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Python爬虫实战之批量下载快手平台视频数据

2022-01-25 00:11松鼠爱吃饼干 Python

读万卷书不如行万里路,学的扎不扎实要通过实战才能看出来,本篇文章手把手带你批量下载快手平台视频数据,大家可以在过程中查缺补漏,看看自己掌握程度怎么样

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

Python爬虫实战之批量下载快手平台视频数据

Python爬虫实战之批量下载快手平台视频数据

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!!!')

Python爬虫实战之批量下载快手平台视频数据

 

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
      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)

Python爬虫实战之批量下载快手平台视频数据

Python爬虫实战之批量下载快手平台视频数据

耗时为57.7秒

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原文链接:https://pythonjx.blog.csdn.net/article/details/120654102

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