Python logging using modules - python

I have multiple modules, which are called by a principal script. Each one does log messages using logging Python builtin package.
How can I log an session ID, set during the execution of the main script, across all modules, without needing to push this variable in each module?
I have set up a python configuration file, called config, with:
import logging
logging.basicConfig(
level=logging.DEBUG,
format="%(filename)s:%(lineno)s|%(funcName)3s()|%(asctime)s|%(levelname)s|%(message)s",
handlers=[
logging.FileHandler("debug.log"),
logging.StreamHandler()
]
)
Other modules are using this pre configured logging object, via import, so I am using this:
from config import logging
But I need to log an ID from my current session, my log should look like:
module_name.py:25|function_name()|2020-04-27 18:28:26,518|INFO|Session_ID=abc123|some_message_here
I have tried to put this variable in the config file, set it, and then use it in a function named "log_info" and "log_debug" in this file, but my output log does not trace python script name and function name any more.
Does anyone knows how to handle this situation?

I don't know if this is the 100% best solution, or for sure if it'll work in your situation, but I used it for something similar (verbosity printing levels that would persist across several scripts).
Create a Python file, named, say, sessionid. Inside that, define a top-level setting named id. To set your id, import sessionid and sessionid.id = 'some_id'. Then have your config file import sessionid as well and use sessionid.id as needed.
It took me a bit to figure out that I had to access it like that; changing it using from sessionid import id; id = 'some_id' only persists within the script that does so.
It would make sense to put the id variable in your config file, but only if you don't need to set it in the same script that also needs to from config import logging.

Related

Python Logging from Library

Hi this is hopefully a basic question. I have a python library with a lot of logger messages such as this:
log = logging.getLogger(__name__)
log.info("blah")
log.warning("blah")
...
Then I have a separate code that imports and runs this library. In that code, I added this, thinking it would cause all logging messages to go to this file:
log = logging.getLogger(__name__)
fh = logging.FileHandler("/some/file/location/log.txt")
log.addHandler(fh)
This does successfully pass all log messages in that script to direct to that file, but the logging messages from the library aren't being passed along. I don't want to specify the file path from within the library, that doesn't make much sense, I want it specified in the code that runs the library. Most of the examples I'm seeing show imports happening with parent/child modules, but what about one module that calls a completely different module? Does my library need to accept a logger as an argument to use, or can I use the logging module to handle this?
Thanks.
Looks like you are creating two instances of the Logger class. Only the instance in your script is being configured to write to the file location.
Each time the 'getLogger' method is called, it provides a reference to the Logger with the specified name. If a Logger with that name doesn't exist, a new one is created. Note that in Python, __name__ specifies the module name. Since you are calling the library from a script, I'd assume you have two separate modules, hence two different Loggers.
For a quick-and-dirty approach, you can use:
import my_library
log = logging.getLogger(my_library.__name__)
fh = logging.FileHandler("/some/file/location/log.txt")
log.addHandler(fh)
Where my_library is your newly defined library. This will provide the logger which the library instantiated, instead of creating a new one.
Another approach would be to define a module-level function like this:
# In your script
import my_library
log_location = "/some/file/location/log.txt"
my_library.set_log_location(log_location)
# In your newly defined library
def set_log_location(path):
log = logging.getLogger(__name__)
fh = logging.FileHandler("/some/file/location/log.txt")
log.addHandler(fh)
The second approach wouldn't require the user knowing that your library uses the logging module.
In your application, e.g. in the if __name__ == '__main__' clause, configure the root logger with the handlers you want, using e.g.
logging.basicConfig(level=logging.DEBUG,
filename='/some/file/location/log.txt',
filemode='w',
format='%(asctime)s %(message)s')
and then all logging from your application, your libraries and third-party libraries should write log messages to the file. The sources of logged events (application or libraries) don't need to know or care where the events they log end up - that's taken care of by the configuration. If you need more involved configuration than basicConfig() provides, you can use logging's dictConfig() API to configure logging.

Initialise logging config from conf file in Python

I want to initialise the logging config using a config file(json or yaml) only once when I call my main module.
Is there a concept of context in python like we have in Java where I can take the logger from config whenever I need.
Something like this in the main module -
logging.config.fileConfig('log-conf.json')
I want to use the loaded config in my entire application without having to load the config in each module.
Also, should I do log = logging.getLogger(__name__) at module level or method level. What is the advantage of doing at method level.
This blog post of mine contains major answers to your question (YAML).
http://glenfant.github.io/the-zen-of-logging-and-yaml.html
You might also have inspiration from this recipe, if you prefer a pure Python config file.
http://glenfant.github.io/simple-customizable-configuration.html

How do I define a different logger for an imported module in Python?

I'm using Advanced Python Scheduler in a Python script. The main program defines a log by calling logging.basicConfig with the file name of the log that I want. This log is also set to "DEBUG" as the logging level, since that's what I need at present for my script.
Unfortunately, because logging.basicConfig has been set up in this manner, apscheduler writes its log entries to the same log file. There are an awful lot of these, especially since I have one scheduled task that runs every minute.
Is there any way to redirect apscheduler's log output to another log file (without changing apscheduler's code) while using my log file for my own script? I.e. is there a way to change the file name for each module's output within my script?
I tried reading the module page and the HOWTO for logging, but could not find an answer to this.
Set the logger level for apscheduler to your desired value (e.g. WARNING to avoid seeing DEBUG and INFO messages from apscheduler like this:
logging.getLogger('apscheduler').setLevel(logging.WARNING)
You will still get messages for WARNING and higher severities. To direct messages from apscheduler into a separate file, use
aplogger = logging.getLogger('apscheduler')
aplogger.propagate = False
aplogger.setLevel(logging.WARNING) # or whatever
aphandler = logging.FileHandler(...) # as per what you want
aplogger.addHandler(aphandler)
Ensure the above code is only called once (otherwise you will add multiple FileHandler instances - probably not what you want).
maybe you want to call logging.getLogger("apscheduler") and setup its log file in there? see this answer https://stackoverflow.com/a/2031557/782168

Python logging with a library (namespaced packages)

My project consists of a number of namespaced packages and I want to set up logging properly for them: they are meant to be used as a library by other "frontends".
Suppose I have the case, for package foo.xyz:
foo/
__init__.py
xyz/
__init__.py
bar.py
baz.py
My idea would be to retain information from where the log is being generated, so for example in bar.py
import logging
log = logging.getLogger(__name__)
log.addHandler(logging.NullHandler()) # Python 2.7
log.setLevel(....)
However I'm not sure how to call this from the frontend (which imports several bits from different packages) to display everything without hassle. For example, I'm using foo.abc and foo.xyz, set up like above for logging. I would like to use propagation, but currently this doesn't work:
from foo.xyz import bar
from foo.abc import baz
log = logging.getLogger()
log.addHandler(logging.StreamHandler())
log.setLevel(logging.DEBUG)
do_my_stuff()
However, no output is being generated from the library's loggers. What am I doing wrong?
EDIT: So far I can get output if I get the logger corresponding to the parent module's namespace:
log = logging.getLogger("foo.xyz")
However I'm trying to grab everything in one call: I wonder if I can do that since, as I wrote earlier, this set of packages uses a namespace.
You don't need to add a NullHandler to all sub-packages of foo - you can just add the NullHandler to the foo logger, which could be done in foo/__init__.py.
The NullHandler is only added to library code to handle situations where the library is used but logging isn't configured by the using application. Thomas Vander Stichele is wrong to state that adding a NullHandler would cause messages to be dropped.
In your application, you can configure logging as you wish - whatever handlers, levels etc. Level setting should not (in general) be done in the modules themselves, but in some central place, typically called similarly to this:
if __name__ == '__main__':
configure_logging() # whatever configuration you need to do
main()
This allows REPL usage without logging being printed (other than WARNING or above), while logging occurs if the application is run.
What happens if you remove addHandler and setLevel from bar.py ? I don't see why you would want your package to actually do the logging instead of generating log messages, and the NullHandler sounds like it would be dropping your messages alltogether.

Incompatibility between import-time logger naming with logging configuration

I am setting up my Python logging in main.py via reading in a file and using the fileConfig option. I want to be able to switch between testing and live logging configurations, so I want to read in a separate config file first and extract the logging config file path from there.
The problem here is that other files that I import from main.py grab their own logger via log = getLogger(__name__), and this happens at import time. These links then get broken when the new configuration is loaded in, and these modules end up without the logging working the way I expect.
I can't easily delay the importing of these modules without a lot of refactoring, so is there any other way of being able to keep this method of setting up loggers by module name while still loading in the log configuration later?
I'm not sure from your question exactly how things are breaking, but here's how I see it. The various modules which do log = logging.getLogger(__name__) will have valid names for their loggers (logger name = package name), unless you were to somehow actually move the modules to some other package location.
At import time, the logging configuration may or may not have been set, and there shouldn't be any actual logging calls made as a side-effect of the import (if there are, the messages may have nowhere to go).
Loading a new configuration using fileConfig typically just sets handlers, formatters and levels on loggers.
When you subsequently call code in the imported modules, they log via their loggers, which have handlers attached by your previous configuration call - so they will output according to the configuration.
You should be aware that on older versions of Python (<= 2.5), calls to fileConfig would unavoidably disable existing loggers which weren't named in the configuration - in more recent versions of Python (>= 2.6), this is configurable using a disable_existing_loggers=False keyword argument passed to fileConfig. You may want to check this, as it sometimes leads to unexpected behaviour (the default for that parameter is True, for compatibility with behaviour under the older Python versions).
If you post more details about what seems broken, I might be able to provide a better diagnosis of what's going on.

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