Python and Youpaiyun interface docking tutorial: implementing image compression function

Tutorial on connecting Python and Youpaiyun interface: Implementing image compression function

In today’s Internet era, pictures are an indispensable part of our daily lives. However, because high-definition image files are large, they not only occupy storage space, but also affect the loading speed of web pages, giving users a bad experience. Therefore, image compression has become an important technical requirement.

As a well-known cloud storage service provider, Youpaiyun provides a wealth of image processing interfaces, including image compression functions. This article will introduce how to use Python to connect with Youpai Cloud interface to implement image compression function.

1. Youpaiyun interface and key acquisition
Before using Youpaiyun interface, we need to register a Youpaiyun account and create a new service. After creating a service, you can obtain the service's operation key. Here we need to obtain the Service Secret (service private key) and Service Name (service name) in the operation key.

2. Install dependent libraries
In Python, we can use the requests library to make HTTP requests. Through this library, we can connect to the Youpai Cloud interface. If the requests library is not installed, you can use the following command to install it:

pip install requests

3. Writing code examples
The following is a sample code that implements the image compression function:

import requests
import hashlib
import time

# 服务私钥
service_secret = "your_service_secret"
# 服务名称
service_name = "your_service_name"
# 图片地址
image_url = "http://example.com/image.jpg"
# 压缩后图片地址
compressed_image_url = "http://example.com/compressed_image.jpg"

# 构建签名字符串
timestamp = str(int(time.time()))
signature_str = service_secret + timestamp + service_name
md5 = hashlib.md5()
md5.update(signature_str.encode("utf-8"))
signature = md5.hexdigest()

# 构建请求头
headers = {
    "content-type": "application/json",
    "Authorization": service_name + ":" + signature + ":" + timestamp
}

# 构建请求参数
params = {
    "source": image_url,
    "tasks": [
        {
            "type": "resize",
            "params": {
                "mode": "scale",
                "width": 800,
                "height": 600
            }
        }
    ],
    "save_as": compressed_image_url
}

# 发送POST请求
response = requests.post("http://api2.upyun.com/your_service_name/tasks", json=params, headers=headers)

# 打印返回结果
print(response.text)

The above code Implemented a simple image compression function. Before using, replace your_service_secret, your_service_name, http://example.com/image.jpg and http:// in the code example.com/compressed_image.jpg are the service private key, service name, original image link and compressed image link of Youpai Cloud service respectively.

4. Code Analysis
In this example, we first obtain the URL of the image and the URL of the compressed image, and construct a signature string for authentication. Then, we use the requests library to send a POST request to Youpaiyun's interface, which contains the compression parameters and storage address of the image. Finally, the return result from the Youpai Cloud interface is received and printed.

It should be noted that when using Youpaiyun interface, the URL requested by the API is http://api2.upyun.com/your_service_name/tasks, where your_service_name needs to be replaced with your own service name.

5. Summary
This article introduces how to use Python to connect with Youpai Cloud interface to implement image compression function. By mastering this technique, we can help us improve the loading speed of web pages and improve user experience. At the same time, Youpaiyun's interface also supports other image processing functions, such as cropping, watermarking, etc. I hope this article can be helpful to everyone in image processing.

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