loguru.logger¶
-
class
Logger
[source]¶ An object to dispatch logging messages to configured handlers.
The
Logger
is the core objet of loguru, every logging configuration and usage pass through a call to one of its methods. There is only one logger, so there is no need to retrieve one before usage.Handlers to which send log messages are added using the
start()
method. Note that you can use theLogger
right after import as it comes pre-configured. Messages can be logged with different severity levels and using braces attributes like thestr.format()
method do.Once a message is logged, a “record” is associated with it. This record is a dict wich contains several information about the logging context: time, function, file, line, thread, level… It also contains the
__name__
of the module, this is why you don’t need named loggers.You should not instantiate a
Logger
by yourself, usefrom loguru import logger
instead.-
start
(sink, *, level='DEBUG', format='<green>{time:YYYY-MM-DD HH:mm:ss.SSS}</green> | <level>{level: <8}</level> | <cyan>{name}</cyan>:<cyan>{function}</cyan>:<cyan>{line}</cyan> - <level>{message}</level>', filter=None, colorize=None, serialize=False, backtrace=True, enqueue=False, catch=True, **kwargs)[source]¶ Start sending log messages to a sink adequately configured.
Parameters: - sink (
file-like object
,str
,pathlib.Path
,function
,logging.Handler
orclass
) – An object in charge of receiving formatted logging messages and propagating them to an appropriate endpoint. - level (
int
orstr
, optional) – The minimum severity level from which logged messages should be send to the sink. - format (
str
orfunction
, optional) – The template used to format logged messages before being sent to the sink. - filter (
function
orstr
, optional) – A directive used to optionally filter out logged messages before they are send to the sink. - colorize (
bool
, optional) – Whether or not the color markups contained in the formatted message should be converted to ansi codes for terminal coloration, ore stripped otherwise. IfNone
, the choice is automatically made based on the sink being a tty or not. - serialize (
bool
, optional) – Whether or not the logged message and its records should be first converted to a JSON string before being sent to the sink. - backtrace (
bool
, optional) – Whether or not the formatted exception should use stack trace to display local variables values. This probably should be set toFalse
in production to avoid leaking sensitive data. - enqueue (
bool
, optional) – Whether or not the messages to be logged should first pass through a multiprocess-safe queue before reaching the sink. This is useful while logging to a file through multiple processes. - catch (
bool
, optional) – Whether or not errors occuring while sink handles logs messages should be caught or not. IfTrue
, an exception message is displayed onsys.stderr
but the exception is not propagated to the caller, preventing sink from stopping working. - **kwargs – Additional parameters that will be passed to the sink while creating it or while logging messages (the exact behavior depends on the sink type).
If and only if the sink is a file, the following parameters apply:
Parameters: - rotation (
str
,int
,datetime.time
,datetime.timedelta
orfunction
, optional) – A condition indicating whenever the current logged file should be closed and a new one started. - retention (
str
,int
,datetime.timedelta
orfunction
, optional) – A directive filtering old files that should be removed during rotation or end of program. - compression (
str
orfunction
, optional) – A compression or archive format to which log files should be converted at closure. - delay (
bool
, optional) – Whether or not the file should be created as soon as the sink is configured, or delayed until first logged message. It defaults toFalse
. - mode (
str
, optional) – The openning mode as for built-inopen()
function. It defaults to"a"
(open the file in appending mode). - buffering (
int
, optional) – The buffering policy as for built-inopen()
function. It defaults to1
(line buffered file). - encoding (
str
, optional) – The file encoding as for built-inopen()
function. IfNone
, it defaults tolocale.getpreferredencoding()
. - **kwargs – Others parameters are passed to the built-in
open()
function.
Returns: int
– An identifier associated with the starteds sink and which should be used tostop()
it.Notes
Extended summary follows.
The sink parameter
The
sink
handles incomming log messages and proceed to their writing somewhere and somehow. A sink can take many forms:- A
file-like object
likesys.stderr
oropen("somefile.log", "w")
. Anything with a.write()
method is considered as a file-like object. If it has a.flush()
method, it will be automatically called after each logged message. If it has a.stop()
method, it will be automatically called at sink termination. - A file path as
str
orpathlib.Path
. It can be parametrized with some additional parameters, see bellow. - A simple
function
likelambda msg: print(msg)
. This allows for logging procedure entirely defined by user preferences and needs. - A built-in
logging.Handler
likelogging.StreamHandler
. In such a case, the Loguru records are automatically converted to the structure expected by thelogging
module. - A
class
object that will be used to instantiate the sink using**kwargs
attributes passed. Hence the class should instantiate objects which are therefore valid sinks.
The logged message
The logged message passed to all started sinks is nothing more than a string of the formatted log, to which a special attribute is associated: the
.record
which is a dict containing all contextual information possibly needed (see bellow).Logged messages are formatted according to the
format
of the started sink. This format is usually a string containing braces fields to display attributes from the record dict.If fine-grained control is needed, the
format
can also be a function which takes the record as parameter and return the format template string. However, note that in such a case, you should take care of appending the line ending and exception field to the returned format, while"\n{exception}"
is automatically appended for convenience ifformat
is a string.The
filter
attribute can be used to control which messages are effectively passed to the sink and which one are ignored. A function can be used, accepting the record as an argument, and returningTrue
if the message should be logged,False
otherwise. If a string is used, only the records with the samename
and its children will be allowed.The record dict
The record is just a Python dict, accessible from sinks by
message.record
, and usable for formatting as"{key}"
. Some record’s values are objects with two or more attibutes, those can be formatted with"{key.attr}"
("{key}"
would display one by default). Formatting directives like"{key: >3}"
also works and is specially useful for time (see bellow).Key Description Attributes elapsed The time elapsed since the start of the program See datetime.timedelta
exception The formatted exception if any, None
otherwisetype
,value
,traceback
extra The dict of attributes bound by the user None file The file where the logging call was made name
(default),path
function The function from which the logging call was made None level The severity used to log the the message name
(default),no
,icon
line The line number in the source code None message The logged message (not yet formatted) None module The module where the logging call was made None name The __name__
where the logging call was madeNone process The process in which the logging call was made name
,id
(default)thread The thread in which the logging call was made name
,id
(default)time The local time when the logging call was made See datetime.datetime
The time formatting
The time field can be formatted using more human-friendly tokens. Those constitute a subset of the one used by the Pendulum library by @sdispater. To escape a token, just add square brackets around it.
Token Output Year YYYY 2000, 2001, 2002 … 2012, 2013 YY 00, 01, 02 … 12, 13 Quarter Q 1 2 3 4 Month MMMM January, February, March … MMM Jan, Feb, Mar … MM 01, 02, 03 … 11, 12 M 1, 2, 3 … 11, 12 Day of Year DDDD 001, 002, 003 … 364, 365 DDD 1, 2, 3 … 364, 365 Day of Month DD 01, 02, 03 … 30, 31 D 1, 2, 3 … 30, 31 Day of Week dddd Monday, Tuesday, Wednesday … ddd Mon, Tue, Wed … d 0, 1, 2 … 6 Days of ISO Week E 1, 2, 3 … 7 Hour HH 00, 01, 02 … 23, 24 H 0, 1, 2 … 23, 24 hh 01, 02, 03 … 11, 12 h 1, 2, 3 … 11, 12 Minute mm 00, 01, 02 … 58, 59 m 0, 1, 2 … 58, 59 Second ss 00, 01, 02 … 58, 59 s 0, 1, 2 … 58, 59 Fractional Second S 0 1 … 8 9 SS 00, 01, 02 … 98, 99 SSS 000 001 … 998 999 SSSS… 000[0..] 001[0..] … 998[0..] 999[0..] SSSSSS 000000 000001 … 999998 999999 AM / PM A AM, PM Timezone Z -07:00, -06:00 … +06:00, +07:00 ZZ -0700, -0600 … +0600, +0700 zz EST CST … MST PST Seconds timestamp X 1381685817, 1234567890.123 Microseconds timestamp x 1234567890123 The file sinks
If the sink is a
str
or apathlib.Path
, the corresponding file will be opened for writing logs. The path can also contains a special"{time}"
field that will be formatted with the current date at file creation.The
rotation
check is made before logging each messages. If there is already an existing file with the same name that the file to be created, then the existing file is renamed by appending the date to its basename to prevent file overwritting. This parameter accepts:- an
int
which corresponds to the maximum file size in bytes before that the current logged file is closed and a new one started over. - a
datetime.timedelta
which indicates the frequency of each new rotation. - a
datetime.time
which specifies the hour when the daily rotation should occur. - a
str
for human-friendly parametrization of one of the previously enumerated types. Examples:"100 MB"
,"0.5 GB"
,"1 month 2 weeks"
,"4 days"
,"10h"
,"monthly"
,"18:00"
,"sunday"
,"w0"
,"monday at 12:00"
, … - a
function
which will be called before logging. It should accept two arguments: the logged message and the file object, and it should returnTrue
if the rotation should happen now,False
otherwise.
The
retention
occurs at rotation or at sink stop if rotation isNone
. Files are selected according to their basename, if it is the same that the sink file, with possible time field being replaced with.*
. This parameter accepts:- an
int
which indicates the number of log files to keep, while older files are removed. - a
datetime.timedelta
which specifies the maximum age of files to keep. - a
str
for human-friendly parametrization of the maximum age of files to keep. Examples:"1 week, 3 days"
,"2 months"
, … - a
function
which will be called before the retention process. It should accept the list of log files as argument and process to whatever it wants (moving files, removing them, etc.).
The
compression
happens at rotation or at sink stop if rotation isNone
. This parameter acccepts:- a
str
which corresponds to the compressed or archived file extension. This can be one of:"gz"
,"bz2"
,"xz"
,"lzma"
,"tar"
,"tar.gz"
,"tar.bz2"
,"tar.xz"
,"zip"
. - a
function
which will be called before file termination. It should accept the path of the log file as argument and process to whatever it wants (custom compression, network sending, removing it, etc.).
The color markups
To add colors to your logs, you just have to enclose your format string with the appropriate tags. This is based on the great ansimarkup library from @gvalkov. Those tags are removed if the sink don’t support ansi codes.
The special tag
<level>
(abbreviated with<lvl>
) is transformed according to the configured color of the logged message level.Here are the available tags (note that compatibility may vary depending on terminal):
Color (abbr) Styles (abbr) Black (k) Bold (b) Blue (e) Dim (d) Cyan (c) Normal (n) Green (g) Italic (i) Magenta (m) Underline (u) Red (r) Strike (s) White (w) Reverse (r) Yellow (y) Blink (l) Hide (h) Usage:
Description Examples Foreground Background Basic colors <red>
,<r>
<GREEN>
,<G>
Light colors <light-blue>
,<le>
<LIGHT-CYAN>
,<LC>
Xterm colors <fg 86>
,<fg 255>
<bg 42>
,<bg 9>
Hex colors <fg #00005f>
,<fg #EE1>
<bg #AF5FD7>
,<bg #fff>
RGB colors <fg 0,95,0>
<bg 72,119,65>
Stylizing <bold>
,<b>
,<underline>
,<u>
Shorthand (FG, BG) <red, yellow>
,<r, y>
Shorthand (Style, FG, BG) <bold, cyan, white>
,<b,,w>
,<b,c,>
The environment variables
The default values of sink parameters can be entirely customized. This is particularly useful if you don’t like the log format of the pre-configured sink.
Each of the
start()
default parameter can be modified by setting theLOGURU_[PARAM]
environment variable. For example on Linux:export LOGURU_FORMAT="{time} - {message}"
orexport LOGURU_ENHANCE=NO
.The default levels attributes can also be modified by setting the
LOGURU_[LEVEL]_[ATTR]
environment variable. For example, on Windows:setx LOGURU_DEBUG_COLOR="<blue>"
orsetx LOGURU_TRACE_ICON="🚀"
.If you want to disable the pre-configured sink, you can set the
LOGURU_AUTOINIT
variable toFalse
.Examples
>>> logger.start(sys.stdout, format="{time} - {level} - {message}", filter="sub.module")
>>> logger.start("file_{time}.log", level="TRACE", rotation="100 MB")
>>> def my_sink(message): ... record = message.record ... update_db(message, time=record.time, level=record.level) ... >>> logger.start(my_sink)
>>> from logging import StreamHandler >>> logger.start(StreamHandler(sys.stderr), format="{message}")
>>> class RandomStream: ... def __init__(self, seed, threshold): ... self.threshold = threshold ... random.seed(seed) ... def write(self, message): ... if random.random() > self.threshold: ... print(message) ... >>> stream_object = RandomStream(seed=12345, threhold=0.25) >>> logger.start(stream_object, level="INFO") >>> logger.start(RandomStream, level="DEBUG", seed=34567, threshold=0.5)
- sink (
-
stop
(handler_id=None)[source]¶ Stop logging to a previously started sink.
Parameters: handler_id ( int
orNone
) – The id of the sink to stop, as it was returned by thestart()
method. IfNone
, all sinks are stopped. The pre-configured sink is guaranteed to have the index0
.Examples
>>> i = logger.start(sys.stderr, format="{message}") >>> logger.info("Logging") Logging >>> logger.stop(i) >>> logger.info("No longer logging")
-
catch
(exception=<class 'Exception'>, *, level='ERROR', reraise=False, message="An error has been caught in function '{record[function]}', process '{record[process].name}' ({record[process].id}), thread '{record[thread].name}' ({record[thread].id}):")[source]¶ Return a decorator to automatically log possibly caught error in wrapped function.
This is useful to ensure unexpected exceptions are logged, the entire program can be wrapped by this method. This is also very useful to decorate
threading.Thread.run()
methods while using threads to propagate errors to the main logger thread.Note that the visibility of variables values (which uses the cool better_exceptions library from @Qix-) depends on the
backtrace
option of each configured sinks.The returned object can also be used as a context manager.
Parameters: - exception (
Exception
, optional) – The type of exception to intercept. If several types should be caught, a tuple of exceptions can be used too. - level (
str
orint
, optional) – The level name or severity with which the message should be logged. - reraise (
bool
, optional) – Whether or not the exception should be raised again and hence propagated to the caller. - message (
str
, optional) – The message that will be automatically logged if an exception occurs. Note that it will be formatted with therecord
attribute.
Returns: decorator / context manager – An object that can be used to decorate a function or as a context manager to log exceptions possibly caught.
Examples
>>> @logger.catch ... def f(x): ... 100 / x ... >>> def g(): ... f(10) ... f(0) ... >>> g() ERROR - An error has been caught in function 'g', process 'Main' (367), thread 'ch1' (1398): Traceback (most recent call last, catch point marked): File "program.py", line 12, in <module> g() └ <function g at 0x7f225fe2bc80> > File "program.py", line 10, in g f(0) └ <function f at 0x7f225fe2b9d8> File "program.py", line 6, in f 100 / x └ 0 ZeroDivisionError: division by zero
>>> with logger.catch(message="Because we never know..."): ... main() # No exception, no logs ...
- exception (
-
opt
(*, exception=None, record=False, lazy=False, ansi=False, raw=False, depth=0)[source]¶ Parametrize a logging call to slightly change generated log message.
Parameters: - exception (
bool
,tuple
orException
, optional) – It if does not evaluate asFalse
, the passed exception is formatted and added to the log message. It could be anException
object or a(type, value, traceback)
tuple, otherwise the exception information is retrieved fromsys.exc_info()
. - record (
bool
, optional) – IfTrue
, the record dict contextualizing the logging call can be used to format the message by using{record[key]}
in the log message. - lazy (
bool
, optional) – IfTrue
, the logging call attribute to format the message should be functions which will be called only if the level is high enough. This can be used to avoid expensive functions if not necessary. - ansi (
bool
, optional) – IfTrue
, logged message will be colorized according to the markups it possibly contains. - raw (
bool
, optional) – IfTrue
, the formatting of each sink will be bypassed and the message will be send as is. - depth (
int
, optional) – Specify which stacktrace should be used to contextualize the logged message. This is useful while using the logger from inside a wrapped function to retrieve worthwhile information.
Returns: Logger
– A logger wrapping the core logger, but transforming logged message adequately before sending.Examples
>>> try: ... 1 / 0 ... except ZeroDivisionError: ... logger.opt(exception=True).debug("Exception logged with debug level:") ... [18:10:02] DEBUG in '<module>' - Exception logged with debug level: Traceback (most recent call last, catch point marked): > File "<stdin>", line 2, in <module> ZeroDivisionError: division by zero
>>> logger.opt(record=True).info("Current line is: {record[line]}") [18:10:33] INFO in '<module>' - Current line is: 1
>>> logger.opt(lazy=True).debug("If sink <= DEBUG: {x}", x=lambda: math.factorial(2**5)) [18:11:19] DEBUG in '<module>' - If sink <= DEBUG: 263130836933693530167218012160000000
>>> logger.opt(ansi=True).warning("We got a <red>BIG</red> problem") [18:11:30] WARNING in '<module>' - We got a BIG problem
>>> logger.opt(raw=True).debug("No formatting\n") No formatting
>>> def wrapped(): ... logger.opt(depth=1).info("Get parent context") ... >>> def func(): ... wrapped() ... >>> func() [18:11:54] DEBUG in 'func' - Get parent context
- exception (
-
bind
(**kwargs)[source]¶ Bind attributes to the
extra
dict of each logged message record.This is used to add custom context to each logging call.
Parameters: **kwargs – Mapping between keys and values that will be added to the extra
dict.Returns: Logger
– A logger wrapping the core logger, but which sends record with the customizedextra
dict.Examples
>>> logger.start(sys.stderr, format="{extra[ip]} - {message}") 1 >>> class Server: ... def __init__(self, ip): ... self.ip = ip ... self.logger = logger.bind(ip=ip) ... def call(self, message): ... self.logger.info(message) ... >>> instance_1 = Server("192.168.0.200") >>> instance_2 = Server("127.0.0.1") >>> instance_1.call("First instance") 192.168.0.200 - First instance >>> instance_2.call("Second instance") 127.0.0.1 - Second instance
-
level
(name, no=None, color=None, icon=None)[source]¶ Add, update or retrieve a logging level.
Logging levels are defined by their
name
to which a severityno
, an ansicolor
and anicon
are associated and possibly modified at run-time. Tolog()
to a custom level, you should necessarily use its name, the severity number is not linked back to levels name (this implies that several levels can share the same severity).To add a new level, all parameters should be passed so it can be properly configured.
To update an existing level, pass its
name
with the parameters to be changed.To retrieve level information, the
name
solely suffices.Parameters: Returns: Level
– A namedtuple containing information about the level.Examples
>>> level = logger.level("ERROR") Level(no=40, color='<red><bold>', icon='❌') >>> logger.start(sys.stderr, format="{level.no} {icon} {message}") >>> logger.level("CUSTOM", no=15, color="<blue>", icon="@") >>> logger.log("CUSTOM", "Logging...") 15 @ Logging... >>> logger.level("WARNING", icon=r"/!\") >>> logger.warning("Updated!") 30 /!\ Updated!
-
disable
(name)[source]¶ Disable logging of messages comming from
name
module and its children.Developers of library using Loguru should absolutely disable it to avoid disrupting users with unrelated logs messages.
Parameters: name ( str
) – The name of the parent module to disable.Examples
>>> logger.info("Allowed message by default") [22:21:55] Allowed message by default >>> logger.disable("my_library") >>> logger.info("While publishing a library, don't forget to disable logging")
-
enable
(name)[source]¶ Enable logging of messages comming from
name
module and its children.Logging is generally disabled by imported library using Loguru, hence this function allows users to receive these messages anyway.
Parameters: name ( str
) – The name of the parent module to re-allow.Examples
>>> logger.disable("__main__") >>> logger.info("Disabled, so nothing is logged.") >>> logger.enable("__main__") >>> logger.info("Re-enabled, messages are logged.") [22:46:12] Re-enabled, messages are logged.
-
configure
(*, handlers=None, levels=None, extra=None, activation=None)[source]¶ Configure the core logger.
Parameters: - handlers (
list
ofdict
, optional) – A list of each handler to be started. The list should contains dicts of params passed to thestart()
function as keyword arguments. If notNone
, all previously started handlers are first stopped. - levels (
list
ofdict
, optional) – A list of each level to be added or updated. The list should contains dicts of params passed to thelevel()
function as keyword arguments. This will never remove previously created levels. - extra (
dict
, optional) – A dict containing additional parameters bound to the core logger, useful to share common properties if you callbind()
in several of your files modules. If notNone
, this will remove previously configuredextra
dict. - activation (
list
oftuple
, optional) – A list of(name, state)
tuples which denotes which loggers should be enabled (if state isTrue
) or disabled (if state isFalse
). The calls toenable()
anddisable()
are made accordingly to the list order. This will not modify previously activated loggers, so if you need a fresh start preprend your list with("", False)
or("", True)
.
Returns: list
ofint
– A list containing the identifiers of possibly started sinks.Examples
>>> logger.configure( ... handlers=[dict(sink=sys.stderr, format="[{time}] {message}"), ... dict(sink="file.log", enqueue=True, serialize=True)], ... levels=[dict(name="NEW", no=13, icon="¤", color="")], ... extra={"common_to_all": "default"}, ... activation=[("my_module.secret": False, "another_library.module": True)] ... ) [1, 2]
- handlers (
-
static
parse
(file, pattern, *, cast={}, chunk=65536)[source]¶ Parse raw logs and extract each entry as a
dict
.The logging format has to be specified as the regex
pattern
, it will then be used to parse thefile
and retrieve each entries based on the named groups present in the regex.Parameters: - file (
str
,pathlib.Path
orfile-like object
) – The path of the log file to be parsed, or alternatively an already opened file object. - pattern (
str
orre.Pattern
) – The regex to use for logs parsing, it should contain named groups which will be included in the returned dict. - cast (
function
ordict
, optional) – A function that should convert in-place the regex groups parsed (a dict of string values) to more appropiate types. If a dict is passed, its should be a mapping between keys of parsed log dict and the function that should be used to convert the associated value. - chunk (
int
, optional) – The number of bytes read while iterating through the logs, this avoid having to load the whole file in memory.
Yields: dict
– The dict mapping regex named groups to matched values, as returned byre.Match.groupdict()
and optionally converted according tocast
argument.Examples
>>> reg = r"(?P<lvl>[0-9]+): (?P<msg>.*)" # If log format is "{level.no} - {message}" >>> for e in logger.parse("file.log", reg): # A file line could be "10 - A debug message" ... print(e) # => {'lvl': '10', 'msg': 'A debug message'} ...
>>> caster = dict(lvl=int) # Parse 'lvl' key as an integer >>> for e in logger.parse("file.log", reg, cast=caster): ... print(e) # => {'lvl': 10, 'msg': 'A debug message'}
>>> def cast(groups): ... if "date" in groups: ... groups["date"] = datetime.strptime(groups["date"], "%Y-%m-%d %H:%M:%S") ... >>> with open("file.log") as file: ... for log in logger.parse(file, reg, cast=cast): ... print(log["date"], log["something_else"])
- file (
-
trace
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'TRACE'
.
-
debug
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'DEBUG'
.
-
info
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'INFO'
.
-
success
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'SUCCESS'
.
-
warning
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'WARNING'
.
-
error
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'ERROR'
.
-
critical
(_message, *args, **kwargs)¶ Log
_message.format(*args, **kwargs)
with severity'CRITICAL'
.
-