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API docs | CHANGELOG | contact & contributing | other Clojure libs | Twitter | current semantic version:

[com.taoensso/timbre "2.6.1"] ; See CHANGELOG for breaking changes since 1.x

Timbre, a (sane) Clojure logging & profiling library

Logging with Java can be maddeningly, unnecessarily hard. Particularly if all you want is something simple that works out-the-box. Timbre is an attempt to make simple logging simple and more complex logging reasonable. No XML!

What's in the box™?

  • Small, uncomplicated all-Clojure library.
  • Super-simple map-based config: no arcane XML or properties files!
  • Low overhead with dynamic logging level.
  • No overhead with compile-time logging level. (v2.6+)
  • Flexible fn-centric appender model with middleware.
  • Sensible built-in appenders including simple email appender.
  • Tunable rate limit and asynchronous logging support.
  • Robust namespace filtering.
  • tools.logging support (optional).
  • Dead-simple, logging-level-aware logging profiler.

Getting started


Add the necessary dependency to your Leiningen project.clj and require the library in your ns:

[com.taoensso/timbre "2.6.1"] ; project.clj
(ns my-app (:require [taoensso.timbre :as timbre
                      :refer (trace debug info warn error fatal spy with-log-level)])) ; ns


By default, Timbre gives you basic print output to *out*/*err* at a debug logging level:

(info "This will print")
=> nil
%> 2012-May-28 17:26:11:444 +0700 localhost INFO [my-app] - This will print

(spy :info (* 5 4 3 2 1))
=> 120
%> 2012-May-28 17:26:14:138 +0700 localhost INFO [my-app] - (* 5 4 3 2 1) 120

(trace "This won't print due to insufficient logging level")
=> nil

There's little overhead for checking logging levels:

(time (trace (Thread/sleep 5000)))
%> "Elapsed time: 0.054 msecs"

(time (when false))
%> "Elapsed time: 0.051 msecs"

And no overhead when using a compile-time logging level (set TIMBRE_LOG_LEVEL environment variable):

(time (dotimes [_ 1000000000] (trace (Thread/sleep 5000))))
%> "Elapsed time: 387.159 msecs"

(time (dotimes [_ 1000000000] nil))
%> "Elapsed time: 389.231 msecs"

First-argument exceptions generate a stack trace:

(info (Exception. "Oh noes") "arg1" "arg2")
%> 2012-May-28 17:35:16:132 +0700 localhost INFO [my-app] - arg1 arg2
java.lang.Exception: Oh noes
            NO_SOURCE_FILE:1 my-app/eval6409


Configuring Timbre couldn't be simpler. Let's check out (some of) the defaults:

{:current-level :debug

 :ns-whitelist []
 :ns-blacklist []

 :middleware [] ; As of Timbre 1.4.0, see source for details

 :timestamp-pattern "yyyy-MMM-dd HH:mm:ss ZZ"
 :timestamp-locale  nil

 {:standard-out        { <...> }
  :spit                { <...> }
  <...> }

 :shared-appender-config {}}

Easily adjust the current logging level:

(timbre/set-level! :warn)

And the default timestamp formatting for log messages:

(timbre/set-config! [:timestamp-pattern] "yyyy-MMM-dd HH:mm:ss ZZ")
(timbre/set-config! [:timestamp-locale] (java.util.Locale/GERMAN))

Filter logging output by namespaces:

(timbre/set-config! [:ns-whitelist] ["some.library.core" "my-app.*"])

Built-in appenders

File appender

(timbre/set-config! [:appenders :spit :enabled?] true)
(timbre/set-config! [:shared-appender-config :spit-filename] "/path/my-file.log")

Email (Postal) appender

;; [com.draines/postal "1.9.2"] ; Add to project.clj dependencies
;; (:require [taoensso.timbre.appenders (postal :as postal-appender)]) ; Add to ns

(timbre/set-config! [:appenders :postal] postal-appender/postal-appender)
(timbre/set-config! [:shared-appender-config :postal]
                    ^{:host "" :user "jsmith" :pass "sekrat!!1"}
                    {:from "" :to ""})

;; Rate limit to one email per message per minute
(timbre/set-config! [:appenders :postal :limit-per-msecs] 60000)

;; Make sure emails are sent asynchronously
(timbre/set-config! [:appenders :postal :async?] true)

IRC (irclj) appender

;; [irclj "0.5.0-alpha2"] ; Add to project.clj dependencies
;; (:require [taoensso.timbre.appenders (irc :as irc-appender)]) ; Add to ns

(timbre/set-config! [:appenders :irc] irc-appender/irc-appender)
(timbre/set-config! [:shared-appender-config :irc]
                    {:host ""
                     :port 6667
                     :nick "logger"
                     :name "Logger"
                     :chan "#logs"})

Socket (server-socket) appender

Listens on the specified interface (use :all for all interfaces, defaults to localhost if unspecified) and port. Connect with either of:

telnet localhost 9000
netcat localhost 9000
;; [server-socket "1.0.0"] ; Add to project.clj dependencies
;; (:require [taoensso.timbre.appenders (socket :as socket-appender)]) ; Add to ns

(timbre/set-config! [:appenders :socket] socket-appender/socket-appender)
(timbre/set-config! [:shared-appender-config :socket]
                    {:listen-addr :all
                     :port 9000})

MongoDB (congomongo) appender

;; [congomongo "0.4.1"] ; Add to project.clj dependencies
;; (:require [taoensso.timbre.appenders (mongo :as mongo-appender)]) ; Add to ns

(timbre/set-config! [:appenders :mongo] mongo-appender/mongo-appender)
(timbre/set-config! [:shared-appender-config :mongo]
                    {:db          "logs"
                     :collection  "myapp"
                     :server      {:host "" :port 27017}})

Custom appenders

Writing a custom appender is dead-easy:

 [:appenders :my-appender]
 {:doc       "Hello-world appender"
  :min-level :debug
  :enabled?  true
  :async?    false
  :limit-per-msecs nil ; No rate limit
  :fn (fn [{:keys [ap-config level prefix throwable message] :as args}]
        (when-not (:my-production-mode? ap-config)
          (println prefix "Hello world!" message)))

And because appender fns are just regular Clojure fns, you have unlimited power: write to your database, send a message over the network, check some other state (e.g. environment config) before making a choice, etc.

See the timbre/config docstring for more information on appenders.


The usual recommendation for Clojure profiling is: use a good JVM profiler like YourKit, JProfiler, or VisualVM.

And these certainly do the job. But as with many Java tools, they can be a little hairy and often heavy-handed - especially when applied to Clojure. Timbre includes an alternative.

Let's add it to our app's ns declaration:

(:require [taoensso.timbre.profiling :as profiling :refer (p profile)])

Wrap forms that you'd like to profile with the p macro and give them a name:

(defn my-fn
  (let [nums (vec (range 1000))]
    (+ (p :fast-sleep (Thread/sleep 1) 10)
       (p :slow-sleep (Thread/sleep 2) 32)
       (p :add  (reduce + nums))
       (p :sub  (reduce - nums))
       (p :mult (reduce * nums))
       (p :div  (reduce / nums)))))

=> 42

The profile macro can now be used to log times for any wrapped forms:

(profile :info :Arithmetic (dotimes [n 100] (my-fn)))
=> "Done!"
%> 2012-Jul-03 20:46:17 +0700 localhost INFO [my-app] - Profiling my-app/Arithmetic
              Name  Calls       Min        Max       MAD      Mean  Total% Total
 my-app/slow-sleep    100       2ms        2ms      31μs       2ms      57 231ms
 my-app/fast-sleep    100       1ms        1ms      27μs       1ms      29 118ms
        my-app/add    100      44μs        2ms      46μs     100μs       2 10ms
        my-app/sub    100      42μs      564μs      26μs      72μs       2 7ms
        my-app/div    100      54μs      191μs      17μs      71μs       2 7ms
       my-app/mult    100      31μs      165μs      11μs      44μs       1 4ms
       Unaccounted                                                       6 26ms
             Total                                                     100 405ms

It's important to note that Timbre profiling is fully logging-level aware: if the level is insufficient, you won't pay for profiling. Likewise, normal namespace filtering applies. (Performance characteristics for both checks are inherited from Timbre itself).

And since p and profile always return their body's result regardless of whether profiling actually happens or not, it becomes feasible to use profiling more often as part of your normal workflow: just leave profiling code in production as you do for logging code.

A simple sampling profiler is also available: taoensso.timbre.profiling/sampling-profile.

This project supports the CDS and ClojureWerkz goals

  • CDS, the Clojure Documentation Site, is a contributer-friendly community project aimed at producing top-notch, beginner-friendly Clojure tutorials and documentation. Awesome resource.

  • ClojureWerkz is a growing collection of open-source, batteries-included Clojure libraries that emphasise modern targets, great documentation, and thorough testing. They've got a ton of great stuff, check 'em out!

Contact & contribution

Please use the project's GitHub issues page for project questions/comments/suggestions/whatever (pull requests welcome!). Am very open to ideas if you have any!

Otherwise reach me (Peter Taoussanis) at or on Twitter (@ptaoussanis). Cheers!


Copyright © 2012, 2013 Peter Taoussanis. Distributed under the Eclipse Public License, the same as Clojure.

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