文章目录
- [1. 常用库安装](#1. 常用库安装)
- [2. 基础爬虫开发](#2. 基础爬虫开发)
-
- [2.1. 使用 requests 获取网页内容](#2.1. 使用 requests 获取网页内容)
- [2.2. 使用 BeautifulSoup 解析 HTML](#2.2. 使用 BeautifulSoup 解析 HTML)
- [2.3. 处理登录与会话](#2.3. 处理登录与会话)
- [3. 进阶爬虫开发](#3. 进阶爬虫开发)
-
- [3.1. 处理动态加载内容(Selenium)](#3.1. 处理动态加载内容(Selenium))
- [3.2. 使用Scrapy框架](#3.2. 使用Scrapy框架)
- [3.3. 分布式爬虫(Scrapy-Redis)](#3.3. 分布式爬虫(Scrapy-Redis))
- [4. 爬虫优化与反反爬策略](#4. 爬虫优化与反反爬策略)
-
- [4.1. 常见反爬机制及应对](#4.1. 常见反爬机制及应对)
- [4.2. 代理IP使用示例](#4.2. 代理IP使用示例)
- [4.3. 随机延迟与请求头](#4.3. 随机延迟与请求头)
BeautifulSoup 官方文档
https://beautifulsoup.readthedocs.io/zh-cn/v4.4.0/
https://cloud.tencent.com/developer/article/1193258
https://blog.csdn.net/zcs2312852665/article/details/144804553
参考:
https://blog.51cto.com/haiyongblog/13806452
1. 常用库安装
bash
pip install requests beautifulsoup4 scrapy selenium pandas
2. 基础爬虫开发
2.1. 使用 requests 获取网页内容
python
import requests
url = 'https://top.baidu.com/board?tab=realtime'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
}
response = requests.get(url, headers=headers)
print(response.status_code) # 200表示成功
print(response.text[:500]) # 打印前500个字符

2.2. 使用 BeautifulSoup 解析 HTML
python
from bs4 import BeautifulSoup
html_doc = """
<html><head><title>测试页面</title></head>
<body>
<p class="title"><b>示例网站</b></p>
<p class="story">这是一个示例页面
<a href="http://example.com/1" class="link" id="link1">链接1</a>
<a href="http://example.com/2" class="link" id="link2">链接2</a>
</p>
"""
soup = BeautifulSoup(html_doc, 'html.parser')
# 获取标题
print(soup.title.string)
# 获取所有链接
for link in soup.find_all('a'):
print(link.get('href'), link.string)
# 通过CSS类查找
print(soup.find('p', class_='title').text)
2.3. 处理登录与会话
python
import requests
login_url = 'https://example.com/login'
target_url = 'https://example.com/dashboard'
session = requests.Session()
# 登录请求
login_data = {
'username': 'your_username',
'password': 'your_password'
}
response = session.post(login_url, data=login_data)
if response.status_code == 200:
# 访问需要登录的页面
dashboard = session.get(target_url)
print(dashboard.text)
else:
print('登录失败')
3. 进阶爬虫开发
3.1. 处理动态加载内容(Selenium)
python
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from webdriver_manager.chrome import ChromeDriverManager
# 设置无头浏览器
options = webdriver.ChromeOptions()
options.add_argument('--headless') # 无界面模式
options.add_argument('--disable-gpu')
# 自动下载chromedriver
driver = webdriver.Chrome(service=Service(ChromeDriverManager().install()), options=options)
url = 'https://dynamic-website.com'
driver.get(url)
# 等待元素加载(隐式等待)
driver.implicitly_wait(10)
# 获取动态内容
dynamic_content = driver.find_element(By.CLASS_NAME, 'dynamic-content')
print(dynamic_content.text)
driver.quit()
3.2. 使用Scrapy框架
python
# 创建Scrapy项目
# scrapy startproject example_project
# cd example_project
# scrapy genspider example example.com
# 示例spider代码
import scrapy
class ExampleSpider(scrapy.Spider):
name = 'example'
allowed_domains = ['example.com']
start_urls = ['http://example.com/']
def parse(self, response):
# 提取数据
title = response.css('title::text').get()
links = response.css('a::attr(href)').getall()
yield {
'title': title,
'links': links
}
# 运行爬虫
# scrapy crawl example -o output.json
3.3. 分布式爬虫(Scrapy-Redis)
python
# settings.py配置
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
REDIS_URL = 'redis://localhost:6379'
# spider代码
from scrapy_redis.spiders import RedisSpider
class MyDistributedSpider(RedisSpider):
name = 'distributed_spider'
redis_key = 'spider:start_urls'
def parse(self, response):
# 解析逻辑
pass
4. 爬虫优化与反反爬策略
4.1. 常见反爬机制及应对
User-Agent检测 :随机切换User-Agent
IP限制:使用代理IP池
验证码:OCR识别或打码平台
行为分析:模拟人类操作间隔
JavaScript渲染:使用Selenium或Pyppeteer
4.2. 代理IP使用示例
python
import requests
proxies = {
'http': 'http://proxy_ip:port',
'https': 'https://proxy_ip:port'
}
try:
response = requests.get('https://example.com', proxies=proxies, timeout=5)
print(response.text)
except Exception as e:
print(f'请求失败: {e}')
4.3. 随机延迟与请求头
python
import random
import time
import requests
from fake_useragent import UserAgent
ua = UserAgent()
def random_delay():
time.sleep(random.uniform(0.5, 2.5))
def get_with_random_headers(url):
headers = {
'User-Agent': ua.random,
'Accept-Language': 'en-US,en;q=0.5',
'Referer': 'https://www.google.com/'
}
random_delay()
return requests.get(url, headers=headers)