网站上写个招贤纳士怎么做seo最新教程
今天想爬取一些政策，从政策服务 (smejs.cn) 这个网址爬取，html源码找不到链接地址，通过浏览器的开发者工具，点击以下红框
分析预览可知想要的链接地址的id有了，进行地址拼接就行
点击标头可以看到请求后端服务器的api地址，通过拿到这个地址，编写python脚本，不会的可以让gpt帮你写，很好用
import requests
import pandas as pd
import logging
import time
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry# 设置日志
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')# 请求头信息
headers = {'Content-Type': 'application/json','User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
}# 基础URL
base_url = 'https://policy-gateway.smejs.cn/policy/api/policy/getNewPolicyList'
base_policy_url = 'https://policy.smejs.cn/frontend/policy-service/'# 参数
params = {'orderBy': '','keyWords': '','genreCode': 'K,A,S,Z','queryPublishBegin': '','queryPublishEnd': '','queryApplyBegin': '','queryApplyEnd': '','typeCondition': '','publishUnit': '','applyObj': '','meetEnterprise': '','title': '','commissionOfficeIds': '','commissionOfficeSearchIds': '','industry': '','relativePlatform': '','level': '','isSearch': 'N','policyType': '','provinceValue': '江苏省','cityValue': '','regionValue': '','current': 1,'size': 15,'total': 23960,'page': 0
}# 总条目数和每页条目数
total_policies = 23960
page_size = 15
total_pages = (total_policies // page_size) + 1# 存储所有政策数据
all_policies = []# 配置重试策略
retry_strategy = Retry(total=5,status_forcelist=[429, 500, 502, 503, 504],allowed_methods=["HEAD", "GET", "OPTIONS"]
)
adapter = HTTPAdapter(max_retries=retry_strategy)
http = requests.Session()
http.mount("https://", adapter)
http.mount("http://", adapter)# 遍历每一页
for page in range(total_pages):params['current'] = page + 1try:response = http.get(base_url, headers=headers, params=params, verify=False)response.raise_for_status()except requests.exceptions.RequestException as e:logging.error(f"Failed to fetch data for page {page + 1}: {e}")continuedata = response.json()if 'records' not in data['data']:logging.error(f"No records found for page {page + 1}")continuerecords = data['data']['records']for record in records:policy_id = record.get('id')level_value = record.get('levelValue')title = record.get('title')type_value = record.get('typeValue')commission_office_names = record.get('commissionOfficeNames')publish_time = record.get('publishTime')valid_date_end = record.get('validDateEnd')policy_url = base_policy_url + policy_idall_policies.append({'ID': policy_id,'URL': policy_url,'Level Value': level_value,'Title': title,'Type Value': type_value,'Commission Office Names': commission_office_names,'Publish Time': publish_time,'Valid Date End': valid_date_end})logging.info(f"Fetched data for page {page + 1}")time.sleep(1) # 防止过快请求# 转换为DataFrame
df = pd.DataFrame(all_policies)# 保存到Excel
df.to_excel('policies.xlsx', index=False)
logging.info("Data saved to policies.xlsx")
然后运行后，就等到爬取完成了，后面也可以多线程爬，还没试，不知道是否有防爬机制。。。。