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文章目录
- 书籍推荐
- 正则抓取腾讯动漫数据
- Flask展示数据
书籍推荐
如果你对Python网络爬虫感兴趣，强烈推荐你阅读《Python网络爬虫入门到实战》。这本书详细介绍了Python网络爬虫的基础知识和高级技巧，是每位爬虫开发者的必读之作。详细介绍见👉： 《Python网络爬虫入门到实战》 书籍介绍
正则抓取腾讯动漫数据
import requests
import re
import threading
from queue import Queuedef format_html(html):li_pattern = re.compile('<li class="ret-search-item clearfix">[\s\S]+?</li>')title_pattern = re.compile('title="(.*?)"')img_src_pattern = re.compile('data-original="(.*?)"')update_pattern = re.compile('<span class="mod-cover-list-text">(.*?)</span>')tags_pattern = re.compile('<span href="/Comic/all/theme/.*?" target="_blank">(.*?)</span>')popularity_pattern = re.compile('<span>人气：<em>(.*?)</em></span>')items = li_pattern.findall(html)for item in items:title = title_pattern.search(item).group(1)img_src = img_src_pattern.search(item).group(1)update_info = update_pattern.search(item).group(1)tags = tags_pattern.findall(item)popularity = popularity_pattern.search(item).group(1)data_queue.put(f'{title},{img_src},{update_info},{"#".join(tags)},{popularity}\n')def run(index):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/537.36'}response = requests.get(f"https://ac.qq.com/Comic/index/page/{index}", headers=headers)html = response.textformat_html(html)except Exception as e:print(f"Error occurred while processing page {index}: {e}")finally:semaphore.release()if __name__ == "__main__":data_queue = Queue()semaphore = threading.BoundedSemaphore(5)lst_record_threads = []for index in range(1, 3):print(f"正在抓取{index}")semaphore.acquire()t = threading.Thread(target=run, args=(index,))t.start()lst_record_threads.append(t)for rt in lst_record_threads:rt.join()with open("./qq_comic_data.csv", "a+", encoding="gbk") as f:while not data_queue.empty():f.write(data_queue.get())print("数据爬取完毕")Flask展示数据
上面能够实现爬取数据，但是我希望展示在前端。
main.py代码如下：
# coding= gbk
from flask import Flask, render_template
import csvapp = Flask(__name__)def read_data_from_csv():with open("qq_comic_data.csv", "r", encoding="utf-8") as f:reader = csv.reader(f)data = list(reader)[1:] # 跳过标题行# 统一转换人气数据为浮点数（单位：亿）for row in data:popularity = row[4]if '亿' in popularity:row[4] = float(popularity.replace('亿', ''))elif '万' in popularity:row[4] = float(popularity.replace('万', '')) / 10000 # 将万转换为亿# 按人气排序并保留前10条记录data.sort(key=lambda x: x[4], reverse=True)return data[:10]@app.route('/')
def index():comics = read_data_from_csv()return render_template('index.html', comics=comics)if __name__ == '__main__':app.run(debug=True)templates/index.html如下：
<!DOCTYPE html>
<html lang="en">
<head><meta charset="UTF-8"><title>漫画信息</title><style>body {font-family: Arial, sans-serif;background-color: #f4f4f4;color: #333;line-height: 1.6;padding: 20px;}.container {width: 80%;margin: auto;overflow: hidden;}h1 {text-align: center;color: #333;}.comic {background: #fff;margin-bottom: 20px;padding: 15px;border-radius: 10px;box-shadow: 0 5px 10px rgba(0,0,0,0.1);}.comic h2 {margin-top: 0;}.comic p {line-height: 1.25;}.comic:nth-child(even) {background: #f9f9f9;}</style>
</head>
<body><div class="container"><h1>人气前10的漫画</h1>{% for comic in comics %}<div class="comic"><h2>{{ comic[0] }}</h2><p><strong>更新信息：</strong>{{ comic[2] }}</p><p><strong>类型：</strong>{{ comic[3] }}</p><p><strong>人气：</strong>{{ comic[4] }}</p></div>{% endfor %}</div>
</body>
</html>效果如下：
