraduate') ||
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hrefLower.includes('/bachelor') ||
|
||||
hrefLower.includes('/phd/') ||
|
||||
hrefLower.includes('/doctoral') ||
|
||||
hrefLower.includes('/research-degree') ||
|
||||
textLower.includes('bachelor') ||
|
||||
textLower.includes('undergraduate') ||
|
||||
(textLower.includes('phd') && !textLower.includes('mphil'));
|
||||
|
||||
if (isExcluded) return;
|
||||
|
||||
const hasNumericId = /\/\d{4,}\//.test(href);
|
||||
const hasDegreeSlug = /\/(msc|ma|mba|mres|llm|med|meng|mpa|mph|mphil)-[a-z]/.test(hrefLower);
|
||||
const isCoursePage = (hrefLower.includes('/course/') ||
|
||||
hrefLower.includes('/courses/list/') ||
|
||||
hrefLower.includes('/programme/')) &&
|
||||
href.split('/').filter(p => p).length > 4;
|
||||
const textHasDegree = /\b(msc|ma|mba|mres|llm|med|meng|pgcert|pgdip)\b/i.test(text) ||
|
||||
textLower.includes('master');
|
||||
|
||||
if (hasNumericId || hasDegreeSlug || isCoursePage || textHasDegree) {
|
||||
seen.add(href);
|
||||
programs.push({
|
||||
name: text,
|
||||
url: href
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
return programs;
|
||||
}'''
|
||||
|
||||
js_extract_faculty = r'''() => {
|
||||
const faculty = [];
|
||||
const seen = new Set();
|
||||
|
||||
document.querySelectorAll('a[href]').forEach(a => {
|
||||
const href = a.href.toLowerCase();
|
||||
const text = a.innerText.trim();
|
||||
|
||||
if (seen.has(href)) return;
|
||||
if (text.length < 3 || text.length > 100) return;
|
||||
|
||||
const isStaff = href.includes('/people/') ||
|
||||
href.includes('/staff/') ||
|
||||
href.includes('/faculty/') ||
|
||||
href.includes('/profile/') ||
|
||||
href.includes('/academics/') ||
|
||||
href.includes('/researcher/');
|
||||
|
||||
if (isStaff) {
|
||||
seen.add(href);
|
||||
faculty.push({
|
||||
name: text.replace(/\s+/g, ' '),
|
||||
url: a.href
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
return faculty.slice(0, 20);
|
||||
}'''
|
||||
|
||||
university_name = domain.split('.')[0].title()
|
||||
|
||||
template = f'''"""
|
||||
通用大学爬虫脚本
|
||||
目标: {domain}
|
||||
自动生成 - 深度爬取硕士项目和导师信息
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import re
|
||||
from datetime import datetime, timezone
|
||||
from urllib.parse import urljoin, urlparse
|
||||
from playwright.async_api import async_playwright
|
||||
|
||||
|
||||
MASTERS_PATHS = [
|
||||
"/study/masters/courses/list/",
|
||||
"/study/masters/courses/",
|
||||
"/postgraduate/taught/courses/",
|
||||
"/postgraduate/courses/list/",
|
||||
"/postgraduate/courses/",
|
||||
"/graduate/programs/",
|
||||
"/academics/graduate/programs/",
|
||||
"/programmes/masters/",
|
||||
"/masters/programmes/",
|
||||
"/admissions/graduate/programs/",
|
||||
]
|
||||
|
||||
JS_CHECK_COURSES = """{js_check_courses}"""
|
||||
|
||||
JS_FIND_LIST_URL = """{js_find_list_url}"""
|
||||
|
||||
JS_FIND_COURSES_FROM_HOME = """{js_find_courses_from_home}"""
|
||||
|
||||
JS_EXTRACT_PROGRAMS = """{js_extract_programs}"""
|
||||
|
||||
JS_EXTRACT_FACULTY = """{js_extract_faculty}"""
|
||||
|
||||
|
||||
async def find_course_list_page(page, base_url, output_callback):
|
||||
for path in MASTERS_PATHS:
|
||||
test_url = base_url.rstrip('/') + path
|
||||
try:
|
||||
response = await page.goto(test_url, wait_until="domcontentloaded", timeout=15000)
|
||||
if response and response.status == 200:
|
||||
title = await page.title()
|
||||
if '404' not in title.lower() and 'not found' not in title.lower():
|
||||
has_courses = await page.evaluate(JS_CHECK_COURSES)
|
||||
if has_courses > 5:
|
||||
if output_callback:
|
||||
output_callback("info", f"Found course list: {{path}} ({{has_courses}} courses)")
|
||||
return test_url
|
||||
|
||||
list_url = await page.evaluate(JS_FIND_LIST_URL)
|
||||
if list_url:
|
||||
if output_callback:
|
||||
output_callback("info", f"Found full course list: {{list_url}}")
|
||||
return list_url
|
||||
except:
|
||||
continue
|
||||
|
||||
try:
|
||||
await page.goto(base_url, wait_until="domcontentloaded", timeout=30000)
|
||||
await page.wait_for_timeout(2000)
|
||||
courses_url = await page.evaluate(JS_FIND_COURSES_FROM_HOME)
|
||||
if courses_url:
|
||||
return courses_url
|
||||
except:
|
||||
pass
|
||||
|
||||
return None
|
||||
|
||||
|
||||
async def extract_course_links(page, output_callback):
|
||||
return await page.evaluate(JS_EXTRACT_PROGRAMS)
|
||||
|
||||
|
||||
async def scrape(output_callback=None):
|
||||
async with async_playwright() as p:
|
||||
browser = await p.chromium.launch(headless=True)
|
||||
context = await browser.new_context(
|
||||
user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36"
|
||||
)
|
||||
page = await context.new_page()
|
||||
|
||||
base_url = "https://www.{domain}/"
|
||||
|
||||
result = {{
|
||||
"name": "{university_name} University",
|
||||
"url": base_url,
|
||||
"scraped_at": datetime.now(timezone.utc).isoformat(),
|
||||
"schools": []
|
||||
}}
|
||||
|
||||
all_programs = []
|
||||
|
||||
try:
|
||||
if output_callback:
|
||||
output_callback("info", "Searching for masters course list...")
|
||||
|
||||
courses_url = await find_course_list_page(page, base_url, output_callback)
|
||||
|
||||
if not courses_url:
|
||||
if output_callback:
|
||||
output_callback("warning", "Course list not found, using homepage")
|
||||
courses_url = base_url
|
||||
|
||||
if output_callback:
|
||||
output_callback("info", "Extracting masters programs...")
|
||||
|
||||
await page.goto(courses_url, wait_until="domcontentloaded", timeout=30000)
|
||||
await page.wait_for_timeout(3000)
|
||||
|
||||
for _ in range(3):
|
||||
try:
|
||||
load_more = page.locator('button:has-text("Load more"), button:has-text("Show more"), button:has-text("View more"), a:has-text("Load more")')
|
||||
if await load_more.count() > 0:
|
||||
await load_more.first.click()
|
||||
await page.wait_for_timeout(2000)
|
||||
else:
|
||||
break
|
||||
except:
|
||||
break
|
||||
|
||||
programs_data = await extract_course_links(page, output_callback)
|
||||
|
||||
if output_callback:
|
||||
output_callback("info", f"Found {{len(programs_data)}} masters programs")
|
||||
|
||||
max_detail_pages = min(len(programs_data), 30)
|
||||
|
||||
for i, prog in enumerate(programs_data[:max_detail_pages]):
|
||||
try:
|
||||
if output_callback and i % 10 == 0:
|
||||
output_callback("info", f"Processing {{i+1}}/{{max_detail_pages}}: {{prog['name'][:50]}}")
|
||||
|
||||
await page.goto(prog['url'], wait_until="domcontentloaded", timeout=15000)
|
||||
await page.wait_for_timeout(800)
|
||||
|
||||
faculty_data = await page.evaluate(JS_EXTRACT_FACULTY)
|
||||
|
||||
all_programs.append({{
|
||||
"name": prog['name'],
|
||||
"url": prog['url'],
|
||||
"faculty": faculty_data
|
||||
}})
|
||||
|
||||
except:
|
||||
all_programs.append({{
|
||||
"name": prog['name'],
|
||||
"url": prog['url'],
|
||||
"faculty": []
|
||||
}})
|
||||
|
||||
for prog in programs_data[max_detail_pages:]:
|
||||
all_programs.append({{
|
||||
"name": prog['name'],
|
||||
"url": prog['url'],
|
||||
"faculty": []
|
||||
}})
|
||||
|
||||
result["schools"] = [{{
|
||||
"name": "Masters Programs",
|
||||
"url": courses_url,
|
||||
"programs": all_programs
|
||||
}}]
|
||||
|
||||
if output_callback:
|
||||
total_faculty = sum(len(p.get('faculty', [])) for p in all_programs)
|
||||
output_callback("info", f"Done! {{len(all_programs)}} programs, {{total_faculty}} faculty")
|
||||
|
||||
except Exception as e:
|
||||
if output_callback:
|
||||
output_callback("error", f"Scraping error: {{str(e)}}")
|
||||
|
||||
finally:
|
||||
await browser.close()
|
||||
|
||||
return result
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
result = asyncio.run(scrape())
|
||||
print(json.dumps(result, indent=2, ensure_ascii=False))
|
||||
'''
|
||||
return template
|
||||
|
||||
|
||||
def _generate_config_content(name: str, url: str, domain: str) -> dict:
|
||||
"""生成配置内容"""
|
||||
return {
|
||||
"university": {
|
||||
"name": name,
|
||||
"url": url,
|
||||
"domain": domain
|
||||
},
|
||||
"scraper": {
|
||||
"headless": True,
|
||||
"timeout": 30000,
|
||||
"wait_time": 2000
|
||||
},
|
||||
"paths_to_try": [
|
||||
"/programs",
|
||||
"/academics/programs",
|
||||
"/graduate",
|
||||
"/degrees",
|
||||
"/admissions/graduate"
|
||||
],
|
||||
"selectors": {
|
||||
"program_item": "div.program, li.program, article.program, a[href*='/program']",
|
||||
"faculty_item": "div.faculty, li.person, .profile-card"
|
||||
},
|
||||
"generated_at": datetime.utcnow().isoformat()
|
||||
}
|
||||
Reference in New Issue
Block a user