Python爬虫实战之批量下载快手平台视频数据

知识点

• requests
• json
• re
• pprint

开发环境：

• 版 本：anaconda5.2.0（python3.6.5）
• 编辑器：pycharm

案例实现步骤：

一. 数据来源分析

(只有当你找到数据来源的时候, 才能通过代码实现)

1.确定需求 (要爬取的内容是什么?)

• 爬取某个关键词对应的视频 保存mp4

2.通过开发者工具进行抓包分析 分析数据从哪里来的(找出真正的数据来源)?

• 静态加载页面
  
• 笔趣阁为例
  
• 动态加载页面
  
• 开发者工具抓数据包

【付费VIP完整版】只要看了就能学会的教程，80集Python基础入门视频教学

点这里即可免费在线观看

二. 代码实现过程

• 找到目标网址
• 发送请求 get post
• 解析数据 （获取视频地址 视频标题）
• 发送请求 请求每个视频地址
• 保存视频

对于本篇文章有疑问，或者想要Python相关资料的同学也可以点这里 今天的目标

三. 单个视频

导入所需模块

import json
import requests
import re

发送请求

data = {
    'operationName': "visionSearchPhoto",
    'query': "query visionSearchPhoto($keyword: String, $pcursor: String, $searchSessionId: String, $page: String, $webPageArea: String) {\n  visionSearchPhoto(keyword: $keyword, pcursor: $pcursor, searchSessionId: $searchSessionId, page: $page, webPageArea: $webPageArea) {\n    result\n    llsid\n    webPageArea\n    feeds {\n      type\n      author {\n        id\n        name\n        following\n        headerUrl\n        headerUrls {\n          cdn\n          url\n          __typename\n        }\n        __typename\n      }\n      tags {\n        type\n        name\n        __typename\n      }\n      photo {\n        id\n        duration\n        caption\n        likeCount\n        realLikeCount\n        coverUrl\n        photoUrl\n        liked\n        timestamp\n        expTag\n        coverUrls {\n          cdn\n          url\n          __typename\n        }\n        photoUrls {\n          cdn\n          url\n          __typename\n        }\n        animatedCoverUrl\n        stereoType\n        videoRatio\n        __typename\n      }\n      canAddComment\n      currentPcursor\n      llsid\n      status\n      __typename\n    }\n    searchSessionId\n    pcursor\n    aladdinBanner {\n      imgUrl\n      link\n      __typename\n    }\n    __typename\n  }\n}\n",
    'variables': {
        'keyword': '张三',
        'pcursor': ' ',
        'page': "search",
        'searchSessionId': "MTRfMjcwOTMyMTQ2XzE2Mjk5ODcyODQ2NTJf5oWi5pGHXzQzMQ"
    }

response = requests.post('https://www.kuaishou.com/graphql', data=data)

加请求头

headers = {
    # Content-Type（内容类型）的格式有四种(对应data)：分别是
    # 爬虫基础/xml: 把xml作为一个文件来传输
    # multipart/form-data: 用于文件上传
    'content-type': 'application/json',
    # 用户身份标识
    'Cookie': 'kpf=PC_WEB; kpn=KUAISHOU_VISION; clientid=3; did=web_721a784b472981d650bcb8bbc5e9c9c2',
    # 浏览器信息 （伪装成浏览器发送请求）
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36',
}

json序列化操作

# json数据交换格式, 在JSON出现之前, 大家一直用XML来传递数据
# 由于各个语言都支持 JSON ，JSON 又支持各种数据类型，所以JSON常用于我们日常的 HTTP 交互、数据存储等。
# 将python对象编码成Json字符串
data = json.dumps(data)
json_data = requests.post('https://www.kuaishou.com/graphql', headers=headers, data=data).json()

字典取值

feeds = json_data['data']['visionSearchPhoto']['feeds']
for feed in feeds:
    caption = feed['photo']['caption']
    photoUrl = feed['photo']['photoUrl']
    new_title = re.sub(r'[/\:*?<>/\n] ', '-', caption)

再次发送请求

resp = requests.get(photoUrl).content

保存数据

with open('video\\' + title + '.mp4', mode='wb') as f:
    f.write(resp)
print(title, '爬取成功！！！')

四. 翻页爬取

导入模块

import concurrent.futures
import time

发送请求

def get_json(url, data):
    response = requests.post(url, headers=headers, data=data).json()
    return response

修改标题

def change_title(title):
    # windows系统文件命名 不能含有特殊字符...
    # windows文件命名 字符串不能超过 256...
    new_title = re.sub(r'[/\\|:?<>"*\n]', '_', title)
    if len(new_title) > 50:
        new_title = new_title[:10]
    return new_title

数据提取

def parse(json_data):
    data_list = json_data['data']['visionSearchPhoto']['feeds']
    info_list = []
    for data in data_list:
        # 提取标题
        title = data['photo']['caption']
        new_title = change_title(title)
        url_1 = data['photo']['photoUrl']
        info_list.append([new_title, url_1])
    return info_list

保存数据

def save(title, url_1):
    resp = requests.get(url_1).content
    with open('video\\' + title + '.mp4', mode='wb') as f:
        f.write(resp)
    print(title, '爬取成功！！！')

主函数 调动所有的函数

def run(url, data):
    """主函数 调动所有的函数"""
    json_data = get_json(url, data)
    info_list = parse(json_data)
    for title, url_1 in info_list:
        save(title, url_1)

if __name__ == '__main__':
    start_time = time.time()
    with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
        for page in range(1, 5):
            url = 'https://www.kuaishou.com/graphql'
            data = {
                'operationName': "visionSearchPhoto",
                'query': "query visionSearchPhoto($keyword: String, $pcursor: String, $searchSessionId: String, $page: String, $webPageArea: String) {\n  visionSearchPhoto(keyword: $keyword, pcursor: $pcursor, searchSessionId: $searchSessionId, page: $page, webPageArea: $webPageArea) {\n    result\n    llsid\n    webPageArea\n    feeds {\n      type\n      author {\n        id\n        name\n        following\n        headerUrl\n        headerUrls {\n          cdn\n          url\n          __typename\n        }\n        __typename\n      }\n      tags {\n        type\n        name\n        __typename\n      }\n      photo {\n        id\n        duration\n        caption\n        likeCount\n        realLikeCount\n        coverUrl\n        photoUrl\n        liked\n        timestamp\n        expTag\n        coverUrls {\n          cdn\n          url\n          __typename\n        }\n        photoUrls {\n          cdn\n          url\n          __typename\n        }\n        animatedCoverUrl\n        stereoType\n        videoRatio\n        __typename\n      }\n      canAddComment\n      currentPcursor\n      llsid\n      status\n      __typename\n    }\n    searchSessionId\n    pcursor\n    aladdinBanner {\n      imgUrl\n      link\n      __typename\n    }\n    __typename\n  }\n}\n",
                'variables': {
                    'keyword': '曹芬',
                    # 'keyword': keyword,
                    'pcursor': str(page),
                    'page': "search",
                    'searchSessionId': "MTRfMjcwOTMyMTQ2XzE2Mjk5ODcyODQ2NTJf5oWi5pGHXzQzMQ"
                }
            }
            data = json.dumps(data)
            executor.submit(run, url, data, )
    print('一共花费了：', time.time()-start_time)

耗时为57.7秒

到此这篇关于Python爬虫实战之批量下载快手平台视频数据的文章就介绍到这了,更多相关Python 批量下载快手视频内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家！