• requests爬取豆瓣top250电影信息


    1.爬取豆瓣top250电影信息
    - 第一页: https://movie.douban.com/top250?start=0&filter=
    - 第二页: https://movie.douban.com/top250?start=25&filter=
    - 第三页: https://movie.douban.com/top250?start=50&filter=
    - 第十页: https://movie.douban.com/top250?start=225&filter=

    2.-爬取步骤:
    - 1) 获取所有电影的主页url
    - 2) 往每一个主页发送请求,获取响应数据
    - 3) 解析并提取想要的数据(获取每一部电影的class为item的div)
    - 4) 根据每一部电影的div提取电影的: 详情页url、电影名字、电影评分、评价人数

    3.解析html数据

    """
    re.findall('正则匹配规则', '匹配文本', '匹配模式')
    
                re.findall(
                '<div class="item">.*?<a href="(.*?)">.*?<span class="title">(.*?)</span>.*?<span class="rating_num".*?>(.*?)</span>.*?<span>(.*?)人评价',
                response.text, re.S)
    
    
                - html:
                    <div class="item">.*?<a href="https://movie.douban.com/subject/1293908/">
                    .*?
                    <span class="title">城市之光</span>.*?<span class="rating_num" property="v:average">(.*?)</span>
                    .*?
                    <span>(.*?)人评价
    """
    
    
    import requests
    import re
    
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36 chrome-extension'
    }
    
    # 1.发送请求
    def get_html(url):
        response = requests.get(url,headers=headers)
        return response
    
    
    # 2.解析数据
    def parse_html(response):
        movie_list = re.findall(
                            '<div class="item">.*?<a href="(.*?)">.*?<span class="title">(.*?)</span>.*? <span class="rating_num" .*?>(.*?)</span>.*? <span>(.*?)人评价',
                            response.text,
                            re.S)
        return movie_list
    
    
    
    # 3.保存数据
    def save_data(movie_data, num):
        url, name, grade, count = movie_data
        movie = f"""
        电影排名: {num}
        电影详情: {url}
        电影名字: {name}
        电影评分: {grade}
        评分人数: {count}
        """
        print(movie)
    
        with open('douban.txt','a', encoding='utf-8') as f:
            f.write(movie)
    
    
    if __name__ == '__main__':
        number = 0
        num = 1
        for i in range(10):
            url = f'https://movie.douban.com/top250?start={number}&filter='
            number += 25
            response = get_html(url)
            movie_list = parse_html(response)
            for movie in movie_list:
                save_data(movie, num)
                num += 1
    
  • 相关阅读:
    谷歌机器学习
    Pycharm使用conda安装的环境
    HAN模型理解2
    HAN模型理解1
    RCNN
    深度CNN
    多通道CNN
    TextCNN
    词向量2
    词向量1.md
  • 原文地址:https://www.cnblogs.com/guapitomjoy/p/12127445.html
Copyright © 2020-2023  润新知