动态数据抓取实战指南

理解动态数据加载机制

现代网站广泛使用JavaScript和AJAX技术动态加载内容，传统爬虫无法直接获取这些数据。动态内容通常通过XHR（XMLHttpRequest）或Fetch API发起异步请求，从服务器获取数据后渲染到页面。理解这种机制是抓取的前提。

分析网络请求

使用浏览器开发者工具（F12）的Network面板监控XHR/Fetch请求。筛选AJAX请求，查看请求URL、参数、响应格式（JSON/HTML）。重点关注Headers中的Request Method（GET/POST）、Query String Parameters和Request Headers。

直接调用API接口

若网站采用前后端分离架构，可直接模拟AJAX请求调用数据接口。使用Python的requests库复制原始请求的Headers和参数：

import requests

headers = {
    'User-Agent': 'Mozilla/5.0',
    'X-Requested-With': 'XMLHttpRequest'
}
params = {'page': 1, 'size': 20}
response = requests.get('https://api.example.com/data', headers=headers, params=params)
print(response.json())

使用无头浏览器技术

对于复杂渲染场景，可采用Selenium或Playwright等工具控制浏览器：

from selenium import webdriver
from selenium.webdriver.chrome.options import Options

opts = Options()
opts.add_argument('--headless')
driver = webdriver.Chrome(options=opts)
driver.get('https://example.com')
ajax_content = driver.execute_script("return fetch('/api/data').then(r => r.json())")
print(ajax_content)

处理反爬机制

动态网站常设置反爬措施：

• 添加随机延迟避免高频请求
• 维护Cookies和Session
• 处理验证码（需第三方服务）
• 轮换User-Agent和代理IP

import time
import random

time.sleep(random.uniform(1, 3))
proxies = {'http': 'http://proxy.example.com:8080'}
requests.get(url, proxies=proxies)

数据解析与存储

根据响应格式选择解析方式：

• JSON数据直接使用json.loads()
• HTML片段用BeautifulSoup解析
• 二进制数据（如图片）需特殊处理

from bs4 import BeautifulSoup

soup = BeautifulSoup(ajax_html, 'html.parser')
items = soup.select('.data-item')

维护爬虫可持续性

定期检查API变更，建立异常处理机制。使用日志记录失败请求，实现自动重试：

import logging
from tenacity import retry, stop_after_attempt

@retry(stop=stop_after_attempt(3))
def safe_request(url):
    try:
        return requests.get(url, timeout=10)
    except Exception as e:
        logging.error(f"Request failed: {e}")
        raise

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