Structured, pluggable logging for Go.
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README.md

Logrus :walrus: Build Status GoDoc

Seeing weird case-sensitive problems? See this issue. This change has been reverted. I apologize for causing this. I greatly underestimated the impact this would have. Logrus strives for stability and backwards compatibility and failed to provide that.

Logrus is a structured logger for Go (golang), completely API compatible with the standard library logger. [Godoc][godoc]. Please note the Logrus API is not yet stable (pre 1.0). Logrus itself is completely stable and has been used in many large deployments. The core API is unlikely to change much but please version control your Logrus to make sure you aren't fetching latest master on every build.

Nicely color-coded in development (when a TTY is attached, otherwise just plain text):

Colored

With log.SetFormatter(&log.JSONFormatter{}), for easy parsing by logstash or Splunk:

{"animal":"walrus","level":"info","msg":"A group of walrus emerges from the
ocean","size":10,"time":"2014-03-10 19:57:38.562264131 -0400 EDT"}

{"level":"warning","msg":"The group's number increased tremendously!",
"number":122,"omg":true,"time":"2014-03-10 19:57:38.562471297 -0400 EDT"}

{"animal":"walrus","level":"info","msg":"A giant walrus appears!",
"size":10,"time":"2014-03-10 19:57:38.562500591 -0400 EDT"}

{"animal":"walrus","level":"info","msg":"Tremendously sized cow enters the ocean.",
"size":9,"time":"2014-03-10 19:57:38.562527896 -0400 EDT"}

{"level":"fatal","msg":"The ice breaks!","number":100,"omg":true,
"time":"2014-03-10 19:57:38.562543128 -0400 EDT"}

With the default log.SetFormatter(&log.TextFormatter{}) when a TTY is not attached, the output is compatible with the logfmt format:

time="2015-03-26T01:27:38-04:00" level=debug msg="Started observing beach" animal=walrus number=8
time="2015-03-26T01:27:38-04:00" level=info msg="A group of walrus emerges from the ocean" animal=walrus size=10
time="2015-03-26T01:27:38-04:00" level=warning msg="The group's number increased tremendously!" number=122 omg=true
time="2015-03-26T01:27:38-04:00" level=debug msg="Temperature changes" temperature=-4
time="2015-03-26T01:27:38-04:00" level=panic msg="It's over 9000!" animal=orca size=9009
time="2015-03-26T01:27:38-04:00" level=fatal msg="The ice breaks!" err=&{0x2082280c0 map[animal:orca size:9009] 2015-03-26 01:27:38.441574009 -0400 EDT panic It's over 9000!} number=100 omg=true
exit status 1

Example

The simplest way to use Logrus is simply the package-level exported logger:

package main

import (
  log "github.com/Sirupsen/logrus"
)

func main() {
  log.WithFields(log.Fields{
    "animal": "walrus",
  }).Info("A walrus appears")
}

Note that it's completely api-compatible with the stdlib logger, so you can replace your log imports everywhere with log "github.com/Sirupsen/logrus" and you'll now have the flexibility of Logrus. You can customize it all you want:

package main

import (
  "os"
  log "github.com/Sirupsen/logrus"
)

func init() {
  // Log as JSON instead of the default ASCII formatter.
  log.SetFormatter(&log.JSONFormatter{})

  // Output to stdout instead of the default stderr, could also be a file.
  log.SetOutput(os.Stdout)

  // Only log the warning severity or above.
  log.SetLevel(log.WarnLevel)
}

func main() {
  log.WithFields(log.Fields{
    "animal": "walrus",
    "size":   10,
  }).Info("A group of walrus emerges from the ocean")

  log.WithFields(log.Fields{
    "omg":    true,
    "number": 122,
  }).Warn("The group's number increased tremendously!")

  log.WithFields(log.Fields{
    "omg":    true,
    "number": 100,
  }).Fatal("The ice breaks!")

  // A common pattern is to re-use fields between logging statements by re-using
  // the logrus.Entry returned from WithFields()
  contextLogger := log.WithFields(log.Fields{
    "common": "this is a common field",
    "other": "I also should be logged always",
  })

  contextLogger.Info("I'll be logged with common and other field")
  contextLogger.Info("Me too")
}

For more advanced usage such as logging to multiple locations from the same application, you can also create an instance of the logrus Logger:

package main

import (
  "github.com/Sirupsen/logrus"
)

// Create a new instance of the logger. You can have any number of instances.
var log = logrus.New()

func main() {
  // The API for setting attributes is a little different than the package level
  // exported logger. See Godoc.
  log.Out = os.Stderr

  log.WithFields(logrus.Fields{
    "animal": "walrus",
    "size":   10,
  }).Info("A group of walrus emerges from the ocean")
}

Fields

Logrus encourages careful, structured logging though logging fields instead of long, unparseable error messages. For example, instead of: log.Fatalf("Failed to send event %s to topic %s with key %d"), you should log the much more discoverable:

log.WithFields(log.Fields{
  "event": event,
  "topic": topic,
  "key": key,
}).Fatal("Failed to send event")

We've found this API forces you to think about logging in a way that produces much more useful logging messages. We've been in countless situations where just a single added field to a log statement that was already there would've saved us hours. The WithFields call is optional.

In general, with Logrus using any of the printf-family functions should be seen as a hint you should add a field, however, you can still use the printf-family functions with Logrus.

Hooks

You can add hooks for logging levels. For example to send errors to an exception tracking service on Error, Fatal and Panic, info to StatsD or log to multiple places simultaneously, e.g. syslog.

Logrus comes with built-in hooks. Add those, or your custom hook, in init:

import (
  log "github.com/Sirupsen/logrus"
  "gopkg.in/gemnasium/logrus-airbrake-hook.v2" // the package is named "aibrake"
  logrus_syslog "github.com/Sirupsen/logrus/hooks/syslog"
  "log/syslog"
)

func init() {

  // Use the Airbrake hook to report errors that have Error severity or above to
  // an exception tracker. You can create custom hooks, see the Hooks section.
  log.AddHook(airbrake.NewHook(123, "xyz", "production"))

  hook, err := logrus_syslog.NewSyslogHook("udp", "localhost:514", syslog.LOG_INFO, "")
  if err != nil {
    log.Error("Unable to connect to local syslog daemon")
  } else {
    log.AddHook(hook)
  }
}

Note: Syslog hook also support connecting to local syslog (Ex. "/dev/log" or "/var/run/syslog" or "/var/run/log"). For the detail, please check the syslog hook README.

Hook Description
Airbrake Send errors to the Airbrake API V3. Uses the official gobrake behind the scenes.
Airbrake "legacy" Send errors to an exception tracking service compatible with the Airbrake API V2. Uses airbrake-go behind the scenes.
Papertrail Send errors to the Papertrail hosted logging service via UDP.
Syslog Send errors to remote syslog server. Uses standard library log/syslog behind the scenes.
Bugsnag Send errors to the Bugsnag exception tracking service.
Sentry Send errors to the Sentry error logging and aggregation service.
Hiprus Send errors to a channel in hipchat.
Logrusly Send logs to Loggly
Slackrus Hook for Slack chat.
Journalhook Hook for logging to systemd-journald
Graylog Hook for logging to Graylog
Raygun Hook for logging to Raygun.io
LFShook Hook for logging to the local filesystem
Honeybadger Hook for sending exceptions to Honeybadger
Mail Hook for sending exceptions via mail
Rollrus Hook for sending errors to rollbar
Fluentd Hook for logging to fluentd
Mongodb Hook for logging to mongodb
Influxus Hook for concurrently logging to InfluxDB
InfluxDB Hook for logging to influxdb
Octokit Hook for logging to github via octokit
DeferPanic Hook for logging to DeferPanic
Redis-Hook Hook for logging to a ELK stack (through Redis)
Amqp-Hook Hook for logging to Amqp broker (Like RabbitMQ)
KafkaLogrus Hook for logging to kafka
Typetalk Hook for logging to Typetalk
ElasticSearch Hook for logging to ElasticSearch
Sumorus Hook for logging to SumoLogic
Scribe Hook for logging to Scribe
Logstash Hook for logging to Logstash
logz.io Hook for logging to logz.io, a Log as a Service using Logstash
Logmatic.io Hook for logging to Logmatic.io
Pushover Send error via Pushover
PostgreSQL Send logs to PostgreSQL
Logentrus Hook for logging to Logentries

Level logging

Logrus has six logging levels: Debug, Info, Warning, Error, Fatal and Panic.

log.Debug("Useful debugging information.")
log.Info("Something noteworthy happened!")
log.Warn("You should probably take a look at this.")
log.Error("Something failed but I'm not quitting.")
// Calls os.Exit(1) after logging
log.Fatal("Bye.")
// Calls panic() after logging
log.Panic("I'm bailing.")

You can set the logging level on a Logger, then it will only log entries with that severity or anything above it:

// Will log anything that is info or above (warn, error, fatal, panic). Default.
log.SetLevel(log.InfoLevel)

It may be useful to set log.Level = logrus.DebugLevel in a debug or verbose environment if your application has that.

Entries

Besides the fields added with WithField or WithFields some fields are automatically added to all logging events:

  1. time. The timestamp when the entry was created.
  2. msg. The logging message passed to {Info,Warn,Error,Fatal,Panic} after the AddFields call. E.g. Failed to send event.
  3. level. The logging level. E.g. info.

Environments

Logrus has no notion of environment.

If you wish for hooks and formatters to only be used in specific environments, you should handle that yourself. For example, if your application has a global variable Environment, which is a string representation of the environment you could do:

import (
  log "github.com/Sirupsen/logrus"
)

init() {
  // do something here to set environment depending on an environment variable
  // or command-line flag
  if Environment == "production" {
    log.SetFormatter(&log.JSONFormatter{})
  } else {
    // The TextFormatter is default, you don't actually have to do this.
    log.SetFormatter(&log.TextFormatter{})
  }
}

This configuration is how logrus was intended to be used, but JSON in production is mostly only useful if you do log aggregation with tools like Splunk or Logstash.

Formatters

The built-in logging formatters are:

  • logrus.TextFormatter. Logs the event in colors if stdout is a tty, otherwise without colors.
    • Note: to force colored output when there is no TTY, set the ForceColors field to true. To force no colored output even if there is a TTY set the DisableColors field to true
  • logrus.JSONFormatter. Logs fields as JSON.

Third party logging formatters:

  • logstash. Logs fields as Logstash Events.
  • prefixed. Displays log entry source along with alternative layout.
  • zalgo. Invoking the P͉̫o̳̼̊w̖͈̰͎e̬͔̭͂r͚̼̹̲ ̫͓͉̳͈ō̠͕͖̚f̝͍̠ ͕̲̞͖͑Z̖̫̤̫ͪa͉̬͈̗l͖͎g̳̥o̰̥̅!̣͔̲̻͊̄ ̙̘̦̹̦.

You can define your formatter by implementing the Formatter interface, requiring a Format method. Format takes an *Entry. entry.Data is a Fields type (map[string]interface{}) with all your fields as well as the default ones (see Entries section above):

type MyJSONFormatter struct {
}

log.SetFormatter(new(MyJSONFormatter))

func (f *MyJSONFormatter) Format(entry *Entry) ([]byte, error) {
  // Note this doesn't include Time, Level and Message which are available on
  // the Entry. Consult `godoc` on information about those fields or read the
  // source of the official loggers.
  serialized, err := json.Marshal(entry.Data)
    if err != nil {
      return nil, fmt.Errorf("Failed to marshal fields to JSON, %v", err)
    }
  return append(serialized, '\n'), nil
}

Logger as an io.Writer

Logrus can be transformed into an io.Writer. That writer is the end of an io.Pipe and it is your responsibility to close it.

w := logger.Writer()
defer w.Close()

srv := http.Server{
    // create a stdlib log.Logger that writes to
    // logrus.Logger.
    ErrorLog: log.New(w, "", 0),
}

Each line written to that writer will be printed the usual way, using formatters and hooks. The level for those entries is info.

Rotation

Log rotation is not provided with Logrus. Log rotation should be done by an external program (like logrotate(8)) that can compress and delete old log entries. It should not be a feature of the application-level logger.

Tools

Tool Description
Logrus Mate Logrus mate is a tool for Logrus to manage loggers, you can initial logger's level, hook and formatter by config file, the logger will generated with different config at different environment.
Logrus Viper Helper An Helper arround Logrus to wrap with spf13/Viper to load configuration with fangs! And to simplify Logrus configuration use some behavior of Logrus Mate. sample

Testing

Logrus has a built in facility for asserting the presence of log messages. This is implemented through the test hook and provides:

  • decorators for existing logger (test.NewLocal and test.NewGlobal) which basically just add the test hook
  • a test logger (test.NewNullLogger) that just records log messages (and does not output any):
logger, hook := NewNullLogger()
logger.Error("Hello error")

assert.Equal(1, len(hook.Entries))
assert.Equal(logrus.ErrorLevel, hook.LastEntry().Level)
assert.Equal("Hello error", hook.LastEntry().Message)

hook.Reset()
assert.Nil(hook.LastEntry())

Fatal handlers

Logrus can register one or more functions that will be called when any fatal level message is logged. The registered handlers will be executed before logrus performs a os.Exit(1). This behavior may be helpful if callers need to gracefully shutdown. Unlike a panic("Something went wrong...") call which can be intercepted with a deferred recover a call to os.Exit(1) can not be intercepted.

...
handler := func() {
  // gracefully shutdown something...
}
logrus.RegisterExitHandler(handler)
...

Thread safety

By default Logger is protected by mutex for concurrent writes, this mutex is invoked when calling hooks and writing logs. If you are sure such locking is not needed, you can call logger.SetNoLock() to disable the locking.

Situation when locking is not needed includes:

  • You have no hooks registered, or hooks calling is already thread-safe.

  • Writing to logger.Out is already thread-safe, for example:

    1) logger.Out is protected by locks.

    2) logger.Out is a os.File handler opened with O_APPEND flag, and every write is smaller than 4k. (This allow multi-thread/multi-process writing)

    (Refer to http://www.notthewizard.com/2014/06/17/are-files-appends-really-atomic/)