I'd like to have loglevel TRACE (5) for my application, as I don't think that debug() is sufficient. Additionally log(5, msg) isn't what I want. How can I add a custom loglevel to a Python logger?
I've a mylogger.py with the following content:
import logging
#property
def log(obj):
myLogger = logging.getLogger(obj.__class__.__name__)
return myLogger
In my code I use it in the following way:
class ExampleClass(object):
from mylogger import log
def __init__(self):
'''The constructor with the logger'''
self.log.debug("Init runs")
Now I'd like to call self.log.trace("foo bar")
Edit (Dec 8th 2016): I changed the accepted answer to pfa's which is, IMHO, an excellent solution based on the very good proposal from Eric S.
To people reading in 2022 and beyond: you should probably check out the currently next-highest-rated answer here: https://stackoverflow.com/a/35804945/1691778
My original answer is below.
--
#Eric S.
Eric S.'s answer is excellent, but I learned by experimentation that this will always cause messages logged at the new debug level to be printed -- regardless of what the log level is set to. So if you make a new level number of 9, if you call setLevel(50), the lower level messages will erroneously be printed.
To prevent that from happening, you need another line inside the "debugv" function to check if the logging level in question is actually enabled.
Fixed example that checks if the logging level is enabled:
import logging
DEBUG_LEVELV_NUM = 9
logging.addLevelName(DEBUG_LEVELV_NUM, "DEBUGV")
def debugv(self, message, *args, **kws):
if self.isEnabledFor(DEBUG_LEVELV_NUM):
# Yes, logger takes its '*args' as 'args'.
self._log(DEBUG_LEVELV_NUM, message, args, **kws)
logging.Logger.debugv = debugv
If you look at the code for class Logger in logging.__init__.py for Python 2.7, this is what all the standard log functions do (.critical, .debug, etc.).
I apparently can't post replies to others' answers for lack of reputation... hopefully Eric will update his post if he sees this. =)
Combining all of the existing answers with a bunch of usage experience, I think that I have come up with a list of all the things that need to be done to ensure completely seamless usage of the new level. The steps below assume that you are adding a new level TRACE with value logging.DEBUG - 5 == 5:
logging.addLevelName(logging.DEBUG - 5, 'TRACE') needs to be invoked to get the new level registered internally so that it can be referenced by name.
The new level needs to be added as an attribute to logging itself for consistency: logging.TRACE = logging.DEBUG - 5.
A method called trace needs to be added to the logging module. It should behave just like debug, info, etc.
A method called trace needs to be added to the currently configured logger class. Since this is not 100% guaranteed to be logging.Logger, use logging.getLoggerClass() instead.
All the steps are illustrated in the method below:
def addLoggingLevel(levelName, levelNum, methodName=None):
"""
Comprehensively adds a new logging level to the `logging` module and the
currently configured logging class.
`levelName` becomes an attribute of the `logging` module with the value
`levelNum`. `methodName` becomes a convenience method for both `logging`
itself and the class returned by `logging.getLoggerClass()` (usually just
`logging.Logger`). If `methodName` is not specified, `levelName.lower()` is
used.
To avoid accidental clobberings of existing attributes, this method will
raise an `AttributeError` if the level name is already an attribute of the
`logging` module or if the method name is already present
Example
-------
>>> addLoggingLevel('TRACE', logging.DEBUG - 5)
>>> logging.getLogger(__name__).setLevel("TRACE")
>>> logging.getLogger(__name__).trace('that worked')
>>> logging.trace('so did this')
>>> logging.TRACE
5
"""
if not methodName:
methodName = levelName.lower()
if hasattr(logging, levelName):
raise AttributeError('{} already defined in logging module'.format(levelName))
if hasattr(logging, methodName):
raise AttributeError('{} already defined in logging module'.format(methodName))
if hasattr(logging.getLoggerClass(), methodName):
raise AttributeError('{} already defined in logger class'.format(methodName))
# This method was inspired by the answers to Stack Overflow post
# http://stackoverflow.com/q/2183233/2988730, especially
# http://stackoverflow.com/a/13638084/2988730
def logForLevel(self, message, *args, **kwargs):
if self.isEnabledFor(levelNum):
self._log(levelNum, message, args, **kwargs)
def logToRoot(message, *args, **kwargs):
logging.log(levelNum, message, *args, **kwargs)
logging.addLevelName(levelNum, levelName)
setattr(logging, levelName, levelNum)
setattr(logging.getLoggerClass(), methodName, logForLevel)
setattr(logging, methodName, logToRoot)
You can find an even more detailed implementation in the utility library I maintain, haggis. The function haggis.logs.add_logging_level is a more production-ready implementation of this answer.
I took the avoid seeing "lambda" answer and had to modify where the log_at_my_log_level was being added. I too saw the problem that Paul did – I don't think this works. Don't you need logger as the first arg in log_at_my_log_level? This worked for me
import logging
DEBUG_LEVELV_NUM = 9
logging.addLevelName(DEBUG_LEVELV_NUM, "DEBUGV")
def debugv(self, message, *args, **kws):
# Yes, logger takes its '*args' as 'args'.
self._log(DEBUG_LEVELV_NUM, message, args, **kws)
logging.Logger.debugv = debugv
This question is rather old, but I just dealt with the same topic and found a way similiar to those already mentioned which appears a little cleaner to me. This was tested on 3.4, so I'm not sure whether the methods used exist in older versions:
from logging import getLoggerClass, addLevelName, setLoggerClass, NOTSET
VERBOSE = 5
class MyLogger(getLoggerClass()):
def __init__(self, name, level=NOTSET):
super().__init__(name, level)
addLevelName(VERBOSE, "VERBOSE")
def verbose(self, msg, *args, **kwargs):
if self.isEnabledFor(VERBOSE):
self._log(VERBOSE, msg, args, **kwargs)
setLoggerClass(MyLogger)
While we have already plenty of correct answers, the following is in my opinion more pythonic:
import logging
from functools import partial, partialmethod
logging.TRACE = 5
logging.addLevelName(logging.TRACE, 'TRACE')
logging.Logger.trace = partialmethod(logging.Logger.log, logging.TRACE)
logging.trace = partial(logging.log, logging.TRACE)
If you want to use mypy on your code, it is recommended to add # type: ignore to suppress warnings from adding attribute.
Who started the bad practice of using internal methods (self._log) and why is each answer based on that?! The pythonic solution would be to use self.log instead so you don't have to mess with any internal stuff:
import logging
SUBDEBUG = 5
logging.addLevelName(SUBDEBUG, 'SUBDEBUG')
def subdebug(self, message, *args, **kws):
self.log(SUBDEBUG, message, *args, **kws)
logging.Logger.subdebug = subdebug
logging.basicConfig()
l = logging.getLogger()
l.setLevel(SUBDEBUG)
l.subdebug('test')
l.setLevel(logging.DEBUG)
l.subdebug('test')
I think you'll have to subclass the Logger class and add a method called trace which basically calls Logger.log with a level lower than DEBUG. I haven't tried this but this is what the docs indicate.
I find it easier to create a new attribute for the logger object that passes the log() function. I think the logger module provides the addLevelName() and the log() for this very reason. Thus no subclasses or new method needed.
import logging
#property
def log(obj):
logging.addLevelName(5, 'TRACE')
myLogger = logging.getLogger(obj.__class__.__name__)
setattr(myLogger, 'trace', lambda *args: myLogger.log(5, *args))
return myLogger
now
mylogger.trace('This is a trace message')
should work as expected.
Tips for creating a custom logger:
Do not use _log, use log (you don't have to check isEnabledFor)
the logging module should be the one creating instance of the custom logger since it does some magic in getLogger, so you will need to set the class via setLoggerClass
You do not need to define __init__ for the logger, class if you are not storing anything
# Lower than debug which is 10
TRACE = 5
class MyLogger(logging.Logger):
def trace(self, msg, *args, **kwargs):
self.log(TRACE, msg, *args, **kwargs)
When calling this logger use setLoggerClass(MyLogger) to make this the default logger from getLogger
logging.setLoggerClass(MyLogger)
log = logging.getLogger(__name__)
# ...
log.trace("something specific")
You will need to setFormatter, setHandler, and setLevel(TRACE) on the handler and on the log itself to actually se this low level trace
This worked for me:
import logging
logging.basicConfig(
format=' %(levelname)-8.8s %(funcName)s: %(message)s',
)
logging.NOTE = 32 # positive yet important
logging.addLevelName(logging.NOTE, 'NOTE') # new level
logging.addLevelName(logging.CRITICAL, 'FATAL') # rename existing
log = logging.getLogger(__name__)
log.note = lambda msg, *args: log._log(logging.NOTE, msg, args)
log.note('school\'s out for summer! %s', 'dude')
log.fatal('file not found.')
The lambda/funcName issue is fixed with logger._log as #marqueed pointed out. I think using lambda looks a bit cleaner, but the drawback is that it can't take keyword arguments. I've never used that myself, so no biggie.
NOTE setup: school's out for summer! dude
FATAL setup: file not found.
As alternative to adding an extra method to the Logger class I would recommend using the Logger.log(level, msg) method.
import logging
TRACE = 5
logging.addLevelName(TRACE, 'TRACE')
FORMAT = '%(levelname)s:%(name)s:%(lineno)d:%(message)s'
logging.basicConfig(format=FORMAT)
l = logging.getLogger()
l.setLevel(TRACE)
l.log(TRACE, 'trace message')
l.setLevel(logging.DEBUG)
l.log(TRACE, 'disabled trace message')
In my experience, this is the full solution the the op's problem... to avoid seeing "lambda" as the function in which the message is emitted, go deeper:
MY_LEVEL_NUM = 25
logging.addLevelName(MY_LEVEL_NUM, "MY_LEVEL_NAME")
def log_at_my_log_level(self, message, *args, **kws):
# Yes, logger takes its '*args' as 'args'.
self._log(MY_LEVEL_NUM, message, args, **kws)
logger.log_at_my_log_level = log_at_my_log_level
I've never tried working with a standalone logger class, but I think the basic idea is the same (use _log).
Addition to Mad Physicists example to get file name and line number correct:
def logToRoot(message, *args, **kwargs):
if logging.root.isEnabledFor(levelNum):
logging.root._log(levelNum, message, args, **kwargs)
based on pinned answer,
i wrote a little method which automaticaly create new logging levels
def set_custom_logging_levels(config={}):
"""
Assign custom levels for logging
config: is a dict, like
{
'EVENT_NAME': EVENT_LEVEL_NUM,
}
EVENT_LEVEL_NUM can't be like already has logging module
logging.DEBUG = 10
logging.INFO = 20
logging.WARNING = 30
logging.ERROR = 40
logging.CRITICAL = 50
"""
assert isinstance(config, dict), "Configuration must be a dict"
def get_level_func(level_name, level_num):
def _blank(self, message, *args, **kws):
if self.isEnabledFor(level_num):
# Yes, logger takes its '*args' as 'args'.
self._log(level_num, message, args, **kws)
_blank.__name__ = level_name.lower()
return _blank
for level_name, level_num in config.items():
logging.addLevelName(level_num, level_name.upper())
setattr(logging.Logger, level_name.lower(), get_level_func(level_name, level_num))
config may smth like that:
new_log_levels = {
# level_num is in logging.INFO section, that's why it 21, 22, etc..
"FOO": 21,
"BAR": 22,
}
Someone might wanna do, a root level custom logging; and avoid the usage of logging.get_logger(''):
import logging
from datetime import datetime
c_now=datetime.now()
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] :: %(message)s",
handlers=[
logging.StreamHandler(),
logging.FileHandler("../logs/log_file_{}-{}-{}-{}.log".format(c_now.year,c_now.month,c_now.day,c_now.hour))
]
)
DEBUG_LEVELV_NUM = 99
logging.addLevelName(DEBUG_LEVELV_NUM, "CUSTOM")
def custom_level(message, *args, **kws):
logging.Logger._log(logging.root,DEBUG_LEVELV_NUM, message, args, **kws)
logging.custom_level = custom_level
# --- --- --- ---
logging.custom_level("Waka")
I'm confused; with python 3.5, at least, it just works:
import logging
TRACE = 5
"""more detail than debug"""
logging.basicConfig()
logging.addLevelName(TRACE,"TRACE")
logger = logging.getLogger('')
logger.debug("n")
logger.setLevel(logging.DEBUG)
logger.debug("y1")
logger.log(TRACE,"n")
logger.setLevel(TRACE)
logger.log(TRACE,"y2")
output:
DEBUG:root:y1
TRACE:root:y2
Following up on the top-rated answers by Eric S. and Mad Physicist:
Fixed example that checks if the logging level is enabled:
import logging
DEBUG_LEVELV_NUM = 9
logging.addLevelName(DEBUG_LEVELV_NUM, "DEBUGV")
def debugv(self, message, *args, **kws):
if self.isEnabledFor(DEBUG_LEVELV_NUM):
# Yes, logger takes its '*args' as 'args'.
self._log(DEBUG_LEVELV_NUM, message, args, **kws)
logging.Logger.debugv = debugv
This code-snippet
adds a new log-level "DEBUGV" and assigns a number 9
defines a debugv-method, which logs a message with level "DEBUGV" unless the log-level is set to a value higher than 9 (e.g. log-level "DEBUG")
monkey-patches the logging.Logger-class, so that you can call logger.debugv
The suggested implementation worked well for me, but
code completion doesn't recognise the logger.debugv-method
pyright, which is part of our CI-pipeline, fails, because it cannot trace the debugv-member method of the Logger-class (see https://github.com/microsoft/pylance-release/issues/2335 about dynamically adding member-methods)
I ended up using inheritance as was suggested in Noufal Ibrahim's answer in this thread:
I think you'll have to subclass the Logger class and add a method called trace which basically calls Logger.log with a level lower than DEBUG. I haven't tried this but this is what the docs indicate.
Implementing Noufal Ibrahim's suggestion worked and pyright is happy:
import logging
# add log-level DEBUGV
DEBUGV = 9 # slightly lower than DEBUG (10)
logging.addLevelName(DEBUGV, "DEBUGV")
class MyLogger(logging.Logger):
"""Inherit from standard Logger and add level DEBUGV."""
def debugv(self, msg, *args, **kwargs):
"""Log 'msg % args' with severity 'DEBUGV'."""
if self.isEnabledFor(DEBUGV):
self._log(DEBUGV, msg, args, **kwargs)
logging.setLoggerClass(MyLogger)
Next you can initialise an instance of the extended logger using the logger-manager:
logger = logging.getLogger("whatever_logger_name")
Edit: In order to make pyright recognise the debugv-method, you may need to cast the logger returned by logging.getLogger, which would like this:
import logging
from typing import cast
logger = cast(MyLogger, logging.getLogger("whatever_logger_name"))
In case anyone wants an automated way to add a new logging level to the logging module (or a copy of it) dynamically, I have created this function, expanding #pfa's answer:
def add_level(log_name,custom_log_module=None,log_num=None,
log_call=None,
lower_than=None, higher_than=None, same_as=None,
verbose=True):
'''
Function to dynamically add a new log level to a given custom logging module.
<custom_log_module>: the logging module. If not provided, then a copy of
<logging> module is used
<log_name>: the logging level name
<log_num>: the logging level num. If not provided, then function checks
<lower_than>,<higher_than> and <same_as>, at the order mentioned.
One of those three parameters must hold a string of an already existent
logging level name.
In case a level is overwritten and <verbose> is True, then a message in WARNING
level of the custom logging module is established.
'''
if custom_log_module is None:
import imp
custom_log_module = imp.load_module('custom_log_module',
*imp.find_module('logging'))
log_name = log_name.upper()
def cust_log(par, message, *args, **kws):
# Yes, logger takes its '*args' as 'args'.
if par.isEnabledFor(log_num):
par._log(log_num, message, args, **kws)
available_level_nums = [key for key in custom_log_module._levelNames
if isinstance(key,int)]
available_levels = {key:custom_log_module._levelNames[key]
for key in custom_log_module._levelNames
if isinstance(key,str)}
if log_num is None:
try:
if lower_than is not None:
log_num = available_levels[lower_than]-1
elif higher_than is not None:
log_num = available_levels[higher_than]+1
elif same_as is not None:
log_num = available_levels[higher_than]
else:
raise Exception('Infomation about the '+
'log_num should be provided')
except KeyError:
raise Exception('Non existent logging level name')
if log_num in available_level_nums and verbose:
custom_log_module.warn('Changing ' +
custom_log_module._levelNames[log_num] +
' to '+log_name)
custom_log_module.addLevelName(log_num, log_name)
if log_call is None:
log_call = log_name.lower()
setattr(custom_log_module.Logger, log_call, cust_log)
return custom_log_module
While subclassing logging.Handler, I can make a custom handler by doing something like:
import requests
import logging
class RequestsHandler(logging.Handler):
def emit(self, record):
res = requests.get('http://google.com')
print (res, record)
handler = RequestsHandler()
logger = logging.getLogger(__name__)
logger.addHandler(handler)
logger.warning('ok!')
# <Response [200]> <LogRecord: __main__, 30, <stdin>, 1, "ok!">
What would be the simplest RequestHandler (i.e., what methods would it need?) if it was just a base class without subclassing logging.Handler ?
In general, you can find out which attributes of a class is getting accessed externally by overriding the __getattribue__ method with a wrapper function
that adds the name of the attribute being accessed to a set if the caller's class is not the same as the current class:
import logging
import sys
class MyHandler(logging.Handler):
def emit(self, record):
pass
def show_attribute(self, name):
caller_locals = sys._getframe(1).f_locals
if ('self' not in caller_locals or
object.__getattribute__(caller_locals['self'], '__class__') is not
object.__getattribute__(self, '__class__')):
attributes.add(name)
return original_getattribute(self, name)
attributes = set()
original_getattribute = MyHandler.__getattribute__
MyHandler.__getattribute__ = show_attribute
so that:
handler = MyHandler()
logger = logging.getLogger(__name__)
logger.addHandler(handler)
logger.warning('ok!')
print(attributes)
outputs:
{'handle', 'level'}
Demo: https://repl.it/#blhsing/UtterSoupyCollaborativesoftware
As you see from the result above, handle and level are the only attributes needed for a basic logging handler. In other words, #jirassimok is correct in that handle is the only method of the Handler class that is called externally, but one also needs to implement the level attribute as well since it is also directly accessed in the Logger.callHandlers method:
if record.levelno >= hdlr.level:
where the level attribute has to be an integer, and should be 0 if records of all logging levels are to be handled.
A minimal implementation of a Handler class should therefore be something like:
class MyHandler:
def __init__(self):
self.level = 0
def handle(self, record):
print(record.msg)
so that:
handler = MyHandler()
logger = logging.getLogger(__name__)
logger.addHandler(handler)
logger.warning('ok!')
outputs:
ok!
Looking at the source for Logger.log leads me to Logger.callHandlers, which calls only handle on the handlers. So that might be the minimum you need if you're injecting the fake handler directly into a logger instance.
If you want to really guarantee compatibility with the rest of the logging module, the only thing you can do is go through the module's source to figure out how it works. The documentation is a good starting place, but that doesn't get into the internals much at all.
If you're just trying to write a dummy handler for a small use case, you could probably get away with skipping a lot of steps; try something, see where it fails, and build on that.
Otherwise, you won't have much choice but to dive into the source code (though trying things and seeing what breaks can also be a good way to find places to start reading).
A quick glance at the class' source tells me that the only gotchas in the class are related to the module's internal management of its objects; Handler.__init__ puts the handler into a global handler list, which the module could use in any number of places. But beyond that, the class is quite straightforward; it shouldn't be too hard to read.
I'm using pytest-3.7.1 which has good support for logging, including live logging to stdout during tests. I'm using --log-cli-level=DEBUG to dump all debug-level logging to the console as it happens.
The problem I have is that --log-cli-level=DEBUG turns on debug logging for all modules in my test program, including third-party dependencies, and it floods the log with a lot of uninteresting output.
Python's logging module has the ability to set logging levels per module. This enables selective logging - for example, in a normal Python program I can turn on debugging for just one or two of my own modules, and restrict the log output to just those, or set different log levels for each module. This enables turning off debug-level logging for noisy libraries.
So what I'd like to do is apply the same concept to pytest's logging - i.e. specify a logging level, from the command line, for specific non-root loggers. For example, if I have a module called test_foo.py then I'm looking for a way to set the log level for this module from the command line.
I'm prepared to roll-my-own if necessary (I know how to add custom arguments to pytest), but before I do that I just want to be sure that there isn't already a solution. Is anyone aware of one?
I had the same problem, and found a solution in another answer:
Instead of --log-cli-level=DEBUG, use --log-level DEBUG. It disables all third-party module logs (in my case, I had plenty of matplotlib logs), but still outputs your app logs for each test that fails.
I got this working by writing a factory class and using it to set the level of the root logger to logger.INFO and use the logging level from the command line for all the loggers obtained from the factory. If the logging level from the command line is higher than the minimum global log level you specify in the class (using constant MINIMUM_GLOBAL_LOG_LEVEL), the global log level isn't changed.
import logging
MODULE_FIELD_WIDTH_IN_CHARS = '20'
LINE_NO_FIELD_WIDTH_IN_CHARS = '3'
LEVEL_NAME_FIELD_WIDTH_IN_CHARS = '8'
MINIMUM_GLOBAL_LOG_LEVEL = logging.INFO
class EasyLogger():
root_logger = logging.getLogger()
specified_log_level = root_logger.level
format_string = '{asctime} '
format_string += '{module:>' + MODULE_FIELD_WIDTH_IN_CHARS + 's}'
format_string += '[{lineno:' + LINE_NO_FIELD_WIDTH_IN_CHARS + 'd}]'
format_string += '[{levelname:^' + LEVEL_NAME_FIELD_WIDTH_IN_CHARS + 's}]: '
format_string += '{message}'
level_change_warning_sent = False
#classmethod
def get_logger(cls, logger_name):
if not EasyLogger._logger_has_format(cls.root_logger, cls.format_string):
EasyLogger._setup_root_logger()
logger = logging.getLogger(logger_name)
logger.setLevel(cls.specified_log_level)
return logger
#classmethod
def _setup_root_logger(cls):
formatter = logging.Formatter(fmt=cls.format_string, style='{')
if not cls.root_logger.hasHandlers():
handler = logging.StreamHandler()
cls.root_logger.addHandler(handler)
for handler in cls.root_logger.handlers:
handler.setFormatter(formatter)
cls.root_logger.setLevel(MINIMUM_GLOBAL_LOG_LEVEL)
if (cls.specified_log_level < MINIMUM_GLOBAL_LOG_LEVEL and
cls.level_change_warning_sent is False):
cls.root_logger.log(
max(cls.specified_log_level, logging.WARNING),
"Setting log level for %s class to %s, all others to %s" % (
__name__,
cls.specified_log_level,
MINIMUM_GLOBAL_LOG_LEVEL
)
)
cls.level_change_warning_sent = True
#staticmethod
def _logger_has_format(logger, format_string):
for handler in logger.handlers:
return handler.format == format_string
return False
The above class is then used to send logs normally as you would with a logging.logger object as follows:
from EasyLogger import EasyLogger
class MySuperAwesomeClass():
def __init__(self):
self.logger = EasyLogger.get_logger(__name__)
def foo(self):
self.logger.debug("debug message")
self.logger.info("info message")
self.logger.warning("warning message")
self.logger.critical("critical message")
self.logger.error("error message")
Enable/Disable/Modify the log level of any module in Python:
logging.getLogger("module_name").setLevel(logging.log_level)
I'm new to classes so using an example I found online to add some custom logging levels. This will be contained in a library which will be importrd into various scripts. It is working as expected but the added levels don't show up in the autocomplete list (using PyCharm) and PyCharm complains of an unresolved attribute reference in LOGGER. When I'm coding and enter 'LOGGER.' I see the normal error, warning, info, etc. to choose from but my custom level 'verbose' is not in the list. There will be more custom levels added as time go by and this will also be rolled out to a team of developers so I need to have this working.
Any idea why verbose is not an option in my autocomplete list?
Here are my files.
px_logger.py
from logging import getLoggerClass, addLevelName, setLoggerClass, NOTSET
public class PxLogger(getLoggerClass()):
def __init__(self, name, level=NOTSET):
super(PxLogger, self).__init__(name, level)
addLevelName(5, "VERBOSE")
def verbose(self, msg, *args, **kwargs):
"""Custom logger level - verbose"""
if self.isEnabledFor(5):
self._log(5, msg, args, **kwargs)
my_script.py
import json
import logging.config
from px_logger import PxLogger
logging.setLoggerClass(PxLogger)
LOGGER = logging.getLogger(__name__)
with open('../logging.json') as f: # load logging config file
CONFIG_DICT = json.load(f)
logging.config.dictConfig(CONFIG_DICT)
LOGGER.verbose('Test verbose message')
Screen output
VERBOSE - Test verbose message
PyCharm offers various ways to accomplish type hinting
Internally, it uses Typeshed to determine the types of standard lib objects and common 3rd party packages.
That's also where PyCharm takes the type of the return value for logging.getLogger from and that's why it does not show your subclass' verbose method in autocomplete, because it assumes LOGGER to be an instance of logging.Logger.
The easiest way to tell PyCharm's type checker that LOGGER is an instance of PxLogger would be a type annotation in the code during assignment. This works in Python 3.5+ only:
LOGGER: PxLogger = logging.getLogger(__name__)
If you went one step further, you would encapsulate the definition of your custom logger class, it being assigned as global logger class and the definition of a wrapper for logging.getLogger inside your module.
This would enable your coworkers to just import your module instead of logging and use it just as they would with the original logging without having to worry about which class to set as logger class or how to annotate the variable that holds their logger.
There's three options to include type hinting for the type checker when going down this road.
px_logger.py
# basically, import from logging whatever you may need and overwrite where necessary
from logging import getLogger as _getLogger, Logger, addLevelName, setLoggerClass, NOTSET
from typing import Optional # this only for the Python 3.5+ solution
class PxLogger(Logger): # Note: subclass logging.Logger explicitly
def __init__(self, name, level=NOTSET):
super(PxLogger, self).__init__(name, level)
addLevelName(5, "VERBOSE")
def verbose(self, msg, *args, **kwargs):
"""Custom logger level - verbose"""
if self.isEnabledFor(5):
self._log(5, msg, args, **kwargs)
setLoggerClass(PxLogger)
"""
Possible approaches, implement one of the below.
The first is Python 3.5+ only.
The second and third work for both, Python 2 and Python 3.
"""
# using type annotation syntax (py35+)
def getLogger(name: Optional[str]=None) -> PxLogger:
_logr: PxLogger = _getLogger(name)
return _logr
# using (legacy) docstring syntax (py2and3)
def getLogger(name=None)
"""
:param name: str
:rtype: PxLogger
"""
return _getLogger(name)
# using a stub file (py2and3)
def getLogger(name=None):
return _getLogger(name)
The Python 2and3 stub file approach requires a file named py_logger.pyi next to the actual module file px_logger.py in your package.
px_logger.pyi
# The PEP-484 syntax does not matter here.
# The Python interpreter will ignore this file,
# it is only relevant for the static type checker
import logging
class PxLogger(logging.Logger):
def verbose(self, msg, *args, **kwargs) -> None: ...
def getLogger(name) -> PxLogger: ...
For all three approaches, your module my_script would look the same:
my_script.py
import logging.config
import px_logger
LOGGER = px_logger.getLogger(__name__)
# I used basicConfig here for simplicity, dictConfig should work just as well
logging.basicConfig(level=5,
format='%(asctime)s - %(levelname)s [%(filename)s]: %(name)s %(funcName)20s - Message: %(message)s',
datefmt='%d.%m.%Y %H:%M:%S',
filename='myapp.log',
filemode='a')
LOGGER.verbose('Test verbose message')
Autocomplete works well with all three approaches:
Approach two and three have been tested with Python 2.7.15 and 3.6.5 in PyCharm 2018.1 CE
NOTE:
In a previous revision of this answer I stated that the docstring approach, although showing the custom verbose() method of your PxLogger class, is missing the base class' methods. That is because you derive PxLogger from whatever logging.getLoggerClass returns, i.e. an arbitrary class.
If you make PxLogger a subclass of logging.Logger explicitly, the type checker knows the base class and can correctly resolve its methods for autocompletion.
I do not recommend subclassing the return value of getLoggerClass anyway. You'll want to be sure what you derive from and not rely on a function returning the correct thing.
Annotate the variable with a typing.
LOGGER: PxLogger = logging.getLogger(__name__)
EDIT:
The solution above works for Python 3.6+. Use # type: type comments for previous versions, as noted by #pLOPeGG in comments.
LOGGER = logging.getLogger(__name__) # type: PxLogger