Learning Python with Advent of Code Walkthroughs

Dazbo's Advent of Code solutions, written in Python

The Python Journey - Logging

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Python Logging

Logging Module Overview

Rather than simply using print() statements, I tend to use the logging module for generating console output.

It has a number of advantages over print() statements. The first is that we can specify a logging threshold level.

For example:

import logging

# initialise the Root logger
logging.basicConfig(format="%(asctime)s.%(msecs)03d:%(levelname)s:%(name)s:\t%(message)s", datefmt='%H:%M:%S')
# now get a named instance of the logger for our application
logger = logging.getLogger(__name__) 

# Set the logging threshold of our logging instance to DEBUG

# print some stuff
logger.debug("We'll see this.")
logger.info("And this.")

# now set threshold to INFO; everything below INFO is now suppressed

# print some more stuff
logger.debug("We will NOT see this.")
logger.info("But we will see this.")

The output from the above looks like this:

09:08:46.929:DEBUG:__main__:    We'll see this.
09:08:46.929:INFO:__main__:     And this
09:08:46.929:INFO:__main__:     But we will see this.

Note that we must first import the logging module.

Customising Output Messages

Another advantage is that you can customise what appears in the console messages. For example, this initial configuration tells the logger to print the time, the logging level, the name of the logger, and then the message.

# It will print the time (including milliseconds), the logging level, and the logger name
logging.basicConfig(format="%(asctime)s.%(msecs)03d:%(levelname)s:%(name)s:\t%(message)s", datefmt='%H:%M:%S')

Logging to a File

We can also configure our logger to print logging messages to a file, rather than to the console. For example:

logging.debug('This message should go to the log file')

The logging configuration itself can also be placed externalised to a file, rather than coded into the program.

Passing Variables

It’s worth noting how we can pass variables into a logging statement. This is a typical example:

import logging

# setup
logger = logging.getLogger("FooBar-App")

my_key = "foo"
my_val = "bar"
logger.info("My key is named %s, and it's value is %s", my_key, my_val)

Here, each %s within the string message itself is a placeholder for a variable. The variables are passed after the string message, as a comma-separated list.

The output looks like this:

08:41:25.172:INFO:FooBar-App:   My key is named foo, and it's value is bar

Writing to Multiple Targets with Handlers

We can use handlers to write to more than one destination simultaneously. E.g. to write to the console and to a file at the same time:

import logging

# setup
logger = logging.getLogger("FooBar-App")

# Write to console with threshold of INFO
stream_handler = logging.StreamHandler()
stream_fmt = logging.Formatter(fmt='%(asctime)s.%(msecs)03d:%(name)s - %(levelname)s: %(message)s', 

file_handler = logging.FileHandler('my_file.log', mode='a')
file_fmt = logging.Formatter(fmt="%(asctime)s.%(msecs)03d:%(levelname)s:%(name)s:\t%(message)s", 

my_key = "foo"
my_val = "bar"
logger.info("My key is named %s, and it's value is %s", my_key, my_val)
logger.debug("Testing a debug line")

Note how we have set different thresholds, as well as different message formats, for the two handlers. So the debug message only gets written to the log file, whereas the info messgae gets written to both the log file, and the console.


To wrap up: the Python logging module is pretty sophisticated. I’ve only touched the surface here. Check the documentation for more details.