Use Python for website data crawling and video processing

Introduction

In the Internet age, we often need to obtain data from websites and analyze or process it. Sometimes, we also need to perform some operations on video data, such as editing, transcoding, compositing, etc. Python is a programming language very suitable for data analysis and video processing. It has many powerful libraries and tools to help us accomplish these tasks. This article will introduce the methods and steps of how to use Python's requests module to crawl website data and perform video processing.

overview

requests is a very popular and easy-to-use Python library, which allows us to send HTTP requests with simple code and get the response data of the website. We can use the requests module to crawl websites we are interested in, such as news, videos, pictures, etc., and save them locally or in the cloud. Then, we can use other Python libraries to process video data, such as moviepy, opencv, ffmpeg, etc. These libraries allow us to edit, transcode, synthesize, add special effects and other operations on the video to achieve the effect we want.

text

To use Python's requests module to crawl website data and perform video processing, we need the following steps:

1. Import the requests module and other required libraries
2. Set crawler proxy and request headers
3. Send HTTP request and get response data
4. Parse the response data and extract the video link
5. Download video files to local or cloud
6. Use libraries such as moviepy to process video files
7. Save or share processed video files

Below we detail the code and explanations for each step.

highlights

• The requests module allows us to send HTTP requests with simple code and get the response data of the website
• The requests module supports multiple HTTP methods, such as GET, POST, PUT, DELETE, etc.
• The requests module supports setting proxy, request header, parameters, timeout and other options, increasing the flexibility and security of crawlers
• The requests module supports automatic processing of encoding, JSON, Cookie and other issues, improving the efficiency and quality of crawlers
• Libraries such as moviepy allow us to edit, transcode, synthesize, add special effects and other operations on videos to achieve the effects we want
• Libraries such as moviepy support multiple video formats, such as MP4, AVI, MOV, etc.
• Libraries such as moviepy support a variety of video operations, such as cropping, rotating, scaling, merging, splitting, etc.

the case

Suppose we want to crawl some animation videos from station B, edit and synthesize them to generate a new video. We can achieve this with the following code:

# 导入所需库
import requests
import re
import os
import threading
from moviepy.editor import *

# 亿牛云 爬虫代理加强版 代理服务器信息
proxyHost = "www.16yun.cn"
proxyPort = "3111"
proxyUser = "16YUN"
proxyPass = "16IP"

# 构建代理字典
proxies = {
    
    
    "http": f"http://{
      
      proxyUser}:{
      
      proxyPass}@{
      
      proxyHost}:{
      
      proxyPort}",
    "https": f"https://{
      
      proxyUser}:{
      
      proxyPass}@{
      
      proxyHost}:{
      
      proxyPort}"
}

# 设置请求头
headers = {
    
    
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/92.0.4515.131 Safari/537.36"
}

# 定义视频文件保存路径和处理后视频路径
video_path = "videos"
output_path = "output"

# 下载视频函数
def download_video(video_url, filename):
    video_data = requests.get(video_url, headers=headers, proxies=proxies).content
    video_file = os.path.join(video_path, filename)
    with open(video_file, "wb") as f:
        f.write(video_data)
    print(f"下载 {
      
      filename} 完成")

# 处理视频函数
def process_video(video_name):
    video_file = os.path.join(video_path, video_name)
    # 使用VideoFileClip方法，读取视频文件并进行剪辑，只保留前10秒
    clip = VideoFileClip(video_file).subclip(0, 10)
    return clip

# 主函数
def main():
    # 定义B站视频网址
    url = "https://www.bilibili.com/video/BV1Xy4y1x7aC"
    # 发送GET请求，获取网页源代码
    response = requests.get(url, headers=headers, proxies=proxies)
    
    # 判断请求是否成功
    if response.status_code == 200:
        print("请求成功")
        html = response.text
        # 使用正则表达式匹配视频链接
        pattern = re.compile(r'"baseUrl":"(.*?)"')
        video_urls = pattern.findall(html)
        
        # 创建视频文件保存路径
        if not os.path.exists(video_path):
            os.mkdir(video_path)
        
        threads = []
        # 遍历视频链接列表，使用多线程下载视频
        for i, video_url in enumerate(video_urls):
            video_name = f"{
      
      i+1}.mp4"
            thread = threading.Thread(target=download_video, args=(video_url, video_name))
            threads.append(thread)
            thread.start()
        
        # 等待所有线程完成
        for thread in threads:
            thread.join()
        
        # 创建处理后视频文件保存路径
        if not os.path.exists(output_path):
            os.mkdir(output_path)
        
        clips = []
        # 遍历视频链接列表，处理视频并添加到剪辑列表
        for i in range(len(video_urls)):
            video_name = f"{
      
      i+1}.mp4"
            clip = process_video(video_name)
            clips.append(clip)
        
        # 合并剪辑列表中的视频并写入输出文件
        output_clip = concatenate_videoclips(clips)
        output_name = "output.mp4"
        output_file = os.path.join(output_path, output_name)
        output_clip.write_videofile(output_file)
        
        print("处理完成")
    else:
        print("请求失败")

# 确保在主程序中运行
if __name__ == "__main__":
    main()

epilogue

This article introduces the method and steps of how to use Python's requests module to crawl website data and perform video processing. We can use the requests module to crawl the websites we are interested in and save them locally or in the cloud. Then, we can use libraries such as moviepy to process the video data to achieve the desired effect. These methods and steps are very simple and easy to use, and only need a few lines of code to complete.