Composable Loggers for the Julia Logging StdLib
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Diagram showing how loggers connect

Discussion: Compositional Loggers

LoggingExtras is designs around allowing you to build arbitrarily complicated systems for "log plumbing". That is to say basically routing logged information to different places. It is built around the idea of simple parts which are composed together, to allow for powerful and flexible definition of your logging system. Without you having to define any custom loggers by subtyping AbstractLogger. When we talk about composability we mean to say that the composition of any set of Loggers is itself a Logger. LoggingExtras is a composable logging system.

Loggers can be broken down into 4 types:

  • Sinks: Sinks are the final end point of a log messages journey. They write it to file, or display it on the console, or set off a red flashing light in the laboratory. A Sink should never decide what to accept, only what to do with it.
  • Filters: Filters wrap around other loggers and decide whether or not to pass on a message. They can further be broken down by when that decision occurs (See ActiveFilteredLogger vs EarlyFilteredLogger).
  • Transformers: Transformers modify the content of log messages, before passing them on. This includes the metadata like severity level. Unlike Filters they can't block a log message, but they could drop its level down to say Debug so that normally noone would see it.
  • Demux: There is only one possible Demux Logger. and it is central to log routing. It acts as a hub that receives 1 log message, and then sends copies of it to all its child loggers. Like in the diagram above, it can be composed with Filters to control what goes where.

This is a basically full taxonomy of all compositional loggers. This package implements the full set. So you shouldn't need to build your own routing components, just configure the ones included in this package.

It is worth understanding the idea of logging purity. The loggers defined in this package are all pure. The Filters, only filter, the Sinks only sink, the transformers only Transform.

We can contrast this to the the ConsoleLogger (the standard logger in the REPL). The ConsoleLogger is an impure sink. As well as displaying logs to the user (as a Sink); it uses the log content, in the form of the max_log kwarg to decide if a log should be displayed (Active Filtering); and it has a min_enabled_level setting, that controls if it will accept a message at all (Early Filtering, in particular see MinLevelLogger). If it was to be defined in a compositional way, we would write something along the lines of:

ConsoleLogger(stream, min_level) =


Load the package with using LoggingExtras. For convenience, this also re-exports the Logging standard library.

Basics of working with loggers

For full details, see the Julia documentation on Logging

To use a logger in a given scope do

with_logger(logger) do

To make a logger the global logger, use


To get the current logger (which can vary per task) use

logger = current_logger()

To get the current global logger (which does not vary per task), use

logger = global_logger()

Loggers introduced by this package:

This package introduces 8 new loggers. The TeeLogger, the TransformerLogger, 3 types of filtered logger, the FileLogger, the DatetimeRotatingFileLogger and the FormatLogger. All of them, except FormatLogger, just wrap existing loggers.

  • The TeeLogger sends the logs to multiple different loggers.
  • The 3 filter loggers are used to control if a message is written or not
    • The MinLevelLogger only allows messages to pass that are above a given level of severity
    • The EarlyFilteredLogger lets you write filter rules based on the level, module, group and id of the log message
    • The ActiveFilteredLogger lets you filter based on the full content
  • The TransformerLogger applies a function to modify log messages before passing them on.
  • The FileLogger is a simple logger sink that writes to file.
  • The DatetimeRotatingFileLogger is a logger sink that writes to file, rotating logs based upon a user-provided DateFormat.
  • The FormatLogger is a logger sink that simply formats the message and writes to the logger stream.
  • The LevelOverrideLogger for overriding the log level of other loggers

By combining TeeLogger with filter loggers you can arbitrarily route log messages, wherever you want.

TeeLogger (Demux)

The TeeLogger sends the log messages to multiple places. It takes a list of loggers. You often want to pass the current_logger() or global_logger() as one of those inputs so it keeps going to that one as well.

It is up to those loggers to determine if they will accept it. Which they do using their methods for shouldlog and min_enabled_level. Or you can do, by wrapping them in a filtered logger as discussed below.

ActiveFilteredLogger (Filter)

The ActiveFilteredLogger exists to give more control over which messages should be logged. It warps any logger, and before sending messages to the logger to log, checks them against a filter function. The filter function takes the full set of parameters of the message. (See it's docstring with ?ActiveFilteredLogger for more details.)


We want to filter to only log strings staring with "Yo Dawg!".

julia> function yodawg_filter(log_args)
    startswith(log_args.message, "Yo Dawg!")
 yodawg_filter (generic function with 1 method)

julia> filtered_logger = ActiveFilteredLogger(yodawg_filter, global_logger());

julia> with_logger(filtered_logger) do
    @info "Boring message"
    @warn "Yo Dawg! it is bad"
    @info "Another boring message"
    @info "Yo Dawg! it is all good"
┌ Warning: Yo Dawg! it is bad
└ @ Main REPL[28]:3
[ Info: Yo Dawg! it is all good

Respecting maxlog convention

An ActiveFilterLogger can be used to wrap another logger to obey maxlog directives, for example, similar to the make_throttled_logger example below,

function make_maxlog_logger(logger)
    counts = Dict{Any,Int}()
    return ActiveFilteredLogger(logger) do log
        maxlog = get(log.kwargs, :maxlog, nothing)
        maxlog === nothing && return true # no limit
        c = get(counts, log.id, 0)
        if c < maxlog
            # log this message and update the count
            counts[log.id] = c + 1
            return true
            return false

wraps another logger to filter logs that have already fired maxlog many times. See https://docs.julialang.org/en/v1/stdlib/Logging/#Logging.@logmsg for more on maxlog.

EarlyFilteredLogger (Filter)

The EarlyFilteredLogger is similar to the ActiveFilteredLogger, but it runs earlier in the logging pipeline. In particular it runs before the message is computed. It can be useful to filter things early if creating the log message is expensive. E.g. if it includes summary statistics of the error. The filter function for early filter logging only has access to the level, _module, id and group fields of the log message. The most notable use of it is to filter based on modules, see the HTTP example below.

Another example is using them to stop messages every being repeated within a given time period.

using Dates, LoggingExtras

julia> function make_throttled_logger(period)
    history = Dict{Symbol, DateTime}()
    # We are going to use a closure
    EarlyFilteredLogger(global_logger()) do log
        if !haskey(history, log.id) || (period < now() - history[log.id])
            # then we will log it, and update record of when we did
            history[log.id] = now()
            return true
            return false
make_throttled_logger (generic function with 1 method)

julia> throttled_logger = make_throttled_logger(Second(3));

julia> with_logger(throttled_logger) do
    for ii in 1:10
        @info "It happened" ii
┌ Info: It happened
└   ii = 1
┌ Info: It happened
└   ii = 4
┌ Info: It happened
└   ii = 7
┌ Info: It happened
└   ii = 10

MinLevelLogger (Filter)

This is basically a special case of the early filtered logger, that just checks if the level of the message is above the level specified when it was created.

Demo: filter out all the log messages that are less severe than Error

julia> using LoggingExtras

julia> error_only_logger = MinLevelLogger(current_logger(), Logging.Error);

julia> with_logger(error_only_logger) do
           @info("You won't see this")
           @warn("won't see this either")
           @error("You will only see this")
┌ Error: You will only see this
└ @ Main REPL[18]:4

TransformerLogger (Transformer)

The transformer logger allows for the modification of log messages. This modification includes such things as its log level, and content, and all the other arguments passed to handle_message.

When constructing a TransformerLogger you pass in a transformation function, and a logger to be wrapped. The transformation function takes a named tuple containing all the log message fields, and should return a new modified named tuple.

A simple example of its use is truncating messages.

julia> using LoggingExtras

julia> truncating_logger  = TransformerLogger(global_logger()) do log
    if length(log.message) > 128
        short_message = log.message[1:min(end, 125)] * "..."
        return merge(log, (;message=short_message))
        return log

julia> with_logger(truncating_logger) do
    @info "the truncating logger only truncates long messages"
    @info "Like this one that is this is a long and rambling message, it just keeps going and going and going,  and it seems like it will never end."
    @info "Not like this one, that is is short"
[ Info: the truncating logger only truncates long messages
[ Info: Like this one that is this is a long and rambling message, it just keeps going and going and going,  and it seems like it wil...
[ Info: Not like this one, that is is short

It can also be used to do things such as change the log level of messages from a particular module (see the example below). Or to set common properties for all log messages within the with_logger block, for example to set them all to the same group.

FileLogger (Sink)

The FileLogger does logging to file. It is just a convenience wrapper around the base julia SimpleLogger, to make it easier to pass in a filename, rather than a stream. It is really simple.

  • It takes a filename,
  • a kwarg to check if should always_flush (default: true).
  • a kwarg to append rather than overwrite (default false. i.e. overwrite by default) The resulting file format is similar to that which is shown in the REPL. (Not identical, but similar)

NOTE: To print to the file in a specific format, e.g. to create a JSON log, use FormatLogger instead.

Demo: TeeLogger and FileLogger

We are going to log info and above to one file, and warnings and above to another.

julia> using LoggingExtras;

julia> demux_logger = TeeLogger(
    MinLevelLogger(FileLogger("info.log"), Logging.Info),
    MinLevelLogger(FileLogger("warn.log"), Logging.Warn),

julia> with_logger(demux_logger) do
    @warn("It is bad")
    @info("normal stuff")
    @error("THE WORSE THING")
    @debug("it is chill")

shell>  cat warn.log
┌ Warning: It is bad
└ @ Main REPL[34]:2
└ @ Main REPL[34]:4

shell>  cat info.log
┌ Warning: It is bad
└ @ Main REPL[34]:2
┌ Info: normal stuff
└ @ Main REPL[34]:3
└ @ Main REPL[34]:4

DatetimeRotatingFileLogger (Sink)

Use this sink to rotate your logs based upon a given DateFormat, automatically closing one file and opening another when the DateFormat would change the filename. Note that if you wish to have static portions of your filename, you must escape them so they are not interpreted by the DateFormat code. Example:

julia> using LoggingExtras

julia> rotating_logger = DatetimeRotatingFileLogger(pwd(), raw"\a\c\c\e\s\s-YYYY-mm-dd-HH-MM.\l\o\g");

julia> with_logger(rotating_logger) do
       @info("This goes in one file")
       sleep(61) # Sleep until next minute
       @info("This goes in another file")

julia> filter(f -> endswith(f, ".log"), readdir(pwd()))
2-element Array{String,1}:

The user implicitly controls when the files will be rolled over based on the DateFormat given. To post-process the newly rotated file pass rotation_callback::Function as a keyword argument. See the docstring with (?DatetimeRotatingFileLogger in the REPL) for more details.

To control the logging output it is possible to pass a formatter function as the first argument in the constructor. See FormatLogger for the requirements on the formatter function.

FormatLogger (Sink)

The FormatLogger is a sink that formats the message and prints to a wrapped IO. Formatting is done by providing a function f(io::IO, log_args::NamedTuple).

FormatLogger can take as its second argument either a writeable IO or a filepath. The append::Bool keyword argument determines whether the file is opened in append mode ("a") or truncate mode ("w").

julia> using LoggingExtras

julia> logger = FormatLogger() do io, args
           println(io, args._module, " | ", "[", args.level, "] ", args.message)

julia> logger = FormatLogger("out.log"; append=true) do io, args
            println(io, args._module, " | ", "[", args.level, "] ", args.message)

julia> with_logger(logger) do
           @info "This is an informational message."
           @warn "This is a warning, should take a look."
Main | [Info] This is an informational message.
Main | [Warn] This is a warning, should take a look.

LevelOverrideLogger (Filter)

Allows overriding the minimum log level set by the logger it wraps. Useful when debug logging and used in conjuction with Logging.with_logger or LoggingExtras.withlevel to temporarily modify the current logger with a custom level. More generally useful if you want to use the current/global logger as a sink but don't know if it is going to have a problematically high min log level set (as julia's default logger sets min level to Info).

julia> using LoggingExtras

julia> logger = LevelOverrideLogger(Debug, global_logger())

julia> with_logger(logger) do
           @debug "This message will log since we're overriding the global Info default log level"
┌ Debug: This message will log since we're overriding the global Info default log level
└ @ Main REPL[33]:2

This is roughly complementary to the MinLevelFilterLogger. The MinLevelFilterLogger lets you effectively raise the level of any logger it wraps to meet the level you specify. The LevelOverrideLogger lets you lower (or raise) the level of the wrapped logger as it bypasses checks on it entirely.


Verbosity macros

Sometimes when logging, it is desirable to be able to specify a verbosity level along with the log level, and to be able to filter on verbosity levels. For example, you may want multiple levels of verbosity for Debug log statements. LoggingExtras.jl exports verbosity macros that act like their non-verbose counterparts, but allow specifying a verbosity level as well:

  • @debugv N msg
  • @infov N msg
  • @warnv N msg
  • @errorv N msg

For verbosity filtering, the LoggingExtras.withlevel(f, Info; verbosity=0) utlility is provided for temporarily (i.e. while f() is executed) allowing log messages with level and verbosity. This is very handy for allowing finer grained control in debug logging for long-running or complex user API function calls. For example:

using LoggingExtras

function complex_user_call(; verbose=0)
    LoggingExtras.withlevel(Debug; verbosity=verbose)
        # execute complex function body
        @debugv 1 "a level 1 verbosity debug message"
        @debugv 2 "a more verbose level 2 debug message"

This allows easy control by the user to specify verbosity (by passing verbose=2 or any > 0 value), and convenience for the function developer by being able to sprinkle @debugv N msg calls as desired, even in highly nested functions.

More Examples

Filter out any overly long messages

using LoggingExtras

function sensible_message_filter(log)
    length(log.message) < 1028

global_logger(ActiveFilteredLogger(sensible_message_filter, global_logger()))

Filterout any messages from HTTP

using LoggingExtras
using HTTP

function not_HTTP_message_filter(log)
    # HTTP.jl utilizes internal modules so call parentmodule(...)
    log._module !== HTTP && parentmodule(log._module) !== HTTP

global_logger(EarlyFilteredLogger(not_HTTP_message_filter, global_logger()))

Raising HTTP debug level errors to be Info level

using LoggingExtras
using HTTP

transformer_logger(global_logger()) do log
    # HTTP.jl utilizes internal modules so call parentmodule(...)
    if (log._module === HTTP || parentmodule(log._module) === HTTP) && log.level === Logging.Debug
        # Merge can be used to construct a new NamedTuple
        # which effectively is the overwriting of fields of a NamedTuple
        return merge(log, (; level=Logging.Info))
        return log


Add timestamp to all logging

using LoggingExtras, Dates

const date_format = "yyyy-mm-dd HH:MM:SS"

timestamp_logger(logger) = TransformerLogger(logger) do log
  merge(log, (; message = "$(Dates.format(now(), date_format)) $(log.message)"))

ConsoleLogger(stdout, Logging.Debug) |> timestamp_logger |> global_logger

This will produce output similar to:

[ Info: 2019-09-20 17:43:54 /es/update 200
┌ Debug: 2019-09-20 18:03:25 Recompiling stale cache file /.julia/compiled/v1.2/TranslationsController.ji for TranslationsController [top-level]
└ @ Base loading.jl:1240
┌ Error: 2019-09-20 17:43:54 ErrorException("SearchLight validation error(s) for Translations.Translation")
└ @ TranslationsController ~/Dropbox/Projects/LiteCMS/app/resources/translations/TranslationsController.jl:69