Teach you step by step how to use Python to connect to Qiniu Cloud interface to achieve video transcoding

Teach you step-by-step how to use Python to connect to Qiniu Cloud interface to achieve video transcoding

With the continuous development of the Internet, video has become an important way for people to transmit information, entertainment, and learning. In our daily lives, we often encounter situations where we need to convert or compress videos. Qiniu Cloud, as a professional cloud storage and cloud processing service provider, provides developers with comprehensive video transcoding solutions. This article will introduce how to use Python language to connect to Qiniu Cloud interface to realize the video transcoding function.

Step 1: Install dependencies

Before we start, we need to install some necessary software packages. First, we need to install the Python development environment, and then we need to install Qiniu Cloud’s Python SDK.

Use the command line to install the Python SDK:

pip install qiniu

Step 2: Introduce dependency packages

Import the required Python packages, including qiniu and json.

import qiniu
import json

Step 3: Configure key information

In order to use Qiniu Cloud’s services, we need to provide access key and secret key. We can create a new key pair on the Qiniu Cloud console.

access_key = 'your_access_key'
secret_key = 'your_secret_key'

Step 4: Create a transcoding preset

On Qiniu Cloud, we can preset some transcoding parameters for direct use during transcoding. By creating a preset, we can specify the target format, resolution, bitrate, etc. for transcoding.

pfop = qiniu.fop.Pfop(access_key, secret_key)
preset_name = 'your_preset_name'  # 预设名称
preset = "avthumb/mp4/s/640x480/vb/1.25m"  # 预设内容
# 创建预设
pfop.create_preset(preset_name, preset)

Step 5: Initiate a transcoding request

We can initiate a transcoding request by constructing a persistence operation (pfop) object. In the transcoding request, we need to specify the URL of the source video and the callback URL of the persistence processing result.

# 源视频URL
src_url = 'your_src_url'
# 目标存储空间和文件名
bucket = 'your_bucket'
key = 'your_key'
# 转码结果回调URL
pipeline = 'your_pipeline'
notify_url = 'your_notify_url'

# 发起转码请求
ret, info = pfop.execute(bucket, key, src_url, pipeline, notify_url=notify_url)
print(info)

Step 6: Process the transcoding results

We can process the transcoding results by listening to the callback URL of the transcoding request. When the transcoding is completed, Qiniu Cloud will send the processing results to the specified callback URL in POST mode.

from flask import Flask, request

app = Flask(__name__)

@app.route('/get_notify', methods=['POST'])
def get_notify():
    # 获取转码结果
    res = json.loads(request.data.decode('utf-8'))
    print(res)
    return 'success'

if __name__ == '__main__':
    app.run(port=8080)

The above are the detailed steps for using Python to connect to the Qiniu Cloud interface to implement video transcoding. For more parameters and advanced features of Qiniu Cloud’s video transcoding function, please refer to the official documentation. I hope this article can be helpful to everyone in video transcoding.

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