UniApp implements best practices for online error log monitoring and processing

UniApp implements best practices for online error log monitoring and processing

Introduction:
When developing and operating mobile applications, it is very important to detect and resolve errors in a timely manner. Error log monitoring and processing is an effective method that can help developers quickly find and fix problems in applications. UniApp is a cross-platform development framework. This article will introduce how to use UniApp to implement best practices for online error log monitoring and processing, and provide corresponding code examples.

1. Prerequisites for error log monitoring
   Before starting to implement error log monitoring, you need to ensure the following prerequisites:
2. Applications built using the UniApp development framework
3. The application is deployed through uniCloud or other cloud services
4. The backend has been configured with an environment for saving and querying error logs
5. Monitoring and reporting error logs
   UniApp provides the App.onError function. Used for global error monitoring. In the main file (main.js), we can add the following code snippet:

App.onError((err) => {
  // 将错误信息上报到后端日志服务
  uniCloud.callFunction({
    name: 'log',
    data: {
      message: err.message,
      stack: err.stack
    }
  }).then(res => {
    console.log('错误日志已上传');
  }).catch(err => {
    console.error('错误日志上传失败', err);
  });
});

In the above code, we call the backend log function through the uniCloud.callFunction function and pass the error information to the parameter form transfer. In the back-end log function, we can store error information in the database for subsequent query and analysis.

3. View error log
   UniApp provides a log query SDK, which can help developers easily view error logs. In the page where we need to view the error log, we can add the following code segment:

import { MpvueLogger } from 'uni-mplike';

const logger = new MpvueLogger('Your log service name');
logger.setFilter('error'); // 设置过滤规则，只显示错误日志

Page({
  data: {
    logs: []
  },
  onLoad() {
    this.loadLogs();
  },
  loadLogs() {
    const that = this;
    logger.queryLogs({
      success(res) {
        that.setData({
          logs: res.result || []
        });
      },
      fail(err) {
        console.error('日志查询失败', err);
      }
    });
  }
});

In the above code, we implement log query through the MpvueLogger class provided by the uni-mplike library. First, we need to create a Logger instance and set the corresponding log service name. Then, call the loadLogs method in the page's onLoad life cycle function to load the error log and display it on the page.

4. Error log analysis and processing
   After error log monitoring, we need to analyze and process the error log. Based on the error log content and stack information, we can better understand the cause of the error and make corresponding repairs and optimizations.

Sample code:
The following is an example code example of error log analysis and processing, which is used to analyze error stack information and provide corresponding solutions.

import { StackTrace } from 'stacktrace-js';

function analyzeError(stack) {
  StackTrace.fromError(new Error(stack)).then((frames) => {
    const errorStack = frames.map(frame => ({
      fileName: frame.getFileName(),
      functionName: frame.getFunctionName(),
      lineNumber: frame.getLineNumber(),
      columnNumber: frame.getColumnNumber()
    }));
    console.error('错误堆栈信息', errorStack);

    // 根据错误堆栈信息进行相应的解决方案
    // TODO: 添加处理逻辑
  });
}

// ...在错误监测的回调函数中调用analyzeError函数
App.onError((err) => {
  analyzeError(err.stack);
});

In the above code, we use the stacktrace-js library to parse the error stack information and display it in the console. Developers can analyze the cause of the error based on the error stack information and provide corresponding solutions.

Summary:
Through the above steps, we can implement online error log monitoring and processing of UniApp applications. From error log monitoring to reporting, and through the log query function provided by UniApp, developers can more comprehensively understand and maintain the running status of the application, improving application stability and user experience.

It should be noted that error log monitoring and processing is a continuous work. After the application is released, the error log needs to be checked regularly, and corresponding optimization and repairs should be made according to the actual situation.

Reference materials:

• UniApp official documentation: https://uniapp.dcloud.io/
• uni-mplike library: https://github.com /zhouyupeng/uni-mplike
• stacktrace-js library: https://www.stacktracejs.com/

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