How to use Python to connect to the cloud interface to implement the video cutting function

How to use Python to connect to Youpaiyun interface to implement video cutting function

Youpaiyun is a well-known domestic cloud storage and content distribution network service provider, providing a wealth of cloud storage services. This article will introduce how to use Python to write code to connect to the cloud interface to implement the video cutting function.

First of all, we need to register an account and create a project on Youpaiyun’s official website. After creating a project, you can obtain the project's service name, operator account, and operator password. This information will be used later in the code.

Next, we need to install the Python development environment locally and install the Python SDK of Youpaiyun. Youpaiyun's Python SDK is an encapsulation of Youpaiyun's RESTful API, which facilitates our development using Python.

The following is a sample code that shows how to use Python to connect to the cloud interface to implement the video cutting function:

import upyun
import requests

# 配置又拍云的服务名、操作员账号和操作员密码
service_name = 'your_service_name'
operator_name = 'your_operator_name'
operator_password = 'your_operator_password'

# 初始化又拍云的Python SDK
up = upyun.UpYun(service_name, operator_name, operator_password)

# 在又拍云创建一个保存剪切后视频的空间
up.mkdir('/cut_videos')

# 读取本地待剪切的视频文件
local_file = 'your_local_video_file_path'
with open(local_file, 'rb') as f:
    file_data = f.read()

# 上传视频文件到又拍云空间
up.put('/cut_videos/original_video.mp4', file_data)

# 视频剪切操作
cut_url = 'http://p0.api.upyun.com/' + service_name + '/cut_videos/original_video.mp4'  # 剪切视频的URL
cut_saveas = '/cut_videos/cut_video.mp4'  # 剪切后保存的路径
cut_slices = '00:00:10-00:00:20'  # 剪切的时间段

# 发起剪切请求
cut_params = {
    'bucket': 'your_bucket_name',
    'save_as': cut_saveas,
    'slices': cut_slices
}
response = requests.post(cut_url, data=cut_params, auth=(operator_name, operator_password))

# 打印剪切结果
print(response.json())

In this sample code, first we initialize it through the upyun.UpYun class Youpaiyun’s Python SDK. Then use the above Youpaiyun account information for identity verification.

Then, we created a directory in Youpai Cloud Space to store the cut video files. Next, we read the local video files that need to be cut and upload them to Youpai Cloud Space.

After the upload is completed, we use the URL of the cut video, the path saved after cutting, and the time period of the cut to construct a cutting request and send it to the Youpai cloud server.

Finally, we print the cutting results.

Of course, this is just a simple example. Youpaiyun provides a rich API interface, which can perform more operations and function expansion. By reading Youpaiyun's official API documentation, we can call other interfaces to complete more complex operations according to actual needs.

To sum up, by using Python to connect to the cloud interface, we can easily implement the video cutting function. Whether uploading files to cloud storage space or performing cutting operations, the flexibility of Python and the SDK provided by Youpai Cloud make development simpler and more efficient.

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