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how do I handle DEBUG level logs, raise their severity to INFO and log to stdout?

I need to raise the severity of all debug logs in my script and log them as INFO. I was intending to use a handler for this. I am importing a package that logs at DEBUG level so I cannot change the original logging level. I need them to be logged as INFO in my script.

You can consider using a file-specific logger. that way in your script you can set the severity level to DEBUG while keeping the logger in the package at its level.
In doing so you create the module logger and set its level instead of the root logger (which will demage the package's output)
This is an example of file-specific logger:
# this creates a logger specific for that "__name__" which is the name of your moduele
module_logger = logging.getLogger(__name__)
module_logger.setLevel(logging.DEBUG)
module_logger.log(...)
now you can use this logger to log while keeping everything else the same,
Hope that helped

How to separate log handlers in Python

I have a situation where I want to create two separate logger objects in Python, each with their own independent handler. By "separate," I mean that I want to be able to pass a log statement to each object independently, without contaminating the other log.
main.py
import logging
from my_other_logger import init_other_logger
logger = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO, handlers=[logging.StreamHandler(sys.stdout)])
other_logger = init_other_logger(__name__)
logger.info('Hello World') # Don't want to see this in the other logger
other_logger.info('Goodbye World') # Don't want to see this in the first logger
my_other_logger.py
import logging
import os, sys
def init_other_logger(namespace):
logger = logging.getLogger(namespace)
logger.setLevel(logging.DEBUG)
fh = logging.FileHandler(LOG_FILE_PATH)
logger.addHandler(fh)
formatter = logging.Formatter('%(levelname)s:%(name)s:%(message)s')
fh.setFormatter(formatter)
#logger.propagate = False
return logger
The only configuration I've been able to identify as useful here is the logger.propagate property. Running the code above as-is pipes all log statements to both the log stream and the log file. When I have logger.propagate = False nothing is piped to the log stream, and both log objects again pipe their output to the log file.
How can I create one log object that sends logs to only one handler, and another log object that sends logs to another handler?

Firstly, let's see what's going on before we can head over to the solution.
logger = logging.getLogger(__name__)
: when you're doing this you're getting or creating a logger with the name 'main'. Since this is the first call, it will create that logger.
other_logger = init_other_logger(__name__) : when you're doing this, again, you're getting or creating a logger with the name 'main'. Since this is the second call, it will fetch the logger created above. So you're not really instantiating a new logger, but you're getting a reference to the same logger created above. You can check this by doing a print after you call init_other_logger of the form: print(logger is other_logger).
What happens next is you add a FileHandler and a Formatter to the 'main' logger (inside the init_other_logger function), and you invoke 2 log calls via the method info(). But you're doing it with the same logger.
So this:
logger.info('Hello World')
other_logger.info('Goodbye World')
is essentially the same thing as this:
logger.info('Hello World')
logger.info('Goodbye World')
Now it's not so surprising anymore that both loggers output to both the file and stream.
Solution
So the obvious thing to do is to call your init_other_logger with another name.
I would recommend against the solution the other answer proposes because that's
NOT how things should be done when you need an independent logger. The documentation has it nicely put that you should NEVER instantiate a logger directly, but always via the function getLogger of the logging module.
As we discovered above when you do a call of logging.getLogger(logger_name) it's either getting or creating a logger with logger_name. So this works perfectly fine when you want a unique logger as well. However remember this function is idemptotent meaning it will only create a logger with a given name the first time you call it and it will return that logger if you call it with the same name no matter how many times you'll call it after.
So, for example:
a first call of the form logging.getLogger('the_rock') - creates your unique logger
a second call of the form logging.getLogger('the_rock') - fetches the above logger
You can see that this is particularly useful if you, for instance:
Have a logger configured with Formatters and Filters somewhere in your project, for instance in project_root/main_package/__init__.py.
Want to use that logger somewhere in a secondary package which sits in project_root/secondary_package/__init__.py.
In secondary_package/__init__.py you could do a simple call of the form: logger = logging.getLogger('main_package') and you'll use that logger with all its bells and whistles.
Attention!
Even if you, at this point, will use your init_other_logger function to create a unique logger it would still output to both the file and the console. Replace this line other_logger = init_other_logger(__name__) with other_logger = init_other_logger('the_rock') to create a unique logger and run the code again. You will still see the output written to both the console and the file.
Why ?
Because it will use both the FileHandler and the StreamHandler.
Why ?
Because the way the logging machinery works. Your logger will emit its message via its handlers, then it will propagate all the way up to the root logger where it will use the StreamHandler which you attached via the basicConfig call. So the propagate property you discovered is actually what you want in your case, because you're creating a custom logger, which you'd want to emit messages only via its manually attached handlers and not emit any further. Uncomment the logger.propagate = False after creating the unique logger and you'll see that everything works as expected.

Both of your handlers are installed on the same logger. This is why they aren't seperate.
logger is other_logger because logging.getLogger(__name__) is logging.getLogger(__name__)
Either create a logger directly for the second log logging.Logger(name) (I know the documentation says never to do this but if you want an entirely independent logger this is how to do it), or use a different name for the second log when calling logging.getLogger().

Getting logs twice in AWS lambda function

I'm attempting to create a centralized module to set up my log formatter to be shared across a number of python modules within my lambda function. This function will ultimately be run on AWS Greengrass on a local on-premise device.
For some reason, when I add in my own handler to format the messages the logs are being outputted twice - once at the correct log level and the second time at an incorrect level.
If I use the standard python logger without setting up any handlers it works fine e.g.
main.py:
import logging
logging.debug("test1")
cloudwatch logs:
12:28:42 [DEBUG]-main.py:38,test1
My objective is to have one formatter on my code which will format these log messages into JSON. They will then get ingested into a centralized logging database. However, when I do this I get the log messages twice.
loghelper.py:
def setup_logging(name):
formatter = logging.Formatter("%(name)s, %(asctime)s, %(message)s")
handler = logging.StreamHandler(sys.stdout)
handler.setFormatter(formatter)
logger = logging.getLogger(name)
if logger.handlers:
for handler in logger.handlers:
logger.removeHandler(handler)
logger.setLevel(logging.DEBUG)
logger.addHandler(handler)
return logger
main.py:
import logging
logger = loghelper.setup_logging('main.test_function')
def test_function():
logger.debug("test function log statement")
test_function()
When the lambda function is now run I get the debug message twice in the cloud watch logs as follows:
cloudwatch logs:
12:22:53 [DEBUG]-main.py:5, test function log statement
12:22:53 [INFO]-__init__.py:880,main.test_function,2018-06-18 12:22:53,099, test function log statement
Notice that:
The first entry is at the correct level but in the wrong format.
The second entry reports the wrong level, the wrong module but is in the correct format.
I cannot explain this behavior and would appreciate any thoughts on what could be causing it. I also don't know which constructor exists at line 880. This may shed some light on what is happening.
References:
Setting up a global formatter:
How to define a logger in python once for the whole program?
Clearing the default lambda log handlers:
Using python Logging with AWS Lambda
Creating a global logger:
Python: logging module - globally

AWS Lambda also sets up a handler, on the root logger, and anything written to stdout is captured and logged as level INFO. Your log message is thus captured twice:
By the AWS Lambda handler on the root logger (as log messages propagate from nested child loggers to the root), and this logger has its own format configured.
By the AWS Lambda stdout-to-INFO logger.
This is why the messages all start with (asctime) [(levelname)]-(module):(lineno), information; the root logger is configured to output messages with that format and the information written to stdout is just another %(message) part in that output.
Just don't set a handler when you are in the AWS environment, or, disable propagation of the output to the root handler and live with all your messages being recorded as INFO messages by AWS; in the latter case your own formatter could include the levelname level information in the output.
You can disable log propagation with logger.propagate = False, at which point your message is only going to be passed to your handler, not to to the root handler as well.
Another option is to just rely on the AWS root logger configuration. According to this excellent reverse engineering blog post the root logger is configured with:
logging.Formatter.converter = time.gmtime
logger = logging.getLogger()
logger_handler = LambdaLoggerHandler()
logger_handler.setFormatter(logging.Formatter(
'[%(levelname)s]\t%(asctime)s.%(msecs)dZ\t%(aws_request_id)s\t%(message)s\n',
'%Y-%m-%dT%H:%M:%S'
))
logger_handler.addFilter(LambdaLoggerFilter())
logger.addHandler(logger_handler)
This replaces the time.localtime converter on logging.Formatter with time.gmtime (so timestamps use UTC rather than locatime), sets a custom handler that makes sure messages go to the Lambda infrastructure, configures a format, and adds a filter object that only adds aws_request_id attribute to records (so the above formatter can include it) but doesn't actually filter anything.
You could alter the formatter on that handler by updating the attributes on the handler.formatter object:
for handler in logging.getLogger().handlers:
formatter = handler.formatter
if formatter is not None and 'aws_request_id' in formatter._fmt:
# this is the AWS Lambda formatter
# formatter.datefmt => '%Y-%m-%dT%H:%M:%S'
# formatter._style._fmt =>
# '[%(levelname)s]\t%(asctime)s.%(msecs)dZ'
# '\t%(aws_request_id)s\t%(message)s\n'
and then just drop your own logger handler entirely. You do want to be careful with this; AWS Lambda infrastructure could well be counting on a specific format being used. The output you show in your question doesn't include the date component (the %Y-%m-%dT part of the formatter.datefmt string) which probably means that the format has been parsed out and is being presented to you in a web application view of the data.

I'm not sure whether this is the cause of your problem, but by default, Python's loggers propagate their messages up to logging hierarchy. As you probably know, Python loggers are organized in a tree, with the root logger at the top and other loggers below it. In logger names, a dot (.) introduces a new hierarchy level. So if you do
logger = logging.getLogger('some_module.some_function`)
then you actually have 3 loggers:
The root logger (`logging.getLogger()`)
A logger at module level (`logging.getLogger('some_module'))
A logger at function level (`logging.getLogger('some_module.some_function'))
If you emit a log message on a logger and it is not discarded based on the loggers minimum level, then the message is passed on to the logger's handlers and to its parent logger. See this flowchart for more information.
If that parent logger (or any logger higher up in the hierarchy) also has handlers, then they are called, too.
I suspect that in your case, either the root logger or the main logger somehow ends up with some handlers attached, which leads to the duplicate messages. To avoid that, you can set propagate in your logger to False or only attach your handlers to the root logger.

Changing logging's 'basicConfig' which is already set

I am using the logging module in python as:
import logging, sys
logger= logging.getLogger(__file__)
logging.basicConfig(stream = sys.stderr, level=logging.DEBUG, format='%(filename)s:%(lineno)s %(levelname)s:%(message)s')
logger.debug("Hello World")
Now, after I have set the basic configuration on line 3, I want to have a command line argument that can change the output stream from sys.stderr to a file.
I have read the doc and it says that if both filename and stream are present at the same time, the stream is ignored.
Now, I wanna know how do change the stream to a file after I have already done the basicConfig thing in line 3?

If you look in the Python sources for logging/__init__.py, you'll see that basicConfig() sets the handlers on the root logger object by calling addHandler(). If you want to start from scratch, you could remove all existing handlers and then call basicConfig() again.
# Example to remove all root logger handlers and reconfigure. (UNTESTED)
import logging
# Remove all handlers associated with the root logger object.
for handler in logging.root.handlers[:]:
logging.root.removeHandler(handler)
# Reconfigure logging again, this time with a file.
logging.basicConfig(filename = 'myfile.log', level=logging.DEBUG, format='%(filename)s:%(lineno)s %(levelname)s:%(message)s')

Attribution to be given in Spack, for his comment. I am just expanding the idea in a proper answer
In 2022 and using Python 3.8, we can use the force input of basicConfig method
As per Python documentation
force
If this keyword argument is specified as true, any existing handlers
attached to the root logger are removed and closed, before carrying
out the configuration as specified by the other arguments.
Based on OP code sample, can just add the following line
logging.basicConfig(filename = 'my_file.log', level = logging.DEBUG, format = '%(filename)s:%(lineno)s %(levelname)s:%(message)s', force = True)

Python logging before you run logging.basicConfig?

It appears that if you invoke logging.info() BEFORE you run logging.basicConfig, the logging.basicConfig call doesn't have any effect. In fact, no logging occurs.
Where is this behavior documented? I don't really understand.

You can remove the default handlers and reconfigure logging like this:
# if someone tried to log something before basicConfig is called, Python creates a default handler that
# goes to the console and will ignore further basicConfig calls. Remove the handler if there is one.
root = logging.getLogger()
if root.handlers:
for handler in root.handlers:
root.removeHandler(handler)
logging.basicConfig(format='%(asctime)s %(message)s',level=logging.DEBUG)

Yes.
You've asked to log something. Logging must, therefore, fabricate a default configuration. Once logging is configured... well... it's configured.
"With the logger object configured,
the following methods create log
messages:"
Further, you can read about creating handlers to prevent spurious logging. But that's more a hack for bad implementation than a useful technique.
There's a trick to this.
No module can do anything except logging.getlogger() requests at a global level.
Only the if __name__ == "__main__": can do a logging configuration.
If you do logging at a global level in a module, then you may force logging to fabricate it's default configuration.
Don't do logging.info globally in any module. If you absolutely think that you must have logging.info at a global level in a module, then you have to configure logging before doing imports. This leads to unpleasant-looking scripts.

This answer from Carlos A. Ibarra is in principle right, however that implementation might break since you are iterating over a list that might be changed by calling removeHandler(). This is unsafe.
Two alternatives are:
while len(logging.root.handlers) > 0:
logging.root.removeHandler(logging.root.handlers[-1])
logging.basicConfig(format='%(asctime)s %(message)s',level=logging.DEBUG)
or:
logging.root.handlers = []
logging.basicConfig(format='%(asctime)s %(message)s',level=logging.DEBUG)
where the first of these two using the loop is the safest (since any destruction code for the handler can be called explicitly inside the logging framework). Still, this is a hack, since we rely on logging.root.handlers to be a list.

Here's the one piece of the puzzle that the above answers didn't mention... and then it will all make sense: the "root" logger -- which is used if you call, say, logging.info() before logging.basicConfig(level=logging.DEBUG) -- has a default logging level of WARNING.
That's why logging.info() and logging.debug() don't do anything: because you've configured them not to, by... um... not configuring them.
Possibly related (this one bit me): when NOT calling basicConfig, I didn't seem to be getting my debug messages, even though I set my handlers to DEBUG level. After a bit of hair-pulling, I found you have to set the level of the custom logger to be DEBUG as well. If your logger is set to WARNING, then setting a handler to DEBUG (by itself) won't get you any output on logger.info() and logger.debug().

Ran into this same issue today and, as an alternative to the answers above, here's my solution.
import logging
import sys
logging.debug('foo') # IRL, this call is from an imported module
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO, force=True)
logging.info('bar') # without force=True, this is not printed to the console
Here's what the docs say about the force argument.
If this keyword argument is specified as true, any existing handlers
attached to the root logger are removed and closed, before carrying
out the configuration as specified by the other arguments.

A cleaner version of the answer given by #paul-kremer is:
while len(logging.root.handlers):
logging.root.removeHandler(logging.root.handlers[-1])
Note: it is generally safe to assume logging.root.handlers will always be a list (see: https://github.com/python/cpython/blob/cebe9ee988837b292f2c571e194ed11e7cd4abbb/Lib/logging/init.py#L1253)

Here is what I did.
I wanted to log to a file which has a name configured in a config-file and also get the debug-logs of the config-parsing.
TL;DR; This logs into a buffer until everything to configure the logger is available
# Log everything into a MemoryHandler until the real logger is ready.
# The MemoryHandler never flushes (flushLevel 100 is above CRITICAL) automatically but only on close.
# If the configuration was loaded successfully, the real logger is configured and set as target of the MemoryHandler
# before it gets flushed by closing.
# This means, that if the log gets to stdout, it is unfiltered by level
root_logger = logging.getLogger()
root_logger.setLevel(logging.NOTSET)
stdout_logging_handler = logging.StreamHandler(sys.stderr)
tmp_logging_handler = logging.handlers.MemoryHandler(1024 * 1024, 100, stdout_logging_handler)
root_logger.addHandler(tmp_logging_handler)
config: ApplicationConfig = ApplicationConfig.from_filename('config.ini')
# because the records are already logged, unwanted ones need to be removed
filtered_buffer = filter(lambda record: record.levelno >= config.main_config.log_level, tmp_logging_handler.buffer)
tmp_logging_handler.buffer = filtered_buffer
root_logger.removeHandler(tmp_logging_handler)
logging.basicConfig(filename=config.main_config.log_filename, level=config.main_config.log_level, filemode='wt')
logging_handler = root_logger.handlers[0]
tmp_logging_handler.setTarget(logging_handler)
tmp_logging_handler.close()
stdout_logging_handler.close()