Day:005 | Python爬虫：高效数据抓取的编程技术（爬虫效率）

import requests
from bs4 import BeautifulSoup
import time
 
def get_html(url):
    try:
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
        response = requests.get(url, headers=headers, timeout=30)
        response.raise_for_status()
        response.encoding = response.apparent_encoding
        return response.text
    except Exception as e:
        print(f"An error occurred: {e}")
 
def parse_html(html):
    soup = BeautifulSoup(html, 'html.parser')
    return soup.find_all('div', class_='post-text')[0].text
 
def main():
    start_time = time.time()
    url = 'https://www.example.com/some-article'
    html = get_html(url)
    text = parse_html(html)
    print(f"The article text is: {text}")
    end_time = time.time()
    execution_time = end_time - start_time
    print(f"Execution time: {execution_time} seconds")
 
if __name__ == "__main__":
    main()

这段代码展示了如何使用Python的requests库和BeautifulSoup库高效地抓取网页数据。同时，代码中加入了异常处理和请求头信息，模拟了一个正规的网络请求，提高了爬虫的合法性和成功率。通过time模块，代码还可以统计爬取数据的耗时，为爬虫效率的评估提供数据支持。