Develop Reference

How to disable discord.py logger?

So I've tried to add some logger to my discord bot, to see logs in file not just in console, cause obviously it's irritating when I reset app and find out that I have to check logs that I've already destroyed, I set it up like this:
logging.basicConfig(filename='CoronaLog.log', level=logging.DEBUG, format='%(levelname)s %(asctime)s %(message)s')
And learned the hard way that discord.py library has its own logger installed so now my logs look like one big mess, is there any way to disable discord.py's logging, or at least output it to another file?
EDIT: I've tried creating two loggers, so it would look like this:
logging.basicConfig(filename='discord.log', level=logging.DEBUG, format='%(levelname)s %(asctime)s %(message)s')
nonDiscordLog = logging.getLogger('discord')
handler = logging.FileHandler(filename='CoronaLog.log', encoding='utf-8', mode='w')
handler.setFormatter(logging.Formatter('%(levelname)s %(asctime)s:%(name)s: %(message)s'))
nonDiscordLog.addHandler(handler)
So the discord log, would be logged as the basic config says to discord.log file and, when executed like this:
nonDiscordLog.info("execution took %s seconds \n" % (time.time() - startTime))
would log into CoronaLog.log file, although it didn't really change anything

discord.py is in this regard terribly unintuitive for everyone but beginners, anyway after confronting the docs you can find out that this behavior can be avoided with:
import discord
client = discord.Client(intents=discord.Intents.all())
# Your regular code here
client.run(__YOURTOKEN__, log_handler=None)
Of course, you can supplement your own logger instead of None but to answer your question exactly, this is how you can disable discord.py's logging.
There's actually a bit more that you can do with the default logging, and you can read all about it on
the official docs

https://discordpy.readthedocs.io/en/latest/logging.html says:
"discord.py logs errors and debug information via the logging python module. It is strongly recommended that the logging module is configured, as no errors or warnings will be output if it is not set up. Configuration of the logging module can be as simple as:
import logging
logging.basicConfig(level=logging.INFO)
Placed at the start of the application. This will output the logs from discord as well as other libraries that use the logging module directly to the console."
Maybe try configuring logging a different way? Because when starting logging, it appears to initialize discord.py's llogging. maybe try
import logging
# Setup logging...
import discord
Maybe if you import it afterwords, it won't set it up.

How to enable logging so messages kept internally until get/clear?

In an application I want to collect messages related to some dedicated part of the processing, and then show these messages later at user request. I would like to report severity (e.g. info, warning), time of message, etc., so for this I considered to use the Python standard logging module to collect the messages and related information. However, I don't want these messages to go to a console or file.
Is there a way to create a Python logger, using logging, where the messages are kept internally (in memory) only, until read out by the application. I would expect start of code like:
log = logging.getLogger('my_logger')
... some config of log for internal only; not to console
log.error('Just some error')
... some code to get/clear messages in log until now
I have tried to look in logging — Logging facility for Python, but most example are for immediate output to file or console, so an example for internal logging or reference is appreciated.

You should just use another handler. You could use a StreamHandler over an io.StringIO that would simply log to memory:
log = logging.getLogger('my_logger')
memlog = io.StringIO()
log.addHandler(logging.StreamHandler(memlog))
All logging sent to log can be found in memlog.getvalue()
Of course, this is just a simple Handler that concatenates everything in one single string, even if for versions >= 3.2 each record is terminated, by default with a \n. For more specific requirements, you could have a look at a QueueHandler or implement a dedicated Handler.
References: logging.handlers in the Python Standard Library reference manual.

How can I completely remove any logging from requests module in Python

How can I completely remove any logging from requests module in Python? I don't need to set even CRITICAL level. Smth like this
import logging
requests_log = logging.getLogger("requests")
requests_log.setLevel(logging.CRITICAL)
but without any messages, even CRITICAL.

First of all, requests doesn't log anything; only the urllib3 library that requests depends on does. That library only logs messages at INFO and DEBUG levels, so setting the log level to logging.CRITICAL disables all messages already:
urllib3_log = logging.getLogger("urllib3")
urllib3_log.setLevel(logging.CRITICAL)
You could also just disable propagation:
logging.getLogger("urllib3").propagate = False
That's enough to completely disable all logging that the urllib3 library does.
The urllib3 project has installed a NullHandler() handler object on the project root logger, which ensures that the lastResort handler is not used for unhandled messages, even when propagation has been disabled.
That said, if you don't trust that future versions of requests won't use sys.maxint as a log level, and at the same time neglect to set a NullHandler(), then by all means add your own NullHandler() on the project root logger object, and then disable propagation there:
import logging
requests_log = logging.getLogger("requests")
requests_log.addHandler(logging.NullHandler())
requests_log.propagate = False
Now all logging within the requests hierarchy will be directed to the NullHandler() instance, and with propagate set to False logging stops there. You can use this to silence any logger in the hierarchy.
In my opinion, that's overkill, no requests release made so far uses logging, and the project is staffed with capable developers that are unlikely to misconfigure the logging setup if they ever did add logging.

The accepted answer didn't work out for me. But urllib3 docs point out that you can disable the logging with this:
import urllib3
urllib3.disable_warnings()
Source: urllib3 docs

syslog.syslog vs SysLogHandler

I'm looking at how to log to syslog from within my Python app, and I found there are two ways of doing it:
Using syslog.syslog() routines
Using the logger module SysLogHandler
Which is the best option to use, advantages/disadvantages of each one, etc, because I really don't know which one should I use.

syslog.syslog() can only be used to send messages to the local syslogd. SysLogHandler can be used as part of a comprehensive, configurable logging subsystem, and can log to remote machines.

The logging module is a more comprehensive solution that can potentially handle all of your log messages, and is very flexible. For instance, you can setup multiple handers for your logger and each can be set to log at a different level. You can have a SysLogHandler for sending errors to syslog, and a FileHandler for debugging logs, and an SMTPHandler to email the really critical messages to ops. You can also define a hierarchy of loggers within your modules, and each one has its own level so you can enable/disable messages from specific modules, such as:
import logging
logger = logging.getLogger('package.stable_module')
logger.setLevel(logging.WARNING)
And in another module:
import logging
logger = logging.getLogger('package.buggy_module')
logger.setLevel(logging.DEBUG)
The log messages in both of the these modules will be sent, depending on the level, to the 'package' logger and ultimately to the handlers you've defined. You can also add handlers directly to the module loggers, and so on. If you've followed along this far and are still interested, then I recommend jumping to the logging tutorial for more details.

So far, there is a disadvantage in logging.handlers.SysLogHander which is not mentioned yet. That is I can't set options like LOG_ODELAY or LOG_NOWAIT or LOG_PID. On the other hands, LOG_CONS and LOG_PERROR can be achieved with adding more handlers, and LOG_NDELAY is already set by default, because the connection opens when the handler is instantiated.

Python multiprocessing logging - why multiprocessing.get_logger

I've been struggled with multiprocessing logging for some time, and for many reasons.
One of my reason is, why another get_logger.
Of course I've seen this question and it seems the logger that multiprocessing.get_logger returns do some "process-shared locks" magic to make logging handling smooth.
So, today I looked into the multiprocessing code of Python 2.7 (/multiprocessing/util.py), and found that this logger is just a plain logging.Logger, and there's barely any magic around it.
Here's the description in Python documentation, right before the
get_logger function:
Some support for logging is available. Note, however, that the logging
package does not use process shared locks so it is possible (depending
on the handler type) for messages from different processes to get
mixed up.
So when you use a wrong logging handler, even the get_logger logger may go wrong?
I've used a program uses get_logger for logging for some time.
It prints logs to StreamHandler and (seems) never gets mixed up.
Now My theory is:
multiprocessing.get_logger don't do process-shared locks at all
StreamHandler works for multiprocessing, but FileHandler doesn't
major purpose of this get_logger logger is for tracking processes'
life-cycle, and provide a easy-to-get and ready-to-use logger
that already logs process's name/id kinds of stuff
Here's the question:
Is my theory right?
How/Why/When do you use this get_logger?

Yes, I believe you're right that multiprocessing.get_logger() doesn't do process-shared locks - as you say, the docs even state this. Despite all the upvotes, it looks like the question you link to is flawed in stating that it does (to give it the benefit of doubt, it was written over a decade ago - so perhaps that was the case at one point).
Why does multiprocessing.get_logger() exist then? The docs say that it:
Returns the logger used by multiprocessing. If necessary, a new one will be created.
When first created the logger has level logging.NOTSET and no default handler. Messages sent to this logger will not by default propagate to the root logger.
i.e. by default the multiprocessing module will not produce any log output since its logger's logging level is set to NOTSET so no log messages are produced.
If you were to have a problem with your code that you suspected to be an issue with multiprocessing, that lack of log output wouldn't be helpful for debugging, and that's what multiprocessing.get_logger() exists for - it returns the logger used by the multiprocessing module itself so that you can override the default logging configuration to get some logs from it and see what it's doing.
Since you asked for how to use multiprocessing.get_logger(), you'd call it like so and configure the logger in the usual fashion, for example:
logger = multiprocessing.get_logger()
formatter = logging.Formatter('[%(levelname)s/%(processName)s] %(message)s')
handler = logging.StreamHandler()
handler.setFormatter(formatter)
logger.addHandler(handler)
logger.setLevel(logging.INFO)
# now run your multiprocessing code
That said, you may actually want to use multiprocessing.log_to_stderr() instead for convenience - as per the docs:
This function performs a call to get_logger() but in addition to returning the logger created by get_logger, it adds a handler which sends output to sys.stderr using format '[%(levelname)s/%(processName)s] %(message)s'
i.e. it saves you needing to set up quite so much logging config yourself, and you can instead start debugging your multiprocessing issue with just:
logger = multiprocessing.log_to_stderr()
logger.setLevel(logging.INFO)
# now run your multiprocessing code
To reiterate though, that's just a normal module logger that's being configured and used, i.e. there's nothing special or process-safe about it. It just lets you see what's happening inside the multiprocessing module itself.

This answer is not about get_logger specifically, but perhaps you can use the approach suggested in this post? Note that the QueueHandler/QueueListener classes are available for earlier Python versions via the logutils package (available on PyPI, too).