How to use Go language for code logging and analysis

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Release: 2023-08-03 16:17:14
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How to use Go language for code logging and analysis

Introduction:
Logging is an indispensable part of software development. By recording key operating information, we can discover and solve problems in time, and also help with system maintenance and performance analysis. This article will introduce how to use Go language for code logging and analysis.

1. Logging

  1. Use the log package in the standard library
    The standard library of the Go language provides the log package for basic logging. Simple logging functions can be implemented by setting different prefixes, output locations and priorities.

Sample code:

package main import ( "log" "os" ) func main() { // 创建一个新的日志记录器 logger := log.New(os.Stdout, "INFO: ", log.Ldate|log.Ltime|log.Lshortfile) // 输出日志 logger.Println("This is a log message.") }
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  1. Using third-party libraries
    In addition to the log package in the standard library, there are many open source log libraries available in the Go language community choose. These libraries provide richer logging capabilities and more flexible configuration options that can be selected based on specific needs.

Commonly used log libraries include logrus, zap, zerolog, etc. The following takes logrus as an example to show how to use a third-party log library.

Sample code:

package main import ( log "github.com/sirupsen/logrus" ) func init() { // 设置日志格式为JSON格式 log.SetFormatter(&log.JSONFormatter{}) // 设置日志级别为info以上 log.SetLevel(log.InfoLevel) // 输出日志到标准输出 log.SetOutput(os.Stdout) } func main() { // 输出日志 log.Info("This is a log message.") }
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2. Log analysis

  1. Basic log analysis
    Using logs for system analysis can help find and solve problems, such as Find potential performance issues, discover unusual behavior, and more. You can use existing log analysis tools such as ELK Stack (Elasticsearch, Logstash, Kibana) or Splunk, etc.

Sample code:

# Logstash配置文件 input { file { path => "/var/log/golang/app.log" start_position => "beginning" } } filter { json { source => "message" } } output { elasticsearch { hosts => ["localhost:9200"] index => "golang-app-logs" } stdout { codec => rubydebug } }
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  1. Customized log analysis
    For some specific needs, we may need to customize the log analysis function. In Go language, you can use regular expressions or related libraries (such as regexp or github.com/logrusorgru/regexp2) to implement customized log analysis.

Sample code:

package main import ( "fmt" "regexp" ) func main() { // 日志消息 logMessage := `[2022-01-01 10:00:00] ERROR: This is an error message.` // 匹配时间和日志级别 r := regexp.MustCompile(`[(.*?)] (.*?):`) result := r.FindStringSubmatch(logMessage) // 输出结果 fmt.Println("Timestamp:", result[1]) fmt.Println("Level:", result[2]) }
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Conclusion:
This article introduces how to use Go language for code logging and analysis. Through the standard library or third-party libraries, we can easily implement basic logging functions. Using existing log analysis tools or custom analysis methods can help us better understand and optimize system performance. I hope this article can provide readers with some help in logging and analysis.

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