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Go language is becoming more and more popular in the field of Internet development due to its high concurrency, high efficiency and other characteristics, and log processing is an essential link. In the Go language, there are many log processing libraries to choose from. This article will introduce some of the commonly used ones.
The log package that comes with the Go language is a simple log library that is very convenient to use. It supports output to console, file, network, etc. You can set the log prefix, output time format, etc., and also support the output of different levels of logs.
Sample code:
package main import ( "log" "os" ) func main() { // 设置日志输出到标准输出 log.SetOutput(os.Stdout) // 设置日志前缀 log.SetPrefix("[INFO] ") // 设置日志输出的时间格式 log.SetFlags(log.Ldate | log.Ltime) // 输出日志 log.Println("This is a log message.") }
zap is a fast and stable log library, open sourced by Uber, and is currently the most popular log One of the libraries. It features high performance, low overhead, and structured logging. For the features of the zap library, please refer to the official documentation https://pkg.go.dev/go.uber.org/zap.
Sample code:
package main import ( "go.uber.org/zap" "go.uber.org/zap/zapcore" ) func main() { // 配置 zap config := zap.NewDevelopmentConfig() config.EncoderConfig.EncodeLevel = zapcore.CapitalColorLevelEncoder logger, _ := config.Build() // 输出日志 logger.Info("This is a log message.") }
glog is a logging library developed by Google, which can handle high concurrency situations well logging. It supports output to a file, standard output, or sent over the network to a remote server. glog supports the use of multiple backends for logging and can correctly format log information.
Sample code:
package main import "github.com/golang/glog" func main() { // 配置 glog glog.CopyStandardLogTo("INFO") // 输出日志 glog.Info("This is a log message.") }
logrus is a very popular logging library. It provides many features such as formatting logs, outputting JSON logs, processing structured logs, etc. logrus is also able to easily integrate with other services such as Sentry, Fluentd, etc. In addition, logrus also provides many hooks to add some operations before and after log output, such as sending emails, writing to the database, etc.
Sample code:
package main import ( "github.com/sirupsen/logrus" ) func main() { // 配置 logrus,设置输出格式为 JSON logrus.SetFormatter(&logrus.JSONFormatter{}) // 输出日志 logrus.WithFields(logrus.Fields{ "key": "value", }).Info("This is a log message.") }
zerolog is another popular logging library that not only has high performance and low memory footprint, but also A variety of output methods and configuration options are provided. Zerolog also supports structured logging and provides an efficient mode for processing log data.
Sample code:
package main import ( "github.com/rs/zerolog" "github.com/rs/zerolog/log" ) func main() { // 配置 zerolog zerolog.TimeFieldFormat = zerolog.TimeFormatUnix // 输出日志 log.Info().Str("key", "value").Msg("This is a log message.") }
The above is an introduction to several log processing libraries commonly used in the Go language. It is very important to choose a library that suits you based on actual needs and scenarios. Each library has its own special features and can be selected according to the actual situation.
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